i, ,, » ::;.;:-‘. “1:9. I .1- p a: . . .. “‘93,," I no ‘5,“ 00—4.... 4w (grating; 574;. 3J- “finial; T%}. "P4 ‘53} a .n. 1 3A; , :39: 7:319 My“: 3! 731' 5;.) . ‘ . 7 .33.»- 4' ”5’“ :. .95.: :23 V mum ' 3,35 2. .. 1"..1 “QT, 1&5». ”rant. N1 F” than. ‘1'; 3341.4. 35., a; 215:: "m 4‘ a. u - 'h‘ vw «:3. K ’fpuv . I". 3 ‘ "N‘s jquw‘ "“t‘f river-:- , 1 53:33 a“??? - y‘i’i {firfi 4;. v , L 7-1;», .24. a a nu-.,--.-‘¢,_,_. w’\ h . 3. .5331.” m"? .. . . at _ ‘1- ”Pg .9": r .2235 1,, . -. Raw"? '3' 35;; 5.3.5 rrrl :3". 2r ‘ i ' a «3:51;,- ‘,A"'~.'$3‘:§'z';~:rr$' #5. ,.. ' ~2§1= «iguwfin 4:21... 1‘ vo- fl’f’" ",2, ”’5';an4” «v.1 -pw .3 grun‘r Qvn’r‘iu 4, ,7: , -, v... o r-' r»- :3 lo no.4 ”filmy”... -. -:.. ,4-—.............‘ ' “N '2 Hr“ "'J.«"".A...“‘“ w. . . . ..., .2 '5- v v 0 II. o 0 m ' c 1r A 4;“)-.-3 1'. - ,, J.- «In 3:“ pvt-Iv- - v. f; '4 ~¢ 1 v»'vv '" 77.. N . , .. an - . - a..- .4. . ,...... - :'«-.«,~»....._1_ «.2...» “y $731: ‘ " -’ *1 V . _ . .. _. ‘_ ‘ ... r “,3. _...zrr-.. '. ' ' ' >' . . ' .M-L,.~1"’3"' ‘ .. .... a . 7 .u.......f,..2:.‘. :3" 5-: , _ _ V .. . 7 _ .. _._ .2: r..,. , . . 7 ... . ‘ . 7 _ ::.:: J": , ‘ .. , _ — ”1' 2:. * ~ . ,m _ ..':...:. ”1:. .H . .1“ “.9 33'” 3'. Jr—vuaummw "~- -- , 2‘ . ..‘ u. .. .. .. "‘Jl'l’é’ZM , (3'11 ‘ .. .._.,..—v, ‘WNOP—OWMQ ' ‘75.." J:;n=.~..;.:::'" -oa—,.... ;£:.m,-m m-m... ..... - EM “.7: 7:2 ... 153?:5"~€m.~,:220.~ "1773' '7'? , kiwi Efitfifl ' 12:2,: .72. '3». “3.. *v'JWE" ’F""‘T'," , ,.. . “7"!” . i u "I" 'J 74" ha. "inn“ IVY—”SF ' 1‘? T J "i. ’,.' "17: .,._.1 3: t", . p. if: exus'fifiwfimmfi‘ ' ' f “:14... ”.35 ' lES MICHIGAN STATE UNIVERSITY L BRAR \\\\ \\\\\\\\\\\l\ ll \ \‘l l l\\\\\\\\\\l \ ll Nil \llll \\ \ 31253 009010715 This is to certify that the thesis entitled PEST MANAGEMENT IN MICHIGAN PUBLIC SCHOOLS presented by DEBORAH L . MILLER has been accepted towards fulfillment of the requirements for M . S . degree in ENTOMOLOGY Major professor Date ' 8-9-91 0-7639 MS U i: an Affirmative Action/Equal Opportunity Institution LIBRARY Michigan State 'Universlty PLACE IN RETURN BOX to remove thIc checkout from your record. TO AVOID FINES return on or before dd. duo. DATE DUE DATE DUE DATE DUE MSU I. An Affirmative ActIoNEqual Opportunlty Institution emails-9.1 ‘ __—u—=~. PEST MANAGEMENT IN MICHIGAN PUBLIC SCHOOLS By Deborah L. Miller A THESIS Submitted To Michigan State University In Partial Fulfillment of the Requirements For the Degree of MASTER OF SCIENCE Department Of Entomology and Urban Aflairs Programs 1991 ABSTRACT PEST MANAGEMENT IN MICHIGAN PUBLIC SCHOOLS By Deborah L. Miller Public school personnel face a variety of pest related problems ranging from health hazards and economic destruction to aesthetic damage. In order to develop model school pest management/pesticide policy guidelines, existing pest problems and control practices need to be identified. A questionnaire designed according to the principles of Dillman's Total Design Method was prepared in 1987 to assess perceived pest prevalence, pest management practices, personnel responsible for pest management, level of satisfaction with current pest management efforts, concern expressed over pesticide use in the school environment, types of pest management records maintained, and interest in new pest management program development. Responses were compared by school district size, location and community type. It was tound that size is an important factor in pest presence and choice of personnel responsible tor management. It was also tound that pest control companies are employed by over 70% of the districts. New program development should take both district size and pest control company employment into consideration. This thesis is dedicated to the memory of my father. ACKNOWLEDGEMENTS I thank my major professors, Dr. George W. Bird and Dr. Dean L. Haynes, for their patience, support and encouragement throughout my graduate program. lthark the members of my committee, Dr. Thomas Edens, Dr. Stuart Gage and Dr. Mark Whalon for their constructive criticism and support. I am grateful to the many members of the Entomology and Nematology Family' at both the Natural Sciences Building and the Pesticide Research Center who have openly shared information and ideas. I thank the Urban Affairs Programs for their support during my academic career and for the opportunity to interact with professionals and students from a diverse range of disciplines. I thank my family for their love and encouragement to continue my education. I also thank my friend, Bill Morgan, for his love, patience and understanding. TABLE OF CONTENTS LIST OF TABLES ........................................................................................................ viii LIST OF FIGURES ........................................................................................................ xi INTRODUCTION ........................................................................................................... 1 LITERATURE REVIEW .................................................................................................. 5 Surveys on General Public Pesticide Use ................................................................. 5 Surveys on Pests, Pesticides and Pest Control ......................................................... 6 Surveys to Obtain Information for Pest Management Program Development ............... 8 Institutional Pest Management Program Implementation .......................................... 12 Mal Surveys ......................................................................................................... 14 METHODOLOGY ........................................................................................................ 15 Questionnaire Development and Distribution .......................................................... 15 Dillman's Total Design Method ......................................................................... 15 School District Questionnaire Development ...................................................... 17 School District Attributes ....................................................................................... 20 Data Analysis ........................................................................................................ 23 RESULTS AND DISCUSSION ...................................................................................... 25 Introduction .......................................................................................................... 25 Comparison of Retumee Attributes with All School Districts ..................................... 25 Posts Within School Districts .................................................................................. 34 General Pest Occurrence ................................................................................ 34 Inportant Pest Concerns .................................................................................... 36 Specific Pest Numbers Needing Management ...................................................... 40 Number of Actual Pest Probiems ......................................................................... 43 Past Problem Locations ..................................................................................... 58 Specific Outdoor Plant Disease and Pest Problems .............................................. 62 Summary ........................................................................................................... 62 Pest Management Methods ...................................................................................... 66 Methods Used for Pest Prevention and Pest Management .................................... 66 District Response Selections ........................................................................ 66 Comparison of Prevention and Management Methods .................................... 74 Pest Management Guidelines ............................................................................. 81 Pesticide Use ..................................................................................................... 85 Safety and Effectiveness .............................................................................. 85 Frequency of Use ........................................................................................ 87 Pesticide Use and Presence of People .......................................................... 9O ' Notification of Use ......................................................................................... 90 Days Applied ............................................................................................... 92 Summary ........................................................................................................... 92 Pest Management Execution .................................................................................... 96 Requests tor Pest Management .......................................................................... 96 Communicable Pest Problems ............................................................................ 96 Selection of Pest Management Methods ........................................................... 100 Pest Management Execution ............................................................................ 102 Indoor Pest Management ........................................................................... 102 Outdoor Pest Management ........................................................................ 105 Pest Control Company Employment .................................................................. 106 Criteria Used to Select PCCs ....................................................................... 110 School Personnel Negotiating PCC Contracts ............................................. 110 Factors Defined in PCC Contracts ............................................................... 115 Contract Time Period .................................................................................. 117 Pests PCCs are Employed to Manage ......................................................... 117 Methods Used or Recommended by PCCs .................................................. 123 PCC Report Recipients .............................................................................. 123 Summary ......................................................................................................... 1 27 Pest Management Evaluation and Satisfaction with Effectiveness ............................. 129 Effectiveness Evaluation .................................................................................. 129 Personnel Perfonning Evaluations .................................................................... 129 Satisfaction with Pest Management Effectiveness .............................................. 132 Concern with Pest Management ....................................................................... 132 Concern over Pesticide Use in the School Environment ..................................... 137 Summary ......................................................................................................... 1 40 Pest Management Records .................................................................................... 142 Record-Keeping .............................................................................................. 142 Pest Management Record lnfonnation ............................................................... 142 Pest Management Record-Keeping Time Period ............................................... 145 Record Storage Location .................................................................................. 145 Summary ......................................................................................................... 149 Technical Assistance and Pest Management Program Development ......................... 150 ' Pest Management lnfonnation Sources ............................................................. 150 Technical Assistance Adequacy or Need ........................................................... 152 Pest Management Method Review Process ....................................................... 152 Pest Management Program Development and Execution ................................... 154 Summary ......................................................................................................... 156 CONCLUSION ............................................................................................................. 158 Summary of School District Responses ................................................................... 158 Questionnaire Concerns ........................................................................................ 162 Implications of Survey Findings for Pest Management Program Development ............ 165 APPENDICES ............................................................................................................. 1 67 A. Cover Letter .................................................................................................... 167 B. Letter of Endorsement ..................................................................................... 168 C. Questionnaire .................................................................................................. 169 LIST OF REFERENCES ............................................................................................... 185 Table 1. Table 2. Table 3. Table 4. Table 5. Table 6. Table 7. Table 8. Table 9. Table 10. Table 11. Table 12. Table 13. Table 14. Table 15. Table 16. Table 17. LIST OF TABLES Attribute Distribution of All School Districts and of Those Returning Questionnaire .................................................................... 26 Attribute Distribution Reported by Districts Completing Questionnaire ............. 31 Comparison of Number of Pest Problems Reported by Administrator and Support Service Respondents (Mean :1: SD) ........................ 32 Pest Occurrence within School Districts ......................................................... 35 Number of Pests Acceptable to School Administrators ................................... 37 Pest Selected as the Most Important School District Concern .......................... 38 Posts Selected as One of the Three Most Important District Concerns ............. 39 Number of Each Specific Pest Considered a Problem that Must be Managed ...41 Number of Different Pest Problems Experienced by School Districts Grouped by Attribute Class ................................................... 44 Comparison of Number of Pest Problems Reported by Districts Grouped by Actual District Building Size ........................................................ 45 Portion of District School Buildings with Pest Problems .................................. 46 Post Occurrence within District School Buildings ............................................ 49 Regression Analyses Results for Percent of District School Buildings with Pest Presence Against Log of Actual District Building Size and Mean :I: SD of the Percent of District School Buildings with Pest Presence for Non—Significant Results ............................................................ 57 Indoor School Building Locations with Pest Problems .................................... 59 Outdoor School Building Locations with Pest Problems ................................. 63 Preferred Pest Prevention and Pest Management Methods ........................... 67 P-Values for Selection of Preferred Pest Prevention and Management Methods Based on District Attribute Class ................................. 72 viii Table 18. Table 19. Table 20. Table 21. Table 22. Table 23. Table 24. Table 25. Table 26. Table 27. Table 28. Table 29. Table 30. Table 31. Table 32. Table 33. Table 34. Table 35. Table 36. Table 37. Table 38. Table 39. ' Table 40. Methods Preferred by Districts Selecting Responses for Both Pest Prevention and Management with Districts Grouped as All Districts, Those Reporting Presence of the Specific Pest and Those Reporting no Presence of the Specific Pest .................................................................. 75 P-Valies for Selection of Prevention and Management Methods Based on Pest Presence ................................................................ 82 Availability of Pest Management Guidelnes ................................................... 84 Pesticide Safety and Effectiveness as a Pest Management Methods ............... 86 Pesticide Use Frequency ............................................................................. 88 Pesticide Use Notification ............................................................................. 91 Pesticide Application Days ............................................................................ 93 School Groups Requesting Management of Pest Problems ............................ 97 Personnel Responsible for Communicable Pest Problems ............................. 99 Personnel Who Dedde on Pest Management Methods ................................ 101 Personnel Who Perform Indoor Pest Management ....................................... 103 Personnel Who Perform Outdoor Pest Management .................................... 107 Employment of Pest Control Companies by School Districts .......................... 109 Selection Criteria Used by Districts Employing Pest Control Companies ............................................................................. 111 School Personnel Negotiating Pest Control Company Contracts ................... 112 Factors Defined in Contracts with Pest Control Companies ............................ 116 Length of Pest Control Company Contracts .................................................. 118 Pests which Pest Control Companies have been Employed to Manage .......... 119 Methods Used or Recommended by Pest Control Companies ....................... 124 School Personnel to Whom Pest Control Companies Provide lnfonnation Concerning Pest Problems and Management Actions ................................... 125 Evaluation of Pest Management Effectiveness ............................................. 130 Personnel Performing Pest Management Evaluation .................................... 130 Satisfaction of Different Personswith Effectiveness of Current Pest Management Efforts ................................................................ 133 Table 41. Table 42. Table 43. Table 44. Table 45. Table 46. Table 47. Table 48. Table 49. Table 50. Table 51. Table 52. Table 53. Persons Who have Expressed Concern with Pest Management Efforts ......... 134 Persons Who have Expressed Concern Over the Use of Pesticides in the School Environment .......................................................... 138 Maintenance of Pest Management Records by School Districts ..................... 143 Review Accessibility of Maintained Pest Management Records ..................... 143 Pest Management Record lnfonnation ......................................................... 144 Time Period which Pest Management Records have been Maintained ........... 146 Location Where Pest Management Records have been Maintained ............... 147 Sources of Pest Management lnfonnation .................................................... 151 Adequacy of Available Technical Assistance ................................................. 153 Need for New Technical Assistance for New Programs .................................. 153 Pest Management Method Review Process ................................................. 153 ' Persons Selected as New Pest Management Program Developer .................. 155 Persons Selected as Responsible for New Program Execution ...................... 155 Figure 1. Figure 2. Fiona 3. Figure 4. Figure 5. Figure 6. Figure 7. Figure 8. LIST OF FIGURES The IPM Process ............................................................................................ 2 A Michigan Lower Peninsula School Districts ................................................ 21 B. Michigan Upper Peninsula School Districts ................................................ 22 Attributes of Michigan School Districts (Size, Location, Student Population) ............................................................. 27 Reported Michigan School District Attributes .................................................. 29 Distribution of Administrative and Support Services Staff as Questionnaire Respondents by Actual District Building Size ............................ 33 Distribution of Districts Reporting Specific Pest Presence as Proportion of All Responding Districts by Actual Building Size ......................... 51 Regression Analysis for Percent Pest Presence Against Log of Actual District Building Size ..................................................... 54 Management Methods Preferred by Districts With and Without the Specific Pests ............................................................... 79 INTRODUCTION Managers of public buildings, health care facilities and schools face a variety of pest related problems ranging from health hazards and economic destniction to aesthetic damage. Common pests which cause such problems include insects (e.g. ants, cockroaches, flies, fleas, mosquitoes, termites and wasps), vertebrates (e.g. rats, mice, birds and bats), weeds and plant pathogens (National Academy of Science, 1980). Various tactics and tools are available for control of these pests. Habitat modification includes sanitation, effective food storage, physical exclusion and removal of harborage. Direct suppression is pcssrble by means of trapping, biological control agents and pesticides. These methods can be utilized as part of a comprehensive pest management program called Integrated Pest Management (IPM). IPM consists of the development, use and evaluation of pest control strategies that result in favorable scale-economic and environmental consequences (Olkowski, 1980; Bird of al., 1990). It is a systems approach to reduce pest damage to tolerable levels through the use of techniques selected as appropriate for the situation in which they are to be used. (See Figure 1.) However, despite the variety of available management methods, pesticides are often relied upon as the primary or sole pest control agents (Thorpe, 1988). When less toxic measures are ignored in favor of pesticides, unnecessary public exposure and increased health risks may result (Flint and van den Bosch, 1981). In recent years, there has been a marked increase in public awareness of potential health hazards and environmental risks associated with pesticide use (Center for the Integration of Applied Sciences, 1981; National Academy of Science,1980; Environmental Defense Fund and Boyle, 1979; von Rumker et al., 1975). In 1985, Michigan Govemor James Blanchard Ascend Post Presence Acceptable? I y" Anode Available A Wait. Until Next Pest Management V Monitoring .._l Methods W l I Any Yes N° Yes Appropflltz? ' aw Reuse-u Anon Effec- A ASSN p tlltyczf implement Post A 2?; Management ' Mamgcntnt Action "0 Now You I- '1 Acceptable? Run-c. Pest Management Method- Available I N I Y 53L ”grips“? ‘5' Figure 1. The IPM Process. A series of decisions are made during the IPM process. After pest assessment, the intial decision concerns whether or not pest presence is within acceptable limits. If it is not, available control methods are evaluated to determine if any are appropriate for the situation. If none are appropriate, pest presence acceptability must be reassessed to decide if the risk of pest presence itself outweighs the risks of using control methods deemed inappropriate. If, however, pest management methods appropriate for the situation exist, they can be used. Following control implementaion, effectiveness of the method(s) used must be evaluated. If effectiveness is found wanting, additional measures may need to be taken. If control is determined to be adequate, no further decision or action is necessary until the next time when pest presence is reassessed. charged the State Cabinet Council on EnvironmeMal Quality with the task of assessing existing pesticide regulations and providing specific recommendations as part of an overall strategy for improving pesticide management and regulation. As a result, the report “A Strategy for Improved Pesticide Management in Michigan” was issued (Michigan Department of Agriculture Pesticide Subcommittee, 1985). The report highlighted four areas of concern regarding public exposure. These included (1) the nature of state policies that govern the use of pesticides in public buildings, (2) whether existing policies adequately consider pesticide-related health risks to the general public, (3) whether individual chemical hypersensitivity is a significant concern and (4) whether widespread residential and agricultural use of pesticides represents a significant risk to human health or environmental Integrity. The Subcommittee proposed ways to minimize human exposure. One recommendation was to ”Develop model public building, school and health care facility pest management/pesticide policy guidelines for adoption by appropriate agencies." In 1987, a preliminary report on ”Integrated Pest Management for Michigan Schools" (Larsen et. al., 1987) was prepared by participants of Michigan State University's College of Natural Science Course 447. This report provided an overview of the public school system, reviewed pest data and discussed IPM and its implementation. It was found that little lnfonnation existed on pest problems and control practices used within schools. Head lice were the only documented pest with over 350,000 cases reported annually to the Michigan Department of Public Health. Other pests said to be problems included cockroaches, rodents, ants and weeds. Management practices were also not documented, but were said to include sanitation and pesticide applications. The first step in the development of any IPM program is the identification of existing pest problems and control practices. In order to acquire this lnfonnation, a five part questionnaire was designed to assess (1) perceived pest prevalence, (2) management practices. (3) school personnel involved in making pest management decisions, (4) degree of satisfaction with practices used and control achieved and (5) the need to implement or improve pest management guidelines. During the fall of 1987, this questionnaire was distributed to 565 Michigan school district superintendents. The purpose of this survey was to obtain new information on Michigan public school districts. It was hypothesized that based on either district size, location or community type: " pests perceived as problems by K-12 public schools vary in intensity and variety , ' control practices used to prevent and manage the pests vary and are also dependent on actual pest presence, ‘ different personnel are responsible for pest management execution, ‘ the level of satisfaction with cunent pest management efforts and control achieved as well as the amount of concern over pesticide use in the school environment differs in expression, ‘ different types of pest management records are maintained and kept for different time ' periods, and ' interest in new pest management technical assistance and program development varies. LITERATURE REVIEW A number of surveys have been conducted to assess general public attitudes,beliefs and behaviors toward pests, pesticides and pest management. These were first conducted at the same time expression of public concern over environmental problems started to show up in polls in the late 19608 (Council on Environmental Quality, 1980). WWW Initial surveys focused primarily on pesticide use. Finklea et al (1969) reported that 90% of _ 196 families surveyed in South Carolina used pesticides in the home and that most users ignored common-sense safety precautions; eg. 88% did not keep pesticides in a locked area, 66% stored them within reach of small children, and 54% placed them near food or medicine. In a survey of three urban communities (Philadelphia, PA, Dallas, TX and Lansing, MI), von Rumker et al. (1972) reported that the average deposit of pesticide active Ingredients per urban residential acre was between 5.3 and 10.6 pounds. Of 525 respondents. 92.5% reported using pesticides. Eighty-four percent said they did so without reservations, whereas 8.5% indicated concern about possible side effects. Three and a half percent reported believing that birds, bees, etc. were diminishing and/or that pets became sick from the use of pesticides around the house and yard. Prompted by local interest in public and environmental health aspects of pesticides, the Pennsylvania Allegheny County Health Department was asked to monitor local use and health effects of pesticides and to develop a public education and lnfonnation program on pest control without pesticides and on safe use of pesticides (Lande, 1975). One hundred ten sites classified as single-family dwellings. commercial and recreational lawns, institutions, farms, 6 rights-of-way, and wildemess/wastelands were randomly selected for the survey. Of the 41 households and wildemess/wastelands were randomly selected for the survey. Of the 41 households interviewed, 84.6% said they used some pesticide in the previous 12 months. Many were not aware of all the pertinent information on pesticide labels. Only 12% claimed to read everything while 21% said they read nothing. Of the five institutions interviewed, four were schools. Three of these said they employed pest control operators but did not know what insecticides or rodenticides were used. No specific questions were asked regarding public concern over pesticide safety or environmental health risks. The author concluded that no observation in this or any other study supported the need for a new educational program in pesticides or indicated that a substantial segment of the public would use its services. This was in contrast to summaries of subsequent researchers who obtained similar survey results (9.9., _ Bennett et al, 1983). Savage et al. (1979) found that among over 8,000 respondents across the nation, 90% reported using pesticides in their home or yard with three times as many using pesticides in their houses than in their yards. Many respondents were not aware of the pesticide they used, less than 50% read labels, and less than 6% went to knowledgeable sources for pest control information. One report conclusion was that “the use of pesticides in the home environment may be a major source of pesticide exposure in the general population. This is of special significance since certain members of the family spend the majority of their time in the home environment.“ WWW Later, other researchers began to include questions on the pests themselves in addition to questions on pesticides and pest control. In 1982, the National Pest Control Association Consumer Affairs committee conducted a national opinion survey on pests and pest control by interviewing 1,005 men and women living in private households in the continental United States. The five most frequently named pests were flies, common ants, cockroaches, spiders and mice (38%, 34%, 30%, 28% and 27% respectively). The past for which PCOs were most often employed was cockroaches. Termites, spiders, common ants and mice followed. However, relative pest importance (in descending order) was assessed as termites, cockroaches, carpenter ants, ticks and spiders in terms of the percent of households with the post that employed PCOs. Three quarters of those interviewed agreed that chemical pesticides can be safely used to rid homes of unwanted pests. However, only 41% agreed that there are relatively few environmental problems related to pest control activies, compared to other industries. Twenty- seven percent disagreed and the remaining 32% had no opinion. Bennett et al. (1983) surveyed 958 households in North Central Indiana to determine the pattern of pesticide use in homes. They found that 78% of the households used pesticides. Most relied on past experience when obtaining an insecticide, but when assistance was sought, it usually came from a friend or relative. Only 14% obtained pest problem diagnosis information and 77% of this came from retail salespersons. In contrast to the conclusions of Lands (1975) the dramatic lack of knowledge in proper selection and use of pesticides prompted the survey authors to conclude that greater control of the use of pesticides by householders be attained. Interviewees were also asked about alternate (nonchemical) control measures, awareness of beneficial insects and the frequency of past and present pest problems. Alternate control measures had been tried by 87% with tly swatters and traps mentioned most frequently. Over 72% knew about beneficial insects with praying mantids and ladybugs being mentioned most frequently. Ants were named as the most common current problem by 41.9% of the respondents. Flies, fleas, mosquitoes, mice, hymenoptera, spiders, cockroaches, miscellaneous pests, rats, silverfish and centipedes followed. Termites were named in addition to the proceeding when frequency of past pests was reported. Byme et al. (1983) conducted a survey of households in Arizona in order to better understand the public's attitude toward arthropods. Over half of 1,117 households interviewed said they either disliked or were afraid of outdoor arthropods and 88% were either afraid of or disliked indoor arthropods. Few, only 6%, said they took actual pleasure from arthropods encountered outside the home, whereas fewer still, less than 1%, enjoyed those found inside the home. Other surveys have focused on specific insects or insect groups. The attitudes and knowledge of Roanoke and Norfolk, Virginia and Baltimore, Maryland public housing residents toward cockroaches was surveyed by Wood et al. (1981). Robinson and Atkins (1983) surveyed the attitudes and knowledge of Virginia Beach, VA homeowners toward mosquitoes. Barrows, et al. (1983) surveyed urban community gardener knowledge of arthropods in vegetable gardens in Washington, DC. G.W. Frankie, et al. (1981b) approached pest and pest management surveys as a means to gain lnfonnation useful for pest management program development. They developed the concept of using the survey as a tool to allow for quantification of attitudes and practices towards pests and pest control which could be used for more intelligent and informed decision-making by pest managers. From 1974 to 1976, Frankie and Levenson (1978) first surveyed rural and urban dwellers' attitudes and practices towards insects and insecticides in two Texas cities. Their survey approach was to format questions to allow for evaluation of the “A, B, C's“ of attitudes - of how people feel (Affect), act (Behavior) and think (Cognition) about insect problems and insecticides (Kretch et al., 1962). They found that 55 to 76% of the respondents in each community had at least one indoor or outdoor insect problem. Information on these problems was sought by 54-81% of all interviewees (551 total) with most people going primarily to extenninators (38-51%). Up to 78% said they used chemicals indoors and outdoors while up to 54% said they used nonchemical control methods. Approximately 2/3rds of the interviewees in both cities said they were aware of beneficial insects. Twenty-nine to 46% of the interviewees said they had had a change in attitude towards the use of chemicals most saying that they no longer use them or use them cautiously. Commonly cited reasons included personal experience with negative results, reading, broadcast media, and the ecology/environment movement. Examination of the general relationship between attitude and behavior led the researchers to say that the data suggest that affective components (feelings) of insecticide use and insect problems are most closely linked with cognitive factors (thoughts) or amount and type of information and not necessarily with any behavioral manifestations (actions). Their results were consistent with other psychological research on attitude change, which indicate that behavioral change appears to lag behind opinion and lnfonnation change. In 1981, Frankie et al. (1981a) surveyed the attitudes and practices of P005 in Berkeley, CA, Dallas, TX and New Brunswick, NJ toward pests and pesticides. All interviewed P005 (25 In each location) said they were an important lnfonnation source for the homeowner. The top six pests In each state included ants, fleas, cockroaches, rodents, and termites. Outdoor pests varied greatly among the states and included ants, white grubs, and stinging insects. Pesticides were found to be the primary tool of the PCOs. Trapping, exclusion, habitat modification and improved sanitation were commonly cited as nonchemical controls. Overall, improved sanitation and habitat modification were the primary ways that PCOs and homeowners combined their efforts. But as homeowners hiring a professional expect the job to be completed as quickly, safely and inexpensively as possible, the PC05 usually relied on pesticides. The authors implied that PCOs were sinply responding to market demand. Some PCOs felt that all insects were beneficial in their natural environments. Awareness of the harm that pesticides may cause was generally expressed by many PCOs. Dangers to animals and human health were citied by some, while a few mentioned dismptions to the environment. 10 Further work by Frankie et al. (1981b) and Levenson and Frankie (1981) detailed homeowner arthropod pest problems, attitudes toward the pests and measures used to control them in Berkeley, CA, Dallas, TX and New Brunswick, NJ. Survey findings suggested that It is possible to develop a profile on those urbanites who, because of their attitudes and behavior, would most likely use IPM technology or implement IPM programs. Characteristics of such a person might include (1) awareness of indoor and outdoor pest problems, (2) ability to tolerate low numbers of at least some pest species, (3) approaches pesticide use with caution, (4) awareness of potential hazards and limitations of pesticide usage, (5) uses some nonchemical means for controlling pests, (6) ability to name more than one beneficial organism in the urban environment, (7) likes some insects, (8) willingness to become Involved with own pest control efforts, (9) seeks information on pests from more than one source, and (10) willingness to try new ideas. 