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A. .37.]..171 5:13:50; p‘. 1.. 4.110 v. 3'2 . ... . 2. .1 . . .. .V11.1.I I. .11 |£1-r| ‘ I. :2... ....‘3(.:(. . .?.n1-l D 1‘! 33.11. 1 fiEEQEEFE .\,. av A:l!.‘[9r|f1.rl.¢lllv . . :11. . .F u 1 . . . .. . 1 ' 1 'I‘ I. I l 1' n, l ' Ill >K'|I’|I.Ilb .|"' .~I" 111111;;1. l \ 111111111111111111111 L This is to certify that the dissertation entitled Absenteeism in Elementary School Students: A Family Ecosystems Model presented by Cynthia A. Cameron has been accepted towards fulfillment of the requirements for Ph.D. degree in Family Ecology ‘1 Wofessor Date M293.— MSU i: an Affirmative Action/Equal Opportunity Institution 0-12771 .. c can State Univ. PLACE IN RETURN BOX to remove this checkout from your record. To AVOID FINES return on or before date due. DATE DUE DATE DUE DATE DUE JUN I 3 I995. fl msu In An Affirmative ActiorVEqua! Opportunity lnmitmim fl emu-1131.1 -\ _ .-—.1 ABSENTEEISM IN ELEMENTARY SCHOOL STUDENTS: A FAMILY ECOSYSTEMS MODEL BY Cynthia A. Cameron A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Family and Child Ecology 1993 ABSTRACT ABSENTEEISM IN ELEMENTARY SCHOOL STUDENTS: A FAMILY ECOSYSTEMS MODEL BY Cynthia A. Cameron Elementary children who do not attend school regularly are at risk for school failure. For some children absen- teeism.may be a temporary problem, while for others, it is the beginning of an ongoing problem. It is important to be able to target children for intervention who are most likely to become persistent absentees. The objectives of this research were (1) to determine how many children identified as absentees in first through third grades had continuing attendance problems, and (2) to use an ecologi- cal model to identify predictors of persistent absentee- ism. Data were collected from 34 children with attendance problems, their parents and teachers, in two communities over a four year period. Slightly more than half of the absentees had poor school attendance in at least three of the four years. Multiple regression analysis was used to identify predictors of continuing attendance problems. Variables in the final regression model included the community in which the child lived, mother's level of education, living in a single parent family, living in a family with a chronically ill member, and shy, withdrawn behavior in the classroom. Variables not significantly related to school attendance were parent's attitude toward education and parent's educational goal for the child, academic success, peer relationships, classroom behavior, and child health. Interventions to help young absentees become more successful in school are dicussed within an ecological framework. Suggestions include influencing sub-culture values, enforcing compulsory education laws, improving home-school relations, providing support for families experiencing chronic stress, and teaching coping skills to shy, withdrawn students. ACKNOWLEDGMENTS I would like to thank the following people who contributed to this effort: Debbie Marciniak, whose friendship made it easier for me to continue when things were difficult. Arnie Greenfield, whose reassurance that this was indeed a hellacious task, and whose assistance on statistics were most welcome. All of my friends and colleagues who provided me with support and encouragement. Those at the Michigan Department of Mental Health and at local Community Mental Health Boards who were involved in the funding and implementation of this research. My committee members who reviewed and critiqued this dissertation with special thanks my major professor, Robert Griffore, Ph.D., who read every word. iv TABLE OF CONTENTS LiSt Of Tables 0 O O O O O O O O O O O 0 List of Figures . . . . . . . . . . . . I. II. INTRODUCT I ON C O O O O O O O O O 0 Purpose of the Study . . . . . . . Statement of the Problem and Research Questions . . . . . . Conceptual Model for the Investigation The Theories of Kurt Lewin . . Ecological Systems Theory . . Family Ecology Theory . . . . Ecological Influences on School Attendance . . . . . Theoretical Assumptions . . . . . The Empirical Model . . . . . . . Propositions and Hypotheses . . . Significance and Generalizability LITERATURE REVIEW . . . . . . . . Historical Perspective . . . . . . Review of the Research . . . . . . Truancy as a Social Problem . School Phobia and Truancy as Clinical Issues . . . . . Ecological Model of Absenteeism ix 11 13 27 27 30 32 34 34 43 43 51 55 III. IV. METHODOLOGY . . . . . . Research Design . . . . Data Collection . . . . Instruments . . . . . . Conceptual and Operation Dependent Variable . Independent Variables The Study Population . . Attrition . . . . . The Communities . . The Families . . . . The Children . . . . Data Analysis . . . . . Definitions Assumptions of Regression Hypothesis Testing . Building the Model . RESULTS 0 O O O O O O O O Tests of the Hypotheses . Macrosystem Propositions . Family System Propositions Child Characteristics Summary of Stage One . . . Test of the Empirical Model Interpretation of the Model vi 91 92 93 94 96 97 97 103 103 104 104 106 109 110 113 113 115 115 116 116 120 124 .124 128 V. DISCUSSION 0 O I O O O O O O 0 Research Question #1 . . . . . . Research Question #2 . . . . . . H o o o o o 0 Proposition Proposition Proposition Proposition Proposition O\ 01 I5 u N o o o o o o Proposition Proposition 7 . . . . . . Research Question #3 . . . . . . Limitations . . . . . . . . . . Implications for Intervention . Macrosystem Interventions Exosystem Interventions . Mesosystem Interventions Microsystem Interventions Child Centered Interventions Suggestions for Future Research