01 601 respondents, 90% said that they have either an indoor or outdoor pest problem with 61% having an indoor pest problem and 56% having an outdoor problem. An average of two pests was mentioned for each habitat. Ants, cockroaches, fleas and flies were among the top five selected in all three communities for indoor pests. Outdoor pests were often location specific such as snails and slugs in Berkeley and chinch bug in Dallas. Other posts such as ants, mosquitoes and wasps were not so restricted. The source of most pest control information came from pest control operators. Most people personally used chemicals both indoors (62%) and outdoors (52%), and a sizable number had professional help (36%) who commonly used chemicals indoors and outdoors. People felt generally satisfied with the information they received about pest problems. They believed that pesticides do good and rarely thought they did harm. While many respondents (47%) said they had changed their attitudes towards greater caution in pesticide use, few (10%) knew the type of chemical used by employed professionals. Half the people (51%) had tried some nonchemical methods to control pests but were 11 somewhat less satisfied with these methods than with chemical ones. About half the respondents also said that they liked some insects, mainly because of their utilitarian value. Comparison of the 61% of homeowners having and the 39% not having indoor pest problems (Levenson and Frankie, 1983) showed that those who had indoor insect problems had a greater likelihood of having outdoor pest problems. They were also more likely to have obtained lnfonnation about pest problems and were more likely personally to use chemicals indoors. In addition, those with an indoor problem used chemicals significantly more frequently indoors. However, they also personally tried more nonchemical means of control. Fifty-one percent of those with indoor problems said that their attitudes had changed versus 40% of those without problems. More people without than with Insect problems felt too many chemicals were used in insect control (25% to 11%). It was thought that people who do not have insect ‘ problems and thus who are not dependent upon chemicals can ”afford" the attitude that we should be more cautious, whereas those who do have insect problems might not have such a cautious attitude. People who were aware of beneficial insects were also found to be more likely to have had indoor and outdoor pest problems. It was thought that people who have pest problems were more sensitive to the presence of insects and therefore more likely to be aware of and sensitive to beneficial insects. It was also hypothesized that persons with awareness of beneficial insects may go to sources that would be consistent with their own ideas and beliefs. Thus, those who were not aware of beneficial insects might be more likely to seek people who would not inform them about beneficial insects. That is, people who were comfortable reaching for a spray can would seek people for help who were also comfortable with sprays. Assessing or detenninlng the needs of intended pest management clientele allows for more relevant and effective program development. A pilot effort to transfer integrated pest management (IPM) information on outdoor pests to urban homeowners in Meridian Township, Michigan, was begun in 1979 (Lambur et al., 1981; Fear of al., 1983). The Initial conponent of 12 Project PEST was a community needs assessment performed by means of a survey which identified types of pest problems experienced, how those problems were addressed, extent of reliance on pesticides and attitudes toward the use of alternatives to pesticides. In the case of Project PEST, researchers felt they would have ”missed the boat" in attenuating to deliver IPM information if they had not first determined the homeowners' needs. Knowing these needs allowed the researchers to focus on the plant groups and related pests that the homeowners were most concerned about. It also allowed researchers to develop urban pest management educational materials more in line with the preferences of the respondents (80% of respondents Interested in educational materials said they preferred manuals and demonstration yards to the traditional Extension education method of a workshop). In addition, the survey allowed the researchers to gauge respondents' receptivity to basic IPM principles and so determine if IPM could be promoted as a realistic pest management program Over 50% of the respondents indicated that they were willing to (1) accept low levels of posts on their plants, (2) spend more time on pest management and (3) seek out and pay more for resistant plant varieties. No major surveys were found in the literature that addressed pest problems and pest management practices of private or governmental institutions. However, implementation of institutional pest management programs has been discussed. Olkowski, et al. (1982), identified nine factors which can serve as psychological barriers to new program adoption in institutional settings. These included (1) inertia over the increased attention and mental effort that change requires, (2) desire to avoid negative implications regarding past decisions and performance suggested by requests to change, (3) fear of loss of personal authority (individuals may fear that their experience in the field will become devalued), (4) fear of loss of supervisory authority if the new program makes the system more efficient and a supervisor loses subordinates, (5) fear of loss of territory should a consultant or an impersonal decision-making procedure be instituted, 13 (6) fear of job loss (although some pest managers contradicted themselves by claiming that a new pest management program, particularly an IPM program, is too labor-Intensive while saying at the same time that it will cause job loss), (7) fear of ridicule should a program be supported that is assumed to be anti-pesticide (as IPM has been incorrectly assessed), (8) imagined difficulty in learning new technology and (9) fear of program failure should supervisory personnel believe that the program will not work even if it has been successful in similar situations. In 1976, Olkowski, et al. (1978) had worked on development of a model IPM program for the Palo Alto, CA school district. The community had formed an ad hoc parent-teacher committee for the purpose of reducing pesticide use in the schools. This committee met with representatives of the district and the researchers to develop a collaborative pest management effort. Although this led to a number of successful changes in pest management practices which resulted in pesticide reduction, district officials interested in the program found it difficult to find a way to allocate the funds necessary to make full program implementation possible. Three basic principles that apply in developing institutional urban IPM programs were summarized. These were: (1) One must have control over enough of the system to include the solutions to the problem being presented. For example, classroom cockroach management involves not just custodians but also requires the cooperation of teachers and student as the handling of lunch remains can be part of the problem. (2) It is essential to set up a communication system so that all the divisions or departments of the institution or system know what‘s going on. For example, a complaint on flies can be due to garbage stuck in the bottom of a school dumpster. A special request would need to be made of the sanitation company to have the material scaped loose and the dumpster washed with soap and water. (3) To be successful a strategy must be designed to provide something useful at every level in the institutional hierarchy. Principals, food service, maintenance and custodial personnel, teachers and students must all be involved and encouraged to cooperate. 14 MalLSunLen Most of the preceding surveys were conducted as personal or telephone interviews. Surveys can also be conducted as mailed questionnaries. These have the advantage of taking less researcher time and of being less threatening to respondents. However, without high return and completion rates, the credibility of such survey results are questionable. Heberiein and Baumgaitner (1978) reported that mailed survey return rates varied between an average of 46 percent for one mailing and an average of nearly 84 percent for four mailings (initial questionnaire mailing and three follow-ups). The return rates for 38 surveys reported by Dillman (1978), ranged from a low of 58 percent to a high of 94 percent. The absence of an interviewer means there is no way to gloss over construction deficiencies and there is no way to respond to any respondent queries. Extreme care must be taken in mail survey preparation and implementation. Othewvise, there can be varying and sometimes incorrect interpretations of survey questions. The Total Design Method (TDM) of Dilman (1978) has been developed as a step-by-step procedure for mail (and also teleohone) surveys. It covers details of question writing, questionnaire design, cover and endorsement letters, mailing procedures and follow-up notices. METHODOLOGY Winn Work on the questionnaire began January 1987 and continued until October 19th when the questionnaire packet was delivered for mail processing. Dillman’s Total Design Method for mail and telephone surveys (Dillman, 1978) was used as a guide during preparation and survey implementation, although some procedures were modified or omitted. Dillman's Total Design Method The TDM is a step—by-step procedure for mail (and also for telephone) surveys. Generally, the most difficult detail is designing questions which can obtain the kind of information desired. Question writing can be divided into three parts. They are (1) the kind of information sought, (2) the question stmcture, and (3) the actual choice of words. lnfomiatlon desired from survey respondents falls into four categories: attitude, belief, behavior and attributes. Attitudes concern how respondents feel about something. Questions are worded to indicate the direction of the respondent's feelings (e.g. favor vs oppose, prefer vs not prefer, good vs bad, right vs wrong, and desirable vs undesirable). Beliefs are what the respondents think to be this, that is, perception of past, present or future reality or actual knowledge of specific facts or opinion on issues for which there is no “correct” answer. Questions designed to acquire this type information are presented as choices (e.g. correct versus incorrect, accurate versus inaccurate, and what happened versus what did not happen). Behavior is what is actually done, or, more accurately, what the respondent perceives (believes) is done. Behavior questions ask respondents to describe actions taken. Attributes are 15 16 personal or demographic characteristics. Questions of this type ask respondents to categorize themselves according to specific measures. Question stnicture depends upon the nature of the response behavior asked of the respondent. Open-ended questions have no answer choices. Instead respondents create their own answers and state them in their own words. Close-ended questions with order choices have answer choices provided as a gradation of a single dimension of some thought or behavior. Respondents are to select the most appropriate place on the continuum for their response. Close-ended questions with unordered response choices have answer choices provided as discrete, unordered categories from which the respondent must choose the one that best reflects his or her situation. Partially close-ended questions have both provided answer choices and the option for respondents to create their own response. Question wording can be a challenge. Words must be selected that are uniformly understood. Care must be taken not to assume too much knowledge on the part of the respondent or to assume too much about the respondent's behavior. Questions cannot be too vague or too precise. They should not be objectionable or too demanding. They should not contain unconventional phrases or abbreviations nor should they contain double negatives. Additionally questions should not be double questions, containing more than one concept or request, and answer choices should be mutually exclusive. The TDM questionnaire design is a 6—1/8" by 8-1/4" booklet. Questions are ordered by importance, similarity in content, continuity of flow from one topic to another and with more objectionable questions placed after less objectionable ones. Very specific recommendations are made for spacing, printing and cover designs. The questionnaire should be pretested on three groups of people. The first group may be described as colleagues, the second consists of potential users of the data and the third are those people drawn from the population to be surveyed. 17 The questionnaire is mailed with a cover letter that communicates an appeal to the respondent for survey completion. A postcard follow-up is sent to all recipients exactly one week later. A second follow-up is mailed to nonrespondents exactly three weeks after the original mailout and a third and final follow-up is mailed seven weeks after the original mailing. School District Questionnaire Development. Desired lnfonnation (attitude, belief, behavior or attribute) was assessed so that questions could be structured and words selected that might best obtain that type information. Pest prevalence and acceptability included beliefs concerning what a pest is, the damage it does and the situation existing within school facilities. Pest management practices and application involved behavior. Questions about methods used, personnel who apply them, existence of guidelines, employment of pest control companies and maintenance of records all concerned behavior. Satisfaction with control achieved and practices used included both belief and attitude as did questions concerning sources of technical assistance and preparation and execution of new pest management programs. School district attributes to be solicited included the number of school buildings within the district, student enrollment, district community type (urban, suburban and niral) and location (by county). Questions were ordered along a descending gradient of pest management procedures, with assessment of pest presence occurring before management practices which occurred before evaluation of effectiveness and satisfaction with methods used. The questionnaire was assembled as a 28-page booklet which was 6-1/4" x 8-1/2”. No questions appeared on the front or back covers. These spaces were reserved for material that had the specific purpose of stimulating interest in the questionnaire. Several persons reveiwed the questionnaire as it was being developed. These included MSU faculty and staff (Drs. George Bird, Gary Simmons, Fred Stehr, Donald Newson, Department of Entomology; Dr. Frank Fear, Department of Resource Development; Dr. Bonnie Morrison, Urban Affairs Program; Dr. Bradley Parks, Center for Remote Sensing; Bruce 18 Montgomery, Doctoral Candidate Department of Educational Administration, Joel Lichty, Specialist, Department of Resource Development; Dr. Michael Lambur, Extension Specialist, Cooperative Extension, Virgina Tech; and Kathleen Cowles, former Michigan education staff member of Center for the Integration of Applied Sciences of John Muir Institute, Berkeley, CA. In addition, early drafts of the questionnaire were taken to Dth, Holt and Lansing School Districts for discussion with key personnel concerning content, format and target audience (individual schools versus entire districts). Mr. Stephan C. Ganett, Superintendent of Dewitt District, felt the questionnaire should be distributed to district superintendents who would after review, be able to direct it to the most appropriate individual within each district for completion. He thought the format was good but that the length might be intimidating. Dr. Richard J. Halik, Superintendent of Lansing School District, approved of the survey objectives and granted permission to speak with Dr. Clyde Carnegie, principal of Sexton High School. Dr. Carnegie felt the questionnaire was inappropriate on an individual school basis and referred comment back to Dr. Halik. A meeting was than scheduled with Mr. Lee Mason, Assistant Superintendent of Support Services and Mr. Charles Parrish, Custodial Services Director. They both expressed concern about confidentiality stating that many Lansing residents would be upset If they found out that a specific Lansing school admitted to having a cockroach problem. They felt the survey needed to be conducted on a district basis and that they would not support a survey directed toward individual schools. They requested that a letter be sent to them describing the survey’s purpose, the individuals/institutions conducting the survey, the use to be made of survey results and a guarantee of anonymity. Mr. Mason said he would forward the letter to Dr. Grace Iverson of Evaluation Services to clear Lansing's participation. A letter was prepared as requested. Dr. Henry Sienkiewicz, Superintendent of Hell District, referred discussion of the survey to Mr. Ronald Van Ennen, Director of Business Services. Mr. Van Ennen thought the survey was a good idea and that there should be no problem with completion of the questionnaire. He 19 volunteered to place the survey on the May 13th, Michigan School Business Officials meeting agenda. Menbers of this organization are involved in school facility planning and management. Copies of the questionnaire along with cover letter were distributed to seven committee merrbers. All indicated that the survey was a good idea and that the questionnaire looked reasonable. MSBO members Mr. James Sneathen (Grand Rapids Public Schools), Mr. Dennis Carpenter (Energy Consultant) and Mr. Van Ennen (Holt School District), were contacted again in September and sent a copy of the finished survey for final comment. All said that they thought there should be no problem with its completion. To encourage questionnaire completion, a memorandum of endorsement was obtained from Mr. Gary Hawks, Interim Superintendent of Michigan's Department of Education. This was obtained though the assistance of Mr. J.D. Snyder, Environmental Specialist, Office of the Govemor. The endorsement accompanied the questionnaire at distribution. 1 Per University regulations, no survey research can be conducted without approval of the University Committee on Research in Human Subjects (UCRIHS). Therefore, on June 24th, a draft of the questionnaire and cover letter addressed to the School District Superintendents was submitted to Dr. Henry Bredeck, Chalnnan. Since the data being collected concerned public institutions, request was made that the questionnaire be exempt from full committee review. Exemption was granted and approval given for conduct of the project on June 25, 1987. A copy of the final questionnaire and cover letter was taken to Dr. Bredeck prior to distribution and received verbal approval October 5th. The questionnaires were mailed with cover letter, memorandum of endorsement and a staimed, preaddressed return envelop to school districts within the state of Michigan on October 19, 1987 (see Appendices A, B and C). Districts which had not responded by the requested November 15 return date, were sent a postcard reminder November 17. 20 W The State of Michigan is divided into 567 school districts (Figures 2A and 2B) which, according to the 1988 edition of the Michigan Education Directory and Buyers Guide, range in size from 1 to 280 buildings and from 2 to 185,000 students. (Population lnfonnation was obtained from MSBE Bulletin 1011 for 11 districts and from MSBE Bulletin 1014 for 37 of the districts.) For comparison purposes, districts were grouped into three classes based on number of buildings. These divisions conelated with degree of management hierarchy pertaining to pest management responsibility (personal communication, Dennis Carpenter, MSBO). In class 1 districts (1 to 3 buildings), the superintendent is in charge of management and supervises actual maintenance. In class 2 districts (4 to 10 buildings), the business manager has ultimate responsibility for pest management while a maintenance director is in charge of actual daily duties. In class 3 districts (11 plus buildings), a hierachy exits with either a separate maintenance supervisor, custodial supervisor, transportation supervisor, etc. under the direction of the business manager (11-20 buildings), or the different supervisors under the direction of a maintenance director who works in cooperation with the business manager (21 -30 buildings), or a variety of categorizations based on several criteria including union and nonunion members, all under the coordination of the business manager (30 plus buildings). The districts were also grouped into 5 classes based on student population: (1) 0-1000, (2) 1001-2500, (3) 2501-5000, (4) 500140.000, and (5) 10,000 plus. These divisions were selected to give a distribution for comparison purposes when analyzing questionnaire returns. The districts were further grouped by location within the state. Southern lower peninsula (SLP) districts reside in counties south of Highway M-46 or in Kent and Muskegon counties. Northern lower peninsula (NLP) districts are those found within the remainder of the lower peninsula. Upper peninsula (UP) districts are those found within counties in the upper peninsula. These divisions were made based on observations expressed by Dennis Carpenter, é -%‘rz?;-7é aé =§g4f§€€t1$i=urs ’" Tb aigfigfifie 5’ .5- én g :1 i- Message-r FIOUI’O 2.A. Michigan LOWSI‘ Peninsula SChOOI Districts. Districts above the dark line are located in the northern lower peninsula while those below the dark line are in the southern lower peninsula. Source: Michigan Education Directory and Buyers Guide, 1988. 23 MSBO. A variety of districts occur in the southern lower peninsula . Typical niraI/suburban districts are eight to nine buildings in size while large districts can include 60 to 80 buildings. The Detroit school district alone has 280 buildings (Michigan Education Directory and Buyers Guide, 1988). Many northern lower peninsula districts are three to six buildings in size, although some urban/suburban districts have 15 to 20. The majority of upper peninsula districts are small with one to three buildings. Again, urban/suburban districts are larger with 15 to 20 buildings. W Data analysis was performed using the SAS PC 6.03 statistical package and the Statview 512+ program for the Macintosh. The Chi-Square Goodness of Fit test was used when comparing the observed frequency distribution of a specific response with the expected frequency for classes of the attribute being examined (Conover, 1980). Expected frequencies ' were calculated by multiplying the number of answering districts within the specific attribute classes by the percent response of all districts. Most comparisons were made with this test. As some districts did not select a response to each question part and as others selected the do not know response, it was decided that the most accurate statistical comparison would be the distribution of those districts selecting positive responses to the expected distribution by attribute class. Responses to specific questions which tested significantly different for districts grouped by size were examined in futher detail. The proportions of the three classes which selected the tested response were compared to determine which were significantly different from each other. Two proportions were compared at a time by calculating pooled 95% confidence intervals using the formula [31-62 :t 1.96 s.e. «31-62) with s.e. (331-62) equal to the square root of [61(1-61)1/n1+[62(1-62)yn2 (Berry and Lindgren, 1986). Those intervals which included zero supported the null hypothesis of no difference between the two classes. Chi-Square was also used to test the measure of dependence of categories of data, such as always, often and sometimes or selection of different personnel types, against district classes of 24 a specific attribute. Pearson's correlation coefficient was used to assess the degree of correlation between types of district attributes or two different responses. ANOVA was used to test for significant differences in the total number of pest problems reported by districts classed by the different attributes and by actual number of school buildings. Student-Newman-Keuls means separation test was used to determine significant differences between levels of independent variables. RESULTS AND DISCUSSION [aluminium On October 19, 1987, questionnaires were mailed to all Michigan school districts except for 2 which were accidentally omitted. Of the 569 distributed, 329 or 58%, were returned between October 30th and March 22, 1988. One of these was returned as unusable since a duplicate mailing had been made, three were returned as unusable since the addressed districts had merged with adjacent districts, and 14 were returned incomplete and so could not be included In analysis. More than half of the returns (70.7%, 220 of 311) were received prior to the November 17th postcard mailing. An additional 45 districts (14.5%) returned their questionnaire during the week immediately following postcard distribution and so could not have been Influenced by postcard receipt. Of the 301 districts receiving a timely postcard reminder, an additional 60 (19.3%) returned their questionnaires. Wald“: Questionnaires were coded with Identification numbers so that attributes of the returned questionaires could be compared to the master list of all districts. Comparison of 310 usable returns (54.7% of all districts) to the 567 state school districts showed that they did not differ significantly from the expected distribution of districts according to number of school buildings, student population and location (Table 1, Figure 3). (One district could not be included In this comparison as Its identification number had been removed.) Therefore, results obtained from these returns were representative of the entire state school district system. 25 26 .8892. 58.8930 .2 ocon was new SEES. on .o: p.38 858% 9.0: 3.5 223 Be .3825 3.33m 38.5.... o... 6 3.3m 82 o... 52. 3523 5.23.... 83 233.... F 5 o 8 Sm course 3 3:52 .98 8.3. mm: 8 .23. 8.8. 3 N 393...... 8...: «a F :3... on»... bE:EEoo 8...: on 8...: mm .5: we 8 c: 8.8. m... 8.8. mm 8.8. 3. N a. 59.32 .5... 8.: «B... 8.5. mm. 8.3. :8 F c. 59.58 5:80.. 8.: m. .3. o. .3. 2.. 8 +52: .3. mm .5. mm 8.8. 88 e 887 SS .58. mm 8.8. on 8.8: a: m 88 - Sum 8.8. e: 8...... en. 8.8. Cu .e. 83 - 5.: 8.3. 3. «E... 8.88. we 8. 8. R. F 8.: - .. 5.8.2.8. 82.2w 88 : S. .3. 8 8.8. om m + 2 8.3. 8. .3: 3: 8...: emu N 8.4 .58. 8.: E... 8.9.. cm. .3: 9.8 F 8-. 82.2.3 .3232 .3532 383:8 .0... .3532 .0... .3532 850 23...... sets... 8.288". 3.3.8... ago :2832830 .2285 ..< 3 333.. 8.3.5... 3. 28>-.. 2.8.3.8 muse... .0.__ac:o=ao:O 05530: 309:. .0 new 30.320 .Oocom =< *0 9.259.330 3:0:3< ._. Each Number of Districts 27 Distribution of All School Districts S M L SLP NLP UP 1 -1 000 I 1 001 -2500 2501 -5000 _ 5001 -1 0000 I 1 0000+ Egg; Distribution of Responding School Districts Number of Districts Figure 3. 032—1 '0.ch O 8 '- ,.'. 8 o 3 z 3 g g 3 District Attributes S 3' .— " O In 2501-5000 31 Attributes of Michigan School Districts. (Size, Location, Student Population) Information obtained from the Michigan Education Directory and Buyers Guide, 1988. 28 Most (294) of the school districts returning usable questionnaires completed the attribute section concerning number of buildings, student population, location and community type. Those that did not were assigned building (4 districts) and student population (5 districts) values found in the “1988 Michigan Education Directory and Buyers Guide”. Omitted locations were determined by district address. Eight districts said they represented more than one community type. These districts, along with 7 others which did not select any community type, were located on a state map. A community type was selected based on city location within the district and comparison with the community type selected by neighboring districts which returned questionnaires. Attributes of the returnees as reported by the districts varied slightly compared to lnfonnation in the school district master list. In general, respondents said they were larger when _ compared by number of buildings and about equally divided between being smaller or larger when compared by student population. For purposes of this study, it was assumed that non- retumees would have also varied in reporting their school district attributes. School district population and number of school buildings within a district were closely related. For the 310 usable returns which could be compared to the school district master list, a Pearson correlation coefficient of .9963 was obtained between these two attributes. As pest management practices relate primarily to school buildings, only the school district building attribute along with location and community type were used for comparison of questionnaire answers. Distribution between building classes was reported as 34.7% (108 districts) for one to three buildings, 52.4% (163) for four to ten buildings, and 12.9% (40) for eleven and more buildings. Location of school districts returning questionnaires was distributed as 62.1% (193) in the southern lower peninsula, SLP, 27.3% (85) in the northern lower peninsula, NLP, and 10.6% (33) in the upper peninsula, UP. Community types were reported as 10.3% (32) urban, 30.2% (94) suburban and 59.5% (185) rural. Figure 4 shows the distribution of the districts by these Number of Districts Number of Districts 29 Distribution by Size, Location, and Community Type 200 150 100 50 District Attributes Distribution by Number of Buildings 50 40 " 30 ‘ 20' “Hnflflnnnr....fln n..? Ill'lllllllll . c . S uv-NMVU'WOIOOINO v-v-‘v-V'v-v-v-v- v-NNW Dlstrlct Size 33 Figure 4. Reported Michigan School District Attributes. 30 reported attributes as well as by the actual number of district buildings. Table 2 shows how these different attributes were related. in general, districts with small building numbers were associated with rural communities while large districts were located in suburban and urban communities. Small districts were predominant in the upper peninsula while large districts occurred primarily in the southern lower peninsula. Mid-sized districts were distributed between community types and occurred in all three locations. A moderate correlation existed between the different attribute types when the actual number of buildings reported by each school district was compared to district location (-O.3469) and to community type (-O.4481). When the building attribute class number was used, these correlations decreased to -0.1559 (location) and to -0.3243 (community type). The correlation of location to community type was 0.2713. Respondents of 259 of the questionnaires identified themselves by their positions within the districts (Table 3, Figure 5). Eighty-nine of these were administrative, (e.g. superintendent, assistant to the superintendent, principal, business manager, secretary to the board), 165 were support service personnel (e.g. maintenance, custodial, transportation and grounds directors), and five were a combination of two individuals, one administrative and the other support service. Fewer administrators completed questionnaires for the large districts (17.6%) and medium sized ones (27.7%) than did so for the small districts (51.1%). This was expected as the three class divisions were based on information received concerning pest management responsibility (see Methodology). However, responses made by the two personnel groups may have varied. In particular, administrators may have perceived different pest problems than support service personnel. To test this hypothesis, the average number of pests reported as probierns by the different groups for each district size that had at least two of each personnel type responding were compared. Questionnaires completed jointly by an administor and support service person were included with support service responses. 31 CV no P mow £2.55 .0 59:32 .98. 6.3 d. 6.3 Ni 6.3 64 65m 63 o 6.3 F 6.3 6 593:6 6.3 o 6.3 6 6.3 6 :85 2225.8 .5 8:83 6.3 6 6.3 on 6.6: 8 65m 63 F 6.3 F 6.: v 5935 6.3 F 6.3 F 6.3 o :3: 2225.8 n: 56582 5:80.. 6.3 6 6.6: Fm 6.5 mm 65m 6.3 66 6.va 9. 6.3 F 5938 6.3 o F 6.3 6 F 6.3 F :35 525.8 n: 69.58 5:83 8533. +FF 352.6 34. 8:28 «F 69.6.3 .3532 E .8532 3 695:2 g 6252 2352 2865 2058 22.65 6:25.830 2:238 82.85 3 8:89... 8.52.66 23:5 .6 2...: 32 Table 3. Comparison of Number of Pest Problems Reported by Administrator and Support Service Respondents (Mean 1 SD ). Number of Districts Reporting Mean 13:) Number of Pest Problems by Respondent: Differences District Administrators Support Service Staff Used for Calculated Size Num. Mean1SD Num. Mean1SD Testing+ T Values 1 17 404713.297 5 380013.493 0.847 0.897 2 15 4.60012.849 12 591713.704 -1.317 1.865 3 12 450012067 25 684013.132 -2.340 4. 2 9 0' 4 19 5.52612.611 13 861512.663 -3.089 5.280* 5 8 6.62512.560 21 733313.411 -0.708 1.019 6 3 700014.583 18 750012.728 -0.500 0.386 7 3 700012.646 16 700013.521 0 8 1 7.000 10 940013.340 9 1 4.000 12 7.16712.480 10 3 733312.517 7 728312.563 0.047 0.043 1 1 2 350010.707 3 533315033 -1.833 1.286 12 2 10.50012.121 1 4.000 13 0 0.0 1 10.000 14 0 0 3 1000013000 15 0 0 5 7.60014.336 17 0 0 2 1100012828 19 0 0 0 0 20 0 0 0 0 22 1 8.000 0 0 24 1 9.000 0 0 27 0 0 1 8.000 28 0 0 1 7.000 30 0 0 1 7.000 32 0 0 3 7.00016.083 33 0 0 2 800015.657 38 0 0 1 5.000 44 0 0 1 10.000 65 0 0 1 10.000 84 0 0 1 15.000 280 0 0 1 15.000 Total Number Districts 88 167 *Indlcates a significant difference as does bOld type. +A P-value of 0.039 was calculated using the Wilcoxon Signed Rank Test. 33 50 40' a E u l- 3 30‘ I NoAnswer a I e '6 SupportServrce 3 20' I Administration a . E z 10- II IIIIIIIIIIIIIII'TTTTWII ' "‘ ”W N District Size Figure 5. Distribution of Administrative and Support Services Staff as Questionnaire Respondents By Actual District Building Size. 34 T-test results showed significant response differences for three and four building districts with support service personnel reporting more pest problems than administrators. A significant difference (p-0039) was also found when the Wilcoxon Signed Rank Test was used to corrpare responses of the nine testable district sizes as a group. This indicates that the mean number of reported pest problems for the small sized district group was most affected by the administrators reduced pest perception and that small districts may have actually had more pests and have been more similar to medium sized districts than was determined in the following survey analysis. WM General Pest Occurrence More than half of 300 responding districts (52.7%) said that pests were a current problem within their school buildings or on their school grounds (CHY. Forty-five percent said that pests had previously been a problem but were not a current problem and 2.3% said pests have never been a problem (Table 4). A significant difference in response was found between districts classed by size and location. More large districts (77.0%) had a current problem than did medium and small ones (54.7% and 40.9%) while more districts in the lower peninsula (56.4% southern, 54.3% northern) had a current problem than did those in the upper peninsula (25.8%). There was no difference in district response when grouped by community. A conparison was made between the proportion of districts for each size class which indicated a current pest presence. A separate comparison was made between the proportion of districts which indicated a previous pest occurrence. The proportion of the size classes which indicated a current pest presence were all significantly different from one another (40.9%-S, 54.7%-M, 77.8%-L), while the proportion of small and medium size districts which indicated a ‘The notation (Ci-number) refers to the survey question number. 35 Table 4. Pest Occurrence within School Districts. Districts P-Value for Response Selection Pest Selecting Based on District: Occurrence Number (% of 300) Size Location Community Current 158 (52.7) 0.001 * 0.01 1 ' 0.441 Previous 1 35 (45.0) Never 7 (2.3) District Distribution (as Percent of Attribute Class) Pest Size Location Community Occurrence S M L SLP NLP UP U S R Current 40.9 54.7 77.8 56.4 54.3 25.8 51.7 60.4 48.9 Previous 54.3 44.0 22.2 42.5 42.0 67.7 44.8 38.5 48.3 Never 4.8 1.3 0.0 1.1 3.7 6.5 3.5 1.1 2.8 Number of Districts 105 159 36 188 81 31 29 91 180 'Indicates significant difference between classes 0t dlStl’lCt attribute. 36 previous pest occurrence were not different from one another but were both different from the proportion of large class districts (54.3%-S, 44.0%-M, 22.2%-L). Slightly more than 75% of 297 responding districts said that no pests are acceptable. 21.5% said a few are not of concern as long as they do not harm people and 1.3% said there is no concern over pest presence (Table 5). No difference was found in district response for any attribute comparison. Important Pest Concerns Head lice was selected as the most important school district concern by 37.4% of 302 responding districts (Q-3, Table 6). Cockroaches, rats, mice, ants and stinging insects followed (19.5%, 8.9%, 7.9%. 6.6% and 6.3%). All other listed pests were selected by fewer than 5% of the districts. Silverfish and communicable diseases were written as 'other' pests. Cockroaches were the only pest for which a significant difference was found in selection for any attribute comparison. it was most important to districts which were large, in the southern lower peninsula and in urban communities. A comparison was made between the proportion of districts for each size class which indicated that cockroaches were the most important school concern. Each proportion was significantly different from the other two (80%-S, 20.8%-M, 44.7%-L). Head lice remained the most important school district concern when districts selecting the different pests as either 151, 2nd or 3rd in importance were totaled, being selected by 64.6% of the districts (Table 7). Mice became second most important, cockroaches third, stinging insects fourth, ants fifth and rats sixth (46.4%, 42.7%, 36.4%, 31 .1%, and 21.9%). Flies and termites (12.3% and 10.9%) followed. All other pests were selected as a 1st, 2nd or 3rd concern by less than 10% of the districts. Silverfish, millipedes, eamigs, hardsheiled bugs, ground schools and communicable diseases were written in as 'other' pests. Again, a significant difference was found between district selection of cockroaches when grouped by any attribute. A significant difference also existed for rats, termites and bats when grouped by location and for files when grouped by community type. Rats and bats were most inportant to districts in the upper 37 Table 5. Number of Pests Acceptable to School Administrators. Districts P-Value for Response Selection Number Selecting Based on District: Acceptable Number (% of 297) Size Location Community Many 4 (1.3) 0.242 0.463 0.257 Few 64 (21.5) None 229 (77.1) District Distribution (as Percent of Attribute Class) Number Size Location Community Acceptable S M L SLP NLP UP U S R Many 1.0 1.9 0.0 0.5 2.5 3.2 0.0 1.1 1.7 Few 28.2 19.0 13.9 19.9 25.0 22.6 6.9 20.9 24.3 None 70.9 79.1 83.1 79.6 72.5 74.2 93.1 78.0 74.0 Number of Districts 103 158 36 186 80 31 29 91 177 38 Table 6. Pest Selected as the Most important School District Concern. Districts Selecting Pest P-Value for Selection of Pest Based on District: Pest Number (% of302) Size Location Community Head Lice 113 (37.4) 0.226 0.127 0.359 Cockroaches 59 (19.5) 0.000' 0.004" 0.000' Rats 27 (8.9) 0.664 0.120 0.857 Mice 24 (7.9) 0.174 0.590 0.102 Ants 20 (6.6) 0.864 0.811 0.126 Stinging insects 19 (6.3) 0.229 0.730 0.670 Termites 1 3 (4.3) .