Macrosystem Research . . . Exosystem Research . . . . Mesosystem Research . . . Microsystem Research . . . Research on Child Characteristics Conclusion . . . . . . . . . . . vii 130 130 131 131 132 134 134 135 136 137 137 139 140 141 141 142 143 144 145 145 146 146 147 148 149 APPENDICES Appendix Appendix Appendix Appendix Appendix BIBLIOGRAPHY MUCH!» Letter to Parents . Consent Form . . . . Research Instruments UCRIHS Approval . . Permission to Reprint Copywrited Materials viii 151 152 153 165 166 168 Table 10 11 12 13 14 15 16 LIST OF TABLES Independent Variables Identified by Three Research Paradigms . Schedule of Data Collection . Items of the ACAD, BEHAVE, SOCIAL, ACT, LEARN and SHY Subscales . Data Sources, Instruments and Variables for the Study . Description of the Study Population Values for ACAD, BEHAVE, SOCIAL, ACT, LEARN Minimum, Maximum and Mean and SHY . . Values of Absences . . . Regression Regression Regression Regression Regression of ABSENCE on of ABSENCE on of ABSENCE on of ABSENCE on of ABSENCE on COMMUN CGED and PARATT GOAL INCOME STRESS, SINGLE and CHRONIC . . . . Regression of ABSENCE on ACAD, LEARN, SOCIAL, BEHAVE, ACT and Regression of ABSENCE on SELF, ACTLRN and SHY Hypothesis Test for Effects Of SELF and ACTLRN . . Regression of ABSENCE on ILL ix SHY 90 93 101 102 106 107 108 116 117 118 118 119 121 122 122 123 17 18 19 Regression Analysis of the Full Model . . . Regression Analysis of the Full Model with Influential Case Deleted . . . . . . . Regression Analysis of the Reduced Model . . 124 126 127 Figure LIST OF FIGURES Model of School Attendance Based on Theories of Kurt Lewin . . Conceptual Model of School Attendance Empirical Model for Investigation . The Social Problem Model of School Attendance . . . . . . . . The Clinical Model of School Attendance Empirical Model for Investigation . Scatterplot of Studentized Residuals Against Fitted Values of ABSENCE . Regression Model of School Attendance xi 26 29 A V’- 50 55 91 125 129 I . INTRODUCTION Succeeding in school is one of the major developmen- tal tasks of childhood in Western society (Sroufe and Rutter, 1984). School success makes it possible for a child to step away from dependence on the family and move toward independence and social maturity (Bloom, 1981; Waller & Eisenberg, 1980). In addition to learning aca- demics, successful students develop social competence, good work habits, motivation and the ability to function as competent citizens and productive workers in today's technological world (Bloom, 1981; Higgins & Mueller, 1988). Unfortunately, one in seven students fails to com- plete school (Schorr, 1988) and therefore fails to develop the skills needed to enter the job market and gain access to money income (Andrews, Bubolz & Paolucci, 1980). School dropouts are twice as likely as graduates to live in poverty, three and a half times as likely to be arrest- ed and seven and a half times as likely to be dependent on welfare (Schorr, 1988). Preventing school failure has become an important task in a society that values and supports school 2 achievement. Numerous programs have been designed to positively influence the life path of students exhibiting behaviors that put them at risk for school failure in an effort to increase their chances of succeeding in school (Lorian, Hightower, Work, Shockley & Clapp, 1983). A recent focus of dropout prevention programs is elementary school students. Prevention programs for children in the primary grades are being designed to provide prompt intervention before more serious problems develop (Cowen, 1982). These programs are based on the belief that it is easier to influence school performance of a young child just beginning to experience school problems than to redirect an adolescent with a history of negative school experiences. Absenteeism in elementary school is one factor that places children at risk for school failure. Regular school attendance is a necessary, but not sufficient condition for succeeding in school. In order for the student to engage in the flow of the learning process, he/she must attend consistently (Reynolds, 1991). Empiri- cal research findings indicate that early school attend- ance is related to achievement in the later elementary and middle school years and is a predictor of school dropout (Harrington & Hendricks, 1989; Easton & Engelhard, 1982; Marockie & Jones, 1987). If we are to attempt to remedy frequent absenteeism, we must understand the processes by which a child develops a pattern of absenteeism behavior. Longitudinal research that examines the development of attendance patterns over time is needed. Purpose _; the Study Proponents of prevention programs are adamant that the most effective prevention programs are those aimed at the youngest children. It is self-evident that dropout prevention programs aimed at students who have already stopped attending school are too late. It is not known, however, if prevention efforts with students who miss more than the average number of school days in early elementary school are viable. While school attendance in elementary school tends to be an indicator of future school problems, certainly not all children with excessive absences in the first few years of school become school dropouts. Retrospective studies on elementary attendance indicate that some ado- lescents who are persistent absentees first exhibited attendance problems in primary school (Reid, 1985). Harrington & Hendricks (1989) reported that dropouts could be distinguished from graduates with 60% accuracy by the third grade, based on school attendance. No research is available on the proportion