+ . . Carpenter Ants 7 (2.3) Flies 6 (2.0) Bats 5 (1.7) Fleas 3 (1.0) Mosquitoes 2 (0.7) Birds 1 (0.3) Other 3 (1.0) Distribution of Districts Selecting Pest (as Percent of Attribute Class) Size Location Community Pest S M L SLP NLP UP U S R Head Lice 44.8 35.2 26.3 31.9 47.6 43.8 25.8 34.1 41.1 Cockroaches 8.6 20.8 44.7 26.1 9.8 6.3 45.2 27.5 11.1 Rats 8.6 10.1 5.3 8.5 6.1 18.8 6.5 9.9 8.9 Mice 3.8 10.1 10.5 8.5 8.5 3.1 0.0 12.1 7.2 Ants 7.6 6.3 5.3 6.4 6.1 9.4 0.0 4.4 8.9 Stinging insects 9.5 5.0 2.6 6.9 6.1 3.1 3.2 5.5 7.2 Termites 4.8 4.4 2.6 6.4 0.0 3.1 6.5 3.3 4.4 Carpenter Ants 3.8 1.3 2.6 1.1 6.1 0.0 0.0 1.1 3.3 Flies 3.8 1.3 0.0 1.6 3.7 0.0 3.2 0.0 2.8 Bats 1.0 2.5 0.0 1.6 1.2 3.1 6.5 1.1 1.1 Fleas 1.0 1.3 0.0 0.5 2.4 0.0 0.0 0.0 1.7 Mosquitoes 1.0 0.6 0.0 0.0 2.4 0.0 0.0 1.1 0.6 Birds 1.0 0.0 0.0 0.0 0.0 3.1 0.0 0.0 0.6 Other 1.0 1.3 0.0 0.5 0.0 6.3 3.2 2.3 1.1 Number of Districts 105 159 38 188 82 32 31 91 180 *indlcates significant difference between classes of district attribute. +No corrparison made as fewer than 5 selecting districts in 2 or more attribute classes. 39 Table 7. Pests Selected as One of the Three Most important District Concerns. Districts Selecting Pest P-Value for Selection of Pest Based on District: Post Number (% of 302) Size Location Community Head Lice 195 (64.6) 0.252 0.449 0.304 Mice 140 (46.4) 0.267 0.369 0.312 Cockroaches 129 (42.7) 0.000' 0.002' 0000* Stinging insects 1 10 (36.4) 0.503 0.666 0.545 Ants 94 (31.1) 0.314 0.212 0.164 Rats 66 (21.9) 0.487 0.047” 0.944 Files 37 (12.3) 0.206 0.171 0.029' Termites 33 (10.9) 0.224 0.001 * 0.304 Carpenter Ants 25 (8.3) 0.944 0.821 0.925 Bats 19 (6.3) 0.532 0 .007' 0.936 Fleas 1 1 (3.6) + . . Birds 7 (2.3) Weeds 7 (2.3) Mosquitoes 5 (1 .7) Skunks 4 (1 .3) Outdoor Plant Pests 2 (0.7) Outdoor Plant Diseases 1 (0.3) Other 7 (2.3) Distribution of Districts Selecting Pest (as Percent of Attribute Class) Size Location Community Pest S M L SLP NLP UP U S R Head Lice 72.4 63.5 47.4 60.1 70.7 75.0 45.2 62.6 68.9 Mice 43.8 44.0 63.2 49.5 45.1 31.3 48.4 54.9 41.7 Cockroaches 24.8 47.8 71.1 53.2 26.8 21.9 71.0 58.2 30.0 Stinging insects 41.9 34.0 31.6 38.3 35.4 28.1 29.0 33.0 39.4 Ants 28.6 35.2 21.1 28.2 40.2 25.0 25.8 23.1 36.1 Rats 25.7 20.8 15.8 20.7 1 7.1 40.6 22.6 23.1 21.1 Files 17.1 9.4 10.5 9.6 18.3 12.5 6.5 5.5 1 6.7 Termites 6.7 13.8 10.5 16.5 1 .2 3.1 19.4 11.0 9.4 Carpenter Arrts 7.6 8.8 7.9 8.0 9.8 6.3 9.7 8.8 7.8 Bats 5.7 7.5 2.6 3.7 7.3 1 8.8 6.5 5.5 6.7 Fleas 3.8 3.1 5.3 3.7 4.9 0.0 6.5 1.1 4.4 Birds 1.9 1.9 5.3 1.6 2.4 6.3 3.2 3.3 1.7 Weeds 1.9 3.1 0.0 0.5 6.1 3.0 0.0 3.3 2.2 Mosquitoes 2.9 1.3 0.0 1.6 2.4 0.0 0.0 1.1 2.2 Skunks 1.0 1.3 2.6 0.5 3.7 0.0 0.0 1.1 1.7 Outdoor PP 0.0 1.3 0.0 0.5 0.0 3.1 0.0 0.0 1.1 Outdoor PD 1.0 0.0 0.0 0.0 0.0 3.1 3.2 0.0 0.0 Other 2.9 1.3 5.3 1.6 2.4 6.3 3.2 2.2 2.2 Number of Districts 105 159 38 188 82 32 31 91 180 tindlcates significant difference between classes of district attribute. +No comparison made as fewer than 5 selecting districts in 2 or more attribute classes. 40 peninsula while termites were most important to those in the southern lower peninsula. Flies were most inportant to rural communities. Specific Pest Numbers Needing Management The number of a specific pest that the majority of school districts considered a problem needing management depended on the specific pest (Q-4,Table 8). Although 307 districts responded to the question, several did not respond to each pest (6 to 31). Eighty-two point four percent of the districts answered that the presence of just one rat required action. Head lice, bats, cockroaches, termites and mice also required management with the presence of just one according to the majority of responding districts (70.4%, 60.3%, 56.4%, 52.4% and 49.2%). The percent of districts requiring management for just one of any other pest was below 35%. Almost 60% of the districts answered that the presence of a few carpenter ants would require action. The majority of districts also selected the presence of a few for other ants, stinging insects, fleas. outdoor plant pests, flies, outdoor plant diseases and birds (58.0%, 54.1%, 53.7%, 47.9%, 45.3%, 41.4% and 34.9%). About 50% of the districts answered that many mosquitoes and weeds would need to be present before management became necessary (55.0% and 49.2%). Few significant differences were found in response selection between districts conpared by attribute classes. Non-responses were not included in district comparisons. No differences were found in response selection of any pest when compared by district size. Only bat, termite and mice responses were significantly different when compared by district location. More upper peninsula districts selected the presence of a few of these pests than did lower peninsula districts. Stinging insect and mosquito response selections differed significantly between districts grouped by community type. Rural and suburban districts tended to select the presence of a few in the case of stinging insects and many in the case of mosquitoes more often than did urban districts. 41 666.6 666.6 646.6 6.6 6.6.. F66 6.6 66663 . F66 .6 F666 6 F66 6.6 6 . 66 6.66 6.6 6625666: F F66 666.6 666.6 6.6 6.66 6 . 66 6.66 6666 666.6 666.6 666.6 F.6F 6.66 6. F6 6.6F 866665 6.6... .8960 666.6 666.6 666.6 6.6 6.3. 6.6.. 6.6 62.6 :66 666.6 666.6 F.6F 6.66 6.6.6 6 6.666 Ema .8650 666.6 666.6 66 F6 6.6 F.6F 6.66 6.66 666.6 . F 66 666.6 666.6 6.6 6.6 F .66 6.66 6.866. 656666 666.6 666.6 6 F66 6.6 6.66 6.66 6.6 6:2 666.6 666.6 F666 6.6 6.6F 6.66 6.6F 662 266.6360 666.6 .6 F66 666.6 6.6 6.6 6.6F. 6. 6e 862 R66 .6666 666.6 6.6 6.6 6.66 e. 66 6265.; 666.6 6666 R66 6.6 6.6 F66 6.66 62669.68 F666 . F666 62.6 6.6 6.6 26 6.66 666 F666 :66 666.6 6.6 3 6.66 6.66 8: 6661 :66 666.6 66 6.6 6.6 F..FF 6.66 6.66 $626860 66:666.. 66% +mz E62 36“. 6:0 .666 1.86.6.6 :6 68.66 66.2 56.62.. 6 8.66668 .8562 8 so“. .660 5 6686.66 .66 36>-.. 6686.66 2656.6 F66 .6 F6866 dongs: an «0:! ~05 5039.6. 5 62022.00 «not 0.2025 30am .0 53:52 .0 039—. 42 6.3.3.6 8520 F0 66666.6 .3652. 62.2656 262F296 6860.2... .666 6.6866 6... .6. 6660666. 6 66.56.66 6856.6 666266 2.8 666:. 66.... 68:69:81 66:866. 6: u m2+ 66 6F 66F 6.8.6.6 .2852 6.6 6.6 3 66.2 6.66 6.6.. 6.: :6... 6.6.. 6.66 6. F6 660 8.5. EF 66 66 6.6.56.6 F6 66 66F 6.2.6.6 .o .69.. :2 F6 .6952 F66 F66 6.6.. 6.62 6 6.6F 6.6 66.2 F66 6.66 F66 36”. 6.6.. 6.66 6.66 36“. 6.6 6.6 6.6 660 662.6666: 6.66 6.66 F66 660 2.666» 66F 66 66 6.66.6.6 F6 66 66F 2656.6 8.6252 .2352 6.6 F.FF 6.6 66.2 6.6 6.6F F..6F 66.2 6.66 6.66 6.66 so“. 6.6666. 6.6... 6.66 6.66 36“. F666 6.66 F66 660 66.6666 6.6 6.66 6.66 6.5 .66 m 6 2 6.6566666... .66.. .5 6.2 6.6 26566666: .66.. 6866.650 866.65% .6“. 9.5.66... 6686.650 E66285 .6". 9.5.56.6 56336.6 656.6 .8266 68356.6 8.5.6 6.8.6.. .3262 A9300. 0 03a... 43 Number of Actual Pest Problems The number of different pests that school districts reported as current or previous problems ranged from 0 to 15 with a total of 1966 for the 306 responding districts and an average of 6.4 per district (O-5, Table 9). ANOVA of the number of pest problems reported by the districts showed significant differences for districts classed by size, by location and by community type. An average of 5.1 pest problems occurred in one to three building districts, 6.9 pest problems in four to ten building districts and 8.1 pest problems in eleven+ building districts. Southern lower peninsula districts had an average of 7.0 pest problems, northern lower peninsula districts an average of 5.8 and upper peninsula districts an average of 4.6. Urban districts reported an average of 7.3 pest problems, suburban districts an average of 6.9 and mrai districts an average of 6.0. An ANOVA was also run on the number of pest problems reported by the different districts grouped according to their actual reported district building sizes (Table 10). A significant difference was found but the Student-Newman-Keuls means separation test showed that only the two largest districts (84 and 280 buildings) differed from districts with 19 buildings in their reported number of pest problems. This indicates that the significant difference found for the size class comparisons may have been an artifact of the district grouping. Seven pests (mice, head lice, ants, stinging insects, flies, weeds and mosquitoes) were indicated as having occurred in all the buildings of 18.6% to 39.9% of the responding districts while other pests were said to have occurred in all the buildings of fewer than 5% of the districts (Table 11). Mice, head lice, ants and stinging insects were said to have occurred in either 1/2 or 3/4ths of the buildings of an additional 10.1% to 19.6% of the districts. Fewer than 10% of the districts said that any of the other listed pests occurred in as many buildings. All the pests were said to occur in at least 1/4 of the buildings of 8.8 to 28.8% of the remaining districts. Many districts said that none of their buildings had ever experienced certain pest problems. Rats led this category with 72.5% of the districts while head lice was last with only 16.3%. A number of districts did not know whether specific pests were problems. This ranged from a low 44 Table 9. Number of Different Pest Problems Experienced by School Districts Grouped by Attribute Class. Number of Districts Number of Districts Pest Problems Number (% of 306) Pest Problems Number (% of 306) 0 1 1 (3.6) 8 23 (7.5) 1 1 2 (3.9) 9 22 (7.2) 2 13 (4.3) 10 27 (8.8) 3 26 (8.5) 1 1 8 (2.6) 4 38 (12.4) 12 10 (3.3) 5 23 (7.5) 13 4 (1 .3) 6 32 (10.5) 14 8 (2.6) 7 46 (15.0) 15 3 (1.0) Distribution of Districts with Specified Number of Pest Problems (as Percent of Attribute Class) Number of Size Location Community Post Problems S M L SLP NLP UP U S R 0 7.6 1.3 2.5 2.1 3.7 12.1 6.3 3.3 3.3 1 7.6 2.5 0.0 2.1 6.2 9.1 6.3 1.1 5.0 2 8.5 2.5 0.0 5.2 2.5 3.0 0.0 4.4 5.0 3 7.6 9.4 7.5 5.7 9.9 21.2 12.5 8.7 7.7 4 13.2 10.6 17.5 10.4 16.1 15.2 3.1 14.1 13.2 5 9.4 7.5 2.5 6.8 12.4 0.0 9.4 4.4 8.8 6 15.1 8.8 5.0 10.4 9.9 12.1 0.0 8.7 13.2 7 12.3 18.1 10.0 17.2 13.6 6.1 15.6 14.1 15.4 8 6.6 8.8 5.0 8.9 4.9 6.1 6.3 6.5 8.2 9 3.8 8.1 12.5 8.9 4.9 3.0 6.3 10.9 5.5 10 2.8 11.3 15.0 8.9 8.6 9.1 12.5 12.0 6.6 11 1.9 3.8 0.0 3.1 2.5 0.0 3.1 2.2 2.8 12 2.8 2.5 7.5 3.7 2.5 3.0 6.3 3.3 2.8 13 0.0 1.3 5.0 1.0 2.5 0.0 0.0 2.2 1.1 14 0.9 3.1 5.0 4.2 0.0 0.0 6.3 4.4 1.1 15 0.0 0.6 5.0 1.6 0.0 0.0 6.3 0.0 0.6 Number of Districts 106 160 40 192 81 33 32 92 182 Total Number of Pest Problems+ 537 1106 323 1345 470 151 235 632 1099 MeanNumber ofPestPriobiems++ 5.1a 6.9b 8.1c 7.03 5.8b 4.6c 7.3a 6.9ab 6.0b +There was a total of 1966 pest problems experienced by all 306 districts and an average of 6.4 pest problems for each. ++ANOVA of the number of pest problems reported by the districts showed a significant difference for districts classed by size (p = 0.000), by location (p - 0.000) and by community type (p a 0.036). Means followed by the same letter did not test significantly different using Student-Newman-Keuls means separation test. 45 Table 10. Comparison of Number of Pest Problems Reported by Districts Grouped by Actual District Building Size. Number Mean District of Number f D stricts Reporting Number of Pest Probierns+ Number Size Districts 0 1 2 3 4 5 6 7 8 9 10 1 1 12 13 14 15 Problems 1 28 5 4 3 2 1 2 5 3 1 1 1 3.93b 2 35 3 2 3 2 7 2 6 3 3 1 1 1 1 5.0ab 3 43 2 3 4 6 6 5 7 3 2 2 1 1 1 5.9ab 4 34 1 1 5 2 4 1 5 4 3 6 1 1 6.7ab 5 34 1 4 4 2 5 10 1 1 2 1 3 6.8ab 6 28 1 2 1 1 2 2 6 2 2 4 1 1 2 1 6.6ab 7 23 1 3 5 2 3 3 1 3 1 1 6.4ab 8 1 3 1 1 1 1 2 2 1 2 1 1 8.8ab 9 1 4 1 2 1 1 5 1 2 1 6.9ab 1 0 14 1 1 1 1 3 2 1 3 1 7.2ab 1 1 6 1 1 2 1 1 4.5ab 1 2 3 1 1 1 8.3ab 1 3 2 1 1 1 1 .0ab 1 4 3 1 1 1 10.0ab 1 5 6 2 1 1 1 1 7.8ab 1 7 2 1 1 1 1 .0ab“ 1 9 1 1 3.0a 20 2 1 1 8.0ab 22 1 1 8.0ab 24 1 1 9.0ab 27 1 1 8.0ab 28 1 1 7.0ab 30 1 1 7.0ab 32 3 1 1 1 8.0ab 33 2 1 1 5.0ab 38 1 1 5.0ab 44 1 1 10.0ab 65 1 1 10.0ab 84 1 1 15.0b 280 1 1 150b +ANOVA of number of pest problems reported based on district size showed a significant difference with a P-value a 0.000. Student-Newman-Keuls means separation test showed that districts with 84 and 280 buildings were significantly different in their reporting of number of pest problems from districts of 19 buildings in size. All other district sizes were not significame different from one another. (Means followed by the same letter were not significantly different from one another.) 46 Table 11. Portion of District School Buildings with Pest Problems. Percent of 306 Districts indicating Portion of School Buildings as Previously or Currently Experiencing the Specified Pest Pest None 1/4 1/2 3/4 Ali DNK NR+ Mice 18.3 28.8 15.4 4.9 27.5 3.3 2.0 Head Lice 16.3 25.5 19.6 10.1 18.6 7.2 2.6 Ants 19.0 26.1 15.4 6.2 24.5 6.2 3.3 Stinging insects 18.3 25.8 15.4 2.6 27.5 7.5 2.9 Flies 23.9 15.0 6.5 3.3 39.9 6.5 4.9 Weeds 28.1 8.8 7.8 2.3 38.2 8.8 5.9 Mosquitoes 43.1 11.8 5.6 1.0 23.2 9.5 5.9 Cockroaches 50.0 20.3 9.5 3.9 4.9 8.2 3.3 Birds 59.5 17.3 3.6 1.0 4.6 8.8 5.2 Bats 63.4 15.4 2.6 0.3 2.0 11.4 4.9 Outdoor Plant Pests 48.7 9.2 3.7 0.7 3.9 23.5 10.8 outdoor Plant Disease 52.0 11.4 1.3 0.3 3.6 21.9 9.5 Carpenter Ants 62.4 10.1 3.3 1.0 2.3 14.7 6.2 Termites 66.3 10.8 4.2 1.3 0.3 12.1 4.9 Fleas 63.7 9.2 2.6 0.3 2.0 17.0 5.2 Rats 72.5 9.8 1.6 0.0 1.6 9.5 4.9 _ Districts indicating Positive Pest P-Value for Positive Pest Presence Presence“ in School Buildings Based on District: Pest Number (% of 306) Size Location Community Mice 234 (76.5) 0.304 0.358 0.959 Head Lice 226 (73.9) 0.721 0.551 0.258 Ants 221 (72.2) 0.120 0.260 0.561 Stinging insects 218 (71.2) 0.102 0.001' 0.790 Files 198 (64.7) 0.568 0.594 0.322 Weeds 175 (57.2) 0.067 0.337 0.300 Mosquitoes 127 (41.5) 0.987 0.476 0.720 Cockroaches 118 (38.6) 0.000" 0000* 0000* Birds 81 (26.5) 0.020' 0.620 0.040" Bats 62 (20.3) 0.454 0.309 0.889 Outdoor Plant Pests 52 (17.0) 0.004' 0012* 0.137 Outdoor Plant Disease 51 (16.7) 0.063 0.068 0.255 Carpenter Ants 51 (16.7) 0.001' 0.037' 0.172 Termites 51 (16.7) 0.133 0.000' 0.002' Fleas 43 (14.1) 0006* 0.139 0.022' Rats 40 (13.1) 0.391 0.981 0.143 Table 11 (cont'd). Distribution of Districts indicating Positive Pest Presence (as Percerri of Attribute Class) Size Location Community Pest S M L SLP NLP UP U S R Mice 67.0 79.4 90.0 80.7 74.1 57.6 78.1 78.3 75.3 Head Lice 68.9 77.5 72.5 70.3 82.7 72.7 59.4 69.6 81.9 Ants 58.5 79.4 80.0 77.1 69.1 51.5 62.5 79.3 70.3 Stinging insects 57.5 76.9 85.0 84.4 56.8 30.3 71.9 76.1 68.7 Files 59.4 69.4 60.0 65.6 67.9 51.5 53.1 57.6 70.3 Weeds 43.4 64.4 65.0 62.0 50.6 45.5 65.6 65.2 51.6 Mosquitoes 41.5 41.9 40.0 40.1 48.1 33.3 43.8 37.0 43.4 Roaches 12.3 46.9 75.0 49.5 23.5 12.1 68.8 53.3 25.8 Birds 21.7 24.4 47.5 28.6 22.2 24.2 37.5 34.8 20.3 Bats 16.0 23.1 20.0 20.3 16.0 30.3 21.9 21.7 19.2 Outdoor PP 9.4 17.5 35.0 22.4 7.4 9.1 25.0 19.6 13.7 Outdoor PD 10.4 18.1 27.5 20.8 9.9 9.1 25.0 21.7 13.2 CarpenterAnts 6.6 19.4 32.5 20.8 12.3 3.0 25.0 20.7 13.2 Termites 10.4 19.4 22.5 24.5 4.9 0.0 40.6 15.2 13.2 Fleas 7.5 14.4 30.0 16.7 12.3 3.0 31.3 13.0 11.5 Rats 9.4 15.6 12.5 13.0 13.6 12.1 25.0 12.0 11.5 Number of Districts 106 160 40 192 81 33 32 92 182 +DNK - do not know, NR - no response. ++includes districts selecting 1/4, 1/2, 3/4 and All as estimated portion of school buildings previously or currently experiencing pest problems. 'indicates significant difference between classes of district attribute. 48 of 3.3% for mice to 17.0% for fleas. Although 306 districts answered the question, several (7 to 33) did not respond to all pests. Responses to this question were summarized by totaling the number of districts indicating that they currently or previously had problems with the specific pests regardless of the number of buildings involved. Mice were found to be the greatest pest problem with 76.5% of the districts citing its occurrence. Head lice, ants, stinging insects, flies, weeds, mosquitoes, cockroaches, bird and bats followed (73.9%, 72.2%, 71.2%, 64.7%, 57.2%, 41.5%, 38.6%, 26.5% and 20.3%). All other listed pest problems occurred in fewer than 20% of the responding districts. Nineteen districts indicated additional problems with five 'other' arthropods (millipedes, silverfish, earwigs, carpet beetles and spiders), one plant (sand burr) and seven vertebrates (woodchucks, chipmunks, racoons, weasels, gophers, moles and skunks). A significant difference was found in the presence of stinging insects between districts grouped by location, in the presence of cockroaches between districts grouped by classes of any attribute, and in the presence of bats between districts grouped by size. In general, large sized districts, districts located in the southern lower peninsula and districts in urban communities responded more frequently as having these specific pest problems. As noted in Table 11, additional significant differences existed for pests which occurred in fewer than 20% of the districts. To examine the prevalence of pest problems in more detail, the actual nurrber of school buildings experiencing each particular pest was calculated by multipiing the portion indicated as having problems by the number of buildings reported within each district. Flies were found to be most prevalent with half (50.8%) of 2389 buildings affected (Table 12). Mice, weeds, ants, stinging insects, head lice, roaches and mosquitoes followed (47.1%, 45.1%, 42.2%, 39.1%, 35.2%, 31.5% and 28.5%). All other listed pests occurred in fewer than 15% of all school buildings. 49 Table 12. Pest Occurrence within District School Buildings. School Buildings P-Value for Number of Buildings with with Specified Pest+ Pest Based on District: Pest Number (%) Size Location Community Files 1214 (50.8) 0.492 0.194 0.000‘ Mice 1125 (47.1) 0.520 0.046' 0.281 Weeds 1076 (45.1) 0.000' 0.166 0.000' Ants 1008 (42.2) 0048* 0.077 0.000' Stinging Insects 934 (39.1) 0.000' 0.001 * 0000' Head Lice 841 (35.2) 0000* 0.000' 0.000' Cockroaches 753 (31.5) 0.000' 0.000' 0.000' Mosquitoes 681 (28.5) 0.301 0.156 0.020' Birds 349 (14.6) 0.000' 0.187 0000* Outdoor Plant Pests 314 (13.1) 0.000' 0.000' 0000* Outdoor Plant Disease 280 (11.7) 0.000' 0.001" 0000" Carpenter Ants 256 (10.7) 0.000‘ 0006* 0.000“ Fleas 236 (9.9) 0.000" 0.013' 0.000' Termites 214 (9.0) 0.000‘ 0.000' 0.000' Bats 210 (8.8) 0.074 0003* 0.000' Rats 123 (5.1) 0.665 0.873 0000* Distribution of Buildings Experiencing Pest (as Percent of Attribute Class) Size Location Community Pest S M I. SLP NLP UP U S R Flies 46.8 52.5 50.1 50.6 54.7 40.5 53.3 41.7 59.1 Mice 42.2 47.3 47.8 48.0 46.5 30.8 50.3 45.2 45.9 Weeds 35.1 53.5 39.7 44.2 50.8 40.0 36.0 51 .4 47.0 Ants 39.5 46.0 39.3 42.0 46.4 30.1 27.5 53.5 43.9 Stinging insects 42.8 47.1 31 .4 40.5 38.0 16.3 29.5 40.2 47.7 HeadLice 40.5 43.1 27.3 32.7 42.5 56.1 27.1 31.6 47.9 Cockroaches 8.0 20.1 46.1 35.6 17.4 6.1 57.8 22.2 15.3 Mosquitoes 30.0 30.2 26.8 27.6 31.1 36.4 30.5 24.5 31.1 Birds 11.0 10.2 19.1 15.2 11.2 15.3 19.4 15.3 8.8 Outdoor PP 6.5 7.7 19.1 14.9 6.1 5.1 20.5 10.5 8.6 OutdoorPD 6.7 7.6 16.3 13.1 6.6 5.1 19.6 8.6 7.2 CarpenterAnts 4.3 8.0 14.3 11.7 7.9 2.9 17.0 8.5 6.8 Fleas 4.5 5.4 14.8 10.6 8.7 1.5 18.5 5.5 6.2 Termites 5.4 6.9 11.5 10.9 1.6 0.0 16.1 5.1 6.2 Bats 7.4 7.5 10.2 9.1 5.4 16.3 13.1 6.1 7.6 Rats 3.9 5.3 5.3 5.2 4.9 4.1 8.5 3.4 3.8 Numberof Buildings 227 1005 1157 1917 369 103 768 880 741 +Number of infested buildings determined by multipiing the portion (0, 0.25, 0.50, 0.75 or 1.00) of buildings said to be infested by the total number of buildings for each district and summing the products. Percent of buildings infested calculated by dividing the number of infested buildings by the total number of buildings (2389) reported by the 306 responding districts. *indlcates significant difference between classes of district attribute. 50 Many comparisons of number of buildings with positive pest presence were significantly different for districts classed by any attribute. Exceptions were flies, mice, ants, mosquitoes, bats and rats for districts grouped by size; flies, weeds, ants, mosquitoes, birds and rats for districts grouped by location; and mice for districts grouped by community. When pest presence was compared to actual district building size, the reporting of pest presence became an all or nothing response for most districts above 17 buildings (Figure 6). in order to assess the influence of actual district building size on each specific pest's presence, regression analyses were performed on the percent of all buildings reported as infested for each district building size against the actual district size transformed to the log scale (Figure 7). Data outliers were not eliminated as each response was unique and characteristic of the district involved. The presence of cockroaches, fleas, head lice and stinging insects were the only pests for which a significant correlation to actual district building size was found to exist (Table 13). The number of buildings with cockroaches and fleas increased as actual district building size increased while the number of buildings with head lice and stinging insects decreased. Mean 1 sd for percent of buildings with pest presence for non-significant regression analyses ranged from 6.96 1 8.56% for bats to 46.16 1 29.59% for weeds. Results of this analysis of pest presence showed fewer significant differences between district responses than did the analysis using the three district size classes of small, medium and large. This means that the increase or decrease of a specific pest's presence over actual district building size was not reported uniformly implying that certain districts had pest problems regardless of size. interpretation of the results of the analysis of pest presence by small, medium and large district sizes must be tempered with the awareness that significance may be due to this district grouping as there was a trend for more of the buildings in the districts within at least one of the three sizes to be infested with the pest under consideration. Overall (Q1) and specific pest presence (05) were compared to verify that districts saying they currently or previously had pest problems did actually list specific pests as problems and Carpenter Ante g 40 s O 8 so ‘8 g 20 3 10 0 ng Ante 8 O E r: ‘5 3 20 E z 10 0 WWfi Cockroaches District Size 51 Piece 50 40 30 20 10 0 """"" WW .. Files 40 1 30 20 10 0 ""“mmmmfi .. 7 Need Lice w 40 30 20 10 0 District Size Figure 6. Distribution of Districts Reporting Specific Pest Presence as Proportion of All Responding Districts by Actual Building Size. In 9 53 ID 5%, Dorris lWllh 52 Mosquitoes nw w m m w 82.6.5 .6 i=5: Birds Stinging Insects MW 0 m m w 325-3 5 66:52 Termites M U. Wfi District Size w m m m 225.9 Fe 66.5.: wmg District Size Figure 6. (cont'd). 53 Rsts Outdoor Plant Diseases 3; 50 2 40 40 0 E .0 a M 5 D Other g 20 i 20 I Mill 3 10 10 0 o 1 “WM Weeds Outdoor insect Pisnt Pests 8 40 i a 6 5 2 20 5 to 0 District Size District Size Figure 6. (cont'd). 54 Carpenter Ants Fleas y . 2.5073 + 7.2762: R42 - 0.056 y - - 0.06882 + 0.4210! R42 - 0.102 W g I 5% 60‘ 2% - I15 ‘0. :3 . 3 I u I I I :5 NI/ 5 r ' t I -- I-fl- o ' . ,__ _ - . . 0 1 2 3 Ants Files y I 47.400 - 3.0300x R42 - 0.004 y - 50.84 - 6.9491: R42 - 0.016 g 100 100 i < - éé 60s I I 80' II fig . I . . I “"5 60‘ I 60' I 5 s :5 “K. ' i." =3 401 ' I ‘0- ; ‘ I II I II I ' I. II I II si 20- 20- 2s . I . I e 5‘ 0 - I - - I ' 0 ‘ I -— I ' 0 1 2 3 0 1 2 3 Cockroaches Head Lice y I - 0.90140 4 24.290: HA2 :- 0334 y I 50.406 - 16.117! R‘Z I 0.256 80 5 I I I i ‘ .é ,,,. Es as - I - as” ' a I i‘g‘ . .- 3” 20- . -- ii ' "' a a: o - . —.— . . 0 1 2 3 0 1 2 3 District Size as Log of Number of Buildings District Size as Log of Number of Buildings Figure 7. Regression Analysis for Percent Pest Presence Against Log of Actual District Building Size. 55 Mosquitoes Bats y x 35.050 - 10.347: R42 I 0.070 y - 4.0503 4 2.4000: R42 - 0.021 .r: I 30 fig 4 ., I I I e w I: 5% .. I . 3 n I i 3 r . .5 to I. - u i . . 2 I 0 . r——— -r . 0 1 2 2i Stinging insects Birds y a 50.165 ~ 11.560x R42 - 0.170 y I 0.0001 + 5.11561 R42 - 0.020 i so I so .§ ' E 50 ‘ ' so - ' {E I I :5 ‘0 ' 4° ‘ I (g ‘ '5 I II I II I I 1 I. I E! - . V ' I ' I f o ' l' — I ' l 1 2 3 0 1 2 3 Termites Mice y - 1.7132 4 5.0020): R“: - 0.030 y - 44.053 - 0.5070: R“: - 0.000 30 1m _ i I . I 8 1 I . a ,0 . Es °°‘ . . I . 3 g 50 ‘ _ I I = ‘01 I I =- - ' ‘ i I ‘0 ‘ I . I I.- ‘5 l" I I I . ¥ - I I - I U 2 20 m i it - . 0 f ‘f‘ I ' 0 I I I l v 0 1 2 3 0 1 2 ti District Size as Log of Number of Buildings District 3'1. as Log of Number of Buildings Figure 7. (cont'd). Percent of All Buildings with Pest for Each District Size Percent of All Buildings with Pest for Each District Size 8 8 8 O 8 8888 0 0 2 3 District Size as Log of Number of Buildings 56 Rats Outdoor Plant Diseases y I 2.1721 + 1.0570x R42 I 0.010 y I 0.42035 + 0.3050: R42 I 0.050 I II w I q . I w I I 40 -. I II - I I ‘ I ‘/ 20 q I I i 9 ' r l - 0 ' I —— - I ' C 1 2 (i 0 1 2 :i Weeds Outdoor Plant Insect Pests y I 54.030 - 0.0701: R“! I 0.013 V I 2.700 4 10.414): R“: I 0.050 ' I I I I 00 . . I f . . I I ' 6° - I I I I 40. ‘ ' I I I - I I I I I m- . I I . W ' I I I I I G V T I ' Figure 7. (cont'd). 0 1 2 3 District Size as Log of Number of Buildings 57 Table 13. Regression Analyses Results for Percent of District School Buildings with Pest Presence Against Log of Actual District Building Size and Mean :I: SD of the Percent of District School Buildings with Pest Presence tor Non-Significant Results. Regression Coefficients Pest Intercept P-Value Slope P-Value Carpenter Ants 2.593 0.723 7.274 0.210 Other Ants 47.475 0. 000' -3.026 0.743 Cockroaches 0901 0.914 24.291 0 . 00 1 * Fleas -0.949 0.822 8.423 0 . 01 6" Flies 50.072 0 . 00 1 * -6.957 0.499 Head Lice 50.497 0.000' -16.118 0.004‘ Mosquitoes 35.058 0.000' -10.347 0.141 Stinging Insects 50.163 0.000' -11.560 0.020' Termites 1.713 0.810 5.692 0.312 Bats 4.060 0.333 2.488 0.447 Birds 9.999 0.178 5.114 0.374 Mice 44.051 0.000" -0.583 0.941 Rats 2.171 0.506 1.859 0.466 Weeds 54.044 0.00 1 * -6.678 0.555 Outdoor Plant Disease 0.433 0.965 9.382 0.235 Outdoor Plant Pests 2.710 0.795 10.413 0.209 Pest Mean i SD Carpenter Ants 11.18 1:15.33 Other Ants 43.90 $24.08 Flies 41.85 1:26.96 Mosquitoes 22.84 $18.68 Termites 8.44 3: 14.82 Bats 6.96 i 8.56 Birds 16.04 $15.11 Mice 43.36 $20.79 Rats 4.37 :t 6.69 Weeds 16.16 1:29.59 Outdoor Plant Diseases 11.51 120.86 Outdoor Insect Pests 14.34 121.91 *IndIcates significant difference as does bold type. 58 that those which said they'd never had a pest problem did not list any specific ones. It was found that 155 of the 158 districts which answered that they currently had a pest problem did indeed select specific pests as infesting a percentage of their school buildings. The three that did not select any specific pests did not respond to the question. Of the 135 districts which answered that they previously had pest problems, 124 selected specific pests as infesting or having infested buildings within their district. Four districts did not know if any of the pests were or had been a problem, five districts said that no buildings had ever been infested with any of the pests and two districts did not respond to the question. Of the seven districts which responded that they had never had a pest problem, only one said that they had none of the specific pest problems. The other six all selected at least one pest problem as currently or previously occurring within some or all of their school buildings. This inconsistency may indicate that some - districts think they have a general problem but deny specific pest presence while others may not wish to acknowledge a general pest presence but do respond when questioned about specific pests. Correlation between the importance of a specific pest (O—3) and its presence within a district (O-5) was low. A Pearson correlation coefficient less than $029805 was obtained for all pests. Correlation between a pest's rated importance and the actual number of district buildings said to be infested with the particular pest was just as low. The correlation between pest number needing management (04) and specific pest presence (Q-5) was also low, less than $021466 for all pests. Correlations were just as low for pest number considered to be a problem and actual number of buildings said to be infested with the particular pest. Pest Problem Locations Few districts (less than 4% of 308) indicated that pests were always found within each of the different building locations (O-6. Table 14). The number of districts indicating that pests were often found within each location was also low, 0.3 to 21.1%. Pests were most frequemly 59 Table 14. indoor School Building Locations with Pest Problems. Percent of 308 Districts Selecting Frequency of Pest Occurrence in each Specified Location Location Always Often Sometimes Never DNK NA NR+ School Kitchen 4.2 19.8 61.4 7.5 1.6 1.9 3.6 Cafeteria 2.9 21.1 60.7 7.8 1.0 2.3 4.2 Classrooms 2.3 8.4 73.1 8.4 3.2 1.0 3.6 Home Ec Room 1.0 12.3 59.4 12.3 4.9 5.2 4.9 Aministration Offices 0.6 2.3 58.4 27.3 2.6 2.9 5.8 Gym Locker Room 1.0 9.4 50.3 21.1 6.8 4.9 6.5 Teacher's Lounge 0.6 4.2 52.6 25.0 7.1 3.2 7.1 Boiler Room 0.3 5.5 51.3 27.6 5.5 2.6 7.1 Custodial Closets 0.3 4.9 48.1 26.9 8.8 3.9 7.1 Restrooms 0.3 4.2 46.1 33.4 5.8 3.9 6.2 Gymnasium 0.3 2.6 44.2 35.1 7.5 3.2 7.1 Book Lockers 0.3 5.2 36.7 30.2 13.3 7.5 6.8 Shop Room 0.3 1.0 36.4 35.1 13.3 6.5 7.5 Library 0.3 0.3 36.7 40.6 10.7 4.2 7.1 Art Room 0.6 0.6 33.4 38.0 12.3 6.5 8.4 Pool Area 0.0 1.9 9.4 22.1 2.9 56.5 7.1 - Districts with Positive Pest Presence within P-Value for Selection of Positive Pest Specified Location++ Presence Based on District: Number (°/o of ) Size Location Community School Kitchen 263 (87.1 of 302) 0.923 0.246 0.931 Cafeteria 261 (86.7 of 301) 0.944 0.517 0.887 Classrooms 258 (84.6 of 305) 0.984 0.782 0.852 Home Ec Room 224 (76.7 of 292) 0.673 0.002' 0.851 Administration Offices 189 (63.2 of 299) 0.243 0.271 0.690 Gym Locker Room 187 (63.8 of 293) 0.261 0.718 0.259 Teacher's Lounge 177 (59.4 of 298) 0.200 0.216 0.490 Boiler Room 176 (58.7 of 300) 0.732 0.400 0.902 Custodial Closets 164 (55.4 of 296) 0.978 0.548 0.461 Restrooms 156 (52.7 of 296) 0.601 0.937 0.245 Gymnasium 145 (48.7 of 298) 0.932 0.738 0.565 Book Lockers 130 (45.6 of 285) 0.819 0.140 0.553 Shop Room 116 (40.3 of 288) 0.672 0.889 0.804 Library 115 (39.0 of 295) 0.838 0.816 0.901 Art Room 107 (37.2 of 299) 0.950 0.420 0.787 Pool Area 35 (26.1 of 134) 0.707 0.842 0.192 60 Table 14 (cont'd). Distribution of Districts Experiencing Pests Within Specified Location (as Percent of Attribute Class) Size Location Community Location S M L SLP NLP UP U S R School Kitchen 84. 2 88.2 90.0 90.1 90.1 60.0 87.1 90.1 85.6 Cafeteria 84.2 88.1 87.5 90.1 85.2 69.0 93.5 87.8 85.0 Classrooms 85. 6 84.5 82.5 81.8 89.0 90.3 83.9 80.2 86.9 Home Ec Room 72. 8 76.3 87.5 96.2 80.2 46.4' 80.6 80.0 74.3 Admin. Offices 53.0 66.7 75.0 66.8 63.0 41.9 74.2 60.0 62.9 Gym Locker Room 58. 3 62.4 82. 5 66.7 59.5 57.1 77.4 71.1 57.6 Teacher'sLounge 53.9 58.0 79. 5 64.9 53.2 41.9 67.7 65.2 55.1 Boiler Room 56. 7 57.7 67.5 62.8 53.8 45.2 64.5 58.4 57.8 Custodial Closets 54.5 55.4 57.5 57.7 55.1 41.9 67.7 58.9 51.4 Restrooms 57. 8 51.3 45.0 53.5 52.6 48.4 64.5 42.5 55.6 Gymnasium 48. 0 48.1 52.5 51.1 44.3 45.2 61.3 47.8 46.9 Book Lockers 4.3 2 45.7 51.3 50.3 42.7 24.1 58.1 44.3 44.0 Shop Room 44. 7 39.0 35.0 41.8 36.4 40. 7 35.5 38.2 42.3 Library 42. 0 37.4 37.5 38.8 41.0 34. 5 41.9 37.1 39.4 Art Room 36. 8 36.6 40.0 38. 5 39.5 23.3 43.3 34.5 37. 4 Pool Area 18. 8 26. 1 27.5 27.7 24.0 20.0 43.5 24.1 21.1 Maximum Number of Districts 107 161 40 192 84 32 31 92 185 +DNK - do not know, NA - location not applicable, NR - no response. 1't‘includes districts selecting Always, Often or Sometimes as frequency of pest occurrence. Percent calculated based on total number of districts responding to the question less those indicating location not applicable to their district. ‘lndicates significant difference between classes of district attribute. 61 reported as being sometimes present in all locations (33.4% to 61.4%) except pool areas which were not applicable for 56.5% of the districts. Except for home economics rooms, classrooms, cafeterias and kitchens, pests were said to have never occurred in the different areas for 20% to 38% of the districts. Only 12.3%, 8.4%, 7.8% and 7.5% of the districts indicated respectively that home economies rooms, classrooms, cafeterias and kitchens have never had a pest problem. Do not know and not applicable responses varied between 1.0 and 13.3%. Three districts responded with not applicable to classroom locations. Two of these districts have two school buildings each while the third has only one. It is not clear why their response was not applicable unless they misunderstood question instructions and meant that the location was 'not applicable' as pests have never occurred in their classrooms. Not applicable responses for all other locations were credible. Positive responses to pest presence were totaled for each location. These frequencies were compared to the total number of districts responding to at least one part of the question less these districts which indicated that the specific location was not applicable for their district. Just over 87% of these districts listed school kitchens making it the most commomly pest inhabited area. This location was followed by cafeterias, classrooms. home economics rooms, administration offices, gym locker rooms, teacher's lounges, boiler rooms, custodial closets and restrooms (867,846, 76.7, 63.2, 63.8, 59.4, 58.7, 55.4 and 52.7%). Only six locations were indicated as having pest problems in fewer than 50% of the responding districts. These were gymnasiurns, book locker areas, shop rooms, libraries, art rooms and pool areas. A significant difference was found between attribute classes for positive pest presence in home economics rooms when districts were grouped by location. Ninety-six point two percent of southern lower peninsula districts indicated pest presence compared to 46.4% of upper peninsula districts. Pests were reported as occurring in the different outdoor areas by 64.7 to 78.0% of the total number of districts responding to at least one part of the question less these districts which 62 indicated that the specific location was not applicable for their district (Q-7, Table 15). Few of the 301 responding districts indicated that pests were always found in such locations (1.7% to 3.3%). Up to 13.6% said that pests were found often and 41.9% to 53.5% said they were found sometimes. No significant differences were found between districts indicating positive pest present for any location by any attribute grouping. Specific Outdoor Plant Disease and Pest Problems Many outdoor plant disease and insect pest problems were listed (08, Q9). Forty-four districts wrote in responses to outdoor plant disease though only sixteen listed actual diseases. These included anthracnose, brown leaf, dutch elm disease, fusarium (grass), leaf spot. a maple tree disease, mold, oak blight, pine tree disease (white pine blight, diplodia), round spot, spmce galls, and tree fungus. - One hundred forty-three disticts listed pests in response to outdoor insect problems. Only 20 districts actually named pests of outdoor plants. These pests included aphids, bagworrns, black clicker bugs, boring insects, box elder bugs, bugs on honey locust, caterpillars, centipedes. earwigs, gmbs, gypsy moth, mealybugs, scale on omamental plums, spider mites (in general and on pine), and tent caterpillars. Summary Eighty-seven tests for differences between responses to pest presence questions were performed for each district attribute. The trend in response selection was usually an increase in frequency of positive response (importance or presence) and a decrease in the tolerable number of pests from small to medium to large districts, from southern lower peninsula to northern lower peninsula to upper peninsula districts, and from mral to suburban to urban districts. Twenty-one significant differences were found for responses grouped by district size, 26 significant differences were found for responses grouped by district location and 25 63 Table 15. Outdoor School Building Locations with Pest Problems. Percent of 301 Districts Selecting Frequency of Pest Occurrence in each Specified Location Location Always Often Sometimes Never DNK NA NR+ Playgrounds 3.0 13.0 53.5 17.9 8.6 1.0 3.0 Athletic Fields 3.3 13.6 50.2 16.9 9.6 3.7 2.7 Landscaped Areas 2.7 9.6 52.2 16.6 8.6 5.0 5.3 Turf Areas 1.7 7.6 41.9 19.6 11.3 11.0 7.0 *— _ Districts with Positive Pest Presence within P-Value for Selection of Positive Outdoor Location++ Pest Presence Based on District: Number (% of) Size Location Community Playgrounds 209 (78.0 of 268) 0.281 0.258 0.266 Athlethic Fields 202 (69.7 of 290) 0.858 0.857 0.626 Landscaped Areas 194 (67.8 of 286) 0.414 0.466 0.941 Turf Areas 154 (64.7 of 238) 0.143 0.185 0.321 Distribution of Districts Experiencing Posts in Specified Location (as Percent of Attribute Class) Size Location Community S M L SLP NLP UP U S R Playgrounds 67.6 70.7 74.4 71.3 70.9 61.3 69.0 66.3 72.3 Athletic Fields 66.0 72.0 69.2 71.2 68.8 62.1 72.4 62.6 72.9 Landscaped Areas 61.1 73.9 60.5 72.4 60.8 58.1 65.5 65.9 69.3 Turf Areas 48.3 62.5 59.5 61.3 52.1 45.8 53.6 59.1 57.2 Maxlrnum Number of Districts 103 159 39 189 81 31 30 92 179 +DNK - do not know, NA = location not applicable, NR = no response. “includes districts selecting Always, Often or Sometimes as frequency of pest occurrence. Percent calculated based on total number of districts responding to the question less those indicating location not applicable to their district. 64 significant differences were also found for responses grouped by district community type. The same responses were often significantly different for each of the three comparisons. Districts grouped by size differed significamly in their reporting of general pest occurrence. They also differed in their selection of cockroaches as being an important as well as a major school district concern (selected as the single most important concern as well as one of the top three concerns). Reporting of the positive occurrence of five pests within the districts in general and of eleven pests within specific numbers of school buildings were significantly different. Three exceptions to the usual frequency trend were for the number of buildings reported as having weeds, head lice and stinging insects. Medium sized districts reported greater occurrence of these pests than did large ones. Districts grouped by location also differed significantly in their reporting of general pest occurrence and in their selection of cockroaches as the most important school district concern. In addition, they differed significamly in their selection of cockroaches, rats, bats and termites as major school district concerns. Reporting of positive occurrence of five pests within the districts in general and often pests within specific numbers of school buildings was significantly different. Four exceptions to the usual trend in frequency of positive response selection occurred. Upper peninsula districts selected bats and rats more frequently as major district concerns and reported head lice and bats as occurring in more school buildings. The selection of cockroaches as the most important district concern was significamly different for districts grouped by community type. This grouping also differed in their selection of cockroaches and files as a major district concern. The concern over flies was expressed most often by rural districts. The frequencies of positive selection for four district pest occurrences and for 15 building pest occurrences were significantly different. Exceptions to the usual frequency trend occurred for mosquitoes, flies, stinging insects, head lice and weeds. More rural districts reported the first four pests while more suburban districts reported weeds. 