of primary level absentees 4 that go on to become truants or dropouts in secondary school. While resources for all human service programs are scarce, in tight economic times resources for prevention programs become close to non-existent. The key to garner- ing more resources for prevention lies in positive cost- benefit analysis, where it can be stated that it takes fewer funds to prevent costly problems than to treat them. What is not known is if elementary school students with attendance problems become persistent absentees. It seems likely that for some elementary students, absenteeism may be a temporary problem, while for others it may be a symptom of the beginning of a long term negative school experience. The goal of this research is twofold: (1) to deter- mine what proportion of children identified as absentees in the early elementary years continue to have attendance problems, and (2) to determine if persistent absenteeism can be predicted by selected family, school and child characteristics. Information in this regard could allow schools to target those who are most likely to become persistent absentees for early prevention programs, and make best use of scarce resources. This study will examine attendance patterns of ele- mentary school children with high rates of absenteeism and 5 identify factors that predict continued absenteeism prob- lems over a three year period. The following research questions will be addressed: 1. Do elementary students identified as having poor school attendance in the early elementary grades continue to exhibit this behavior in subsequent years? 2. Can predictors of absenteeism be identified by examining selected characteristics of the commu- nity and family environments, and individual child characteristics? 3. Can an ecological model of absenteeism be de- veloped which aides in identifying students who may be in need of intervention for attendance problems? Conceptual Model for the Investigation The first step in building a model of school attend- ance is to employ a theory of child behavior that provides an explanation of the interaction between the child and the school. Kurt Lewin's theory of child behavior, with emphasis on the interaction between the developing child and the environment, is used here as the underpinning of the model. The Theories of Kurt Lewin Lewin (1935) proposed that a child's behavior is based on the interaction between the personal characteris- tics of the child and the child's environment (1935). He 6 formulated an equation to represent this relationship B =- f(PE) where B stands for behavior, P stands for the person and E stands for the child's environment. The equation signi- fies that behavior is a function of the interaction be- tween a person and the environment. Lewin further explained child behavior using the con- cept of valances. He theorized that objects, behaviors, goals or environments in a child's world have a negative or positive valance for the child. Positive valances encourage a child to approach a situation, and negative valances encourage withdrawal. Valances are based on a child's perception of the environment and come about through direct experience of the child. For example, a child's repeated failure at a task will lead to the development of a negative valance associated with the task and to withdrawal from the activ- ity. The school arena presents a child with many opportu- nities to succeed or fail. A child may fail academically, behave inappropriately in the classroom, or find it diffi— cult to establish relationships with peers. Each time a child attends school the child may succeed or fail in any of these domains. If the child perceives success, then the child's attendance at school will be reinforced. If the child perceives failure, the child's motivation to attend school will diminish. 7 Valances also can be induced through force fields, or other environments. A child is not only aware of his own perception of an event, but also is sensitive to the perceptions of others. The perceptions of others act as a force field and influence the child's perception. If a parent perceives the school as having a negative valance, the child may share this perception. The ability of a child's environment to induce a va- lance changes as the child develops. In a very young child, boundaries between the child and the environment are blurred and the environment has its greatest influ- ence. As a child matures and gains direct experience with the environment, the concept of self solidifies, and the strength of the environment to induce a valance lessens. In the case of school attendance, the child's perceived valance of the school is likely to be induced from the parent's perception of the school at school entry. As the child attends school, direct experience will be a stronger force in determining the perception of the school. As a child reaches adolescence, peers become a greater influ- ence on the child relative to the family (Cooper, 1986; Pennebaker, Hendler, Deurette & Richards, 1981; Thornberg, Hoffman & Remeika, 1991). It is the composite of a child's direct interaction with the school and his/her interaction with influential others that determines the 8 valance, or driving force, that motivates school attendance. Behavior is not just a result of the driving force, or valance of a situation, however. Restraining forces also play a role in school attendance (Lewin, 1935). A restraining force acts as a barrier to a child's actions. A barrier can keep a child from approaching a positive valance or withdrawing from a negative one. In the case of school attendance, school may have a positive valance for a child, but a parent might act as a restraining force if a child is needed at home to help care for younger children. Conversely, a child who views school as having a negative valance and wants to stay home may have a parent who acts as a barrier to this behavior, when the parent repeatedly takes the child to school (Mitchell & Shepherd, 1980). In summary, a child's motivation to attend school will be the result of the perceived valance of the school, which is acquired through transactions between the child and the school environment, or induced by the influence of others. The child's level of motivation will be tempered by any restraining forces. This is represented by the model in Figure 1. 