65 All district groupings showed a significant difference in the number of reported pest problems. Only one significant difference in the selection of pest problem locations was found. This was for home economics rooms for districts grouped by location. 66 W Methods Used for Pest Prevention and Pest Management W. The methods districts selected as preferred for prevention and management depended upon the pest under consideration (O-10, O-11). Method selections included change in sanitation practices, facility repair or modification, change in turf/ landscape care, use of traps, use of pesticides and education to encourage students, teachers and school personnel to reduce pest presence by changing habits. Some districts identified 'other' methods or indicated do not know or no method used. Three hundred two districts selected prevention methods while 294 selected ones for management (Table 16). Some districts did not select methods for each pest. Up to 29.8% did not select prevention methods and up to 33.3% did not select management methods. Districts which did not select prevention methods often did not select management methods (ranging from 74.1% for head lice and 95.8% for ants other than carpenter ants). Many of these districts indicated earlier in the questionnaire (OS) that the specific pest under consideration had never been a problem within their district (30.0% for head lice to 66.7% for cockroaches). A few districts selected prevention methods but did not select management methods (2.2% for stinging insects to 9.0% for outdoor insect pests) while a few others selected management methods but none for prevention (from 0.4% for ants to 3.3% for birds and rats). These districts may not differentiate between prevention and management. Or, they may utilize the methods as selected, not needing to manage the pest where a problem does not exist or to prevent a problem from developing where one already exists. Other districts selected a primary prevention or management method but not a secondary one (up to 42.1% for prevention and 42.2% for management). These districts added to those that made no response revealed that more than 50% of the districts did not select secondary prevention and management methods for ten of the pests and more than 75% did not select secondary methods for the other six. Because of this low response, only the most preferred methods were examined further. 67 oém «.mm YN v... o; v.5 N..... 5.0 5.0 5.0 mm m. 5 m.m~ ad od 0... m.» $6.. 06 m6 9N mm «mm .2? 0...: TN v.5 Wow 0.0 0.0 TP 0.9. m.m~ 9m N.5.. m... cm Now 0.0 m... 5... mdm 9mm de 5... 06 m6 «.0? 5.5.. ...m 56 mé 9.5.. N.¢N «.5? MN 5% 5.0 $6.. Ndm 0.? 0.0 Cd «.mw You 5... m6 ...m c... adv ad ad o.N ...FN m.5.. m4 9.5 9N 9N ...vm 0% m... 0N mdm Qmm NA: 0d 5.0 5.0 N.o.. o.5.. Sm 5.? Q5 #6.. de m.5 ON 5; 0.0 m... mdm 6.5 m... 0.5 m.o.. «.3 o; v6 SN o... 5.mm fim o.o fin 0.0.. m5 5... 0d o.m mm .....v o.m 0... m6 m.mN odm m cm YN 5.0 5.0 v.0 odw ON 5.. mdp mm wdm m mm 0.” ad ad 9v m.m.. od oé mm 0.5 m vw SN 0.0? ad ad m an o... o... wd mdp mdm 9N $6.. 9N m... mdw 9N m6 md «.mw oancns. oz c2 .22 .8 50 am so a: 9... on”. :8 £32.22 EoEomncns. 9.823 more... an .o as... 89.5: 2252.25 8.828 mecca no... .0 28.5 anocooow .co>o5 omncns. .an.5 Eo>o5 moor. ooncns. anocooow .co>o5 omncnz 5.955 Eo>o5 mononoiooo ooncnz bnccooow .co>o5 ooncni bnEcn. .co>o5 m2; .850 ooncns. .cnocooom .co>o5 ooncns. .ancn. .co>o5 2c< .98 85:09:. .35 .0009302 2.0500093: «not 0:0 :O_~:O>O._n— «mom ghufinflht .IP 309—. Table 16 (cont'd). NS NR Fac Lnd Trp Cid Ed 0111 an San Importance Pest Files 16.2 184 ".5. 0° “2°? 51:) '5". Os- ‘9". In? 27 40. “2°. FF 0.0. 0° “2"? com Primary u C .§ >r: 0n h 52 9*. N!- «2°. PF 95. 1-0 cm. CO <=.~. ‘0‘!) am OV’ 1 Secondary Prevent Manage I-Ieadllce ‘3? “! coo 0. N o. co °. v 0? as q o o. o O. P Primary 29 Prevent Manage q or F 00' “2 V 40.1 ‘2 n- O. o ‘2 o O. F 24. 68 31.1 8 02“! mo 0.". N1- 9°. F0 ‘2". NN 0.0. CO ‘2". PF Mosquitoes 0.5. ?F 0.0. N‘- Primary Prevent Manage ‘9". NF «2*. N!- 9°. FF 0". coin Stinging Insects 15.2 14.3 9". PO me. (O'- NO «2°. NN 41. 51. «an. CO 0.". N7- Pfi Prevent Manage ‘2". (01-- 5.5. F0 00.0. FF ‘2". com 0.“. NN om 0&0 F (V)!- Secondary Prevent Manage Termites 26. 27. ‘9. 0') °. co ‘2 o 30.1 C O [x 0 P11 Prevent Manage V. er ? «5 °_ . 0 °. o "-3 c Table 16 (cont'd). NS Fac Lnd Trp Cid Ed Oth an San lnportance Pest Termites 95. N‘- 99 OD 99. FF 12.6 10.9 5.5. CO ‘2‘: FF 12.6 13.6 99. 010] Secondary Prevent Manage Bats 25 28 ‘2‘2 #10 99 N0] '5". co 0."). min ‘9”. 105 Primary Prevent Manage Prevent Manage (O'- ““100 9‘2 coco 5.5. CO 99 NO) 9“: moo Secondary 69 Birds 27 29. 9": so- 26 24. 99. FF ‘2". oo 95. NCO 9.9 l0" 5°. 00 Primary Prevent Manage Q'- 0009 99. 000] ‘2“? co 0.". com Ov- V0“) 99. [5'5 99 00 9m 95. NN Secondary Prevent Manage Mice ‘2"? 50 ‘2‘2 00 ‘2‘? 0]!- if? FN GO." 00° Primary :8 >2 2n 5: 99 N!- ‘2". F0 99 FF 99 0’“) Secondary Prevent Manage Rats 24 26. '2". PF '5". PN '2‘2 v-O Primary Prevent Manage 23 25 . ere: N 95. NO 5.9 CO 9". F0 ‘2‘”. ms 99 N15 99. PF 99 COCO 901 Secondary Prevent Manage 70 6058.. 3.5.2.. ccoooo o: u wz .68 2.88... o... 0. $558.. 0: u 52 69.5.... 02 u .22 .265. .oz 8 u v.20 .850 n 50 .28.. 8938... 0. on 8 £52 oocnco c. 23.55 .88... .0 .coEoonSooco .. cm 8.3.058 .. so .89. u e. 8859.. 28 @8825... .o 5.853.. .. 2.. 52.8.56... .258. 5.8. u on“. 582:8 a can. 9.... 98 .n 9. 9. 9. 9... 9o 9. 9. 5o Swans. ..... 98 9m 9.. 9o 5.. 9... 5.. 9o 9... 9.. 58:88 596... m 8 9m 98 5. 9.. ...~ 9.. 9... 5.. .n ounce... 9mm 9m 9 .n 9. 5.. 9m. 9.. 9.... 5. 9.” 5.2.5 .555 23.. an... 322.6 9.0... 95 9. 5. 5o .... 9o 9.. 9o 5. 5o 8an... ..N.. 9%.. 9m 9m 9.. 5. 9.. 5.. 9m 5. 5o 528% .85... o .n 9m ...~ 9n 9.. 5.. 9o 5... 9.. 9n 82...... 98. 9.. 9a 9. 9.. 9m. 9.. 98 9. 9a .595 .565 omamma an... 3850 99. 9mm .8 ...~ 5.. 4. 9n. no 9... 9... 5o 82.... v.8 98 9m 9n 5.. m. 9... so 9... 9~ 5. 58:88 .53... «no 5.. 9o 9. 9.. 9% m o 9 .o 5.. so 82...... 98 5o 9.. 9. o o 98 s o 9.... 5. 9m .55.... .53.... coo... oz $2 .22 .8 so am. .20 e. 65 on”. can 85:8,... can. ..c..coo. o. sank 71 Pesticides were selected most frequently as the preferred method for prevention and management of carpenter ants, other ants, cockroaches, mosquitoes, stinging insects, termites, and outdoor plant pests. Pesticides were also selected most frequently for management of fleas, flies, and weeds with sanitation selected most frequently as the preferred prevention method for fleas and flies and modification of landscape care practices selected for weed prevention. Education was selected most frequently for head lice prevention and management; facility modification was most often selected for bats and birds; traps were favored for mice and rats and change in landscape care practice was preferred for outdoor plant disease. Methods written in as 'other' referred most often to the use of private pest control companies or contractors (79.1% of the 86 prevention and 71.8% of the 110 management write-ins). Inspections for and parental and public health department involvement with head lice accounted for an additional 11.6% prevention and 11.0% management write-ins. The remaining 'other' methods included destruction of nests for stinging insects (3 prevention and 2 manage- ment), brooms for bats (1 prevention) and electronic pest comrollers for bats (1 prevention and 1 management). Inspections were listed as being used to help prevent carpenter ants (1 district) and termites (2 districts) and to help manage carpenter ants, other ants, roaches, termites, bats, plant diseases, and plant insects (1 district each except termites with 2). Two districts wrote that they use a variety of methods for the control of roaches, fleas, flies, mosquitoes, stinging insects, bats, and birds (1 response each) and 1 district wrote that it uses whatever method local farmers advise for the management of outdoor plant diseases. Only these districts selecting actual methods were compared by attribute to determine if significant differences existed in method preference for the specific pests (Table 17). Any method chosen by fewer than 15 districts was included as part of the 'other' category. This created data sets with different method categories depending on the pest. For example, only sanitation, pesticides and 'other' methods were compared for cockroaches whereas sanitation, facility modification, traps, pesticides and 'other' methods were compared for mice. 72 Table 17. P-Values for Selection of Preferred Pest Prevention and Management Methods Based on District Attribute Class! Primary Prevention Method Primary Management Method Pest Size Location Community Size Location Community Carp. Ant 0.388 0.669 0.965 0.546 0.367 0.519 Other Ants 0.082 0.511 0.241 0.221 0.107 0.739 Cockroaches 0.393 0.026‘ 0.422 0.060 0.381 0.369 Fleas 0.300 0.660 0.997 0.023' 0.638 0.518 Flies 0.842 0.809 0.509 0.316 0.964 0.730 Headlice 0.037' 0.815 0.883 0.633 0.409 0.683 Mosquitoes 0.133 0.317 0.201 0.162 0.427 0.209 Sting Insects 0.894 0.186 0.993 0.446 0.349 0.901 Termites 0.085 0.195 0.910 0.230 0.679++ 0.992 Bats 0.940 0.692 0.183 0.823 0.578 0.718 Birds 0.824 0.611 0.137 0.805 0.251 0.802 Mice 0.404 0.843 0.044* 0.266 0.677 0.107 Rats 0.030' 0.413 0.005' 0.287 0.561 0.485 Weeds 0.134 0.883 0.909 0.01 2* 0.952 0.626 Outdoor Plant Diseases 0.461 0.585 0.329 0.496 0.828 0.854 Outdoor Plant Posts 0.446 0.140 0.108 0.826 0.945 0.245 Distribution of Districts with Significamly Different Preferred Pest District Methods (as Percent of Attribute Class)+++ Prevention Type San Fac Lnd Trp Cid Ed Oth Tot Headlice Small 33.0 3.3 56.0 7.7 91 Medium 37.8 15.6 43.0 3.7 135 Large 26.5 8.8 55.9 8.8 34 Rats Small 18.6 33.9 32.2 6.8 8.5 59 Medium 29.8 15.4 39.4 11.5 3.8 104 Large 17.9 28.6 25.0 25.0 3.6 28 Roaches SLP 38.4 51.7 7.9 151 NLP 58.2 36.4 5.5 55 UP 50.0 27.8 22.2 18 Mice Urban 16.7 20.0 26.7 23.3 13.3 30 Suburban 26.5 16.9 34.9 15.7 6.0 83 Rural 20.8 18.9 48.4 8.2 3.8 159 Rats Urban 12.0 24.0 20.0 28.0 16.0 25 Suburban 33.3 17.6 29.4 15.7 3.9 51 Rural 23.5 25.2 40.9 7.0 3.5 115 73 Table 17 (cont'd). Pest District Management Type San Fac Lnd T rp Cid Ed Oth Tot Fleas Small 23.1 . . . 46.2 17.3 13.5 f 52 Medium 24.0 . . . 62.7 9.3 4.0 75 Large 38.5 . . . 30.8 26.9 3.8 26 Weeds Small . . 32.8 . 56.3 7.8 64 Medium . . 48 .6 . 47.6 3.8 105 Large . . 65.6 . 25.0 0.0 32 +The categories DNK ( Do Not Know), NM (No Method) and NR (No Response) of Table 16 were not part of the comparison. Any method chosen by fewer than 15 districts (5% in Table 16) was included with the Other (Oth) category. ++Comparison was made between SLP and NLP districts as fewer than 5 UP districts selected methods. +++San = sanitation, Fac . facility repair/or modification, Lnd = modification of turf/landscape care practices, Trp = traps, Cid - pesticides, Ed = encouragement of school members to change habits so as to discourage pests, Oth = other, Tot = number of districts within each district type. *lndlcates significant difference between classes of district attribute. 74 When districts were compared by size, methods used to prevent both head lice and rats were found to be significantly different with medium sized districts selecting pesticides more and education less for head lice and large sized districts selecting pesticides more and traps less for rats. Cockroach prevention methods were significamly different for districts compared by location. Southern lower peninsula districts selected sanitation less and pesticides more frequently than either northern lower peninsula or upper peninsula districts. Methods preferred to prevent mice and rats were significantly different between districts compared by community type. Traps were preferred more and pesticides less in rural districts while suburban districts selected sanitation more often than did either rural or urban. Selected management methods were significantly different for two pests and only when the districts were compared by size. Pesticides were preferred more and education less in medium- sized districts for flea management while pesticides were preferred less and landscape practice modification more in large districts for weed management. For all pests. pesticides were more preferred for management than for prevention. Similarly, use of traps for bats, birds, mice and rats was listed more often for management than for prevention. 'Other' methods were also more preferred for management than for prevention but some of the responses were questionable. Although eleven additional districts that did not employ pest control companies for prevention wrote that they did so for management, twelve additional districts wrote that they either inspected for the pest (not actually management at all) or used a variety of methods (basically a do not know response). . In order to examine the relationship between prevention and management methods, the responses of only these districts answering both questions were analyzed (Table 18, Figure 8). Since districts experiencing problems with a particular pest may prefer methods other than the ones said to be preferred by districts which have never experienced the pest, responses were further separated into two groups, those with and those without the specific pests as determined by answers to 0-5. 75 Table 18. Methods Preferred by Districts Selecting Responses for Both Pest Those Reporting Presence of the Specific Pest and Those Reporting Prevention and Management with Districts Grouped as All Districts, No Presence of the Specific Pest.+ District Selection of Preferred Method (as Percent of Total)“ Fac Lnd Trp Cid Ed Oth an NM Tot San Pest Carp. Ants 1.0.8. 237 564 4.3.7. 140 Other Ants 959 639 90.8. 214 3.1.0. 790 9.5.6. 368 442 01.4 5.62 1.5.8. 104 851. 337 28 28 28 Without Manage With Prevent 9.1.5. 940 564 7.6.7. 564 0.0.0. 000 A55. 329 19.8 21. 16 Without With Cockroaches Prevent 120.9 203 1.5.0. 240 39.3. 084 452 3.9.9. 101 40.0. 001 599 204 40.3 33.6 44 7 Without Manage 3.8.0. 585. 419 564 6.7.9 221 0.0.0. 000 6.99 204 26 29. 21 4 With Without Fleas Without With Manage Files 0.90. 000 1.92 784 26. 23. 37 5 Without With Manage 76 Table 18 (cont'd). Ed Oth an NM Tot Fac Lnd Trp Cid Sari Pest Headlice 1.0.3. 325 6.0.9 447 46 46 42 10.0 10.0 7 9 0.0.0. 000 0.0.0. 000 2.0.0 1112 33.1 35.5 31 6 Without Prevent Mosquitoes Without With Prevent Stinging insects 4.00. 220 6.1.4” 821 453 A90. 000 4.1.0 222 21 . 22 20. 11.7 10.4 22 9 With Without Prevent 7.7.9 742 6.1.9 332 4.6.0. 220 96.8 944 563 4.0.0. 000 01.0. 120 8.1.6. 548 112 Termites 0.0.1. 032 463 0.0.0. 000 0.2.7. 120 17.6 19. 19 7.6 2.2 10.0 Without Prevent Bats 56.2. 429 323 958 270 0.0.5 101 28.2. 736 7.18. 653 4| 590. 010 4.4.3. 532 343 5.56. Without Manage With Prevent 0.9.2 189 11 0.0.0. 000 6.8.0. 150 333 4.93. Without With 77 Table 18 (cont'd). Tot Fac Lnd Trp Cid Ed Oth an San P881 Birds 57.6 612 324 0.0.8. 1.00 500. 000 0.7.5 462 53.6. 786 0.7.3 110 50.9 852 353 5.72 With Without Prevent 0.3.0. 531 324 50.6. 101 00.3. 100 57.5 462 0.0.0. 000 53.3 730 353 Mice 3.59 217 95.6. 112 3.32. With Without Manage Prevent Without With Rats 4.7.0. 222 I O C see 853 242 0.0.0 000 9J9 981 1 2 032. 212 With Without Prevent WOGdS 1.7.7. 153 2 1 847. 0.0.0. 000 820. 182 442 40.0. 000 0.6.0. 029 443 97.7. 001 Outdoor Plant Disease 390. 107 323 599 1.21 0.0.9 000 21 25 13.0 5.0.0. 000 013 343 5.30. 121 427. With Without Manage Prevent 330. 007 323 0.7.0. 342 0.00 000 545 231 5.0.0. 000 3.30. 741 233 5.0.0. 004i 3.45. Without With 78 Table 1 8 (cont'd). Pest San Fac Lnd Trp Cid Ed Oth an NM Tot Outdoor Plant Pests Prevent 5.2 2.6 24.2 0.0 26.8 0.5 1.5 32.0 7.2 194 With 2.3 4.7 32.6 0.0 39.5 2.3 0.0 14.0 4.7 43 Without 9.0 2.2 28.1 0.0 16.9 0.0 1.1 37.1 5.6 89 Manage 4.6 1.0 21.6 0.0 31.4 0.0 2.6 30.4 8.2 194 With 4.7 0.0 30.2 0.0 48.8 0.0 2.3 9.3 4.7 43 Without 6.7 2.2 27.0 0.0 16.9 0.0 1.1 38.2 7.9 89 +Only districts selecting both prevention and management methods were included. Districts were grouped as all districts (Prevent and Manage categories), those who said they have or have previously experienced the specific pest problem (With) and those who said they have never experienced the specific pest problem (Without). +++San =- sanitation, Fac = facility repair/or modification, Lnd =- modification of turf/landscape care practices, Trp = traps, Cid = pesticides, Ed = encouragement of school members to change habits so as to discourage pests, Oth = other, DNK = Do Not Know, NM a No Method. Tot . number of districts providing responses for each grouping. - 79 .384. 2:88 .5 5.5.3 o... 5.3 «8.5.6 .5 52.2.... .35.: 5.532.: .a 2.3.". .35.: 9500.6 30.5.5 5o :32... 2: on cm 3 3 o . ".6 5.55. 4.6 5.; 2.5. .02 on. . 550 3535. 02 no.0 505.? 888:... 9.0 5.; 5.528 . 0.8.2.84. 882. .85.; 4.8.; 5.? 2.... .5 5.5.: a... 5.3 325...... 3 35...... .35.: ‘05.: 0.5—«00.0% luv—=20 no «COO-OE SF 8 8 3 on a - . . - , 8.th . .68... 9.2.6 3850““ “ \\\\\\.. 88.3.80: 5.8.3 m Ii§ 828.: 32.5%.. I l....§\\\\\\\\\\\\\t 85 3.5.53 E . 8.... 0838“. I 39.0.3208 8. i - 3.555 382.328 3823“.“ m 89.38: 858.3 B 823.... 8.5.3.: I § .§ 8.... 83.3 s _§V\\\\\\\\\\t 82". 8.38.. I .nV\\\\\\\\\\s 858.58 _I § 3...... .\\\\\\\\. a... .5 5.... 30.5.3 3 .25.: .35.: 80 Except for head lice, pesticide treatment was the most preferred method of prevention and management for districts having the specific insect pests. For districts without these pests, pesticide treatment was also the most preferred method for prevention and management of carpenter ants, other ants. stinging insects and termites and for management of cockroaches, fleas and mosquitoes. The majority of districts without cockroaches. fleas, flies and mosquitoes preferred sanitation for their prevention and for the management of flies. Education was most preferred by all districts for prevention and management of head lice. The majority of districts with bats and birds preferred facility modification for prevention and management while the majority of those without these pests did not know what method was preferred. Traps were most preferred for prevention and management in districts with mice and rat problems, whereas facility modification, sanitation and traps were almost equally preferred for prevention in districts without the rodents. with traps and facility modification most preferred for management of mice and traps most preferred for management of rats. The use of pesticides and modification of landscape practices were most preferred for prevention and management by districts with weeds. Those without preferred modification of landscape practices twice as often as pesticide use. The majority of districts with outdoor plant disease problems preferred modification of landscape practices for prevention and the use of pesticides as well as modification of landscape practices for management. Most districts experiencing outdoor insect plant pest problems preferred the use of pesticides or modification of landscape practice for both prevention and management. The majority of districts without these disease or insect problems either did not know what method was used or preferred landscape practice change. For almost every pest, pesticides were selected as appropriate for management and prevention more frequently by districts actually having problems with that pest than by districts without them. Pesticides were also selected more frequently by all districts as a management than as a prevention method. Except for bats, birds, mosquitoes, outdoor plant diseases and 81 outdoor insect pests, all pests of low importance, few districts which actually have specific pest problems said that they did not know what method was used for prevention or management. Statistical conparisons were made only between districts which actually selected methods, with those methods chosen by fewer than 10 districts being included as part of the 'other' category (Table 19). Methods preferred by districts with a specific pest were compared to those preferred by districts without the pest. Significant differences were found between methods used by districts for the prevention of carpenter ants, other ants, cockroaches, flies, mosquitoes and weed prevention and for the management of flies, stinging insects and weeds. Districts experiencing certain pest problems did use different methods than did those without the pest, particularly for prevention. Comparisons were also made between preferred prevention methods and preferred management methods. When no distinction was made between districts concerning pest presence, methods preferred for carpenter ants, other ants, cockroaches, fleas, flies, mice and rats tested significame different. However, when methods selected only by districts with the specific pests were compared, methods preferred to prevent and manage other ants were the only comparison found to be significantly different. The use of similar methods to both prevent and manage existing pests could mean that once a problem develops, prevention is no longer a separate issue. Methods said to be preferred by districts without the pests were significamly different for carpenter ants, cockroaches, fleas and rats. Pest Management Guidelines Of 307 respondees, 19.2% said that written guidelines exist that specify what should be done when pest problems occur, 75.9% said they had no guidelines and 4.9% did not know. Four districts chose not to answer the question. A significant difference was found between district's responding yes when compared by size (Table 20). More than twice as many large districts said they have written guidelines compared to small and medium sized districts (42.5% compared to 13.2% and 17.4%). These proportions were compared to each other to determine 82 Table 19. P-Values for Selection of Prevention and Management Methods Based on Pest Presence+ Methods Selected by Districts with Pest Compared to Prevention Methods Compared to Management Methods Selected by: Methods Selected by Districts Districts Districts Without Pest for: All With Without Pest Prevention Management Districts Pest Pest Carpenter Ants 0.012' 0.416 0.016* 0.988 0.008* Other Ants 0.005‘ 0.076 0.000* 0.002' 0.337 Cockroaches 0.000" 0.312 0.007“ 0.695 0.001' Fleas 0.158 0.799 0.020* 0.978 0.021 ‘ Flies 0.006' 0.012‘ 0.007* 0.056 0.113 Headlice 0.562 0.758 0.151 0.224 0.891 Mosquitoes 0 .01 1 * 0.768 0.220 0.487 0.294 Stinging Insects 0.086 0.023* 0.155 0.124 0.375 Termites 0.063 0.948 0.337 0.827 0.248 Bats 0.111 0.689 0.566 0.612 0.336 Birds 0.137 0.418 0.764 0.845 0.416 Mice 0.092 0.074 0.024" 0.108 0.803 Rats 0.052 0.729 0.035* 0.718 0.047* Weeds 0.001 * 0.004' 0.820 0.755 0.951 Outdoor Plant Diseases 0.520 0.289 0.744 0.615 0.866 Outdoor Plant Pests 0.162 0.051 0.730 0.761 0.975 Distribution of Districts with Significantly Different Preferred Pest Methods (as Percent of Total)+++ Pest Presence San Fac Lnd Trp Cid Ed Oth Tot Prevention: Carp. Ants With 20.9 4.7 . . 65.1 9.3 43 Without 27.7 22.8 . . 38.6 10.9 101 Other Ants With 30.2 3.7 6.3 48.7 9.5 1.6 189 Without 37.85 9 4 3.1 37.5 0.0 12.5 32 Roaches With 34.3 . . . 59 .3 6.5 108 Without 55.4 . . . 30.1 14.5 83 Flies With 36.5 13.5 42.3 6.4 1.3 156 Without 59.5 4.8 19.0 11.9 4.8 42 Mosquitoes With 21.1 14.4 60.0 4.4 90 Without 36.5 15 .9 34.9 12 .7 63 Manage: Flies With 25.0 8.8 58.8 6.3 1.3 160 Without 45.0 5.0 40.0 2.5 7.5 40 Sting. lns. With 8.8 14.8 68.1 8.2 182 Without 11.5 38.5 46.2 3.8 26 Table 19 (cont'd). 83 Pest Presence San Fac Cid Tot Weeds With 51.1 133 Without 30.2 43 All Districts Carp. Ants Prevent 26.5 15.3 48.2 0.0 170 Manage 17.7 11.4 65.1 5.7 175 Other Ants Prevent 30.8 4.2 5.4 47.9 7.9 3.8 240 Manage 21.4 3.7 6.2 64.6 1.2 2.9 243 Roaches Prevent 45.0 2.9 45.5 6.7 209 Manage 28.8 2.8 59.9 8.5 212 Fleas Prevent 40.4 34.2 17.8 7.5 146 Manage 26.3 51.3 15.1 7.2 152 Flies Prevent 41.5 11.1 37.3 7.4 2.8 217 Manage 28.8 7.8 54.8 5.5 3.2 219 Mices Prevent 22.2 19.0 11.9 3.2 2.0 252 Manage 14.5 16.1 17.6 0.8 3.4 255 Rats Prevent 25.0 22.7 11 .9 5.7 176 Manage 15.3 17.6 19.9 4.5 176 With Pests Other Ants Prevent 30.2 3.7 48.7 9.5 1.6 189 Manage 21.8 2.6 65.8 1.6 f .5 193 Without Pests Carp. Ants Prevent 27.7 22.8 38.6 0.9 101 Manage 16.0 16.0 62.3 5.7 106 Roaches Prevent 55.4 6.0 30.1 8.4 83 Manage 25.6 5.8 59.3 9.3 86 Fleas Prevent 44.6 29.2 9.8 92 Manage 26.0 50.0 8.3 96 Rats Prevent 27.4 26.6 12.1 4.8 124 Manage 17.2 18.0 18.9 4.1 122 +The categories DNK ( do not know) and NM (no method) were not part of the comparison. Any method chosen by fewer than 10 districts was included with the Other (Oth) category. 'lndlcates significant difference between classes of district attribute. 84 Table 20. Availability of Pest Management Guidelines. Districts Selecting P-Value for Selection of Yes Response Guidelines Response Based on District: Available Number (% of 307) Size Location Community Yes 59 (19.2) 0.00 1 * 0.837 0.282 No 233 (75.9) Do Not Know 15 (4.9) r — Distribution of Districts Selecting Yes Response Guidelines (as percent of Attribute Class) Available Size Location Community S M L SLP NLP UP U S R Yes 13.2 17.4 42.5 20.3 17.9 16.1 25.0 23.7 15.9 Number of Districts 106 161 40 192 84 31 32 93 182 Guidelines Districts Selecting Prepared Response P-Values for Response Selection Based on District: By Number (% of 58) Size Location Community School 29 (50.5) 0.058 0.577 0.568 District 19 (32.8) Other 1 0 (17.2) 'lndlcates significant difference between classes of district attribute. 85 which of the class sizes were the source of the difference. It was found that the proportions of small and medium classes were not different from each other but were both different from the proportion of the large class. Fifty-eight of the districts with guidelines indicated who prepared them. Twenty-nine said they were prepared by staff in the individual schools, 19 by district personnel and 10 by others. These 'other' responses included four combinations of local and district school personnel, three combinations of school personnel and public health departments, one public health department by itself and two pest control companies. No significant difference existed between district responses for any comparison made. The guidelines covered a number of different pests. Fifty-four districts gave 14 different responses. These were for head lice, mice, other ants, cockroaches, stinging insects, flies, rats, termites, birds, weeds, carpenter ants, fleas, bats and miscellaneous pests such as skunks, spiders. snakes and pests in general. Pesticide Use W. The question about pesticide safety and effectiveness combined two issues making it a poor question as districts could mean different things by the same answer (O-13). Most appeared to respond to the issue of pesticide safety, but a few addressed the effectiveness question, as indicated by written comments. Three hundred three districts responded with 90.4% saying pesticides were safe and effective and 9.6% that they were not (Table 21). A significant difference existed for districts selecting a yes response when grouped by location. Over 92% of the northern and southern lower peninsula districts said pesticides were safe and effective while seventy-five percent of the upper peninsula districts agreed. Almost all districts provided a comment on their response. Yes comments fit 4 general categories. One group spoke of application procedure and pesticide registration saying pesticides are "safe when applied properly”, that they are used "following MSDS requirements ', 86 Table 21. Pesticide Safety and Effectiveness as a Pest Management Method. Districts Selecting P-Values for Selection of Yes Response Safe and Response Based on District: Effective Number (% of 303) Size Location Community Yes 274 (90.4) 0.905 0 .007* 0.786 No 29 (9.6) Distribution of Districts Selecting Yes Response (as Percent of Attribute Class) Safe and Size Location Community Effective S M L SLP NLP UP U S R Yes 87.3 92.6 98.7 92.1 92.7 75.0 87.1 90.3 91.1 Nqu of Districts 102 162 39 189 82 32 31 93 179 'MGICBtOS 819111116811! difference between 0188868 01 (11817161 attribute. 87 or that they use ”only approved pesticides" including ”(pesticides used are approved) around students and food.“ Another group specified that pesticides are safe as long as people are not present saying that they do not use pesticides "around people or food or anywhere that could cause harm", they are used "when students are not in immediate area” , they are used ”during off hours of school building use”, or they are used as a ”last resort and only during designated breaks without children present.“ A third group didn't concern themselves with safe application or presence of people. Instead they left everything up to a pest control company saying ”we use licensed pest control companies”, “we have exterminators out once a month", or “we have an outside firm do the work-~we trust them to use safe methods." The last group said pesticides work well or are the only available method giving responses such as “seem to work well', ”not used extensively“, it's ”been done for years". ”umil pesticides won‘t do the job“, or “pesticides are the only method available to the staff at this time.” Two responses reflected community pressure. One district said ”We keep use down because of public concern." But another district said “Parents demand quick-effective action- it's a PR. problem- We haven't found an answer to head lice, it gets ugly at times.“ Most districts which said pesticides were not safe and effective were concerned about health risks, "I prefer not to use pesticides where children or food may become contaminated“, ”dangerous to students“, and “due to health hazards, pesticides are not considered a safe method.“ One district gave legal reasons ”in some cases yes, but with 'Right-to-Know" and other monitoring laws, one must be careful.” Another district felt it was not proper for its staff to apply pesticides but that it was acceptable for a hired company, “we are now using a pest control service and trying to get away from spraying our own insecticide.” W. Pesticides were said to be used by 69.9% of the 306 responding districts for prevention and by 96.1% for management (Q-14). Twenty-three percent of the districts said they never use pesticides for prevention and only 1.3% said they never use pesticides for management (Table 22). The frequency of pesticide use for prevention as always, 88 Table 22. Pesticide Use Frequency. Pesticide Percent of 306 Districts Selecting Use Frequency Response Use for: Always Often Sometimes Never DNK N R+ Prevention 16.3 18.3 35.3 22.9 2.0 5.2 Management 22.9 42.2 31.0 1.3 0.7 2.0 Districts Indicating P-Value for Selection of Positive Pesticide Pesticide Use” Response Based on District: Use for: Number (% of 306) Size Location Community Prevention 214 (69.9) 0.314 0.306 0.339 Management 194 (96.1) 0.939 0.863 0.995 Number of Districts Selecting P-Values for Response Pesticide Pesticide Use Frequency Selection Based on District: Use for: Always (%) Often (%) Sometimes (%) Total Size Location Community Prevention 50 (23.4) 56 (26.2) 108(50.5) 214 0.014' 0.136 0.103 Managment 70 (23.8) 129 (43.9) 95(32.3) 294 0.041' 0.002' 0.369 Percent of Districts Selecting Pesticide Use Frequency Pesticide By Size By Location By Community Use for: Frequency S M L SLP NLP UP U S R Prevention Always 16.9 24.4 32.4 23.8 20.3 26.7 40.7 25.7 18.0 Often 15.4 30.4 32.4 32.2 18.6 13.3 25.9 27.1 25.6 Sometimes 67 7 45 2 35.3 44.1 61.0 60.0 33.3 47.1 56.4 Numberof Districts 65 115 34 140 59 15 27 70 117 Management Always 20.4 25.5 25.6 26.9 21.0 11.1 26.7 25.6 22.4 Often 35.7 46.5 53.9 45.7 46.9 22.2 56.7 52.2 42.5 Sometimes 43.9 28.0 20 5 27.4 32.1 66.7 16.7 32.2 35.1 Numberof Districts 98 157 39 186 81 27 30 90 174 +DNK .. do not know, NR =- no response. ++Districts with pesticide frequency use of always, often or sometimes. 'lndlcates significant difference between classes of district attribute. 89 often and sometimes was 16.3%, 18.3% and 35.3% of the districts. Frequency of use for management as always, often and sometimes was 22.9%, 42.2% and 31.0%. Selection of a positive pesticide use response was not significamly different for either prevention or management for districts grouped by any atttibute. Significant differences were found, however, in their frequency of pesticide use. For pest prevention, a significant difference occurred between districts grouped by size. Large districts were evently split between always, often or sometimes using pesticides for prevention. Among small districts, 67.7% said they sometimes used pesticides,15.4% responded often and 16.9% always. Conparison of the proportion of each district size class indicating that they always use pesticides for prevention found no significant differences (16.9%-S, 24.3%-M, 32.4%—L). Comparison of the proportion indicating that they often use pesticides found that small districts were significantly different from medium sized districts but that the proportion of large districts was not different from either small or medium ones (15.4%-S, 30.4%-M, 32.4%-L). The lack of a significant difference from small districts was probably due to the low number of large districts selecting the often response. Comparison of the proportion of each district size class indicating that they sometimes use pesticides for prevention found a significant difference between small districts and the other two size classes (67.7%-S, 45.2%-M, 35.2%-L). The frequency of pesticide use for pest management was significantly different between districts grouped by size or location. Large and medium sized districts responded similarly, with approximately 50% often using pesticides and the remainder divided between sometimes and always compared to 36% of the small districts responding often, 20% always and 44% sometimes. Almost 50% of districts in the lower peninsula districts said they used pesticides often while over 66% of upper peninsula districts said they used them sometimes. Comparisons of the proportions selecting the different frequency responses for districts grouped by size found that no differences existed between the proportions selecting the response always (20.4%-S, 25.5%-M, 25.6%-L), no differences existed between the 90 proportions selecting the response often (35.7%-S, 46.5%-M, 53.8%—L), but that the proportion of small districts selecting the response sometimes differed significamly from both medium and large sized districts (43.9°/o-S, 28.0°/o-M, 20.5°/o-L). Two hundred eighty-five districts selected pesticide use responses for both prevention and management. Response con’parison showed that of the districts using pesticides for prevention, most selected equal or greater use frequencies for management. Those districts (10%) that selected lower frequencies may be using pesticides on a preventative basis, resorting to different or multiple pest management methods such as traps or facility modification when specific pests are actually present. Frequency of pesticide use was also compared to district pesticide safety and effectiveness response (O-13). A use frequency of always was not selected for prevention or management by any district which said pesticides were not safe and effective (29 total). We. The question concerning appropriateness of pesticide use in school districts when people are present was not well presented, especially part three which contained a double negative (O-15). Several districts commented that they felt the question was misleading. Review of responses showed that an equal number of districts answered each question part but that most districts answered only two parts. Those districts which did answer all three parts often gave responses to part three which were in conflict with their answers to parts one and two. The question was dropped from analysis. W. More districts indicated that they sometimes, often or always announce intended pesticide use than post notices once pesticides have been applied (78% compared to 45.1% of 304 responses). Amost 15% said they never announce intended use while 40.8% said they never post notices after use (O-16, Table 23). The remaining districts either did not know or did not respond to part of the question. No significant difference in total posting response was found between districts grouped by any attribute. However, a significant difference was found in frequency of posting iMended use 91 Table 23. Pesticide Use Notification. Percent of 304 Districts Selecting Notification Frequency Response Notification Always Often Sometimes Never DNK N R+ Intended Use 31.9 13.5 32.6 14.5 4.6 3.0 Following Use 14.5 6.6 24.0 40.8 9.9 4.3 Districts Selecting Positive P-Values of Positive Response Pesticide Use Notification++ Selection Based on District: Notification Number (% of 304) Size Location Community Intended Use 237 (78.0) 0.887 0.860 0.887 Following Use 137 (45.1) 0.702 0.920 0.897 Number of Districts Selecting Frequency of P-Values for Selection Pesticide Use Notification Based on District: Notification Always (%) Often (%) Sometimes (%) Total Size Location Community Intended Use 97 (40.9) 41 (17.3) 99 (41.8) 237 0.021" 0.739 0.209 Following Use 44 (32.1) 20 (14.6) 73 (53.5) 137 0.178 0.184 0.332 Percent of Districts Selecting Frequency of Notification By Size By Location By Community Notification Frequency S M L SLP NLP UP U S R Intended Use Always 39.8 39.0 51.6 39.7 38.7 54.2 40.7 42.3 40.3 Often 13.3 16.3 32.3 17.9 17.7 12.5 25.9 22.5 13.0 Sometimes 47.0 44.7 16.1 42.4 43.6 33.3 33.3 35.2 46.7 NumberofDistricts 83 123 31 151 62 24 27 71 139 Following Use Always 36.7 24.7 53.3 25.3 41.7 50.0 25.0 31.7 33.8 Often 16.3 13.7 13.3 14.9 16.7 7.1 0.0 17.1 16.3 Sometimes 46.9 61.6 333 59.8 41.7 42.9 75.0 51.2 50.0 NunberotDistricts 49 73 15 87 36 14 16 41 80 +DNK - do not know, NR - no response. “Districts with pesticide frequency use of always, often or sometimes. 'lndlcates significant dlfference between classes of district attribute. 92 announcements for districts grouped by size. More large districts said they always or often announce intended pesticide use (51.6% and 32.3%) compared to almost 50% of small or medium sized districts which said they sometimes announce intended use. Pesticide use notification was compared with responses to pesticide safety and effectiveness (013) to determine if the 29 districts which said pesticides are not safe and effective notify school occupants more frequently about pesticide use than do other districts. Twenty-seven answered the question on intended use notification. Of these ten said they always announce. six often, six sometimes, four never and one do not know. Two hundred sixty-one of the districts which said pesticides are safe and effective answered the same question. 01 these. 86 said they always announce, 32 often, 92 sometimes, 40 never and 11 do not know. No significant difference was found between the two groups (p=0.524). Similar responses were found for posting notices after pesticide application. No significant difference was found (p=0.656). W. Pesticides were applied on all days of the week (017). Approximately 30% of the 303 responding districts applied them on Mondays, Tuesdays, Wednesdays, and Thursdays. Friday, Saturday and Sunday applications were made by 56.1%, 37.3% and 13.9% of the districts (Table 24). Approximately 30% of the districts did not know whether or not they use pesticides on any one of the specific days. Significant differences in positive response were found between districts grouped by size for Monday, Tuesday, Wednesday and Thursday applications. More than half of the large size districts used pesticides on these days compared to approximately 25% of small and medium size districts. Summary Forty-nine tests for differences between response selection to pest prevention and management questions were performed for each district attribute. Twelve significant differences were found for responses grouped by district size while only two significant differences were found for responses grouped by either location or community type. Table 24. Pesticide Application Days. 93 Percent of 303 Districts Selecting Response Day Applied Yes No DNK NR+ Monday 30.7 18.8 31.7 18.8 Tuesday 28.4 20.1 32.0 19.5 Wednesday 29.7 19.1 31.7 19.5 Thursday 28.7 20.1 32.0 19.1 Friday 56.1 7.3 25.7 10.9 Saturday 37.3 19.8 24.4 18.5 Sunday 13.9 28.7 27.1 30.4 Districts Applying P-Values for Selection of Yes Pesticides Response Based on District: Day Applied Number (% of 303) Size Location Community Monday 93 (30.7) 0.028' 0.173 0.675 Tuesday 86 (28.4) 0 .009' 0.132 0.570 Wednesday 90 (29.7) 0 . 0 o 7 ' 0.095 0.383 Thursday 87 (28.7) 0 .0 1 1 * 0.253 0.494 Friday 170 (56.1) 0.062 0.142 0.262 Saturday 1 13 (37.3) 0.114 0.582 0.262 Sunday 42 (13.9) 0.385 0.183 0.167 Distribution of Districts Applying Pesticides (as Percent of Attribute Class) Size Location Community Day Applied S L SLP NLP U S R Monday 26.5 28.0 52.5 33.7 30.1 13.3 31.3 34.8 28.5 Tuesday 25.5 24.2 52.5 31.1 28.9 10.0 31.3 32.6 25.7 Wednesday 24.5 26.7 55.0 33.2 28.9 10.0 31.3 35.9 26.3 Thursday 25.5 24.8 52.5 30.5 30.1 13.3 34.4 32.6 25.7 Friday 47.1 55.9 80.0 62.4 49.4 36.7 62.5 65.2 50.3 Saturday 31.2 36.6 55.0 40.0 33.7 30.0 50.0 41.3 33.0 Sunday 9.8 15.5 17.5 16.8 9.6 6.7 15.6 19.6 10.6 Nunber of Districts 102 161 40 190 83 30 32 92 179 ++DNK .. Do Not Know, NR . No Response. *lndlcates significant difference between classes 01 district attribute. 94 Significant differences were found in district selection of preferred methods for head lice and rat prevention and for fleas and weed management for districts grouped by size. Methods selected for cockroach prevention were significamly different for districts grouped by location and methods selected for mice and rat prevention were significame different for districts grouped by community. The presence of pest management guidelines was significantly different for districts grouped by size. In addition, seven significant differences were found between pesticide question responses. Frequency of use was different for both prevention and management, frequency of announcement of application intent was different, and positive response to pesticide application on Mondays, Tuesdays, Wednesdays and Thursdays was different. Districts grouped by location differed in their frequency of pesticide use for management while districts grouped by community had no differences. The trend in positive response to a question was from small to medium to large districts and from southern lower peninsula to northern lower peninsula to upper peninsula districts. In addition, 80 tests for differences between prevention and management method selection by districts with and without the specific pests were completed. Six significant differences were found between prevention methods selected by districts with and districts without carpenter ants, other ants, cockroaches, flies, mosquitoes and weeds while just three significant differences were found between management methods selected by districts with and those without flies, stinging insects and weeds. Comparison of methods selected for prevention and those selected for management by all districts combined showed seven significant differences. These were for carpenter ants, other ants, cockroaches, fleas, flies, mice and rats. Only one significant difference, for other ants, was found between prevention and management methods selected by districts with the pest while four significant differences, for carpenter ants, cockroaches, fleas and rats, were found between the methods selected by districts without the pests. This indicates that districts with pest 95 problems use more similar methods for both prevention and management than do districts without the specific pest problems. In general, pesticides were selected more frequently by all districts as the preferred method for management compared to prevention. Pesticides were also selected more frequeme for prevention by districts with the pests compared to those without the pests. This indicates that districts with pests consider pesticides as their most effective prevention and management method while districts without the pests can afford to be more lenient in their choice of methods for prevention. 96 W20 Requests for Pest Management Requests for pest management (O—20) were reported as made by all types of school personnel, even students. Less than 20% of the districts said that any one group often requests pest management but more than 50% of the districts said that each group sometimes requests management, except for students (Table 25). Almost 93% of the districts said that school administrators have requested pest management. This group was closely followed by kitchen staff with 90.6% of the districts, custodial staff with 88.3% and teachers with 84.4%. Maintenance staff have requested pest management in 76.9% of the districts, grounds staff in 72.6%, other district personnel in 67.8% and students in 29.3%. Responses entered as Other by 2.7% of the districts included parents, neighbors, county health inspector, pest control company and two unidentified supervisors. No significant difference was found in the number of districts reporting that a particular school personnel group requests pest management when districts were compared by any of the 3 attributes. But when frequency of request was compared, a significant difference was found for school administrators and kitchen staff when districts were compared by size and for custodial and maintenance staff when compared by community type. The number of districts with personnel requesting pest management often increased from small to large districts while few suburban districts reported that personnel requested pest management often compared to urban and niral districts. Communicable Pest Problems Health professionals were selected by more than half of the districts (53.3% of 302 respondees) as the personnel responsible for communicable pest problems such as head lice (Ct-26, Table 26). These were school nurses or district health employees or a combination of persons from the local and district levels along with an occasional county health department (21 .2%, 23.2% and 8.9% of all responding districts). Non-health personnel were selected by 97 Table 25. School Groups Requesting Management of Pest Problems. Percent of 307 Districts Selecting Pest Management Request Frequency for each School Group School Group Often Sometimes Never DNK NR+ School Administrators 14.3 78.2 4.2 1.6 1 .6 Teachers 5.5 78.8 7.5 3.6 4.6 Students 0.3 29.0 47.9 15.6 7.2 Kitchen Staff 17.3 73.3 3.6 1.6 4.2 Custodial Staff 14.3 73.9 4.9 2.3 4.6 Maintenance Staff 10.4 66.4 12.7 2.6 7.8 Grounds Staff 9.4 63.2 13.7 3.9 9.8 District Personnel 11.7 56.0 10.7 4.9 16.6 Other 0.7 2.0 . . 97.4 Districts Selecting Positive Request P-Values for Positive Selection Frequency“ Based on District: School Group Number (% of 307) Size Location Community School Administrators 284 (92.5) 0.926 0.783 0.796 Teachers 259 (84.4) 0.974 0.966 0.997 Students 90 (29.3) 0.121 0.883 0.334 Kitchen Staff 278 (90.6) 0.593 0.135 0.688 Custodial Staff 271 (88.3) 0.539 0.704 0.638 Maintenance Staff 236 (76.9) 0.890 0.497 0.802 Grounds Staff 223 (72.6) 0.652 0.274 0.860 District Personnel 208 (67.8) 0.140 0.204 0.513 P-Values for Positive Frequency Selection Based on District: Districts Reporting School Group as Requesting Pest Management School Group Often (%) Sometimes (%) Total Size Location Community School Adm. 44 (15.5) 240 (84.5) 284 0.003' 0.912 0.813 Teachers 17 (6.6) 242 (93.4) 259 0.843 0.956 0.969 Students 1 (1.1) 89 (98.9) 90 . . . Kitchen Staff 53 (19.1) 225 (80.9) 278 0.026' 0.075 0.146 Custodial Staff 44 (16.2) 227 (83.8) 271 0.428 0.304 0.023* Maintenance Staff 32 (13.6) 204 (86.4) 236 0.783 0.879 0.037‘ Grounds Staff 29 (13.0) 194 (87.0) 223 0.249 0.995 0.864 District Personnel 36 (17.3) 172 (82.7) 208 0.972 0.099 0.379 Table 25 (cont'd). 98 Percent of Districts Reporting School Group as Requesting Pest Management Often or Sometimes. By Size By Location By Community School Group Frequency S M L SLP NLP UP U S R School Admin. Often 10.5 14.0 33.3 15.8 14.1 17.2 19.4 14.6 15.2 Sometimes 89.5 86.0 66.7 84.2 85.9 82.8 80.6 85.4 84.8 NumberDistricts 95 150 39 184 71 29 31 89 164 Teachers Often 5.7 6.6 8.6 6.2 7.0 7.4 7.7 6.3 6.5 Sometimes 94.3 93.4 91.4 93.8 93.0 92.6 92.3 93.7 93.5 Numberof Districts 88 136 35 161 71 27 26 79 154 Students Often 0.0 0.0 7.7 1.7 0.0 0.0 0.0 3.7 0.0 Sometimes 100.0 100.0 92.3 98.31000 100.0 100.0 96.3 100.0 Number of Districts 39 38 58 22 0 5 27 58 Kitchen Often 10.3 21.6 28.9 22.9 13.5 8.0 25.8 23.9 15.1 Sometimes 89.7 78.4 61.1 77.1 86.5 92.0 74.2 76.1 84.9 Number of Districts 87 153 38 179 74 25 31 88 159 Custodial Often 11.9 18.0 18.9 18.1 10.3 19.2 30 . 0 9.2 17.5 Sometimes 88.1 82.0 81.1 91.9 89.7 80.8 70.0 90.8 82.5 Nunberof Districts 84 150 37 177 68 26 30 87 154 Maintenance Often 12.7 14.8 10.3 14.1 11.7 15.0 1 6.7 5.3 17.6 Sometimes 87.3 95.2 89.7 85.9 88.3 85.0 83.3 94.7 82.4 Number of Districts 79 128 29 156 60 20 24 76 136 Grounds Often 8.6 13.7 20.7 12.9 13.3 12.5 13.0 11.3 14.0 Sometimes 91.4 86.3 79.3 87.1 86.7 87.5 87.0 88.7 86.0 Numberof Districts 70 124 29 147 60 16 23 71 129 District Pers. Often 17.2 16.9 18.8 17.5 22.9 0.0 9.1 21.4 17.9 Sometimes 82.8 83.1 81.2 82.5 77.1 100.0 90.9 78.6 82.1 Numberof Districts 58 118 32 143 48 17 22 70 106 +DNK = do not know, NR . no response. ++Districts in which school group often or sometimes requests pest management. *lndlcates significant difference between classes of district attribute. 99 Table 26. Personnel Responsible for Communicable Pest Problems. ‘ Districts Selecting Personnel Personnel Number (% of 302) Nurse at School where problem exists (local personnel) 64 (21.2) District Health Personnel 70 (23.2) Other Health Personnel, mixed levels (local, district, county) 27 (8.9) Health Personnel, mixed levels, with non-health Personnel, mixed levels 23 (7.6) Non-Health Local School Personnel 85 (28.1) Non-Health District Personnel 7 (2.3) Non-Health Personnel, mixed levels (local, district) 7 (2.3) Pest Control Companies 4 (1 .3) Parents 2 (0.7) Do Not Know 13 (4.3) Total Number Responding Districts 302 P-Values for Response Selection Districts Selecting Based on District: Personnel Type Number (% of 283) Size Location Community Health 161 (55.7) 0.065 0.509 0.323 Non-Health 99 (34.3) Mix 23 (8.0) Local 149 (51.6) 0.187 0.257 0.332 Districts 77 (26.6) Mix 57 (19.7) 100 32.7% of the districts. Most often these were principals and teachers but sometimes superintendents were named or personnel at both local and district levels (28.1%, 2.3% and 2.3% of all responding districts). A mix of health and nonhealth personnel was selected by 7.6% of the districts while 1.3% selected pest control companies and 0.7% selected parents. Selections were compared to determine if there was any difference between districts naming health, non-health or health and non-health personnel. Selections were also compared on the basis of local, district or local and district personnel. No significant differences were found for either personnel type distribution for any district groupings. Selection of Pest Management Methods As school districts are composed of personnel with different levels of authority, pest management decisions can be made and executed by different people. Districts were asked whether the selection of pest management methods was the responsibility of those who decide management is required or up to those who actually perform pest management (Cl-25). Of 305 responding districts, 80.7% said that the personnel who decide that management is needed at least sometimes decide on the method to be used, 87.9% of the districts said that the personnel who perform pest management decide on the method, and 4.1% of the districts said that others, such as an unidentified supervisor, contractor or director, decide (Table 27). The frequency of district selection of each personnel type was compared against the expected selection frequency for the different district groupings. No significant differences were found. Districts which said the management methods were selected by those who decide management was needed were evenly distributed between choosing always, often and sometimes as frequency of method selection (27.5% to 26.9% to 26.2%). Districts which said the management methods were selected by those who perform pest management were not as evenly distributed. Always, often and sometimes were selected by 36.7%, 32.1% and 19.0% of the districts . Comparison of selection frequencies showed a significant difference only between districts that said personnel who perform management decide on methods and only 101 Table 27. Personnel Who Decide on Pest Management Methods. Percent of 305 Districts Selecting Frequency with which Specified Personnel Make Method Decisions Personnel Who Always Often Sometimes Never DNK N R+ Decide Mgmt Need 27.5 26.9 26.2 4.3 2.0 13.1 Perform Mgmt 36.7 32.1 19.0 2.6 1.6 7.9 Other 2.6 1.3 0.3 . . 95.7 Districts Reporting Personnel P-Values for Response Selection as Making Decisions:H Based on District: Personnel Who Number (% of 305) Size Location Community Decide Mgmt Need 246 (80.7) 0.944 0.588 0.792 Perform Mgmt 268 (87.9) 0.853 0.896 0.938 Districts Reportinfi’ersonnel as P-Values for Frequency Personnel Selecting Pest Management Methods Selection Based on District: . Who Always (%) Often (%) Sometimes (%) Total Size Location Community DOCldO Mgtheed 84 (34.1) 82 (33.3) 80(32.5) 246 0.696 0.598 0.410 Penonn Mgmt 112 (41.8) 98 (36.6) 58(21.6) 268 0.006' 0.064 0.257 Percent of Districts Reporting Personnel as Selecting Method Always, Often or Sometimes. By Size By Location By Community Personnel Who Frequency S M L SLP NLP UP U S R DecideMgmt Always 35.2 32.5 37.5 34.0 35.2 32.1 50.0 32.5 32.7 Need Often 37.5 31.7 28.1 30.6 39.4 32.1 27.3 29.9 36.1 Sometimes 27.3 35.7 34.4 35.4 25.4 35.7 22.7 37.7 31.3 NumberofDistricts 88 126 32 147 71 28 22 77 147 Perform Mgmt Always 33.7 42.3 59.5 46.7 32.9 34.6 51.7 46.3 37.7 Often 34.8 37.3 37.8 34.9 43.8 26.9 37.9 36.3 36.5 Sometimes 31.5 20.4 2.7 18.3 23.3 38.5 10.3 17.5 25.8 NumberofDistricts 89 142 37 169 76 26 29 80 159 +DNK :2 do not know, NR = no response. ++Districts in which personnel always, often or sometimes make decisions on methods to be used for pest management. 'Indlcates significant difference between classes of district attribute. 102 when districts were grouped by size. More than half of the large districts said these personnel always decide on methods to be used and all but one of the remaining said such personnel decide often. Since districts could select both personnel types, each district's selections were examined. Twenty-five (8.2%) only selected personnel who decide management is needed, 47 (15.4%) only selected personnel who perform management, 221 (72.5%) selected both, 8 (2.6%) selected other and 4 (1 .3%) did not know. No significant differences were found in the distribution of districts selecting either or both personnel types for any district grouping. It was observed that 43 districts (14.1%) selected always for both personnel types. These districts did not belong to any specific district group. This implies that for some districts, the personnel that decide pest management is needed may also be the personnel that perform pest management. Pest Management Execution Districts were asked to identify personnel who use (apply) pest management methods such as pesticides, traps and other special equipment not used in normal sanitation and maintenance procedures (O-27). Three hundred five districts indentified personnel responsible for indoor pest management but only 241 did so for outdoor pest management. The 64 nonresponding districts represented all district attributes and could not be distinguished by any specific characteristic. Those districts may not have considered outdoor pest management a necessity and so failed to select a response. WW- Custodial staff was selected most frequently (78.0%) as the personnel type who at least sometimes performed indoor pest management (Table 28). Pest control companies followed closely (73.4%). However, more districts selected pest control companies as most likely to perform pest management than did so for custodial staff (47.2% compared to 45.6%). Maintenance was selected by 62.6% of the districts, kitchen staff by 44.3%, and grounds staff by 38.7%. It is not clear why districts selected grounds staff for indoor pest management. Perhaps these districts did not distinguish between this personnel type and 103 Table 28. Personnel Who Perform Indoor Pest Management. Percent of 305 Districts Selecting Frequency with which Each Personnel Group Performs Indoor Pest Management Personnel Most Likely Sometimes Never DNK RLU NR+ Custodial Staff 45.6 32.5 7.9 0.0 14.1 Grounds Staff 15.7 23.0 21.0 1.3 39.0 Maintenance Staff 28.9 33.8 11.1 1.0 . 25.2 Kitchen Staff 17.0 26.9 31.8 1.0 0.3 23.3 Pest Control Company 47.2 26.2 10.5 3.3 . 12.8 Other 1.0 0.3 . . 0.3 98.7 Districts Selecting Positive P-Values for Positive Frequency Frequency Response++ Selection Based on District: Personnel Number (% of 305) Size Location Community Custodial Staff 238 (78.0) 0.821 0.942 0.893 Grounds Staff 1 18 (38.7) 0.780 0.300 0.943 Maintenance Staff 191 (62.6) 0.202 0.719 0.412 Kitchen Staff 135 (44.3) 0.708 0.508 0.304 Pest Control Company 224 (73.4) 0.001' 0.000" 0.039' Distribution of Districts Selecting Positive Response for Personnel (as Percent of Attribute Class) Size Location Community Personnel S M L SLP NLP UP U S R CustodialStaff 80.0 78.8 70.0 77.5 77.4 83.3 71.0 78.3 79.1 GroundsStaff 35.2 40.6 40.0 42.9 31.0 33.3 41.9 39.1 37.9 Maintenance Staff 62.6 67.9 42.5 65.4 58.3 56.7 54.8 55.4 67.6 Kitchen Staff 47.6 43.8 37.5 40.8 50.0 50.0 41.9 35.9 48.9 PestControICompany 47.6 85.0 95.0 85.9 57.1 40.0 90.3 88.0 63.2 Percent Distribution of Districts Selecting Multiple Personnel as Districts Performing Indoor Pest Management Number of Selecting By Size By Location By Community Personnel Number (%) S M L SLP NLP UP U S R 1 64 (21.0) 25.7 17.5 22.5 18.9 26.2 20.0 22.6 20.7 20.9 2 50 (16.4) 17.1 13.1 27.5 14.1 17.9 26.7 19.4 14.1 17.0 3 67 (22.0) 23.8 22.5 15.0 19.9 25.0 26.7 12.9 27.2 20.9 4 74 (24.3) 21.0 30.0 10.0 28.3 16.7 20.0 22.6 23.9 24.7 5 50 (16.4) 12.416.9 25.0 18.9 14.3 6.7 22.6 14.1 16.5 Numberof Districts 305 105 160 40 191 84 30 31 92 182 Table 28 (cont'd). 104 Percent Distribution of Districts Selecting Multiple Personnel as Distrias Performing Indoor Pest Management Personnel Selecting By Size By Location By Community Type“+ Number (%) S M L SLP NLP UP U S R School 81 (26.6) 52.4 15. 0 5.0 14.1 42. 9 60. 0 9. 7 12. 0 36.8 PC 44 (14.4) 9..515622.5 15.2 1311 13.3 22..616312.1 Both 180 (59.0) 38.1 69. 4 72.5 70.7 44. 0 2.6 7 67. 7 71. 7 51.1 Number of Districts 305 105 160 40 191 84 30 31 92 182 P-Values for Selections Based on District: — Comparison Size Location Community Multiple Personnel Performing Indoor Pest Management (1,2, 3, 4, 5) 0.041“ 0.184 0.857 Personnel Type Performing Indoor Pest Management (School, PC, Both) 0.000' 0.000' 0.000' +DNK - do not know, RLU a response level unknown because either multiple responses were selected for the personnel category or no response was selected for an entry made under Other, NR = no response. +‘l'lncludes districts selecting personnel type as most likely, sometimes or RLU. +++Personnel types were categorized as local (belonging to the school system), PC (a private pest control companY). and Both (somepersonnel belonging to the school system and some part of a private pest control company). 'Indlcates significant dlfference between classes of district attribute. 105 maintenance or custodial staff. Other personnel were selected by 1.6% of the districts and included a mix of grounds and maintenance (Building and Grounds), indicating that these two staff types are not separate in all districts. Pest control companies were the only personnel type which showed a significant difference in selection frequency between district groupings. Large and middle sized districts selected pest control companies more than small ones (95.0 and 85.0% compared to 47.6%), districts in the southern lower peninsula selected them more than districts elsewhere (85.9% compared to 57.1 and 40.0%), and urban and suburban districts selected them more than mral ones (90.3 and 88.0% compared to 63.2%). Many districts made multiple selections. These were totaled for comparison to determine if more personnel perform pest management in certain district types. Fifty (16.4%) of the districts selected all five personnel types, 74 (24.3%) selected four types, 67 (22.0%) selected three, 50 (16.4%) selected two, and 64 (21.0%) selected one. A significant difference was found between districts when grouped by size. But no trend was observed between district size and number of personnel selected. Districts were further identified by category of personnel selected as performing indoor pest management. Eightly-one (26.6%) of the districts selected just school personnel while 44 (14.4%) only selected pest control companies. Both were selected by 180 districts (59.0%). Highly significant differences were found for district selections grouped by size, location or community type. Approximately 70% of large and medium sized districts selected both compared to 52% of small districts selecting school personnel alone; 70.6% of the southern lower peninsula districts selected both while 86.7% of the upper peninsula districts selected school personnel alone; and almost 70% of urban and suburban community districts selected both while twice as many rural as urban and suburban districts selected school personnel alone. Went. Districts made fewer selections for personnel performing outdoor pest management. Grounds staff was selected most frequemly with 175 (57.4%) 106 districts choosing such staff as most likely or sometimes performing outdoor pest management (Table 29). Maintenance staff followed closely with 154 (50.5%) selecting districts. Pest control companies were selected by 44.3% of the districts and followed both custodial and maintenance staff as being most likely to perform outdoor pest management. Custodial staff was selected by 110 (36.1%) of the districts and kitchen staff by 32 (10.5%). A district can interpret kitchen staff as having outdoor responsibilities if they are involved with garbage sanitation or outdoor food facility care. Significant differences were found for selection of grounds staff between districts grouped by size and location, selection of kitchen staff between districts grouped by location and selection of pest control companies between districts grouped by size, location and community. Selection trends were similar to those for indoor pest management except for an opposite trend in the selection of kitchen staff. Almost four times as many upper peninsula districts selected kitchen staff as did southern lower peninsula districts (23.3% compared to 6.8%). Multiple selections for personnel types performing outdoor pest management were fewer than for indoor pest management. Only 12 (5.0%) of the districts selected all five categories while 50 to 63 districts made one to four selections. No significant differences in the number of multiple selections were found between district groups. More districts (44.0%) selected only school personnel for outdoor pest management than did so for indoor pest management. Fewer districts selected only pest control companies (7.5%) or both school personnel and pest control companies (48.5%). Personnel category selection (school only, pest control company only, or both) was significantly different for all district comparisons with selection trend similar to that for indoor pest management. Pest Control Company Employment Pest control companies (PCCs) have been employed by approximately three quarters of 310 responding districts (028, Table 30). Of the 221 districts which employed PCCs, 210 indicated that the P003 performed indoor and/or outdoor pest management. Two districts did 107 Table 29. Personnel Who Perform Outdoor Pest Management. Percent of 305 Districts Selecting Frequency with which Each Personnel Group Performs Outdoor Pest Management Personnel Most Likely Sometimes Never DNK RLU NR Custodial Staff 16.3 19.7 19.3 0.0 44.6 Grounds Staff 43.3 14.1 5.2 1.6 35.7 Maintenance Staff 25.9 24.6 10.8 1.0 37.7 Kitchen Staff 4.3 6.2 41.6 0.7 47.2 Pest Control Company 22.3 22.0 14.4 2.6 . 38.7 Other 1.3 . . . 0.3 98.4 Districts Selecting Positive P-Values for Positive Response Frequency Response+ Selection Based on District: Personnel Number (% of 305) Size Location Community Custodial Staff 1 1 0 (36. 1) 0.705 0.175 0.281 Grounds Staff 175 (57.4) 0.023' 0.01 6* 0.155 Maintenance Staff 154 (50.5) 0.302 0.603 0.700 Kitchen Staff 32 (10.5) 0.228 0.0 1 6" 0.080 Pest Control Company 135 (44.3) 0.001' 0.028' 0.022* (as Percent of Attribute Class) Distribution of Districts Selecting Positive Response for Personnel Size Location Community Personnel S M L SLP NLP UP U S R CustodialStaff 40.0 33.8 35.0 31.4 41.7 50.0 48.4 29.3 37.4 GroundsStaff 41.0 66.3 65.0 67.0 40.5 43.3 64.5 68.5 50.5 MaintenanceStaff 45.7 56.3 40.0 53.4 440 50.0 45.2 46.7 53.3 Kitchen Staff 14.3 7.5 12.5 6.8 14 3 23 3 16.1 4.3 12.6 PestControICompany 26.7 50.0 67.5 51.3 36 9 20 0 61.3 55.4 35.7 Percent Distribution of Districts Selecting Multiple Districts Personnel as Performing Outdoor Pest Management Number of Selecting+++ By Size By Location By Community Personnel Number (%) S M L SLP NLP UP U S R 1 63 (26.1) 31.6 24.2 21.2 22.7 34.4 26.1 28.0 27.3 25.2 2 60 (24.9) 26.3 22.7 30.3 24.0 23.4 34.8 12.0 26.0 26.6 3 56 (23.2) 21.1 25.8 18.2 26.0 21.9 8.7 8.0 26.0 24.5 4 50 (20.7) 15.8 24.2 18.2 22.7 14.1 26.1 40.0 16.9 19.4 5 12 (5.0) 5.3 3.0 12.1 46 6.3 44 12.0 3.9 4.3 Numberof Districts 241 76 132 33 154 64 23 25 77 139 1 08 Table 29 (cont'd). Percent Distribution of Districts Selecting Multiple Districts Personnel as Performing Outdoor Pest Management Personnel Selecting+++ By Size By Location By Community Type++++ Number (%) S M L SLP NLP UP U S R School 106 (44.0) 63. 2 39. 4 18. 2 36.7 51.6 73.9 24. 0 33. 8 33.2 PC 18 (7.5) 5.3 7. 6 12. 1 7.1 9.4 4.4 8. 0 7.8 7.2 Both 117 (48.5) 31. 6 53.0 69. 7 56.5 39.1 21.7 68.0 58.4 39.6 Number of Districts 241 76 132 33 154 64 23 25 77 139 P-Values for Selections Based on District: Comparison Size Location Community Nurrber of Personnel Performing Outdoor Pest Management (1, 2, 3, 4, 5) 0.333 0.408 0.121 Personnel Type Performing Outdoor Pest Management (School, PC, Both) 0.000 ' 0 . 005' 0 .0 1 3* +DNK - do not know, RLU a response level unknown because either multiple responses were selected for the personnel category or no response was selected for an entry made under Other, NR = no response. “Includes districts selecting personnel type as most likely, sometimes or RLU. ++~‘Sixty-four districts were omitted as 58 did not respond to this part of the question and 6 did not know what personnel type performed outdoor pest management. ++“Personnel types were categorized as local (belonging to the scth system), PC (a private pest control company), and Both (somepersonnel belonging to the school system and some part of a private pest control company). 'lndlcates significant difference between classes of district attribute. 109 Table 30. Employment of Pest Control Companies by School Districts. Pest Control Districts Selecting P-Value for Selection of Yes Repsonse Company Response Based on District: Employed Number (% of 310) Size Location Community Yes 221 (71.3) 0.000' 0.000* 0.000' No 85 (27.4) Do Not Know 4 (1 .3) Distribution of Districts Selecting Yes Response Pest Control (as Percent of Attribute Class) Company Size Location Community Employed S M L SLP NLP UP U S R Yes 44.4 82.7 97.5 86.5 54.1 27.2 90.6 88.2 59.5 Number of Districts 108 162 40 192 85 33 32 93 185 *Indlcates significant difference between classes Of dlStl’lCt attribute. 110 not answer the question, eight did not select a response concerning PCCs and one said that PCCs never perform indoor and outdoor pest management. Of the 224 districts which said that PCCs performed indoor and/or outdoor pest management, 14 did not select yes for PCC employment. Thirteen said they did not employ PCCs while one did not answer the question. The multiple response stnicture of O-27 may have caused some confusion in district answers. In addition, some districts may have responded no to PCC employment because they perceived this employment as preventative instead of being for pest management (wording used in O-28). Yes response selection by districts grouped by size, location or community type were highly significant. Over 80% of all large and medium sized districts, of those in the southern lower peninsula and of those that were located in urban or suburban communities employed PCCs. Only 44.4% of small districts, 27.2% of those in the upper peninsula and 54.1% of those in the northern lower peninsula, and 59.5% of those located in rural communities employed PCCs. Comparison of the proportion of districts indicating that they employ PCCs by the different size classes showed that the proportions of all three were significamly different from each other (44.4%-S, 82.7%-M, 97.5%-L). W. Districts which employed PCCs identified quality of service as the most important criteria used in hiring decisions (029, Table 31). Cost was named second while being a local business was chosen third (97.2%, 86.3% and 72.6% of all selections). Other responses were mostly concerned with quality of service. Examples included 'qualified personnel', 'safety‘, 'type of chemicals used', 'reliable', 'Iiability and reputation', 'knowledge', 'availability' and 'compliance with Right—to-Know'. No difference was found in criteria selection between district groupings. Wm. Both administrative and support service personnel were said to negotiate PCC contracts. The questionnaire presented school (principal and secretary) and district (superintendent and business management) level administration choices (O—30). These were selected by 215 of the 221 districts employing PCCs (Table 32). In 111 Table 31. Selection Criteria Used by Dlstrlcts Employing Pest Control Companies. Number and Percent of 212 Districts All Districts Selection Selecting Criteria Importance Level + Selecting Criteria Crieria First Second Third Total (% of 212) Quality of Service 184 (86.8) 16 (7.5) 6 (2.8) 206 (97.2) Cost 14 (6.6) 142 (67.0) 27 (12.7) 183 (86.3) Local Business 5 (2.4) 31 (14.6) 118 (55.7) 154 (72.6) Other 6 (2.8) 2 (0.9) 4 (1.9) 12 (5.7) Do Not Know 3 (1.4) 2 (0.9) 13 (6.1) 18 (8.5) No Response 0 (0.0) 19 (9.0) 44 (20.8) 63 (29.7) Level of Nunber of Districts P-Value for Selection of Criteria Based on: Importance Selecting Criteria Size Location Community First 209 0.551 0.061 0.773 Second 191 0.728 0.887 0.985 Third 145 0.496 0.661 0.631 +Criteria were selected by 212 of the 221 districts which indicated that they hire pest control companies In response to question 28. 112 Table 32. School Personnel Who Negotiate Pest Control Company Contracts. Percent of 221 Districts Selecting Frequency with which Each Personnel Group Negotiates Pest Control Company (PCC) Contracts+ Personnel Always Often Sometimes Never DNK RLU NR” Principal 1.8 2.3 8.6 45.2 0. 5 . 41.6 Secretary 0.5 0.5 0.5 55.2 0. 9 . 42.5 Superintendent 19.0 6.3 12.2 29.4 0. 9 0.5 31. 7 Business Manager 28.5 5.4 10.9 18.6 0. 9 0.5 35. 4 Other Administration 2.3 0.5 Purchasing 1.4 0.5 . . . . 49.8 Support Services 26.7 12.2 1.4 . . 5.9 Districts Selecting Positive P-Value for Positive Frequency Frequency Response+++ Selection Based on District: Personnel Number (% of 221) Size Location Community Principal 28 (12.7) 0.208 0.600 0.319 Secretary 3 (1 .4) . . .++++ Superintendent and other Administration 90 (40.7) 0 . 0 0 0" 0 . 0 2 9" O . 000* Business Manager and Purchasing 104 (47.1) 0.040‘ 0.671 0.646 Support Services 102 (46.2) 0.0 1 8' 0.044' 0.148 Distribution of Districts Selecting Positive Frequency Response (as Percent of Attribute Class) Size Location Community Personnel S M L SLP NLP UP U S R Principal 18.8 12.7 5.1 11.4 17.4 11.1 3.4 13.4 14.5 Secretary 4.2 0.7 0. 0 0.6 4.3 0.0 0.0 1.2 1.8 Superintendent and otherAdministration 70.8 39.6 7. 7 33.7 60.9 55.6 20. 7 23. 2 59.1 Business Manager and Purchasing 25.0 52.2 56.4 45.8 47.8 66.7 51.7 51.2 42.7 Support Services 22.9 50.0 61.5 52.4 30.4 11.1 51.7 56.1 37.3 Nunber of Districts 48 134 39 166 46 9 29 82 110 113 Table 32 (cont'd). Percent Distribution of Districts Selecting Multiple Districts Personnel as Negotiating PCC Contracts Number of Selecting+++++ By Size By Location By Community Personnel Number (%) S M L SLP NLP UP U S R 1 138 (62.7) 67.0 58.2 74.4 64.2 56.5 66.7 72.4 65.9 57 8 2 59 (26.8) 25.5 29.9 18.0 26.1 30.4 22.2 27.6 23 2 29 4 3 21 (9.5) 8.5 10.5 7.7 9.1 10.9 11.1 0.0 9 8 119 4 2 (0.9) 0.0 1 5 0 0 0.6 2.2 0.0 0.0 1 2 0.9 Number of Districts 220 47 134 39 165 46 9 29 82 109 Percent Distribution of Districts Selecting Multiple Districts Personnel as Negotiating PCC Contracts Personnel Selecting+++++ By Size By Location By Community Type Number (%) S M L SLP NLP UP U S R Admin. 118 (53.6) 76.6 50.0 38.5 47.3 69.6 88.9 48.3 43.9 62.4‘ Support Staff 59 (26.8) 10.6 27.6 43.6 32.7 10.9 0.0 37.9 36.6 16.5 Both 43 (19.5) 12.8 22.4 18.0 20.0 19.6 11.1 13 8 19.5 21.1 Number of Districts 220 47 134 39 165 46 9 29 82 109 P-Value for Selections Based on District: Comparison Size Location Community Number of Personnel Who Negotiate PCCContracts (1,2,3-4) 0.451 0.897 0.257 Personnel Type Who Negotiates PCC Contracts (Adm, Support Staff, Both) 0.002* 0.005' 0.01 5' +Distribution was based on responses made by the 221 districts who indicated that they employ pest control companies in response to question 28. +‘fDNK a do not know, RLU :- response level unknown because either multiple responses were selected for the personnel category or no response was selected for an entry made under Other, NR . no response. +++Includes districts selecting personnel type as Always, Often, Sometimes and RLU. ++++Statistics were not calculated as few districts selected personnel type. +++++One district was omitted from comparison as it did not know what personnel type negoitated PC contracts. ‘Indlcates significant difference between classes of district attribute. 114 addition, 112 districts wrote in other administrators (6), purchasing personnel (4) and support service personnel (102) such as Director of Building and Grounds, Supervisor of Maintenance, Physical Plant Supervisor, Custodial Supervisor, Director of Transportation, Building and Grounds, Director of Operations, Director of Grounds, Auxilliary Services Director, etc. Administrator write-ins were totaled with superintendent selections while purchasing personnel write-ins were added to business manager selections. Most PCC contract negotiation was said to be performed by district administration and/or support service personnel. Superintendent, business manager and support services personnel were each selected by almost half of the districts (40.7%, 47.1% and 46.2%). Relatively few districts selected local school administrators (12.7% principal, 1.4% secretary). Frequency of district administration and support services personnel selection was significantly different for several district comparisons. Superintendent selection was highly significant between districts compared by size or community and significant when conpared by location. More than 50% of all small districts, northern lower peninsula and upper peninsula districts, and districts located in rural communities selected these personnel. By contrast, business managers personnel selection was significamly different only for districts compared by size with over 50% of medium and large districts selecting these personnel. Support services personnel selection was significantly different for districts compared by size or location. Again, over 50% of all large and medium sized districts as well as of districts located in the southem lower peninsula selected these personnel. A number of districts selected several personnel as negotiating PCC contracts. Two districts (0.9%) selected four types, 21 (9.5%) selected three, 59 (26.8%) selected two and 138 (62.7%) selected one. One district selected do not know for all personnel types and was not included for comparison purposes. Although many districts selecting 3 or 4 personnel types were medium sized, located in the southern lower peninsula and found in mral communities, no significant differences were found for the number of multiple selections made by different 115 district types. Some districts which made multiple personnel selections may have done so because the person responsible for PCC negotiations could be classified as more than one type rather than because different individuals actually negotiate contracts. Question design did not allow for this discrimination. Districts were also compared on the basis of selection category, that is administration alone, support services personnel alone or both. Highly significant differences were found for district size or location comparisons and a significant difference was found for community type comparison. In general, small sized districts, northern lower peninsula and upper peninsula districts and those in rural communities selected administration personnel. Support staff alone was selected most frequently by large sized districts, those in the southern lower peninsula and those In urban and suburban communities. Both personnel types were selected by 11 to 22% of all district groupings. MW. Pest management methods, pesticides used and a requirement for effectiveness evaluation were selected by 70.8, 65.3 and 63.0% of 216 responding districts (O-31, Table 33). Records filed with school personnel and pest number requiring management were selected by only 38.4% and 20.4% of the districts. Factors written in as Other concerned frequency of service. Four districts said weekly, monthly or regular visitations were specified in PCC contracts. Up to 25% of the districts Indicated do not know and an additional 3% to 7% did not respond to each factor. Comparisons between district groups were made only on the frequency of yes responses. No signficant differences were found. Many districts selected multiple factors. The number of factors selected by 192 of the 216 responding districts was totaled. Twenty-four districts were eliminated as they selected do not know for all contract factors. Five factors were selected by 10.9% of the districts, four by 24.5%, three by 30.2%, two by 19.3% and one by 10.4%. Nine districts selected no for each factor implying that they do not negotiate PCC contracts. No significant differences were found in 116 Table 33. Factors Deflned In Contracts with Pest Control Companies. Percent of 216 Districts Selecting Response+ Factors Yes No DNK NR++ Pest Number Requiring Management 20.4 49.1 24.1 6.5 Pest Management Methods to be Used 70.8 10.6 15.3 3.2 Pesticides to be Used 65.3 13.4 16.2 5.1 Evaluation of Effectiveness Required 63.0 11.6 22.2 3.2 Records on Pest Management Action 38.4 27.8 26.9 6.9 to be filed with School Personnel 1.9 . . 