9 Barriers Family School Perception "// \ Child Child's :7 School Perception Attendance . Figure 1 Model 9; School Attendance Based 93 Theories 9: Kurt Lewin Lewin states that in order to analyze the influence of environmental factors on behavior, the total situation must be considered. Ecological systems theory provides a framework for exploring the complexities of environmental influence on school attendance. Ecological Systems Theory Ecological systems theory builds on Lewin's theory of behavior. It dictates that development is the result of the characteristics of the child, the characteristics of the environment and the interaction between the two. Urie Bronfenbrenner (1979, 1989) has been a major contributor to ecological systems theory. He developed a paradigm that defines hierarchical levels of environments that influence development. The microsystem is the environment where a child's activities, roles and relations take place. The microsystem contains specific physical and 10 material characteristics and other persons with their own temperament, personality and beliefs. The mesosystem is described as the interrelationships between the microsys- tems; it is a system of microsystems. The exosystem consists of a setting in which the child does not have interactions, but other components of the microsystems interact. The macrosystem consists of the characteristics of a culture or sub-culture including belief systems, resources, opportunities and life course options (Bronfenbrenner, 1979, 1989). In addition to these hierarchical levels of systems, Bronfenbrenner included the dimension of time in the model, which he named the chronosystem. The chronosystem is defined by the time in which we live and its impact on the developing child and the environment. Taken together, the micro-, meso-, exo- and macrosys- tems make up the environments in which a child lives. The chronosystem overlays all other systems and the developing child. While this model focuses on the many environmental influences on the child, Bronfenbrenner (1989) emphasizes that development is dependent upon the child's individual characteristics. Bronfenbrenner uses the term developmen- tally-instigative to describe characteristics of the child that are particularly significant to development; charac- teristics which influence the way in which the child 11 approaches the environment and the way in which the envi- ronment responds to the child. The transactions between the environment and the individual child determine devel- opment (Bronfenbrenner, 1979). Bronfenbrenner's work in ecological systems theory is of major importance in presenting a model of the complex- ities of the transactions between child and environment over time. What the model does not convey is the process by which these systems influence development. Family ecology theory provides a framework for looking at the processes within systems that influence school attendance. Family Ecology Theory While Lewin's theory predicts that the environment influences behavior, and Bronfenbrenner identifies levels of environments that influence development, family ecology theory "integrates human development and family relation- ships within a family resource management framework" (Bubolz & Sontag, in press). The theory focuses on the interdependence among systems, including the natural environment (Bubolz, Eicher & Sontag, 1979) and processes that occur within and among these systems. There are four categories of system characteristics described by family ecology theory that influence school attendance: openness of the system, system goals, resources available to the system and interaction between system members. 12 Family systems have boundaries which delineate the family and its members from other systems (Broderick & Smith, 1971). These boundaries are permeable to allow for interaction between systems. All family systems are semi- open and interact with other systems. The degree to which a family expends energy on boundary maintenance, or ex- cludes interaction with other systems is based on previous experience and information about that system. Interaction between a family system and a system viewed as harmful or antagonistic will be discouraged while interactions with a system perceived as beneficial will be encouraged (Kantor and Lehr, 1975). Family systems are goal directed (Bubolz & Sontag, in press). The family system interacts with other systems and the environment to attain family goals. Family eco- systems theory proposes that the transactions between the family and any other system is related to the degree to which the other system can assist the family in meeting its goals. A family system uses both physical and psychic re- sources to survive and maintain system stability. In order for a family to move beyond system.maintenance toward other goals, additional energy is required. A family with only enough resources to maintain the family system will have difficulty meeting other goals. 13 The physical resource base of a system is critical to system functioning. A.minimal level of physical resources such as food clothing and shelter is needed for survival. Family systems require a minimal level of psychic resources to maintain stability. Psychic resources can be depleted if the family is in a state of entropy, experi- encing high levels of stress and instability. Ecological Influences on School Attendance By using the concepts from Lewin, Bronfenbrenner and family ecology theory, it is possible to build a conceptu- al model of school attendance that provides an explanation of how system characteristics influence attendance. Chronosystem Influence 9n Sghggl_gtt§gdange The level of technology in a society influences school attendance. In an agricultural society, children are needed at home to help with the farm work during the growing season. The nine month school year with summers off results from our agricultural roots and takes into account seasonal attendance patterns. As a society he- comes more technological, fewer families are engaged in farming and fewer family members are needed to run the farm. Children are needed less at home and can attend school with more regularity. Movement from an agricultural to an industrial to a post-industrial society requires more complex skills and 14 more education to attain economic survival. Regular school attendance for an increased number of years has become the norm to gain access to the job market. The availability of preventive medicine and access to medical care is another factor in school attendance. In the late 19th century, children were often absent for extended periods of time with diseases such as small pox and diphtheria (Ellis, 1973; Pallister, 1969). The devel- opment of vaccines to prevent such diseases and the re- quirement that all children must be vaccinated prior to school enrollment has led to an overall increase in school attendance. Weather is an element of the natural environment that affects school attendance. Extreme weather conditions may act as a barrier to school attendance, especially if a family is lacking in physical resources. Children who must walk to school will be less likely to attend if it is storming and they don't have appropriated apparel to wear (Ellis, 1973; M. Moreland, personal communication, October 1989). Macrosystem.Influence 9; School Attendance The parameters for school attendance are set by the values of the dominant culture. In the United States, the high value placed on equal opportunity for all persons has 15 greatly influenced school attendance policies. The dominant culture views education as an equalizing agent among all social classes and as the key to equal opportu- nity. Every child has a right to an education that will provide the skill level necessary to become a successful member of society. Education is viewed not just as a right, but as a duty. When children don't attend school, they are viewed as self-destructive and deviant because they are not preparing themselves for a productive future (Kahn, Nursten & Carroll, 1981) and their parents are viewed as negligent. The belief by the dominant group that education is an entitlement gag a duty has led to the development of public policy which supports a free compulsory education system, with legal consequences for non-attendance. Parents who do not ensure that their children are in school can be fined or imprisoned. Sub-cultures may value school attendance more or less than the dominant culture. American society is culturally diverse and consists of numerous sub-cultures based on race, religion, national origin, social class, geographic location and rural/urban status. Asian and Jewish fami- lies have traditionally placed a high value on educational success (Schorr, 1988). Minority sub-cultures which have had negative experiences with the educational system and 16 have been unable to reap the economic benefits of higher education because of racial or ethnic prejudice may place less importance on school attendance. At times local community practices cut across all sub-cultures. In Michigan's Upper Peninsula schools all but shut down during the first week of deer hunting sea— son. It is an accepted community norm that students who are old enough to hunt will not attend school during this time (K. Frazier & D. Woody, personal communication, August 1990). Exosystem.Influence 9p School Attggggngg Compulsory education laws vary by state, and each school district sets its own standards for enforcing the state compulsory law. In many communities, courts will not prosecute for educational neglect unless a child never attends school. Legal action for irregular attendance may be viable where there is a cooPerative relationship be- tween schools and courts and each has the resources neces- sary to prosecute (D. Nover, personal communication, October 1992). In communities where compulsory attendance laws are strictly enforced, parents may make a more effec- tive effort to ensure that their children are attending school regularly. Inconsistent enforcement of compulsory attendance laws may make a difference in the degree to which parents comply to the law across communities (Levine, 1984). 