98.1 Other Districts Selecting Yes P-Value for Yes Selection Based on District: Factors Number (% 01216) Size Location Community Pest Number 44 (20.4) 0.350 0.380 0.321 Pest Mgmt. Methods 153 (70.8) 0.642 0.830 0.807 Pesticides 141 (65.3) 0.145 0.810 0.497 Evaluation 136 (63.0) 0.097 0.198 0.383 Records 83 (38.4) 0.213 0.564 0.739 Other 4 (1.9) . . . P-Value for Selection of Multiple Number of Districts With Multiple Factors Factors Based on District: Factors Number (% of 192)+++ Size Location Community 0 9 (4.7) 0.639 0.676 0.962 1 20 (10.4) 2 37 (19.3) 3 58 (30.2) 4 47 (24.5) 5 21 (10.9) +Factors were identified by 216 of the 221 districts which indicated that they hire pest control companies in response to question 28. ++DNK - do not know, NR = no response. +++Twenty-four districts were omitted as they selected do not know for all contract factors. 117 number of districts selecting multiple contract factors for districts grouped by size, location or community type. W. Hall of the districts (56.4% of 220 employing PCCs) said they negotiate contracts for one year periods (O-32, Table 34). Several (30.9%) said contracts are in effect only for the duration of a specific job while a few said contracts are negotiated to last two to three years (4.1%). Other responses included unidefined time periods (5 districts) or the combination of job and one year time periods depending on pest and situation (4 districts). Ten districts (4.5%) selected do not know. No significant differences in selection were found for any district grouping. Wee. PCCs have been employed to manage a minimum of 21 different pests (Q-33). In addition to the 16 pests listed in the questionnaire, moles, silverfish, carpet beetles, red mites and skunks were added as Other. More than half the districts employing PCCs have done so specifically for cockroaches, mice and ants other than carpenter ants (Table 35). Twenty-five to 50% of the districts have errployed PCCs for stinging insects, termites, carpenter ants and rats. Ten to 25% have employed them for weeds, fleas, flies, head lice, diseases of outdoor plants and mosquitoes while less than 10% have employed them for Insect pests of outdoor plants, bats, birds and others. The number of districts employing PCCs for each specific pest was compared against the expected number for each district attribute. Significant differences were found for several pests. PCC employment for management of cockroaches, stinging insects, rats, fleas, head lice and bats was significant for districts compared by size. PCC employment for management of carpenter ants and insect pests of outdoor plants was significant for districts compared by location. And PCC employment for management of cockroaches, stinging insects, weeds and bats was significant for districts compared by community type. In general, large districts hired PCCs more frequently than small or medium sized ones. Southern lower peninsula districts hired PCCs more frequently for termites while upper peninsula districts hired them more often 118 Table 34. Length of Pest Control Company Contracts. Districts Selecting Contract Length Length Number (% of 220)+ Duration of Specific Job 68 (30.9) One Year 124 (56.4) Two Years 5 (2.3) Three Years 4 (1.8) Other 9 (4.1) Do Not Know 10 (4.5) Pest Control Districts Selecting P-Value for Selection of Yes Repsonse Company Response Based on District: Employed Number (% of 201) Size Location Community Specific Job 68 (32.4) 0.184 0.413 0.130 One Year 124 (59.0) Multiple Years 9 (4.3) +Factors were identified by 220 of the 221 districts which indicated that they hire pest control companies in response to question 28. 119 Table 35. Pests which Pest Control Companies have been Employed to Manage. Percent of 221 Districts Employing PCCs (Pest Control Companies) for Each Specific Pest Pest Yes No DNK NR+ Cockroaches 61.4 28.2 5.0 5.5 Mice 58.2 30.9 2.3 8.6 Other Ants 52.7 35.0 3.2 9.1 Stinging Insects 37.7 45.5 4.1 12.7 Termites 33.2 44.5 7.3 15.0 Carpenter Ants 29.1 47.3 9.5 14.1 Rats 26.4 51.8 4.1 17.7 Weeds 21.4 60.0 2.7 15.9 Fleas 13.2 60.0 8.6 18.2 Flies 13.2 62.7 7.7 16.4 Head Lice 10.9 63.2 9.1 16.8 Diseases of Outdoor Plants 10.5 64.5 5.0 20.0 Mosquitoes 10.0 64.1 8.2 17.7 Insect Pests of Outdoor Plants 9.5 64.5 5.0 20.9 Bats 9.1 66.4 5.9 18.6 Birds 5.9 69.1 5.9 19.1 Other 3.6 0.9 0.0 95.5 Districts Employing PCs P-Value for Yes Response for Specific Pest Mgmt Based on Districts: Pest Number (% of 221) Size Location Community Cockroaches 135 (61.4) 0.01 6* 0.978 0.028' Mice 128 (58.2) 0.131 0.570 0.198 Other Ants 116 (52.7) 0.762 0.806 0.640 Stinging Insects 83 (37.7) 0.01 2* 0.571 0.005' Termites 73 (33.2) 0.944 0.042' 0.096 Carpenter Ants 64 (29.1) 0.409 0.579 0.334 Rats 58 (26.4) 0.01 1 ' 0.940 0.188 Weeds 47 (21.4) 0.915 0.996 0.026' Fleas 29 (13.2) 0.000' 0.199 0.194 Flies 29 (13.2) 0.663 0.199 0.599 Head Lice 24 (10.9) 0.024' 0.999 0.822 Diseases of Outdoor Plants 23 (10.5) 0.143 0.354 0.364 Mosquitoes 22 (10.0) 0.125 0.511 0.103 Insect Pests of Outdoor Plants 21 (9.5) 0.608 0.036' 0.288 Bats 20 (9.1) 0.033' 0.361 0.011' Birds 13 (5.9) . . . Other 8 (3.6) Table 35 (cont'd). 120 Distribution of Districts Employing PCs for Management of the Specific Pests (as Percent of Attribute Class) Size Location Community Pest S M L SLP NLP UP U S R Cockroaches 35.4 64.7 82.1 61.2 60.9 66.7 78.6 74.4 47.3 Mice 47.9 55.6 79.5 60.6 47.8 66.7 71.4 65.9 49.1 Other Ants 47.9 55.6 48.7 54.5 47.8 44.4 46.4 58.5 50.0 Stinging Insects 29.2 33.1 64.1 40.0 32.6 22.2 57.1 48.8 24.5 Termites 33.3 32.3 35.9 38.8 1 5.2 22.2 53.6 34.1 27.3 Carpenter Ants 20.8 30.1 35.9 30.3 28.3 11.1 42.9 25.6 28.2 Rats 20.8 2 1 .8 48.7 26.1 28.3 22.2 42.9 23.2 24.5 Weeds 22.9 20.3 23.1 21.1 21.7 22.2 42.9 15.9 20.0 Fleas 14.6 5.3 38.5 10.9 21.7 11.1 21.4 15.9 9.1 Flies 12.5 12.0 17.9 10.9 21.7 11.1 17.9 14.6 10.9 Head Lice 4.2 9.8 23.1 10.9 10.9 11.1 14.3 9.8 10.9 Diseases of Outdoor Plants 4.2 10.5 17.9 12.1 4.3 11.1 17.9 11.0 8.2 Mosquitoes 12.5 6.8 17.9 9.7 13.0 0.0 14.3 14.6 5.5 Insect Pests of , Outdoor Plants 6.3 9.8 12.8 9.7 4.3 33.3 17.9 7.3 9.1 Bats 6.3 6.8 20.5 9.1 6.5 22.2 25.0 6.1 7.3 Birds 2.1 3.0 20.5 7.3 2.2 0.0 17.9 4.3 1.8 Other 2.1 4.5 2.6 3.0 6.5 0.0 3.6 3.7 3.6 Nunber of Districts 48 133 39 165 46 9 28 82 110 Pest Presence in Districts Employing PCs for Management of the Specific Pests Total Those With Those Without Pest Number Pest (% of Total) Pest (% of Total) Cockroaches 135 94 (69.6) 41 (30.4) Mice 128 114 (89.1) 14 (10.9) Other Ants 116 103 (88.8) 13 (11.2) Stinging Insects 83 69 (83.1) 14 (16.9) Termites 73 41 (56.2) 32 (43.8) Carpenter Ants 64 29 (45.3) 35 (54.7) Rats 58 20 (34.5) 38 (65.5) Weeds 47 34 (72.3) 13 (27.7) Fleas 29 10 (34.5) 19 (65.5) Flies 29 24 (82.8) 5 (17.2) Head Lice 24 23 (95.8) 1 (4.2) Diseases of Outdoor Plants 23 10 (43.5) 13 (56.5) Mosquitoes 22 1 5 (68.2) 7 (31.8) Insect Pests of Outdoor Plants 21 10 (47.6) 1 1 (52.4) Bats 20 10 (50.0) 10 (50.0) Birds 1 3 9 (69.2) 4 (30.8) 121 Table 35 (cont'd). Districts With Positive Pest Presence that Employ PCs Those Which Hire Those Which Hire PCs for Specific Total PCs for Specific and/or Other Pest NumberH Pest (% of Total) Pests (% of Total) Cockroaches 1 1 8 94 (79.7) 1 06 (89.8) Mice 234 1 14 (48.7) 173 (73.9) Other Ants 221 103 (46.6) 169 (76.5) Stinging Insects 218 69 (31.7) 166 (76.1) Termites 51 41 (80.4) 5 0 (98.0) Carpenter Ants 51 29 (56.9) 44 (86.3) Rats 40 20 (50.0) 30 (75.0) Weeds 175 34 (19.4) 133 (76.0) Fleas 43 1 0 (23.3) 37 (86.0) Flies 198 24 (12.1) 143 (72.2) Head Lice 226 23 (10.2) 162 (71.7) Diseases of Outdoor Plants 51 10 (19.6) 38 (74.5) Mosquitoes 127 15 (11.8) 89 (70.1) Insect Pests of Outdoor Plants 52 10 (19.2) 39 (75.0) Bats 62 10 (16.1) 48 (77.4) Birds 81 9 (11.1) 63 (77.8) +DNK a do not know, NR = no response. “Total number of districts with positive pest presence was the number of districts reporting pest presence in response to question 3. ‘lndlcates slgnlflcant dlfference between classes of district attribute. 122 for insect pests of outdoor plants. Urban and suburban districts both employed PCCs more frequeme for cockroaches and stinging insects while urban districts hired them most often for weeds and bats. With the exception of carpenter ants, rats, fleas, diseases of outdoor plants and insect pests of outdoor plants, over 50% of the districts employing PCCs for each pest reported that they had that pest (O-S). The best match between districts that had a specific pest and who also employed PCCs for management of the pest occurred for mice, ants other than carpenter ants, stinging insects, flies and headlice (over 80%). Rats were reported by only 34.5% of the districts which hired PCCs for their control, the lowest presence of all the pests. Possibly those districts which hired PCCs for pests which they did not report as problems believe that the PCCs prevented these pests from becoming problems. The number of districts which had the specific pests and hired PCCs for their management compared to the number of all districts which reported that they had the specific pests varied greatly. As few as 10.2% of the districts (head lice) and as many as 80.4% of the districts (termites) which said that they had the pests also hired PCCs for their management. The percentage of districts with cockroaches that hired PCCs for cockroach control was almost as high as that for termites (79.7%). This was followed by the percentage of districts with carpenter ants, rats, mice and ants in general which hired PCCs for their control (46.6% to 56.9%). A lower percentage probably meant that the districts placed lower priority on that particular pest's management, as in the case of birds, mosquitoes, flies, bats, insect pests of outdoor plants, weeds and diseases of outdoor plants, (all between 10 and 20%). Fleas (23.3%) and stinging insects (31.7%) were probably considered low management priority as well. The employment of P006 for head lice management, however, cannot be used as a measure of importance as head lice require a different management strategy. The percent of districts with specific pest problems that hired PCCs in general was high, (that is, the district may have had the pest but did not hire the PCC for control of the specific 123 pest). Almost 100% of the districts which reported termites and over 80% of the districts with cockroaches, carpenter ants and fleas employed PCCs. Except for mosquitoes, a greater percent of districts with pest problems hired PCCs compared to the percent of all districts (71.3%) hiring PCCs. WWW- Except for changes in turf/landscape care practices, PCCs were reported as using or recommending all types of methods presented as choices in the question by over 50% of 219 districts which employed them (Ci-34, Table 36). Trap use was reported most frequently, followed by recommendations for changes in student and staff behavior, improvement in sanitation, use of pesticides, repair or modification of facility structure, and turf/landscape care modification (92.2%, 75.3%, 70.8%, 68.0%, 62.6% and . 44.7%). Only one significant difference was found when frequency of method selection was compared to expected frequency for different district groupings. This was for districts selecting turf/landscape care modification when compared by size. Large districts selected the method more often than small or medium sized districts. Wm. PCCs were reported as providing promotional and follow-up lnfonnation to both administration and support services personnel. Superintendents, school principals and district business managers were selected as PCC report recipients by 43.6 to 45.5% of 220 districts (035, Table 37). Local school secretaries were selected by only 15.9% of the districts. Many districts wrote in Other responses (35.5%) which were all support services personnel. Selection of superintendents for districts grouped by size and selection of support services personnel for districts grouped by location were the only response distributions which differed significame from expected numbers. Superintendents were selected more frequently by small districts while support services personnel were selected most often by southern lower peninsula districts. 124 Table 36. Methods Used or Recommended by Pest Control Companies. Percent of 219 Districts Selecting Frequency for Method Use or Recommendation+ Method Always Often Sometimes Never DNK N R” Sanitation 16.4 17.4 37.0 18.7 5.5 5.0 Facility 4.1 13.7 44.7 25.6 5.0 6.8 Landscape 5.0 8.2 31.5 32.9 11.9 10.5 Traps 5.5 24.2 45.7 12.8 3.7 8.2 Pesticide 17.4 37.0 37.9 1.8 3.2 2.7 Education 10.5 18.3 39.3 21.5 5.5 5.0 Districts Selecting P-Value for Selection of Positive Positive Frequency+++ Frequency Based on District: Method Number (% of 219) Size Location Community Sanitation 155 (70.8) 0.41 1 0.857 0.284 Facility 137 (62.6) 0.078 0.319 0.690 Landscape 98 (44.7) 0.020' 0.581 0.106 Traps 202 (92.2) 0.967 0.989 0.887 Pesticides 149 (68.0) 0.082 0.176 0.282 Education 165 (75.3) 0.547 0.373 0.547 Distribution of Districts Selecting PCC Methods (as Percent of Attribute Class) Size Location Community Method S M L SLP NLP UP U S R Sanitation 58.3 72.0 82.1 71.5 71.1 55.6 81.4 79.3 61.8 Facility 43.8 63.6 82.1 66.7 53.3 33.3 70.4 65.9 58.2 Landscape 22.9 47.7 61.5 46.1 44.4 22.2 59.2 52.4 35.5 Traps 89.6 92.4 94.9 92.7 91.1 88.9 96.3 95.1 89.1 Pesticides 47.9 69.7 87.2 73.9 51.1 44.4 85.2 73.2 60.0 Education 64.6 76.5 84.6 80.0 60.0 66.7 85.2 80.5 69.1 NumberofDistricts 48 132 39 165 45 9 27 82 110 +Methods were identified by 219 of the 221 districts which indicated that they hire pest control companies in response to question 28. ++DNK . do not know, NR = no response. ++'tlncludes districts selecting a method type as always, often and sometimes. *Indlcates significant dlfference between classes 01 dlStl’lCt attribute. 125 Table 37. School Personnel to Whom Pest Control Companies Provide lnfonnation Concerning Pest Problems and Management Actions. Percent of 220 Districts Selecting Frequency that Each Personnel Group Receives PCC Information+ Personnel Always Often Sometimes Never DNK RLU NR++ Principal 10.0 10.0 25.5 25.5 5.9 23.2 Secretary 0.9 3.2 12.7 46.8 7.3 29.1 Superintendent 18.2 10.5 16.8 27.7 6.4 20.5 Business Manager 18.2 9.1 16.4 20.9 6.8 . 28.6 Support Services 22.3 8.2 5.0 0.0 0.0 5.5 59.1 Districts Selecting P-Value for Selection of Positive Positive Frequency+++ Frequency Based on District: Personnel Number (% of 220) Size Location Community Principal 100 (45.5) 0.939 0.719 0.233 Secretary 35 (15.9) 0.136 0.360 0.349 Superintendent 100 (45.5) 0.039' 0.112 0.135 Business Manager 96 (43.6) 0.326 0.537 0.842 Support Services 78 (35.5) 0.178 0.022' 0.765 Distribution of Districts Selecting Personnel Type (as Percent of Attribute Class) Size Location Community S M L SLP NLP UP U S R Principal 43.8 45.1 48.7 46.7 39.1 55.6 64.3 46.3 40.0 Secretary 14.6 14.3 28.2 15.2 23.9 11.1 25.0 18.3 13.6 Superintendent 64.6 43.6 28.2 40.0 60.9 66.7 35.7 36.7 54.5 Business Manager 33.3 48.9 38.5 45.5 34.8 55.6 50.0 43.9 41.8 Support Services 22.9 36.8 46.2 41 .8 1 7.4 1 1 .1 42.9 35.4 33.6 Number of Districts 48 133 39 165 46 9 28 82 110 Percent Distribution of Districts Selecting Multiple Districts Personnel to Whom PCs Report Number of Selecting++++ By Size By Location By Community Personnel Number (%) S L SLP NLP UP U S R 0 6 (2.8) 0.0 3.9 2.6 2.5 4.9 0.0 0.0 2.5 3.8 1 90 (42.5) 48.9 39.5 44.7 40.7 48.8 44.4 25.9 46.3 43.8 2 48 (22.6) 22.2 23.3 21.1 25.9 9.8 22.2 40.7 20.0 20.0 3 37 (17.5) 15.6 19.4 13.2 17.9 14.6 22.2 11.1 18.8 18.1 4 29 (13.7) 13.3 13.2 15.8 12.4 19.5 11.1 18.5 11.3 14.3 5 2 (0.9) 0.0 0.8 2.6 0.6 2.4 0.0 3.7 1.3 0.0 Number of Districts 212 45 129 38 162 41 9 27 80 105 126 Table 37 (cont’d). Percent Distribution of Districts Selecting Multiple Districts Personnel to Whom PCs Report Personnel Selecting++++ By Size By Location By Community Type Number(%) S M L SLP NLP UP U S R Admin. 116 (56.3) 73.3 54.0 43.2 50.0 74.4 88.9 48.2 53.9 60.4 Support Staff 48 (23.3) 13.3 23.4 35.1 27.2 10.3 11.1 18.5 29.5 19.8 Both 42 (20.4) 13.3 22.6 21.6 22.815.4 0.0 33.3 16.7 19.8 Numberof Districts 206 45 124 37 158 39 9 27 78 101 P-Value for Selection Based on District: Comparison Size Location Community Number of Personnel to Whom PCs Report (0,1, 2, 3, 45) 0.873 0.491 0.285 Personnel Type to Whom PCs Report (Adm., Support Services, Both) 0.058 0.0 1 5* 0.236 +Personnel Types were identified by 220 of the 221 districts which indicated that they hire pest control companies in response to question 28. ++DNK a do not know, RLU - response level unknown because either multiple responses were selected for the personnel category or no response was selected for an entry made under Other, NR - no response. +++lncludes districts selecting a personnel type as always. often, sometimes and RLU. MMEight districts were omitted as they did not know if any personnel were contacted by pest control companies. 'lndlcates significant difference between classes of district attribute. 127 Almost half of the districts selected only one personnel type as recipient of PCC reports. Two, three, four and five recipients were selected by 22.6%, 17.5% ,13.7% and 0.9% of the remaining districts. Six indicated that no personnel received such reports. Eight did not know who received them and were dropped for comparison purposes. No statistical differences were found between district groups selecting multiple personnel. Districts were also identified by personnel type selected as recipient of PCC reports. Approximately half selected administration personnel only while support services personnel or both were selected by 22.6% and 19.8%. Comparison of selections between districts grouped by location showed a significant difference. Upper peninsula districts did not select both while up to 23% of southern lower peninsula districts did. Summary Seventy-nine tests for differences between response selection to pest management execution questions were performed for each district attribute. Twenty significant differences were found for responses grouped by district size, 14 significant differences were found for responses grouped by district location and 15 significant differences were found for responses grouped by district community type. The trend in positive response to a question was generally from small to medium to large districts, from southern lower peninsula to northern lower peninsula to upper peninsula districts and from rural to suburban to urban districts. Districts grouped by size differed in their reporting of the frequency with which school administrators and kitchen staff request pest management. They did not differ in regard to the personnel type who decides on methods to be used for pest management. A significant difference was found in the frequency of pest control company (PCC) employment for both indoor and outdoor pest management. Significant differences were also found when comparing district selection of personnel type negotiating PCC contracts. Small districts selected the superintendent more frequently than the other districts types while the business manager or support services staff were selected most frequently by large districts, in accordance with the 128 usual positive selection trend. Differences were found in the reported frequency for which PCCs were hired to control cockroaches, fleas, head lice, stinging insects, bats and rats and for the frequency with which pest control companies recommend modification in tur/landscape care practices. The final difference found between districts grouped by size was in the reporting of PCC report recipients. Small districts reported superintendents more frequently than did the other district sizes. Districts grouped by location and community type differed for many of the same response selections although fewer differences were found between positive response selection of PCCs for management of specific pests. The usual selection trend was observed with the same exceptions as found for districts grouped by size, namely, superintendents were selected most frequently as the personnel who negotiate PCC contracts both by districts in the upper peninsula and by districts in rural communities than by either of the other districts groups. In addition, upper peninsula districts selected kitchen staff most frequently as the personnel performing outdoor pest management and they hired PCCs more frequently for control of outdoor plant insect pests. 129 Effectiveness Evaluation Approximately 75% of 306 responding districts said that pest management effectiveness is evaluated in their districts (O-36, Table 38). Twenty-one percent said it is not evaluated and a few (3.6%) did not know. No significant differences were found to exist though yes responses were selected more often by large and medium sized districts, those located in the entire lower peninsula and those located in urban and suburban communities than were selected by small districts, ones located in the upper peninsula and those in niral communities. Personnel Performing Evaluations Pest management evaluations were said to be performed most frequently by the personnel who decided that management was necessary (83.0% of 230 districts which said that evaluations were performed in their districts). Personnel performing the action and pest control companies were selected by more than 50% of the districts while support service personnel were written in as Other by 15.2% (037, Table 39). Frequency of personnel selection was compared to expected frequency for districts grouped by the different attributes. Only selection of support service personnel showed a significant difference for districts grouped by size or location. Large districts and those located in the southern lower peninsula selected this personnel type more frequemly than other district groups. Approximately 70% of the districts selected several categories of personnel as performing pest management evaluations. Four types were selected by 3.5% of the districts while three, two and one selections were made by 36.5%, 29.6% and 30.4% of the districts. Comparison of the number of selections made by districts grouped by location showed a significant difference. Most upper peninsula districts selected one or two personnel types while many lower peninsula districts selected two, three or four. 130 Table 38. Evaluation of Pest Management Effectiveness. Districts Selecting P-Value for Selection of Yes Response Evaluation Response Based on District: Performed Number (% of 306) Size Location Community Yes 231 (75.5) 0.150 0.218 0.413 No 64 (20.9) Do Not Know 11 (3.6) Table 39. Personnel Performing Pest Management Evaluation. Percent of 230 Districts Selecting Frequency that Personnel Perform Evaluation+ Personnel Always Often Sometimes Never DNK RLU NR++ Decided Need 45.7 22.6 14.8 1.3 . . 15.7 Performed Action 21.7 21.7 19.1 7.0 1.3 0.9 28.2 Pest Control Co. 17.0 12.2 22.2 17.0 0.9 . 30.9 Support Service 9.6 2.6 0.9 . . 2.3 84.8 Districts Selecting P-Value for Positive Frequency Positive Frequency“+ Selection Based on District: Personnel Number (% of 230) Size Location Community Decided Need 191 (83.0) 0.966 0.917 0.767 Performed Action 146 (63.5) 0.807 0.571 0.995 Pest Control Co. 118 (51.3) 0.340 0.259 0.452 Support Service 35 (15.2) 0.01 9* 0.025' 0.072 Distribution of Districts Selecting Positive Frequency for Personnel Performing Pest Management Evaluation (as Percent of Attribute Class) Size Location Community Personnel S M L SLP NLP UP U S R Decided Need 84.6 82.4 82.4 81.4 85.7 88.9 72.0 87.2 82.7 Performed Action 64.6 64.9 55.9 65.4 64.3 44.4 64.0 64.1 63.0 Pest Control Co. 40.0 55.7 55.9 56.4 42.9 33.3 64.0 55.1 46.5 Support Service 6.2 16.0 29.4 19.9 7.1 0.0 32.0 14.1 12.6 Number of Districts 65 131 34 156 56 18 25 78 127 Table 39 (cont'd). 131 Percent Distribution of Districts Selecting Multiple Personnel Districts Number of Selecting By Size By Location By Community Personnel Number (%) S M L SLP NLP UP U S R 1 70 (30.4) 35. 4 27. 5 32. 4 29. 5 28. 6 44. 4 32.0 28.9 32.3 2 68 (29.6) 35.4 29. 0 20. 6 22.4 44. 6 44. 4 12.0 28.2 33.9 3 84 (36.5) 27.7 40. 5 38. 2 43.6 25. 0 11. 1 48.0 42.3 30.7 4 8 (3.5) 1.5 3.1 8. 8 4.5 1 .8 0. 0 8.0 2.6 3.2 Number of Districts 230 65 131 34 156 56 18 25 78 127 P-Value for Multiple Selection Based on District: Comparison Size Location Community Number of Personnel Types Who Evaluate Effectiveness (1, 2 , 3-4) 0.254 0.001 ' 0.126 +Only responses of the 231 districts who said they maintain pest management records in answer to question 38 are presented. One of those districts did not respond to this question. ++DNK a do not know, RLU .. response level unknown because either multiple responses were selected for the personnel category or no response was selected for an entry made under Other, NR = no response. +“Includes districts selecting personnel type as Always, Often, Sometimes and RLU. 'lndlcates significant difference between classes of district attribute. 132 Satisfaction with Pest Management Effectiveness AI least 70% of 300 responding districts said that all school groups were satisfied or very satisfied with pest management effectiveness (O-43, Table 40). Two groups, school administration and school custodians, were said to be satisfied in 94.0% and 92.7% of the districts. Over 80% of the districts said that school maintenance, district administration, teachers/librarians, school groundskeepers, district maintenance and district custodians were satisfied. Two Other responses were entered as being satisfied, one for a food service manager and one for a superintendent of building and grounds. This last entry indicates that district personnel cannot always be placed into separate groups. Most districts selected a specific response for each school group but approximately 25% of the districts did not know whether students or parents of the students were satisified and 10- 14% indicated that school groundskeepers, district custodians and district groundskeepers did not exist within their district by selecting not applicable responses. Few districts said that the specific school groups were not satisfied (3 maximum per group). No significant differences were found in the frequency of each school group reported as satisfied between districts classed by any attribute type. Most districts reported that many school groups were satisfied. Almost 50% (144 districts) said that all 11 were satisfied. Another 29% said that 8 to 10 groups were satisfied, whil916.3% said 4 to 7 groups and 4.0% said 1 to 3 groups were satisfied. Only 18 districts (6.0%) selected no groups as being satisfied. These districts gave a combination of do not know, group not in existence and no response to the specific groups. Concern wlth Pest Management Concern over pest management has been expressed by school personnel as well as by some students and parents (O-45). This concern could be focused on pest management effectiveness, methods used in pest management or a combination of both. Almost 40% of 305 responding districts said that school administrations have expressed concern (Table 41). 133 Table 40. Satisfaction of Different Persons with Effectiveness of Current Pest Management Efforts. Percent of 300 Districts Selecting Persons Satisfaction Level As Persons Very Satisfied Not DNK NA NR+ School Administration 23.0 71 .0 0.3 4.0 1.0 0.7 Teachers/Librarians 18.0 67.0 0.7 9.7 2.0 2.7 Students 16.3 54.0 0.3 22.0 4.0 3.3 Parents of Students 13.3 50.7 1.0 27.0 4.3 3.7 School Custodians 20.0 72.7 1.0 2.7 2.0 1.7 School Groundskeepers 17.0 64.7 0.3 3.3 10.0 4.7 School Maintenance 19.3 68.0 0.7 3.3 4.7 4.0 District Administration 18.0 68.0 0.0 5.0 6.0 3.0 District Custodians 16.3 63.7 0.7 3.0 12.3 4.0 District Groundskeepers 16.0 60.0 0.3 3.3 14.0 6.3 District Maintenance 17.3 64.0 0.3 3.7 9.3 5.3 Other . 0.7 . . . 99.3 P-Value for Satisfaction Selection Based on District: Districts Indicating Persons as Satisfied“ Persons Number (% of 300) Size Location Community School Administration 282 (94.0) 0.951 0.958 0.969 Teachers/Librarians 255 (85.0) 0.714 0.974 0.779 Students 21 1 (70.3) 0.505 0.827 0.693 Parents of Students 192 (64.0) 0.332 0.816 0.726 School Custodians 278 (92.7) 0.912 0.996 0.981 School Groundskeepers 245 (81.7) 0.817 0.877 0.896 School Maintenance 262 (87.3) 0.890 0.983 0.925 District Administration 258 (86.0) 0.702 0.943 0.788 District Custodians 240 (80.0) 0.329 0.747 0.464 District Groundskeepers 228 (76.0) 0.088 0.349 0.607 District Maintenance 244 (81.3) 0.248 0.530 0.565 +DNK - do not know, NA= not applicable, NR = no response. ++Includes districts selecting very satisfied and satisfied. 134 Table 41. Persons Who have Expressed Concern wlth Pest Management Efforts. Percent of 305 Districts Indicating Concern Expressed Persons Yes No DNK NR+ School Administration 39.3 52.5 5.9 2.3 Teachers/Librarians 32 . 5 55. 1 9.2 3.3 Students 10.2 67.9 17.4 4.6 Parents of Students 19.0 59.0 18.7 3.3 School Custodial, Grounds, or Maintenance Staff 34.8 53.8 7.9 3.6 District Administration 32.1 52.8 9.8 5.2 District Custodial, Grounds, or Maintenance Staff 29.5 55.1 9.8 5.6 Other 0.7 . . 99.3 Districts Indicating P-Value for Yes Response Concern Expressed Based on District: Persons Number (% of 305) Size Location Community School Administration 1 20 (39.3) 0.059 0.157 0.806 Teachers/Librarians 99 (32.5) 0.053 0.469 0.530 Students 31 (10.2) 0.534 0.395 0.402 Parents of Students 58 (19.0) 0.042* 0.659 0.082 School Custodial, Grounds, or Maintenance Staff 106 (34.8) 0.093 0 .006‘ 0.697 District Administration 98 (32.1) 0.141 0.058 0.821 District Custodial, Grounds, or Maintenance Staff 90 (29.5) 0.008* 0.005' 0.272 Distribution of Districts Indicating Concern Expressed (as Percent of Attribute Class) Size Location Community Persons S M L SLP NLP UP U S R School Administration 32.3 38.8 60.0 44.4 33.3 25.0 45.2 40.7 37.7 Teacherleibrarians 27.6 30.6 52.5 34.9 31.0 21.9 38.7 36.3 29.5 Students 10.5 8.8 15.0 10.6 11.9 3.1 3.2 12.1 10.4 Parents of Students 15.2 17.5 35.0 20.1 19.0 12.5 12.9 27.5 15.8 School Custodial, Grounds, or Maintenance Staff 26.7 35.0 50.0 42.9 25.0 12.5 41.9 36.3 32.8 District Administration 26.7 31.9 47.5 38.1 23.8 18 8 32.3 35.2 30.6 District Custodial, Grounds, orMaintenanceStaff 21.9 29.4 50.0 36.5 19.0 15 6 32.3 34.1 26.8 135 Table 41 (cont'd). Districts Percent Distribution of Districts Selecting Different Numbers of Selecting Concerned Persons Number of Total By Size By Location By Community Persons Number (%) S M L SLP NLP UP U S R 1 23 (14.1) 15.2 12.6 16.7 11.4 25.0 0.0 5.6 15.4 15.1 2 34 (20.9) 17.4 26.4 10.0 21.1 17.5 33.3 22.2 13.5 24.7 3 19 (11.7) 19.6 9.2 6.7 13.2 10.0 0.0 16.7 11.5 10.8 4 26 (16.0) 8.7 18.4 20.0 16.7 12.5 22.2 27.8 21.2 10.8 5 29 (17.8) 19.6 17.2 16.7 17.5 15.0 33.3 22.2 13.5 19.4 6 17 (10.4) 10.9 8.1 16.7 9.7 12.5 11.1 5.6 13.5 9.7 7 15 (9.2) 8.7 8.1 13.3 10.5 7.5 0.0 0.0115 9.7 Number ofDistricts 163 46 87 30 114 40 9 18 52 93 Distribution of Districts Indicating Multiple Concerned Persons (as Percent of Attribute Class) Number of Total Size Location Community Persons Number (%) S M L SLP NLP UP U S R Multiple 163 (53.4) 43.8 54.4 75.0 60.347.628.1 58.1 57.1 50.8 Number ofDistricts 305 99154 40 183 78 32 31 87175 P-Value for Indication of Multiple Persons as Concerned Based on District: Comparison Size Location Community Districts Indicating Multiple Concerned Persons 0.070 0.049' 0.743 +DNK :- do not know, NR = no response. *Indlcates slgnlflcant dlfference between classes of district attribute. 136 Affirmative responses for school custodial, grounds and maintenance staff as a group, teachers/librarians, district administration, and district custodial, grounds, and maintenance staff as a group followed with 34.8%, 32.5%, 32.1% and 29.5% of the districts selecting each. Only 10.2% and 19.0% of the districts reported that students and their parents have expressed concern. At least twice as many districts (17.4% and 18.7%) did not know if these two groups had ever expressed concern compared to other groups. There were significant differences in the expressed concerns of parents and district custodial, grounds, or maintenance staff between districts grouped by size. Significant differences were also found for reported concerns for both school and district custodial, grounds, or maintenance staff between districts grouped by location. More large districts and those located in the southern lower peninsula said that these groups have expressed concern. Almost half the districts (46.6%) did not select any groups as expressing concern. Of the 163 districts reporting concerned groups, only 14.1% selected just one. All remaining districts selected between 2 and 7 groups (20.9%, 11.7%, 16.0%, 17.8%, 10.4% and 9.2%). When concern is expressed within a district, it appears to be widespread. The distribution between attribute classes of districts that selected at least one school group as expressing concern was significantly different for location. Sixty point three percent of the southern lower peninsula districts said that at least one school group had expressed concern compared to only 28.1% of the upper peninsula districts. Although distribution for districts grouped by size was not quite significant, a distinct range in percent of districts selecting at least one group as expressing concern existed. Seventy-five percent of the large districts selected at least one group while only 43.8% of the small districts did so. District community distributions were very close ranging from 50.8% of rural community districts to 58.1% of urban districts. No significant difference was found in the number of school groups selected as expressing concern for districts selecting at least one group when such districts were classed by any attribute. 137 Concern over Pesticide Use In the School Environment Districts reported almost the same type and number of school groups as expressing concern over the use of pesticides in the school environment as they had reported as expressing concern over pest management in general (O—46, Table 42). School administrators were again selected as expressing concern most often by 34.3% of 306 districts. Teachers/librarians, school custodial, grounds, or maintenance staff as a group, district administration, district custodial, grounds, or maintenance staff as a group, parents and students followed in the number of districts selecting them as expressing concern (28.4%, 28.4%, 26.1%, 23.9%, 14.1% and 7.8%). Comparison of responses to the questions on concern over pest management and concern over pesticide use showed that at least 45% of these districts were the same (64.8% for school administration, 60.9% for teachers/librarians, 45.8% for students, 67.4% for parents, 66.7% for school custodial, grounds, or maintenance staff, 63.8% for district administration, and 67.1% for district custodial, grounds, or maintenance staff.) This indicates that at least half the concern over pest management is with regard to pesticide use. Except for students, highly significant differences were found for all group selections between districts categorized by size. Each group was selected most often by large districts. Significant differences were also found for selection of district custodial, grounds, or maintenance staff between districts categorized by location and for selection of teachers/librarians as well as district custodial, grounds, or maintenance staff between districts categorized by community type. Both southern lower peninsula districts and those located in urban communities selected the groups more often than other district types. Of 149 districts which reported groups as being concerned with pesticide use, 76.5% selected more than one group. Two to seven different groups were selected by 16.1%, 18.1%, 12.8%, 11.4%, 7.4%, and 10.7% of the districts. The remaining 23.5% selected only one group. Again, concern tends to exist within many district groups when it is expressed. However, comparison of the number of districts selecting at least one group as expressing 138 Table 42. Persons Who have Expressed Concern Over the Use of Pesticides In the School Environment Percent of 306 Districts Indicating Concern Expressed Persons Yes No DNK NR+ School Administration 34.3 54.9 9.2 1.6 Teachers/Librarians 28 .4 5 6. 2 1 2.7 2. 6 Students 7.8 68.6 19.6 3.9 Parents of Students 14.1 62.4 19.6 3.9 School Custodial, Grounds, or Maintenance Staff 28.4 60.5 8.2 2.9 District Administration 26.1 56.5 11.4 5.9 District Custodial, Grounds, or Maintenance Staff 23.9 58.5 10.8 6.9 Other 1.3 . . 98.7 Districts Indicating P-Value for Yes Response Concern Expressed Based on District: Persons Number (% of 306) Size Location Community School Administration 105 (34.3) 0 .0 1 1 * 0.092 0.084 Teachers/Librarians 87 (28.4) 0.000* 0.062 0.003' Students 24 (7.8) 0.064 0.236 0.325 Parents of Students 46 (14.1) 0.000' 0.296 0.056 School Custodial, Grounds, or Maintenance Staff 87 (28.4) 0.023' 0.121 0.512 District Administration 80 (26.1) 0.01 5" 0.130 0.126 District Custodial, Grounds, or Maintenance Staff 73 (23.9) 0.003‘ 0.025" 0.020' Distribution of Districts Indicating Concern Expressed (as Percent of Attribute Class) Size Location Community Persons S M L NLP UP U S R School Administration 28.3 31 .9 60.0 2821.8 9 48.4 41.3 28.4 Teachers/Librarians 18.9 27.5 57. 5 25.9 9.4 51.6 35.9 20.8 Students 6.6 6.3 17. 5 9.4 0. 0 12.9 9.8 6.0 Parents of Students 9.4 10.0 42. 5 11.8 6. 3 19.4 20.7 9.8 School Custodial, Grounds, orMaintenance Staff 25.5 25.0 50.0 21.2 18. 8 35.5 31.5 25.7 District Administration 20.8 24.4 47.5 20.0 15. 6 35.5 32.6 21.3 District Custodial, Grounds, orMaintenanceStaff 17.0 22.5 47.5 29.6 16.5 9. 4 35 5 32 6 17.5 139 Table 42 (cont'd). Districts Percent Distribution of Districts Selecting Different Numbers of Selecting Concerned Persons Number of Total By Size By Location By Community Persons Number (%) S M L SLP NLP UP U S R 1 35 (23.5) 26.2 26.7 12.5 20.0 24.2 54.6 28.6 22.2 23.0 2 24 (16.1) 19.1 14.7 15.6 16.2 18.2 9.1 9.5 11.1 21.6 3 27 (18.1) 16.7 20.0 15.6 20.0 15.2 9.1 9.5 22.2 17.6 4 19 (12.8) 14.3 9.3 18.8 11.4 15.2 18.2 14.3 11.1 13.5 5 17 (11.4) 4.8 17.3 6.3 15.2 3.0 0.0 19.1 14.8 6.8 6 11 (7.4) 9.5 4.0 12.5 6.7 9.1 9.1 9.5 5.6 8.1 7 16 (10.7) 9.5 8.0 18.8 10.5 15.2 0.0 9.5 13.0 9.5 Number of Districts 149 42 75 32 105 33 11 21 54 74 Distribution of Districts Indicating Multiple Concerned Persons Districts (as Percent of Attribute Class) Number of Total Size Location Community Persons Number (%) S M L SLP NLP UP U S R Multiple 149 (48.7) 39.6 48.7 88.9 55.6 38.8 34.4 67.7 58.7 40.4 Number ofDistricts 306 106 154 36 189 85 32 31 92 183 P-Value for indication of Multiple Persons as Concerned Based on District: Comparison Size Location Community Districts Making Multiple Selections 0 .001 " 0.087 0.034' +DNK - do not know, NR - no response. *Indlcates significant difference between classes of district attribute. 140 concern over pesticide use was significantly different for districts grouped by either location or community type, comparisons that were not significame different for expression of concern over pest management efforts in general. Comparison by location was highly significant with 88.9% of the large districts selecting at least one school group and only 39.6% of the small districts doing so. Sixty-seven point seven percent of the urban districts selected at least one group compared to 40.4% of the rural districts. No significant difference was found in the number of school groups selected as expressing concern for districts selecting at least one group when such districts were classed by any attribute. Summary Thirty-five tests for differences between response selection to pest management evaluation, satisfaction over pest management efforts and concern regarding pest management and pesticide use in the school environment were performed for each district attribute. Ten significant differences were found for responses grouped by district size, six were found for . responses grouped by district location and three were found for responses grouped by district community type. No differences existed between district response selection for execution of pest management evaluation. But the selection of support services staff as the personnel responsible for performing effectiveness evaluations was signficantly different for districts grouped both by size and by location. The usual trend was observed In frequency of selection with large districts and those in the southern lower peninsula selecting support services staff more frequenly than the other district groups. No differences were found in the reporting of school personnel satisfaction with existing pest management efforts for any district grouping. However, significant differences were found between districts grouped by size and by location in the reporting of three different school groups as having expressed concern over pest management efforts. Selection of parents and of district custodial, grounds and maintenance staff was significantly different for districts 141 grouped by size while selection of local school as well as of district custodial, grounds and maintenance staff was significantly different for districts grouped by location. Significant differences were also found for districts grouped by size in the reporting of six different school groups as having expressed concern over pesticide use in the school environment. Response selections for local school and district administration, teachers/librarians, parents,and local school and district support services staff were all significamly different. Positive response selection was significantly different for only one school group, district support services staff, when districts were grouped by location while response selection for two school groups, teachers/librarians and district support services staff was significame different when districts were grouped by community. Large districts, those located in the southern lower peninsula and those in urban communities all selected positive expression of concern more frequently than the other district types. 142 W Record-Keeping Approximately one-third of 306 responding districts said that they kept pest management records (O—38, Table 43). Fifty-seven percent said they did not keep records and 6.2% did not know. Differences in yes response selection were significant between districts grouped by size, location or community type. Just over 72% of the large sized districts kept records while only 17.8% of small ones did so. Almost half of the southern lower peninsula districts and approxi- mately half of both urban and suburban districts kept records whilefS to 27% of the other district classes kept records. Comparison of the proportion of districts grouped by size which Indicated that they kept pest management records found a significant difference between all proportions (17.8%-S, 40.9%-M, 72.5%-L). These records were accessible for review in 84.5% of the 110 responding districts which kept them (O-39, Table 44). No significant different in record accessibility was found between districts classed by any attribute. Pest Management Record Information At least 74% of 112 record-keeping districts answered that they retain information on the different record types listed in the questionnaire (040, Table 45). lnfonnation on pest problem location was selected most frequently as always, often or sometimes being kept in 92.9% of the districts. Information on the type of pest problem and management methods used were both kept by 89.3% of the districts while records on the cost of management, the person who decided management was needed, the person performing management, and evaluation of effectiveness were reported kept by 87.5, 83.0, 77.7 and 74.1% of the districts. No significant difference was found for frequency of type of record maintenance between districts classed by any attribute. Most districts said they kept more than one type of record. Over 60% selected all seven types. Six, five, four, three and one types were reported by 11.7, 9.0, 9.0, 5.4 and 3.6% of the remaining districts. Districts were identified as keeping few (one, three or four types) or as 143 Table 43. Maintenance of Pest Management Records by School Dlstrlcts. Districts Selecting P-Value for Selection of Yes Response Records Response Based on District: Kept Number (% of 306) Size Location Community Yes 113 (36.9) 0.000' 0.001* 0.004' No 174 (57.0) Do Not Know 19 (6.2) Fl Distribution of Districts Selecting Yes Response (as Percent of Attribute Class) Records Size Location Community Kept S M L SLP NLP UP U S R Yes 17.8 40.9 72.5 47.1 22.4 15.6 45.2 52.7 27.7 Number of Districts 107 159 40 189 85 32 31 91 184 *Indlcates slgnlflcant dlfference between classes Oi diSti’iC‘t attribute. Table 44. Review Accessibility of Maintained Pest Management Records. - f 1 fi — Districts Selecting P-Value for Selection of Yes Response Records Response Based on District: Accessible Number (% of 110)+ Size Location Community Yes 93 (84.5) 0.768 0.889 0.962 No 5 (4.5) Do Not Know 12 (10.9) +Only responses of the 113 districts who said they maintain pest management records in answer to question 38 are presented. Three of those districts did not respond to this question. 144 Table 45. Pest Management Record Information. Percent of 112 Districts Selecting Frequency that Record Information is Kept (as Percent of Attribute Class)+ Record Type Always Often Sometimes Never DNK N R” Pest Problem 42.0 22.3 25.0 5.4 2.7 2.7 Location of Problem 46.4 21.4 25.0 3.6 2.7 0.9 Person Deciding Need for Action 40.2 19.6 23.2 4.5 4.5 8.0 Mgmt Methods Used 54.5 18.8 16.1 3.6 2.7 4.5 Person Performing Mgmt Action 46.4 16.1 15. 2 8.0 6.3 8.0 Cost 59.8 19.6 8. 0 5.4 2.7 4.5 Evaluation 28.6 16.1 29. 5 9.8 6.3 9.8 Districts Selecting P-Value for Positive Frequency Positive Frequency“+ Selection Based on District: Record Type Number (% of 112) Size Location Community Pest Problem 100 (89.3) 0.793 0.944 0.956 Location of Problem 104 (92.9) 0.794 0.953 0.991 Person Deciding Need for Action 93 (83.0) 0.762 0.813 0.877 Mgmt Methods Used 100 (89.3) 0.966 0.975 0.885 Person Performing Mgmt Action 89 (77.7) 0.840 0.438 0.766 Cost 98 (87.5) 0.934 0.493 0.867 Evaluation 83 (74.1) 0.944 0.811 0.575 Districts Keeping P-Value for Multiple Record Keeping Number of Records+++ (1-3-4/5-6-7) Based on District: Record Types Number (% of 111) Size Location Community 1 4 (3.6) 0.141 0.306 0.107 3 6 (5.4) 4 10 (9.0) 5 10 (9.0) 6 13 (11.7) 7 68 (61.3) +Only responses of the 113 districts who said they maintain pest management records in answer to question 38 are presented. One of those districts did not respond to this question. ++DNK =- do not know, NR = no response. +++Includes districts selecting personnel type as Always, Often and Sometimes. ++++One district was not Included as it answered do not know for all record types. *lndlcates significant difference between classes of district attribute. 145 keeping many (five, six or seven types). There was no significant different for any district attribute between districts keeping few records and those keeping many. Pest Management Record-Keeping Time Period Approximately half of 108 record-keeping districts said that they maintain the different records for one year (O-41, Table 46). Fewer than 10% selected one month time periods and only one district said that they keep specific record types for a week. Ten to 15% of the districts said that they maintain records for two or more years as written-in responses for Other. Up to 25% of the districts did not know how long records are maintained and several (up to 15%) did not select a response for each record type. Comparison of one and two year selections was made for districts grouped by size, location or community type. No significant differences were found. Record Storage Location Pest management records were said to be kept most frequently in district maintenance offices (56.4% of 110 districts selected location as always, often or sometimes). This was followed by offices of the local school administration, district custodians, superintendent, school maintenance and school custodians (44.5%, 41.8%, 40.0%, 37.3% and 30.9%). Additional locations noted under other included two pest control companies, one nurse, nine business manager/purchasing offices and four support service offices not identified by school or district level (O—42, Table 47). A significant difference was found for selection of the superintendent's office between districts grouped by size or by community type. More than 50% of small districts and of those in rural communities selected the superintendent's office compared to 3.7% in large districts and 15.4% in urban communities. Over 50% of the districts selected multiple record storage locations. All six locations were selected by 9.1% of the districts while five, four, three and two locations were selected by 146 Table 46. Time Period for which Pest Management Records have been Maintained. Percent of 108 Districts Selecting Time Period for Record Type+ Record Type 2+ Years Year Month Week DNK NR++ Pest Problem 15.7 50.9 5.6 0.0 25.0 2.8 Location of Problem 14.8 50.0 9.3 0.0 20.4 5.6 Person Deciding Need for Action 12.0 48.1 6.5 0.9 24.1 8.3 Mgmt Methods Used 13.9 55.6 2.8 0.0 23.1 4.6 Person Performing Mgmt Action 12.0 51.9 3.7 0.0 22.2 10.2 Cost 15.7 60.2 2.8 0.0 19.4 1.9 Evaluation 10.2 45.4 3.7 0.0 25.9 14.8 P-Value for Selection of Time Districts Selecting Time Period Period Based on District: Record Type 2+ Years (%) 1 Year (%) Total Size Location Community Pest Problem 17 (23.6) 55 (76.4) 72 0.195 0.395 0.197 Location of Problem 16 (22.9) 54 (77.1) 70 0.199 0.226 0.120 Person Deciding NeedforAction 13 (20.0) 52 (80.0) 65 0.405 0.267 0.223 Mgmt Methods 15 (20.2) 60 (80.0) 75 0.088 0.411 0.260 Person Perfoming MgmtAction 13 (18.8) 56 (81.2) 69 0.138 0.546 0.142 Cost 17 (20.7) 65 (79.3) 82 0.244 0.600 0.378 Evaluation 11 (18.3) 49 (81.7) 60 0.116 0.656 0.179 +Only responses of the 113 districts who said they maintain pest management records in answer to question 38 are presented. Five of those districts did not respond to this question. ++DNK a do not know, NR = no response. 147 Table 47. Location Where Pest Management Records have been Maintained Percent of 110 Districts Selecting Frequency Response for Maintaining Records at Office Location+ Office Always Often Sometimes Never DNK RLU NR‘H' School Administration 191 7.3 18 .2 24.5 5.5 25.5 School Custodial 8.2 6.4 16.4 39.1 3.6 26.4 School Maintenance 14.5 4.5 18.2 36.4 2.7 23.6 Superintendent 24.5 6.4 9.1 32.7 5.5 21.8 District Custodial 19.1 5.5 17.3 29.1 1.8 27.3 District Maintenance 32.7 8.2 15.5 19.1 1.8 . 22.7 Other 11.8 0.9 . . . 1.8 85.5 DistrictsSelecting P-Value for Positive Frequency Positive Frequency+++ Selection Based on District: Office Number (% of 110) Size Location Community School Administration 49 (44.5) 0.574 0.841 0.400 School Custodial 34 (30.9) 0.623 0.444 0.450 School Maintenance 41 (37.3) 0.623 0.621 0.342 Superintendent 44 (40.0) 0.002' 0.113 0.01 3* District Custodial 46 (41.8) 0.446 0.292 0.1 17 District Maintenance 62 (56.4) 0.828 0.541 0.565 Distribution of Districts Selecting Positive Frequency for Maintaining Records at Office Location (as Percent of Attribute Class) Size Location Community Office S M L SLP NLP UP U S R School Administration 57.9 43.8 37.0 43.0 47.4 60.0 23.1 43.5 51.0 SchoolCustodial 42.1 28.1 29.6 32.6 31.6 0.0 15.4 37.0 29.4 School Maintenance 47.4 32.8 40.7 36.0 47.4 20.0 15.4 43.5 37.3 Superintendent 63.2 48.4 3.7 33.7 57.9 80.0 15.4 26.1 58.8 DistrictCustodial 36.8 37.5 55.6 45.3 36.8 0.0 38.5 56.5 29.4 District Maintenance 47.4 59.4 55.6 58.1 57.9 20.0 462 652 51.0 P-Value for Multiple Record Selection Number of DistrictsSelecting (1 -2, 3-4, 5-6) Based on District: Locations Number (% of 110) Size Location Community 1 45 (40.9) 0.064 0.360 0.400 2 17 (15.5) 3 12 (10.9) 4 13 (11.8) 5 13 (11.8) 6 1 0 (9.1) Table 47 (cont'd). 148 P-Value for Office Type Type of DistrictsSelecting Based on District: Office Number (% of 110) Size Location Community Local (School) 48 (43.6) 0.139 0.677 0.117 District 10 (9.1) Both 51 (46.4) NeitherH‘H 1 (03) Administration 35 (31.8) 0.185 0.252 0.092 Support Service 26 (23.6) Both 48 (43.6) Neither++++ 1 (0.9) +Only responses of the 113 districts who said they maintain pest management records in answer to question 38 are presented. Three of those districts did not respond to this question. ++DNK = do not know, RLU a response level unknown because either multiple responses were selected for the personnel category or no response was selected for an entry made under Other, NR - no response. +++Includes districts selecting personnel type as Always, Often, Sometimes and RLU. ++++The district that selected neither office type location selected the offices of a pest control company. 'IfldiOfltOS Significant dlfference between classes Oi dlstrlct lttfibUtO. 149 11.8%, 11.8%. 10.9% and 15.5%. No significant difference was found for number of locations selected between districts grouped by any attribute. Districts were further Identified by the types of offices selected as record storage locations. Local school locations alone were selected almost as often as both local and district office locations (43.6% compared to 46.4%). District office locations alone were selected by 9.1% of the districts. One district selected neither local school or district office locations. Instead it selected the offices of a pest control company. Districts were also identified by the type of personnel found in the offices were pest management records were said to be located. Administrative offices alone were selected by 31.8% of the districts, support service offices alone were selected by 23.6% while a combination of both was selected by 43.6%. The distribution of either type of selection (local, district, both or adminitration, support service, both), showed no significant difference for districts classed by any attribute. Summary Few significant differences were found between responses to questions on pest management records. Thirty-six tests were performed for each district attribute. Only two differences were found for districts grouped by size, one for districts grouped by location and two for districts grouped by community type. Significant differences for all district groupings were found for the number of districts reporting that pest management records were maintained. Selection of the superintendent's office as a location for record storage was significamly different for districts grouped by size and community. In both cases, small districts or ones located in niral communities selected the superintendent's office more frequently than did either medium sized or suburban districts which in turn selected them more frequeme than did either large or urban districts. This indicates that although the act of record-keeping is dependent on district size, location or community type. the specifics of record-keeping are not. Pest Management lnfonnation Sources Only 163 districts reported that technical assistance (TA) on pest management was available (050) while 297 districts selected sources of pest management lnfonnation (051). The 60 districts which had said no to TA availability all selected information sources and 78 of those which did not know of TA availability also selected sources. Apparently the term technical assistance was not understood to include information sources and many districts perceived themselves as not having assistance with their pest management programs. Twelve possible sources of pest management information were listed in the questionnaire. A few districts wrote in government agencies and pesticide sales people as additional sources and the telephone book was listed as the one miscellaneous source (Table 48). Six sources were selected by districts as most important. Pest control corrpanies were listed as the most inportant source by almost half the districts (46.8%) and as the major source of lnfonnation for 71.4% (all districts selecting as either first, second or third in importance). Cooperative extension service materials and personnel, district past experience, conferences and meetings, personal contacts and trade publications with commercial sponsors followed in order of selection as the most Important sources of information (22.2%, 9.8%, 7.4%, 5.1% and 3.0%). When ranked by overall importance, past experience followed pest control companies as the second major information source (51.9% of the districts). Cooperative extension service, personal contacts, conferences and meetings, and trade publications were selected by 47.8%, 38.7%, 27.3% and 15.8% of all districts. Selection of these six information sources was significamly different only for districts grouped by community type for comparison of sources selected as most important. Rural districts selected pest control companies as the most important source less frequently (40.6%) than suburban or urban (52.7% and 64.5%). 151 Table 48. Sources of Pest Management Information. Information Distribution of 297 Districts Selecting lnfonnation Source Source First-Most (%) Second (%) Third (%) Total—Major (%) Pest Control Companies 139 (46.8) 47 (15.8) 26 (8.8) 212 (71.4) Experience 29 (9.8) 59 (19.9) 66 (22.2) 154 (51.9) Cooperative Extension 66 (22.2) 29 (13.1) 37 (12.3) 142 (47.6) Personal Contacts 15 (5.1) 53 (17.9) 47 (15.8) 115 (38.8) Conferences/Meetings 22 (7.4) 28 (9.4) 31 (10.4) 81 (27.2) Trade Publications 9 (3.0) 16 (5.4) 22 (7.4) 47 (15.8) Non-Extension University 1 (0.3) 18 (6.1) 3 (1.0) 22 (7.4) Text/Reference Books 2 (0.7) 9 (3.0) 9 (3.0) 20 (6.7) Popular Periodicals 3 (1.0) 5 (1 .7) 9 (3.0) 17 (5.7) Government Agencies 7 (2.4) 2 (0.7) 3 (1.0) 12 (4.1) Scientific Periodicals 1 (0.3) 2 (0.7) 4 (1.4) 7 (2.4) Pesticide Sales People 2 (0.7) 4 (1.4) 1 (0.3) 7 (2.4) Radio/Television 0 (0.0) 1 (0.3) 3 (1.0) 4 (1.3) Miscellaneous 1 (0.3) 0 (0.0) 0 (0.0) 1 (0.3) College/Technical Courses 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) No Response 0 (0.0) 14 (4.7) 36 (12.1) 50 (16.8) P-Value for Selection Based on District: Comparison Size Location Community Six Most Important Information Sources 0.160 0.196 0.038“ Six Major lrrformatlon Sources 0.224 0.223 0.417 Most Important Percent Distribution of Districts Selecting Information Sources lnfonnation Total By Size By Location By Community Source Number S M L SLP NLP UP U S R PestControICompany 139 40.0 52.6 60.5 56.8 37.7 37.0 66.7 54.6 43.8 Cooperative Extension 66 28.9 20.4 23.7 18.8 29.9 37.0 10.0 21.6 27.2 Experience 29 14.4 9.9 2.6 9.1 13.0 11.1 6.7 8.0 12.4 Conferences 22 6.7 9.2 5.3 8.0 7.8 7.4 6.7 1 1 .4 6.2 Contacts 15 8.9 4.0 2.6 4.0 7.8 7.4 0.0 3.4 7.4 Trade Publications 9 1.1 4.0 5.3 3.4 3.9 0.0 10.0 1.1 3.1 Numberof Districts 280 90 152 38 176 77 27 30 88 162 'Indlcates significant difference between classes of district attribute. 152 Technical Assistance Adequacy or Need Most districts said that current technical assistance (TA) is adequate (85.4% of 302 districts). Comparison of yes response selection showed no significant differences although more small districts and those in rural communities responded that cunent TA was adequate (Table 49). The need for new TA to implement new pest management programs was expressed by 41.3% of 303 districts ((353, Table 50). Eighty-seven of these respondees said that current TA was adequate for current needs. The 38 other respondees had said that it was not adequate. Comparison of yes response selection showed a signficant difference only between districts classed by size. Almost twice as many large and medium sized districts expressed a need for new TA than did small districts. Comparison of the proportion of these district sizes which indicated that new TA would be needed showed a significant difference between small districts and the other two class sizes which were not different from each other (23.1%—S, 51 .3%-M, 48.7%-L). Pest Management Method Review Process Few districts said that a pest management method review process exists (15.2% of 303). Over 75% said no while 9.2% did not know (O-47, Table 51). Significant differences were found for yes response selection between districts grouped by size or community. Large districts and urban and suburban districts reported the existence of review processes more frequently than other district types. Many districts offered comments on their pest management review process. A number of these concerned cooperation with the state ”Right-to-Know" policy, ”compliance with Right-to- Know, board policy”. Others indicated that review was dependent on an effectiveness evaluation saying, "if it doesn't work, we review and look for another approved product to use". Some districts reported who performs the review, such as ”school board“ or “safety committee” or "head custodian”. 153 Table 49. Adequacy of Available Technical Assistance. Technical Districts Selecting P-Value for Selection of Yes Response Assistance Response Based on District: Adequate Number (% of 302) Size Location Community Yes 258 (85.4) 0.569 0.961 0.624 No 44 (14.6) Table 50. Need for New Technical Assistance for New Programs. Technical Districts Selecting P-Value for Selection of Yes Response Assistance Response Based on District: Need Number (% of 303) Size Location Community Yes 125 (41.3) 0.002" 0.475 0.180 No 119 (39.3) Do Not Know 59 (19.5) Technical Distribution of Districts Selecting Yes Response (% of Attribute Class) Assistance Size Location Community Need S M L SLP NLP UP U S R Yes 23.1 51.3 48.7 43.9 39.8 29.0 54.8 47.3 35.9 Numberof Districts 104 160 39 189 83 31 31 91 181 Table 51 . Pest Management Method Review Process. Existence Districts Selecting P-Value for Selection of Yes Response of Review Response Based on District: Process Number (% 01303) Size Location Community Yes 46 (15.2) 0.019' 0.533 0.034" No 229 (75.6) Do Not Know 28 (9.2) Existence Distribution of Districts Selecting Yes Response (% of Attribute Class) of Review Size Location Community Process S M L SLP NLP UP U S R Yes 9.6 15.1 30.0 16.9 13.4 9.4 23.3 22.0 10.4 Number of Districts 104 159 40 189 82 32 30 91 182 *lndlcates slgnlflcant dlfference between classes of district attribute. 154 Pest Management Program Development and Execution More districts selected a pest control company or private pest consultant as the developer of new pest management programs than any other group, 43.4% 01302 (O-47, Table 52). Response selections listed in the questionnaire also included local educational agency and qualified educational institution. These two selections were intended to represent the local school district and an institution such as a university or college which researches educational issues. It is not certain that district interpretation was similar. Almost equal numbers selected a local educational agency or a qualified educational institution (22.8% and 21.9%). Other entries included a mix of the three listed agencies as well as six miscellaneous agencies, Health Department, MSBA (Michigan Small Business Association), Michigan Department of Education, State Health and Education Departments and a mix of the local community, school board and staff. Significant differences were found for agency selection between districts grouped by size and community. Local educational unit was selected most frequently by small or rural districts, educational Institution was selected most by medium or suburban districts, and pest control companies as well as a mix of the three listed agencies were selected most often by large or urban districts. More than 50% of 308 districts said that the execution of any newly developed pest management program should be the responsibility of existing district personnel (O-49, Table 53). Existing personnel in individual schools and pest control con'panies followed (20.1% and 16.6%). Only 2.9% of the districts said that a new district pest manager position should be developed. Other entries included a mix of the listed options as well as one miscellaneous response which was for a state-paid county advisor. Comparison of response selections between districts classed by any attribute were significantly different. Small, upper peninsula or rural districts selected existing personnel in Individual schools most often while existing district personnel were selected most by the other 155 Table 52. Persons Selected as New Pest Management Program Developer. Districts Selecting P-Value for Selection Agency Based on District: Agency Number (% of 302) Size Location Community Local Educational Agency 69 (22.8) 0.046' 0.214 0.028‘ Educational Institution 66 (21.9) Pest Control Company 131 (43.4) Other: Mix of the Above 30 (9.9) Miscellaneous 6 (2.0) Percent Distribution of Districts Selecting Agency By Size By Location By Community Agency S M L SLP NLP UP U S R Local Educational Unit 33.7 18.2 12.8 17.0 31.7 34.4 9.7 14.4 29.3 Educational Institution 18.3 25.8 15.4 22.9 20.7 18.8 16.1 25.6 21.0 Pest ControlCompany 37.5 44.0 56.4 46.3 39.0 37.5 54.8 44.4 40.9 Other: MixofAbove 8.7 9.4 15.4 11.7 7.3 6.3 19.4 13.3 6.6 Miscellaneous 1.9 2.5 0.0 2.1 1.2 3.1 0.0 2.2 2.2 Numberof Districts 104 159 39 188 82 32 31 90 181 Table 53. Persons Selected as Responsible for New Program Execution. Districts Selecting P-Value for Selection Personne/Agency Based on District: Executed by Number (% 01308) Size Location Community Personnel in Schools 62 (20.1) 0.000" 0.002' 0.001“ District Personnel 156 (50.6) New District Pest Manager 9 (2.9) Pest Control Company 51 (16.6) Other (Mix and Misc.) 29 (9.7) Percent Distribution of Districts Selecting Agency By Size By Location By Community Executed by S M L SLP NLP UP U S R Personnel in Schools 35. 9 14. 8 0.0 12. 0 31. 0 40. 6 12.9 6.5 28.3 District Personnel 39. 6 54.3 65.0 53.7 48. 8 37. 5 58.1 58.1 45.7 NewDistrict PestManager 0. 9 3.1 7.5 3. 7 2.4 0.0 3.2 6.5 1.1 PestControICompany 15. 1 16.122.5 18. 8 11.9 15.6 12.9 15.1 17.9 Other(MixandMisc.) 8. 5 11. 7 5.0 12. 0 6.0 6.3 12.9 14.0 7.1 NumberofDistricts 106 162 40 192 74 32 31 93 184 *lndlcates slgnlflcant dittOl‘Ol‘lOO between classes Oi diStl‘iOt attribute. 156 district types. Pest control companies were selected most often by large districts, those in the southern lower peninsula and those in rural communities. Summary Seven tests were performed for each district attribute to assess differences between responses to technical assistance and questions concerning new pest management program development and execution. Four significant differences were found for district size and community type comparisons. Only one was found for location comparisons indicating little influence of location on district response selection. Only districts grouped by community differed in their selection of the top six pest management information sources. All other district comparisons showed no difference in district use of technical information sources. Districts grouped by size differed significantly in their indication of a need for new technical assistance, should a new pest management program be implemented. Large districts selected positive responses to the need for new sources most frequently. Districts grouped by size also differed in their positive response to the existence of a pest management review process, in their selection of a new pest management program developer, and in their selection of who should execute a new pest management program. Districts grouped by location only differed significantly in their selection of the personnel who should execute a new pest management program. Districts grouped by community type differed in their positive response to the existence of a pest management review process, In their selection of a new pest management program developer, and in their selection of who should execute a new pest management program. A pest control company was selected most frequently by large sized districts as a new pest management program developer while small districts selected the local education unit (including district personnel) most frequently. A pest control company was also selected most frequently 157 by urban district communities while rural districts selected the local educational unit more frequently than either urban or suburban districts. Existing district personnel was selected most frequently by large districts, those in the southern lower peninsula and those in urban communities as the personnel type that should be responsible for execution of a new pest management program. Small, upper peninsula and rural districts selected an existing person within the individual schools more often than did any of the other district types. Clearly pest management program development and execution is dependent on district size and community type. CONCLUSIONS W A data base of school district pests, pest management practices, pest management performance, effectiveness evaluation and satisfaction, record-keeping and future pest management needs has been developed. Of the 567 schwl districts found in Michigan, 311 returned usable questionnaires (54.9% of the total). Distribution by size was 34.7% with one to three buildings, 52.4% with four to ten and 12.9% with eleven or more. Distribution by location was 62.1% In the southern lower peninsula, 27.3% in the northern lower peninsula and 10.6% in the upper peninsula. Distribution by community was 10.3% urban, 30.2% suburban and 59.5% rural. Pest Presence. Certain pests perceived of as problems by K-12 public schools were found to vary in intensity and variety based on district size, location or community type. Current pest presence was reported as significantly different for districts grouped by size or location. Of the 300 districts responding to the question on pest presence or absence, 97.7% either currently had or previously had pests in their school buildings or on their school grounds. More than half the districts said that pests were a current problem (52.7%). Large districts, those in the southern lower peninsula and those in urban communities reported a significamly greater current pest presence. Tolerance of pest presence was low . Three-quarters of 297 districts said that no pests are acceptable. Only 1.3% said there is no concern over pest presence. Districts differed in there selection of cockroaches as both the most inportant and the major school district concern. Again, large districts, those in the southern lower peninsula and those in urban communities reported significantly more concern with cockroaches. They did not differ in their selection of head lice which were selected as the number one school pest concern by 158 159 Traps were most preferred for prevention and management in districts with mice and rat problems. Districts without these pests selected traps, sanitation and facility modification almost equally for prevention while more selected traps for management. For districts reporting weeds, outdoor plant diseases and outdoor plant insect pests, the most preferred prevention and management methods were modification of landscape care practices and use of pesticides. For outdoor plant disease prevention, twice as many districts preferred landscape care modification to pesticides, while each of the two options was selected by equal portions of the districts for disease management. For outdoor plant insect pest prevention, equal numbers preferred landscape care modification and pesticides, while for management pesticides were more preferred. Districts which did not report presence of these pests either preferred landscape care modification or did not know what method was preferred. A significant difference was found between districts reporting the presence of written pest management guidelines when grouped by size with more large districts reporting their existence. Just over 90% of 303 districts said pesticides were safe and effective with 9.6% saying they were not. Significant differences were found In the frequency of pesticide use for both prevention and management when districts were grouped by size and location. Pesticides were said to be used by 69.9% 01306 districts for prevention and by 96.1% for management. Seventy-eight percent of 304 districts said they either always, often or sometimes announce Intended pesticide use but only 45.1% said they post notices once a pesticide has been applied. Pesticides were said to be applied on all days of the week. Significant differences were found for application on Mondays, Tuesdays, Wednesdays and Thursdays when districts were grouped by size with large districts reporting their application more frequently. Pest Management Execution. Different school district personnel were found to be respon-sible for pest management execution dependent on district size, location and community type. 160 Two significant differences were found in district reporting of personnel who request pest management action. These were for school administrators and kitchen staff when districts were grouped by size with small districts reporting the personnel types more frequently and for custodial and maintenance staff when grouped by community type with urban districts reporting them most frequently. No significant differences were found for the personnel reported as responsible for communicable pest problems. Pest management methods were said to be selected in over 80% of 305 districts by both the personnel deciding management is needed and the personnel who perform the pest man- agement. Differences were found to exist only between districts grouped by community type. Custodial staff and pest control companies (PCCs) were reported most frequently as the personnel who performed indoor pest management. Grounds staff, maintenance staff and PCCs were reported most frequently as personnel said to perform outdoor pest management. A significant difference was found for the selection of PCCs by all district groupings with more large districts, those located in the southern lower peninsula and those in urban communities reporting their employment. PCCs were said to be employed by 71.3% of 310 districts. Quality of service was the most important criteria used in selecting a company. Both administrative and support service personnel were said to negotiate PCC contracts. Superintendents, business managers and support services personnel were selected differently by the different district groupings. No differences were found to exit between district selection of factors said to be written Into PCC contracts, nor in the length of time for which PCC contracts were negotiated. PCCs were said to be hired to manage 21 different pests. More than half of the 221 districts employing PCCs have done so specifically for cockroaches, mice and ants other than carpenter ants. Twenty-five to 50% of the districts have employed PCCs for stinging insects, termites, carpenter ants and rats. Ten to 25% have employed them for weeds, fleas, flies, head lice, diseases of outdoor plants and mosquitoes. Fewer than ten percent have employed them for 161 insect pests of outdoor plants, bats, birds and miscellaneous others. Significant differences were found in the reporting of PCCs hired for management of cockroaches, fleas, head lice, stinging insects, termites, bats, rats, weeds and outdoor plant insect pests by the different district groupings. Except for head lice management, the hiring of PCCs indicates perceived pest importance better than any other measure. This is especially apparent when the number of districts reporting that they have had a specific post is compared to the number reporting that they have hired PCCs for control of that pest. Approximately 80% of 51 districts reporting termites and 80% of 118 reporting cockroaches said they have hired PCCs for control of those pests. PCCs were said to report to both administrative and support services personnel. Superintendents and district business managers were selected as PCC report recipients differemly by districts grouped by size and location. Pest Management Satisfaction and Concern. The level of satisfaction with current pest management efforts and control achieved did not differ by any district grouping. However, the amount of concern over pest management and pesticide use in the school environment did differ in expression between districts grouped by size, location and community type. The reporting of concern expressed over pest management by local and district custodian, grounds and maintenance personnel as well as by parents was significantly different between districts grouped by size and location. The reporting of concern expressed over pesticide use by all school groups except students (i.e. local and districts administrators, teachers, parents, local and district support services staff), was significantly different for districts grouped by size. Large districts reported each group as expressing concern more frequently. One difference was also found for districts grouped by location and three for districts grouped by community type. Pest Management Records. The types of pest management records kept by districts and the time periods for which they were maintained did not differ. However, the actual act of 162 record-keeping was significantly different for districts grouped by either district size, location or community type. Technical Assistance and Pest Management Program Development. Interest in new pest management technical assistance and program development varied depended on district size, location or community type. Little difference was found in the reporting of sources of technical assistance, but a significant difference was found in the need expressed by large districts for new technical assistance for new pest management program implementation. A significant difference was found between districts indicating who should be responsible for new pest management program development when grouped by size and community type. More small and mral districts selected local school personnel while more large and urban districts selected pest control companies. The selection of personnel who should be responsible for new pest management program execution was significantly different for all district groupings. More small, upper peninsula and anal districts selected local school personnel while more large, southern lower peninsula and urban districts selected district school personnel. Wm: Dillman's Total Design Method, TDM, (1978) was used as a general guide during survey preparation and implementation. Initially it was believed that that all questions were worded in accordance with Dillman's principles. However, upon analysis of survey returns, the true challenge of question wording became apparent. Probably the most serious problems were those of using words which were not uniformly understood and of making questions too vague. For example, a fine line exists between pest prevention and pest management and the two practices may not be perceived as being separate in all districts. This probably made response selection variable as some districts may have selected the same answers for both prevention and management. Others may have answered only questions on management while still others 163 might have answered only questions on prevention omitting answers on management since they would have felt they'd already responded. Questions with this fault included Q-10 and Q-11. The same situation occurred in the effort to have districts indicate which personnel decide pest management is needed, which select methods to be used for pest prevention and/or management and which actually apply the methods. In some districts, the same personnel may perform all three tasks. These districts may have considered the response selections (or entire questions) to be redundant, and selected the same responses for all of the personnel types. Alternatively, they may have selected a response to only one question. In other districts, different personnel may have been responsible for different combinations of the three tasks while in still other districts, different personnel may have actually performed the different tasks. Response selection may therefore have meant different things to different respondents depending on personnel responsibilities. Questions with this limitation included Q-25, Q-37, G40 and Q-41. Question Q-48 was also vague as no definition was given for ”local educational agency” or "qualified educational Institution”. ”Local educational agency" was intended to mean the school district Itself while ”qualified educational Institution" was to have meant an institution such as Michigan State University or the University of Michigan. Districts could have interpreted the ”qualified educational institution“ as an agency that services education or even the Department of Education. As the questionnaire was sent to districts of all sizes with different hierachies of administration and management, an effort was made to include all possible types of personnel within a district. Since some districts contain only one school, this may have made some questions appear to have duplicate responses (i.e., in such districts there is little distinction between school principal and district superindentant). In questions Q-20, Q-27, Q-30, Q-35, Q- 42, Q—43, Q-45 and Q46 school personnel were listed as response selections, followed by their district-wide counterparts. Respondees in small districts may have had difficulty deciding 164 whether to select from both lists, the local list only or the district list only. Some pairs of questions (the pairs Q-21/Q-22 and Q-23 /Q-24) would have appeared to be completely redundant to respondees in such districts, as the questions were identical, but with one question listing only district-level personnel as selection responses, and the other listing only local-level personnel. No analysis was attempted for such question pairs. Questions Q-1 and Q-15 contained double negatives. Answers to Q-1 were analyzed as no response contradiction was evident. However, responses to Q-15 were in conflict and analysis of the question was dropped. Question Q-13 presented two concepts, making response interpretation possible only by reviewing the respondees' written explanations. Question Q-27 contained two separate requests (one a response for indoor pest management,and the other a response response for outdoor pest management ) for each personnel type. While most districts did select two responses, several did so for indoor only. Responses to questions Q-18 and Q-19 were not analyzed as the information obtained was judged inelevant to the survey focus. It was not uncommon for five to six districts to decline answering any specific question. No pattern to such lack of response was evident. Analysis of questions was based on the responses of districts which did answer them. More difficulty in analysis was created by districts which gave incomplete responses to the questions . Districts may not have responded to certain parts of questions because (1) the lack of an answer was an implied no, (2) the provided responses did not apply, (3) the answer was not known by the respondent or (4) the answer was know h, but the respondent did not want to admit to a specific response. In these situations only the number of positive response selections were compared between districts grouped by attribute. Questions with large numbers of do not know responses were handled the same way. The questionnaire was formatted as a 6-1/4" by 8-1/2" booklet with a cover designed to interest respondents and encourage them to respond. A cover letter to establish contact and a letter of endorsement were included. Contrary to the TDM, only one follow-up was mailed 165 instead of three. This was sent out four weeks after the questionnaire itself. Usable questionnaire return was low by TDM standards, 54.9% compared to a TDM low of 58%. The main complaint made about the questionnaire by respondees was that it was too long and that the questions were beyond their scope of involvement. Concern was expressed over collected data reliability and validity. Some districts did not feel that pest presence or management was a problem of concern. One district felt that survey results would lead to more school pest management regulation which would cost money. A few districts said that there is a real need for information and for an ongoing program of pest control. Certain responses may have been different if a shorter and more defined questionnaire had been prepared and implemented. However, it is not possible to determine the extent of such variation. The number of districts answering each question varied between 294 and 310, with the exception of the question concerning outdoor pest management, which was responded to by only 241 districts . Reported percentages were based on the number of districts actually responding to each specific question. Comments made concerning this survey as well as observations made during survey response analysis indicated that future assessments of district pest concerns and pest management practices would be best served by developing surveys directed toward districts of specific sizes. A series of short surveys with the focus of subsequent questionnaires being built upon the findings of completed surveys would allow for more detailed evaluation of school district concerns and needs and would prevent respondent fatigue over questionnaire completion. “0 = 01" e: 1010‘ o 'z‘ ir:i=-'ri:i 'Hrirr '1‘-°'llil This survey found that districts classed by size exhibited the most significant differences in their selection of question responses. This was probably due to differences in administrative structure and school personnel responsibilities as well as to differences in the potential number of pest problems due to different numbers of buildings. 166 Any new pest management program would need to take these size differences into account. In fact, different programs geared for districts of different sizes might meet with the most success. Throughout the questionnaire small districts selected superintendents and local school personnel while large and medium sized districts selected support service district personnel most frequently as the personnel type most responsible for pest management decision-making. When asked who should be responsible for new pest management program execution, small districts indicated local school personnel most frequently while large districts indicated district personnel. This indicates that two different types of pest management programs would probably be most successful, one for small district implementation directed toward individual schools and one for medium and large district implementation directed toward the concurrent pest management needs of a number of buildings. Most small districts responded that current technical assistance was adequate for their projected pest management needs while more than 50% of both medium and large districts said that new technical assistance would be needed for new programs. This further Implies that large districts may be more receptive to new program implementation. A key figure in any new program development would be the pest control company (PCC). Almost 100% of the large districts said they hire PCCs while 83% of medium and 45.7% of small sized districts reported doing so. In fact, over 50% of the large districts selected a pest control company as the agency that should develop new pest control programs for their district. This indicates that regardless of any new school pest management program development, pest control companies should be trained in school pest management and required to follow certain defined procedures in their pest management performance. APPENDICES 167 Appendix A. Cover Letter. MICHIGAN STATE UNIVERSITY DEW OI MOIOLOGY EAST LANSING 0 IICHIGAN 0 08244113 October 19, 1987 Dear School District Superintendent. The 1985 report to the Governor's Cabinet Council on Environmental Protection titled "A Strategy for Improved Pesticide Management in Michigan,“ recommended that model pest management guidelines be developed for public schools. In response to this recommendation. we have designed the enclosed questionnaire, ”Pest Management Within illchigan Public Schools,” to gather information on school pests and pest management practices. Responses to the questionnaire will be analyzed and used to support future decisions concerning the development of pest management guidelines and implementation procedures for Michigan public schools. Your district's participation will directly influence these decisions. This questionnaire concerns only those buildings in which students attend classes. Questions are asked concerning: - prevalence of pests. - practices used to manage pest problems, - school personnel involved In making pest management decisions, satisfaction with practices used and control achieved, and - need to implement or improve pest management guidelines. We have .addressed this questionnaire to you and other school district superintendents, but we would like it to be completed by the individual within each school system who has the most comprehensive understanding of pest management as it Is practiced in your school facilities. Upon completion, that person should return the questionnaire in the enclosed pro-addressed stamped envelope. We request that completed questionnaires be returned by November 15th. You may be assured of complete confidentiality. The return envelope has an identification number for mailing purposes only. A follow-up request will be sent to those school districts from which a completed questionnaire has not been recorded as received. if you have questions concerning the purpose or content of this questionnaire or if you wish to obtain a copy of the summarized results, send a separate request to either Deborah Killer, Project Coordinator, or Dr. George w. Bird. Professor, care of the Department of Entomology, 243 Natural Science Building. Michigan State University, East Lansing. MI 48824. Phone: (517) 355-4662. Enclosed you will find a copy of a letter from the Michigan Department of Education encouraging your cooperation in this project. Your participation is greatly appreciated. Sincerely, Deborah Miller. Coordinator MSU is all We. Adieu/w Opportunity Institutio- 168 Appendix B. Letter of Endorsement. STATECFW “‘2' DEPARTMENT OF EDUCATION 3"“ °°‘“'° °' mm“ eAitaAaA accents MASON uunmg,anb814&MB hmwm ooaorm' suaowoar Iar Medal CHERRY “(onus GAaY D.MAWKS fixnnn Interim Superintendent July 13' 1987 DR. GUMECINIX) SAL-ts or Public Instruction Trmrum Dir. EDMUND r. VANDETTE sisal! (Manic CARROLL w. HUTTON ANNE'nA MILLER NORMAN orto srocxiuri‘ta. sa Goscrnor JAMES J eLANmAito 151-(Minn MEMORANDUM TO: School District Supe endents FROM: Gary D. Hawks F39' \ In 1985, a report t Governom”s Cabinet Council on Environmental Protection entitl , 'A Strategy for Improved Pesticide Management in Michigan," identified school system pest management programs as an area for study. Michigan State University has initiated a research project to assess existing pest problems and pest management procedures in Michigan schools. In the near future, you will be receiving a research questionnaire covering this important topic. As the issue of pests and pest management impacts the health of our students, I encourage your cooperation in distributing the question- naire to the appropriate individual within your district for comple- tion. Results will be analyzed to assess the need for development of a school integrated pest management program. All efforts will be made to maintain the confidentiality of your response. Your cooperation will be greatly appreciated. Thank you. 169 Sewn .2 .3526: 3 ocean! Sela .e._ecco=-e:a =eIE8 35.351 .0530 Bacon .5: Leno—0° 5 35.391 .85. 23.523. 2 0:35:32: Barce- Ssei JEevceitenam .0520 .223 dag—.2: .9...»an 3am 5.2035 29m c3222 3 uESoEa $.92 :35 2: ecu 3295.5 .0 Eoessmaoo a5 5 3.8:on :39 an: 9.35.7633 £5. \lilw wAOOIUm 0153a z<0=._0_5_ Z=._._._>> x {FZmEm0 c. 209.3 o. $358 .38 .o audience-ex. e323 0cm «05.0230 .coEoomcmE 38 .0 30:30.95“. 0.... 05:30:00 2.8 n 39.. 8:3 8:: .398 as... 2.8 2. £3 2338.. 3:82 82 28:8 .25 «.0 «Sign 92:. 32.2.5 9o... :3, .0986 2:. E cozaafifan 50> mbmgbgggzyoggflwg n .0ab—0’3. £2.50. $321.02 2.. .0 2.252339 2.. .esze co .25.... 32.3 BEEQozBQonzooLoSzmflmEEtoBzwwEwc N 52. 2:52 .2. on 5:22.228 £35.... or .2 170 aghozgcggbmfiwa . 62552826 2.. .0 ...358 23.8.8. 226. 22...... 52. s .38 223. new cc. .a :33 a. 3225 522 a 6893.2 53 m2 m2. 5 2283.56“... .023. .o 958. Eeceu on. 3:83 .39 2:95 9.32.2 2.. .o 5.55 «.0 60.2.6. ”On—=3. .uomnobuuu‘.n 00.20:. 05 5.2—3 Sacco-.33. e... 532 28.525... .co_.e_nEoo con... 3. .mawaggmmfizmizwsdz n .22.... 32.0. 5o» .2 22322. .3... 2e .2: eeeconee. .o 3:23! 302m5w3>§¥oz<¢w> m 2: .8... :2.» 52.8.... 5.. an: 2.228 38E C. Embmwa>5w>§hggw>>§fiw> . 336:: 22528.. 29.0. 929:8 o. 95. 50> .o 3556 on zofiéxoaom 9:... >08 ._ 22.7.6 50> c. 3:306 6023 co .9st 209.0: :22! 00:38 Swen SE: TO .xon a 2:. .0053: 09.093. 6 05.2.5 >9 .0 .0063... owcoamo. a 058:0 E 356 883% on 58 22.32. __~ .382 .Eoc. Sacco 0. new: $2.09.. .coanman .mg on. can 209.8 9.26 2.6222 c. 952 .2539... peace 2:. .2: 9:... act... .33 .o .255. 22x. co 5.56.25 3:60 o. 3:930 :25 man 2:35.32... 25. 6:3... .83... >5. caoE e3 :2. a >m .25.... 32.3 So> 5 2.33332. coon 2:... 2.2. .23 So cc: 2 3.: 2:2: 25 .35. Edam.” 171 $83 Ago... Sued. . J20.” . D I) V ('3 N e— . .gcoooguoflnmnng . Sguogunoa. . ................. momma... . .................. $2.2 . .................. moss. . ................. mama... . .................. 33.2 ............... 3:25. .o . . . 3806;. usual. 02.02:» .0 p .............. 221530 .« D O O 0 O O O 0 O 0 0 fl 0 O 0 O O V V V V V V V V V V V V V V V V V n M M D n '3 fl 0 fl (9 0 ('3 I') 0 I) 0 9 N N N N N N N N N N N N N N N N N '— . ....... Eco. mg 5.59.56 .— J i“ I) m U) I! m m I) I) In I) In I) I, I, n I) 56. #98 5 z. 59. a N \ ' _1 .62. 58 .o. .852 .8 s26. _ 8582533433 3.8 9.382 o... 5.3 .518... .32 $.88 8 is. 2.... 22.. .o 8282.. .23 22.528- 638 5% 5....) .328 2. =- 3.8130 «6 M £92? 1:0. 0 . Queue . aghast . . ggabmggip . . . . .oigbgdp D N w p ................. 00mg..— . .................. ”hair w .................. wgzfip — ................. ”0‘0. —— ............... mwtgmh .c p . . . fined-3.3. whowmz. 02.02:.» .0 — ............. mw128¥08 .0 p .............. mh2( ngo .N O 0 D O 9) O O ('3 0 0 D 0 0 0 fl 0 Q N N N N N N N N N N N N N N N N . N p . ....... Eco. mg thzwaso .p >2; 3w... W8 3 .80.. zone .0. .863: 80 0.9.0. _ a; scenes... en .36 .9... Solo... s 921333 en 3303 >29 23!. 5...... .853 So» c. eEooen 2 use: seen 9.36:2 e... .0 goes Boo! 3925c to... 70 172 x503 cthOd — £88 Illcwzpog . O on V 0 N .- ? 6:528 33... .< =0:on new 4 0 an V I'D N u- — ..... gagdp — ......... 381%.». p ...... Zgotxg.v— . ......... Engéw ..oSufiBflBoisgolitogfiaggPuta 03.5 ad p .......... 2.5.0.4.: — ....... $83.0. FE. Sggd p ............. 30 .0 .83.... .85. 50» S 958 2- .2... .6039... .33! In... .833 P- 5. .310. ..0 £903 . lllcwzho .m — ....... 35gb. HHHIHHHIIHI H D n fl 0 fl 0 fl 0 O 0 fl 0 I" N O gemsamozfi . .39qu 292592.29 . koooooooooooooooo a: ”I “l “l .l ”l v ...... 0230:0><.E . a N ¢ 00 ”ea 3%vvvvvvvvvvvvvvvv N, fiyONNNNNNNNNNNNNNNN F g (%)/nnnnmnoommnommmm _ 7» a. 5 fi. 017 - { caucus 33% v v i v v ow «w b '1 “(banana ' .....mSwa 0.5412. 8.5 hm. %% 7» adds—and J b4 :3: a. .64 a $1 W4 a. .EzfiaoisnnscnaoQG. _ 0» s,‘ :52. £000 3. .363: 0:0 0.9.9 Baud-dug gag 303.3 5% c2...» ...... .8 88 8:82 u :8. = :8 5.2.22 3: 885. «83. 2.8 2.. .05.... 52, 5....) 882.. 328 S 223 5.0 39.56 .850. 50> c. ...... .0... .000 3:30. o co:- = :8 298.33 .02 885. $82 2.8 an .25... 5% 5 35:3 828 $5.3 223 m 0.0 v 173 393—28 .0 3.0.10 .25 .0 3.003 0.000 3.580% n 33.85220. azzzgu230§§o§§§§:183.€gm .0 393.88 a 3...... 30.0... ... $80- 0.8 5.8 9 ... _ :12 .89.... 0- .050 08000 0.0002030 28 000000555... . b.000- IGO .n 80.3.2 8:00. .0 ...... 03.9.0 0. 02.0 002.000. 9.23... >560». .w 0.8-0.58.02 3§§o3?13.o880§326 .— 232 .2. cue-5 a. woo-.88. .8838 .85. u..- 2231.30.25 .0 a; 3...... 80.8.... . 00 :88 0. >3...- 223 0000.0 .0- .. 8 3:8... 0M8... 28. .083... .“55 00.0.. 8300 00 0990 00.0 out-£0030 5.0.4.30. 0» $0000 2.1m D D 332% 51.8.0. D D 02.55.. .a D D 0.80- 515.: D D 03202.5 “0 D m 0.3 . 0.25.. . . D €80. 080.380.305me o. D D 8305! o D D .028 D D 0:30» 225.. 3.0 ... D D a .3 0500202025 08980005090 .2 D D . 315 D D . 2w: . D D 5.5 . .5 ._ D H. 5 .U .U gbmfiflfi DD 0039.! . 05...: D D D D U D as.“ D D 2555 .N ...UD 09:28.5... .0 .3 C. a 03.35 D DDDDDDUEJE 5 5555 53g [J DDDDDDDDD 5 :5: f5 5 5 000.:0E ...-E00000... .000 .0000 2.0.3000 ...- 0! 00:00- 0 : ...-9.8 38.... :8 «:82..- .co... 0:03 Eons-:0... :00...— 0.0050500080h... “1653:: 0.0-0.0.0.0 0.00ij“:— .0. :0. .0 .0000. 50> :. 0000 .0305...- 0.8.0.5053 .003 :20... :0558328 .505 2.0 HIE—HUM“ 174 fl 600.300 0000... .9 00:00.0. 00m _ a a . ....... >320» .0 n a . ...... ><0¢B<0 .0 0 0 . ........ >095 .5. a u . ...... £30520. .4 a a . ..... >333; .0 0 a 2 ....... >333 .0 0 0 . ....... >320: .. .5... 500580580126. 000 >522 02 00> 628 2.3%-88.00.8000 305.003 103000050300 2.0 m 0 n N —..Owgzwwmw$2th$¢§§eowh§ my? mkag .0; zwwm «(I wQthwn( ng .N v o p ................. mm: .05.: no woz<>o< z. .7 o§93953<§0h29>2§g .. ..fiwoo 0., 0505107); « 0015 033:3 60.. 5W0 .0. .0005: 000 00.9.9 gang 000: 0.5 .0 0.030 0006 09.506 0: :0 00 00.0.3 .0200 05 0. 0.0000 0.0 ..000 0.2.0000 0 .0. 305000005 .0 0050:. 05 00 00005 0.0 00300000 005$ 2.0 N ' 0000000000000000000 O wmw>wm m- zwdmga hmg 2W2; zw>w ESE ¢w>wz m. t .02 .0 ~ . .............. 0550 0. 230020 800 u. ad 0200000 05 30000 2022, 350002052 0. : 00> .0. 0 . ............... 02: >z< .2 05.000292 0. : 00> . 2 .50.. :80 a. 30.5: 08 0.9.0. 9503?. 02 00> 200020 20 0.0000 00...! 830.0 .0200 50> 0. 00202000 000 2 30.009000 00.02008 .. 0. 005.00! 0. E0320 .000 0 .22 3.0 n v n N - ................ OwEr—Zwo. m. t Cw; Ighmwn0§§1008003000300020§061 3.0 202.000 50> 0.0.9.0 0000.0 9 N mw> . ...-05%;.0130 gsasgitgoeéuizfluiis 9.0 >208.- . €008 >200} (5 0§§§08§858¥8.i= .0 £00.00 2025 0 09985009000830.0086» 0 331329.23EE000851553E0229 . 23.5.. 0.0.028- 126. 2.85.8.3 8.5 02002.. 9.3 .3» = .0 éhgg a 9 N mm) . 2368 03.02000 0.2.0. 22...... .828 So» 0. 5000 0E0_00.0 .000 :02! 0000 00 0.0050 .003 90.3.0000 005.0030 002:) 30... 30> 00 4 N70 175 v v 02% flay n n 94 ..oBEcoo 032% N — N p N p N p N p N p N p N — 0&0» «Yo «0% _ .68. no: 5. .363: 80 0.8.0. $.02? CthO . ........... ZQhowamZ E.=O .2985 .83.... o... 2.0 .3: 2 32:00-52 .o 32...... .23 on. 530 o. 3:: 22:32.2... :2. c2...» .20... 2 3:33:23! 3.2. .23»... 32.0. 50> 55.3 6...: So ac: o. 8... 2:03 a! 302 clad—Hum“ O— 176 h 0 o v o u . «EEO o. o o n o n v n w . lldwxho a. 0.88 0.6.3 h o r. v a u . 51.5 2 a o a o w. v n a . lulllnldwEo n. h o n v n a . .......... 9.25.. a o h o n v Q ~ . . . . . 0,550,600.00 500535502... 3058.082 2 u u a v a a . .......... 055.. o o n o ... v n a . ......... 3250 509883930 2 585.8050 .... u u n v n u . .......... mome. 2 a o h o ... v n ~ . .......... 0033. 2 u o ... c o a . ........... 92¢ a. a o n n ... v n ... . ........... mind. 5 o m c n w . ........... 8.2.... a o h m ... c n N . ........... 3.1.... u m n v n u . ........... 005...: Ill... 0 n o o v a ... . .......... 00:6... 5 o m o n a . ........... 33.9 Illa a n o m c a w . ........... 050.8 s o ... . c n a . ......... 3:15» .a Illa o a o ... v n w . ........ 8:25» .o h o a v a a . 30me 0202.5 a g o o s o n v a ... . . . . 2,082. 02.02:» .o s o m c n a . ....... $950002 5 o o u o m c n u . ...... 39.00003. N n o n v n w . ......... moss; o a o n o o c n N . ........ 339m: .0 s o a v n a . ........... mun... ... a o h o m e n m . ........... 3...“. n s o ... v n m . ........... «<3... .v o o u o m c n ... . .......... 9a.“. v s o n v a u . ....... $1305.80 .0 a o s o ... 0 a a . ...... $103580 .n h o n v n m . ........ 32.. $15 ... a o h o n v n a . ....... mg 5:5 .... s o a v n a . . 21332.. $59.56 .. lllllo o s o .... c n a . ...toipz.‘ 55350 .. «we Guava $.90an {a Q%%%%%%%@Ww%%% a... 00 $0 «0%on hwy our Q tax 0% 0% «W a...“ 00 q» 2 — .50.. £000 .0. 2000 .2. 200600 ... 0.2.0. _ .80... £000 .0. >100 .05 20060: ..0 0.2.0. _ : 32...... 52. ‘ 3.00:3 30> 0. 0002.0.» .00 0.0 .2. 02¢... 00 >08 3000200 600.30.; 30.0.20 .900 0 .5 «0000.580 r... .0000 00.30: a. 3% 60:30.0 2. co .0 .0023 a 0. 00.2000. 2 .30 0 005$ 3.0 c. 5000 .0: 00 .0... 00.... 00 >06 .8002... 6000-3... .0233. .0500 0 2 500.300. 0.. .0000 3:6: a. 34093 .8250 ... co 5 .028 a c. 025...... a. :8 a :22. 3.0 n— N— 177 m. h o n v n h ....s. .08 .o. .00.. .0... 0.3.5.. .... 0.9.0. >...0000 . Illll 00.00.... 0.08.0 . lllll 00:6... . . . . . whowmggazbh .o p ....... mthDOmg .h — ......... H23: .0 . ........ mg EthO .N p . .>...0.m.r2( EthwaSO .. 0.0%... .5 _ 32...... so. ... .38 .8 8 .0... 00.... 0.. .0... 05.8.... 302.3... 00.2.0 .060 0 ... ...000 9.6000 0 30.000 03.0. 0... 00:00 .0... 000 0000000. 00 0.09.0 .000 050000 a 00...! 00.000 . .8828 9.32.... .... .o 02...... 0.... 0 0 0.0.0.. .60.. ..000 .0. >.000 .0... 0.00.000 ..0 0.2.0. $0000 . waho . 0 . 0.88 . Illmw.¢0... . ... . 9.26.0350 uOmhmwahmeZ6— . ....... 05.. 00:00 .a . ......o. 9.2.. 00.20056 .. aim ..0.00..00 30> 0. 0002.80 .00 0.0 .0... 00.0.. 00 >00. $0000.00 6000023 .020...0 .060 0 t ...000 050000 0 30.000 09.0. 00 00.000 .0... 000 000000... 0.. 0.0000 .000 00.0000 0 00...! 00.000 .8822. 00.32.... 0... .o 5...... 00.0 v. 178 v v 0 «WM... a n a ..w 0.. 0. .60.. 0000 .0. .0060: 000 0.0.6. 33.00% 00.003.02.00... N N N ...“... '- p v v ...”... 00% 0%6%0b‘flv0 0..., .60.. ...000 .0. .0060: 000 0.0.6. 30.030800“ n N N 033.02.502.00: >00000 . turbo . — . . Egghmwmwh<2¢0 . . ....... 03025.. m. 0000 mum; m 0. 002. 3.0 u. $20.98 b.0000 KthO gm... 1.5% 0.9590 whflxm Egg§§h(fi(§ww§ v n N 0 ...0060: 0.0009000 0.25. 0.00.0.0. .0003 50> 0. 80000.0 00060 000.0000 60:000.. 00 0000 660.020 .000 0.000.:06600 .0 606000006 .0. 10.000000. 0. 0....) 3.0 ..0...0.0 .00000 .00.. 0. 0000 0000.06 606000006 .000 02.000 0...... .0000 000.600.. ..00 0.... ...02 Glad—Hum“ _ 600.600 0000.0 .0 02.000 00w _ 0.80. .... 0 a ... . 00:6 . 0 v a m . ........ 0.2.0.000 0000.00 .00.. 00600.20 «00280000086030.2909 ghefigflggwn . v a N .10 0 0 )0 fmrQr «VVO‘IO‘Q AAVVV La? 00 @1 g :68. 0000 .0. .0060: 000 0.8.0. «02.000. 0. 09.00 0000.000 00.0000 . .. owowwzflfiwiggggwa . 0 000006 0. 0000 00 0. 0.0 «005.08 .00.... 00.000 0. 0000.00 9.32.0. 0... 0.0 >.0....!01 3.0 b— 179 fig 3 2 a. gown—m ..ku 56:5 002.0000. 0.0008000 .006 0.2.0. «00.00000: 00.00063 .0008 .000 5.! 0.000000 0.0 00.50 06.. .0..) .0.. N06 000000 a N . IthO . o o N . ....... .5ng 409.3 ...—.5003... mm Oh mg kg 8§0muum E22 88 g Eggggsg .m n N . ...................... wojn 93.. 0.. 8§§w§3§54<>m .0 n N . ........ own: mm 50 65.... m8.0..—.mw0 “.0 mg . a n N . ....................... me3 mm 2(0 hggfiwghwwatmg .N o N . ...... meD we Z<0 801.53. 629505122 hmwn. wtOuwm Ewmwmn. mm .835 ks... wcwmfiDZ hmwa . — .60.. 0000 .0. .0060: 000 0.9.0. — a 2.96....98 Q. mw> «00.000600 .00000 .000 .....s 00.00000: 0.06.000 :. 00:..00 >..00...0000 0.0 0.0.0... 00.0.2.0. 0... .0 00.02. 8.0 Q— >...0000 m 0 n N . CwaO .0. n v n N . ............ «mg; mwmzaa 0.03me 0 m 0 n N p ............. hzwozwhziwaam b.9590 n m n N .. .130 ...wwa gs. 48.5w “Ru >553 N n n N .. . 5.80.0 ..mwa 02>(I 38 ...O 45.9.50. p .0400 010...”..000035 _ .68. 0000 .0. .0005: 000 00.2.0. .7— ..0060068 30:00 .000 .....s 0.0.0.000 00.00000: 0...... no.0 305.62 8 .0 b.0000 .050 .0 3600000 .000. .3003. 0000.000 .30.. .n .5800... .80.. .30 .0 .88500... 0.0.8.3... 0832.. 8600 .o 0:80 .. 00001800....“ 290600 200.0600 20.5000 550an 55000.2. 0250002 50:00.3 8929.080 502% 0000 0.0009000 00. 0. 0000 00000.0 0... .0 .0005: 00. 000.0 £6.00 .0.. 00. 60.0. 060068 .0008 .000 0 90.30.00 0. 0000 0.0 0..0...0 .033 0N.0 23:98 0 .000 .0 20.500 0. o0 .oclil 02 0 mm) . 00000000. 0.0009000 0.8.0. 0.00.0.0 .0003 50> 00...! 060.090 .000 000006 0. 023.060 .0>0 00.000600 .0..:0o .000 0.< 0N6 o. — 6:52.30 0...: .0 9.0—~00” 9cm x;— $905 n v n w . * cwxho .m $.68» n u . cmxbo .0. r. v n w — .............. mo.qu wwwzfiam ...O.¢...m.0 .v $.62: n c n w p ......... onuO Ewozwsmwnam 5.0.590 .n n a — turbo .5 w. v n a w ....Iwghmwngiguogfiowm .« n a . ....mECOODSOuOmbmwnkomm-s .m— m v a a ’ ....Smaoghmwn03><:§u04(§cm J n w . ...... mggbmwgflo .m— .4 AI % % 949 % My“ sauna n N w ................... moww; . v w W o p 1‘ $4 .................... . 0.. n m _ mpg n. .63. 53 8. .368 2o :26. _ L ... N , .................... as .2 «gust-6:935:32. 05:89.8 n w , ................... moci .: cos-6.2:. 9-32.2 8 3:205... 835:. £868 .238 .08 a coat Eon? o» 3.0 a u . .................... 9:0 . a. £03. 0 N w . . . . u ............ mutzCWP .0 0 r. v n u — (9:0 5 8 a w . . . .9. .88 .88.... .30me 0262.5 .o 1 n v n N p ....................... ow”: ”g 0 n w _ ................ mwOCDOmOS .h n v a w , ....... haul $2520 2 955.. 823.6 0.. 0369B “ES—m 8.82 g £2825 m n w — ................. w030 .o 3: .o 3:808“. R58 22.3% 30» 5 28:0. 55.? ...-on cont-E 2 c.2858 «8.0.... 9339.2 0.... .923 72. .5 “3938882 3 new: .288 30a .0 39:2... 9.36:2 05 2- 32.302. 301 3.0 .0 >5 .0 225093.: 5. .256 .0028 52. c. 33.an cwon macano 25:3 Son 26: 00.0 a ON 181 c n N — CthO .0 m n v n N . ............... mmwzmzpomtm §15Eu0§w .. m c n a . 29§§5wau058 .o n v n u . .......... 0.00:5: Swims; 5m... 2830136185.. .... n v n N . ..................... 83 6605!. 539.53 52.08.: .v m c n n . ............ 80mm: 9.... 20:9. Eugfiuaowaowogg .n m c a u . ........ 2309... ..mwauozoE‘oQ. .« n q o m . ....om_u..»zwo_:m..ooc..5mauo§ .. a? 404% 920 are 96 fio g «Q7 o e»? 49% £94 + .52. so... 8. .362. .8 0.2.0. 82 % o4 4mm” 6%“.5fihw _ nn «3.08... 9:09 0.20.. .3550. 0980. 0.0 0:0. 30... 3060005... .000 .0 80:00 £000 .0“. 3.0 n D ID If! n v v ('3 0 n M n 3303 . cwzho . u — . wmwzwzswuuwswaghmwabggda .0 p .......... ZthhzgwgzghmwnuOPmOO .n F ....................... Amghw: Eggghmwngomggfig .m ~ . ....omm:.m59¢m55wzwoc0 co .09. 0980. 02 070 292528 a oz ... mm> . .6888. anion..- 126. 3...): .o. 5.3.80 .282 8.5 2< and 3.6.828» E. 02“ a... .0880! 80.58.80 0.9.9 2560030... .00.. .o .0800 >5 05509.3 .0308 .0050 Sea 55.) 50.. 8.000.. 02 00.0 0.88 n v n m F 5:5 .v m w n u . ................. 0015: 533.93. hmwawcowmascgfifiogzoofiwa ... ... v n ... . ................. 8:5: Emzmosgz 5w. goggdég .... m c a ... . .............. 3852 ms... Emzu0<20... .0.: 00.000. 3.050005... .00.. .900: 09050.: 508002.00. .000 .0 00000280.: 0.: 52.0 23:00.... x00 03 9.2.000 0.5 .... ulzdfiddw «a 182 $3 $3; a a . $15 a m c n u . 51.5.“. n N . . unthm 39.7-<5 8859.5 g h9g8 .n n v n N — ............. un—(hm w02 n v n N — ........................ mhzwoam .n «c830. 25 c. 0108 co 26... >2: «8:833 805 8.95 a... u:- .coEc2.>co .028 05 c. ................. . 320.38. .0 8: I. .96 58:8 “5329.. .3. 8:20 .o 2820: 0539.0. 9... .o .6. 0).... 3.0 m ¢ n N — m2§¢<¢9€m¢wxu ..................... «3.0:. 82:008.... .i 32.3 n v n N . (I no 2300:... 5w... .9 .o .009... €- 5.: 28:8 903893 .26 .985 3 .382. 2.330. .5 .0 >5. 261 3.0 «55 8.0m Egg 303.528 o N: a m c n ~ . 2§»m&g§§335§ N v: N n v ... v. _ ..................... 1m4m0¢ a 5w... 4.2 m 9400 ‘94 vvvo .7% 025$. 69.8.03.qu 2959.57.29 .. .3 . 9.02 . flow 6&1 o 4 $1; 2: ... 4 EC: 50¢. .0 5 . ..C OCO 6 08. ..8592 3.398- 186. 22...... 52. 5 no.5 89...... — . «858mg .... _ o. .coEomacwE 7.8 05 Soon 305. 20033 50> osteoa- oEgo 08 .o «2.2!... .62... :61 3.0 . . 29:. 308.593... 33 co «Eco! 2- 2623 N70 0N §§8 n 183 9. N am» — _ 63:2:00 Glut—n .W 22.0.0 2W _ ...-coo... 8% 03:0. to..." .85. 50> u:- ao> o. .31.!- >=co§o ...-5.0.5... 3% ... 8.5....- _8.=..o.. .. 3.0 336298 a £90... Km ..0 Q. N >2<§§5mu< a —. ngur. 59:52: a .88.... is... 12.9 ...-52. 8.5%-Se .... 38 . Egon... ...... o. 3...: 8 .88....- _8_..5.. .6: 33>. 3.0 49.285... 332% u mgggggggflxw _ ...! ... ......E... 15.8.... 12.0. «8...... .86. so: mm) . ...-252.8015... jogs-3.8.3.: igllziisiu .70 . A Icon... 3:39.8- o_u..o. have... ...-.50 50> .c. I; 86.8.... .8150! 0.5 a. No.0 szo v .z... ......n.:..::.):l :1. ‘50 v. >29...- Ezgga N .060.»— %w ité— $3196.18; — 80580 1:38... §§3&.o— ......ng Salon!- Suaov .... 8.2.33.2. .3631 §§§§d 8at!ash-Igiivllaogschg.§.i§ol§c= .70 7 :38... ...... ......8 5.... 888.33.. on!» .M .882... 2.33.: 3...... ... ...... 2.21.2.5 ......lxweoz .« _§.Oo 1:0 .It’l’ ”355 g 8}“ gueagé .380... oz. onto-cu i 60> x .0 NH- 9 g g 50:98 a g: D #3; LEE 3 N g a fig 5 33 13528- ”) — 05 EST 0233 5:552: 29 .o 35:5: .5 83a. €05.95... .0! :o con-E53 ...-:09! 83.028- :in a. 0.: >233... 39.. 30> .858 025 It .038 3.01 26.8 .... 0‘ Set 3.0 0.2.0. 5.352.. 32:82.... ...... £2.39 50> .o .33! B. ...... 38o... >5 .30 .4 =6 184 .08. 50.5.: .0523 ....m 050.50 85.00 .9202 90 5.0.0203 0.06 00020.5. 32060.5 .0 20.5.0000 >025 .0003 .0. 00202.0 09:06:: :0 c. 02.0... 00 0.30.... 9.05.2630 0... $000.00.... 0000 00.. 00202.0 0.... .. 000.0000 000.080 600020000... 0000.000 0... 5...... 2.00:0..0000 0... 50.0. 0000... .0000 0.... 0. E0... 000 00020 £05393 2.0600000... .000 60:00 .0 €063.02... .0. 000.. 05 .0 «00:00.0 50600000... .000 .3000 05500000 8.0... 0. 0.... 0.003 00> 0.006600 .0002000 >00 0.6: 30> ._ 2.2.3.0 .0028 50> 0.5.3 0.0.. 00> 02.600 .23 00.305. 0.082000 0.003 0.5 ...0..0S.0=00:0 0.... 05.0.0500 .0. 00> x005 _ .. 02.0.0 0:0 _ $2.8. 3...... .02... 50.. ._ :58 .2... 0.5.? 3.0 23508 ~ 3.2. 0 23¢: . ...BEZ 30.09.... 22.0. 20.5.... .85. 50> 5...... 3523.5. 3 .8£§;0.8 .0 .283... .28... .... .85.... ..B 0:30.... .... .o 5...; 5.0 80... . .80 n .8... 2....» 550:0 . 8.0 . .8. a 08.0. . .8. c 80. . o . 38.5.. 10.520... 0.2.0. 2.3.0 .020. 50> 5 2.5.8.... .502. 002.30. 2. 3:82.... .... .00.... 0532.0. .... .o 5...; 8.0 n v n ... . 82.2.5505 .... ... v o 0 . 8. .... .v n v a u . 9.. . : .n ... c a m . o. . 0 .... n v n ... . ... .0 .. 3.. In a: I. 0.9 0.00381 — 08533.85 _ 7.000 .0. 02.0000. 0.0.0.2000 0.0.5. £6.00 00.... 000090.00 000 0... .0 5000 5.5.3 .... .2. 8.082.. .... 0.8.0:. 0...... 02...... 52. c. .0533 .09.». 2. ... 0:08.230 3.0 D 6005.03... 39.3.00: 0020:. .0... 00 ...00 c. .0060... .0.:w. «5:56 50> c. 00.30. 0.0 000.33 .0200 >006 .501 3:0 .00..0...0.00.0..0 .0320 .00000 .20000 500000 002.0000 050.050.. 0.... g 0N LIST OF REFERENCES LIST OF REFERENCES Barrows, E.M., J.S. DeFiIippo and M. Tavallall. 1983. Urban community gardener knowledge of arthropods in vegetable gardens in Washington, D.C. pp. 107-126. In: Urban entomology: interdisciplinary perspectives (G.W. Frankie and 0.8. Koehler, eds.), Academic Press, New York. Bennett, G.W., E.S. Runstrom and FA. Wieland. 1983. Pesticide use in homes. Bull. Entomol. Soc. Am. 29:31 -38. Berry, D.A. and SW. Lindgren. 1990. Statistics: theory and methods. Brooks/Cole Publishing Company, California. Bird, G.W., T. Edens, F. Drummond and E. Groden. 1990. Design of pest management systems for sustainable agriculture. pp. 55-110. In: Sustainable agriculture ' in temperate zones (Francis, Flora and King, eds.), John Wiley 8 Sones, New York. Bottrell, DR. 1979. Integrated Pest'Management. Council on Environmental Quality. U.S. Government Printing Office, Washington, D.C. Byme, D.N., E.H. Carpenter, E.M. T horns, and S.T. Cotty. 1984. Public attitudes toward urban arthropods. Bull. Entomol. Soc. Am. 30:40-44. Center for the Integration of Applied Sciences. 1981. A resource notebook on the human health hazards of pesticides. Prepared for The Office of Parks and Open Space Management, City of Palo Alto, California. Conover, W.J. 1980. Practical nonparametric statistics. 2ed. Wiley 8. Sons, New York. Council on Environmental Quality. 1980. Public opinion on environmental issues. Resources for the Future and Council on Environmental Quality, Superintendent of Documents, U.S. Government Printing Office. Dillman, D.A. 1978. Mail and telephone surveys, the total design method. John Wiley & Sons, Ltd., New York. Environmental Defense Fund and FLH. Boyle. 1979. Malignant neglect. New York, Vintage Books. Fear, F.A., G.A. Simmons, M.T. Lambur and 8.0. Parks. 1983. A comunity development approach to IPM: Anatomy of a pilot effort to transfer IPM information on outdoor vegetation to suburban homeowners. pp. 127-150. In: Urban entomology: interdisciplinary perspectives (G.W. Frankie and CS. Koehler, eds.), Academic Press, New York. 185 186 Finklea, J.F., J.E., Keil, S.H. Sandifer, and RH Gadsden. 1969. Pesticides and pesticide hazards in urban households. J.S.C. Med. Assoc. 65:31-33. Flint, ML. and R. van den Bosch. 1981. Introduction to integrated pest management. Plenum Press, New York. Frankie, G.W. and H. Levenson. 1978. Insect problems and insecticide use: public opinion, information, and behavior. pp. 359-99. In: Perspectives in Urban Entomology (G.W. Frankie and CS. Koehler, eds.), Academic Press, New York. Frankie, G.W., T.A. Granovsky, and C. Magowan. 1981 a. A study of attitudes and practices of pest control operators towards pests and pesticides in selected urban areas of California, Texas, and New Jersey. pp. 9-32. In: Proc. Urban Integrated Pest Mgt. Workshop. Nat'l Coop. Exten., Dallas, Texas. Frankie, G.W., RM. Mandel, H. Levenson, and T.A. Granovsky. 1981b. A survey of the arthropod pests and measures to control them in three U.S. metropolitan areas. pp. 33-67. In: Proc. Urban Integrated Pest Mgt. Workshop. Nat'l Coop. Exten., Dallas, Texas. Heberlein, T.A. and IR. Baumgartner. 1978. Factors affecting response rates to mailed questionnaires: a quantitative analysis of the published literature. American Sociological Review 43:447-462. Kretch, D., RS. Crutchfleld, and EL. Ballachey. 1962. Individual and Society. McGraw-Hill, New York. Lambur, M.T., G.A. Simmons, F.A. Fear, and 8.0. Parks. 1981. Project PEST: a pilot effort to transfer IPM information to urban homeowners. pp. 92-103. In: Proc. Urban Integrated Pest Mgt. Workshop. Nat'l Coop. Exten., Dallas, Texas. Lande, 8.8. 1975. Public attitude toward pesticides. Public Health Rep. 90:25-28. Larsen, K., J. Mena, D. Miller, S. Ozminski, L. Shem and Y. Suhaya. 1987. An urban integrated pest management program for use in Michigan schools. Prepared as partial fulfillment of requirements for Michigan State University course NS447. Levenson, H., and G.W. Frankie. 1981. Pest control in the urban environment. pp. 251 -72. In: Progress in Resource Management and Environmental Planning (T .O. Riodan and R.K. Turner, eds.), Wiley, England. Levenson, H. and G.W. Frankie. 1983. A study of homeowner attitudes and practices toward arthropod pests and pesticides in three U.S. metropolitan areas. pp. 67- 106. In: Urban entomology: interdisciplinary perspectives. (G.W. Frankie and CS. Koehler, eds.), Praeger Publishers, New York. Michigan Department of Agriculture Pesticide Subcommittee. December 1985. A strategy for improved pesticide management in Michigan. A report to the Governor's Cabinet Council on Environmental Protection. Michigan Education Directory. 1988. 1988 edition Michigan education directory and buyer’s guide. Michigan Education Directory, 925 East Kalamazoo Street, Lansing, MI. 187 Michigan State Board of Education. 1985. Analysis of Michigan public school revenues and expenditures 1984-85. Bulletin 1011. Michigan State Board of Education. 1985. Michigan K-12 school districts ranked by selected financial data 1984-85. Bulletin 1014. National Academy of Science. 1980. Urban Pest Management. A report of the committee on urban pest management. National Research Council. National Academy Press, Washington, D.C. National Pest Control Association. 1982. The public appraises the pest control industry. Pest Management 1:8-12. Olkowski, H. 1980. What is IPM? IPM Practitioner 2(5):3-4. Olkwoski, H., W. Olkowski, K. Davis, and L. Laub. 1978. Developing an integrated pest management program for a school district. Presentation at the XII Annual Conference of the Association of Applied Insect Ecologiests, February 2 and 3, 1978, Newport Beach, CA. Olkowski, H., T. Stewart, W. Olkowski, and S. Daar. 1982. Designing and implementing integrated pest management programs for cities. pp. 149-155. In: Urban and suburban trees: pest problems, needs, prospects, and solutions. Proc. of a conference held at MSU, April 18-20, 1982, Departments of Entomology, Resource Development, and Forestry. Robinson, W.H. and R.L Atkins. 1983. Attitudes and knowledge of urban homeowners towards mosquitoes. Mosquito News 43(1):38-41. Savage, E.P., T.J. Keefe and H.W. Wheeler. 1979. National household pesticide usage study, 1976-1977. Colorado State University. Final report for E.P.A. Thorpe, K. 1988. The dangers of pesticides in schools. PTA Today. February issue, pp 24-25. von Rumker, R., RM. Matter, D.P. Clement, and F.K. Erickson. 1972. The use of pesticides in suburban homes and gardens and their impact on the aquatic environment. Office of Water Programs, U.S. E.P.A., Washington, D.C. U.S. Government Printing Office. von Rumker, R., E. W. Lawless and A.F. Meiners. 1975. Production, distribution, use and environmental impact potential of selected pesticides. Final report by Midwest Res. Inst. for Council on Environmental Quality and Environmental Protection Agency. Wood, F.E., W.H. Robinson, S.K. Kraft and P.A. Zungoli. 1981. Survey of attitudes and knowledge of public housing residents toward cockroaches. Bull. Entomol. Soc. Am. 27(1):9-13.