17 Mesosystem Influence 9p School Attendance Bronfenbrenner (1979) suggests that the interaction or linkage between systems is as important as what happens within the system on influencing development. The inter- face, or point of interaction, enables information to flow between systems. This interaction is related to the performance of a component that is a part of both systems. This linkage can be supportive and influence performance positively, or non-supportive and influence performance negatively. Until school entry, a child functions as a part of one microsystem, the family. Upon reaching school age, the child goes through an ecological transition, where the settings in which s/he is involved change to include school. It is at this time that the mesosystem becomes important to the child's development, as the interaction between the two settings of family and school effects the child's performance in the new role of student. In general, a greater number of transactions between school and family are viewed as a more favorable influence on school performance than fewer transactions. However, it is not just the quantity of the transactions, but also the quality, that is important to a child's success in school. The way in which parents and school personnel transact must be complementary (Garbarino & Asp, 1981; Wissbrun & Eckart, 1992). Either lack of trust, or lack 18 of congruent values in the home-school mesosystem can contribute to negative transactions. Trust facilitates transactions and functioning be- tween systems, while lack of trust impedes them (Andrews, Bubolz & Paolucci, 1980). Families who fear that teachers are prying into their home life to learn family secrets will develop less permeable boundaries (Powell & Bartholo- mew, 1987). Schools also may discourage interaction between home and school. Teachers may fear that parents will question their methods. Rigid boundaries make it is easier for teachers to blame a child's trouble at school on the family rather than the school (Powell & Bartholo- mew, 1987). Garbarino & Asp (1981, p. 68) use the term academic culture to describe the attitudes, values and behavior related to school success. If the academic culture is continuous across home and school environments, the home- school mesosystem will have a positive influence on a child's school performance. If the academic culture across the two systems is discontinuous, the child will find it difficult to succeed in school. Microsystem Influence 9n School Attendance The microsystems of which the child is a component will influence a child's motivation to attend school, and also can act as a barrier to school attendance. The 19 microsystems most likely to affect school attendance of elementary students are the family and the school. Each will either facilitate or impede school attendance. Family Influence Families manage the interaction of individual members with other systems (Hook & Paolucci, 1970), and are thought to be the most influential microsystem on young children's school attendance (Garbarino & Asp, 1981). Families who value education will expend energy to encourage school attendance, while families who place little value on education are unlikely to assign resources to make sure a child attends school regularly. Barrington & Hendricks (1989) hypothesized that the high accuracy with which elementary school attendance records could be used to identify high school dropouts is due to the par- ents' lack of interest in the child's school success. Parents who allow a young child to miss school in the early years are likely to be agreeable when the child decides to leave school. The degree to which family members view interaction with the school as a positive or negative experience will influence the level of openness toward the school. Par- ents who enjoyed their own school experience tend to be more supportive of a child's school attendance than par— ents who remember their own schooling as a negative experience. Parents who felt rejected by their schools 20 will fear failure for their children (Wood, 1989). Chil- dren of parents who withdrew from school prior to high school completion are more likely to have poor attendance records than children of high school graduates. The lack of either physical or psychic resources in a family can act as a barrier to school attendance. Poor nutrition, chronic or acute trauma, or lack of supportive interactions will keep a child from participating fully in the educational system (Andrews, Bubolz & Paolucci, 1980). A child who is often absent may have parents who are overburdened and need material or social support (Barth, 1984). A child living in a family struggling to meet minimal physical needs due to temporary or chronic poverty will have worse attendance than a child living in a family with a higher income that can easily meet physical needs. Absenteeism may be a result of lack of appropriate cloth- ing or transportation to school. When families cannot purchase needed services due-to lack of income, children may be required to stay home from school to care for younger siblings (Barth, 1984) or an ill family member. Poor nutrition and the inability to access medical care make a child more susceptible to absences due to illness. Some illnesses that are minor when treated early with antibiotics, such are ear infections, are much more seri- ous and can lead to chronic ill health in children who 21 don't have access to medical care. These children tend to have repeated episodes of absenteeism throughout the school year (K. Frazier, personal communication, February 1991). Stress can be a result of events outside the family or from within the family system (Andrews, Bubolz & Pao- lucci, 1980). Neighborhood violence and an unstable economy may cause stress. Stressors within the family include events resulting from family movement through the life cycle, such as a child starting school, or instabil- ity, such as transience. High stress levels deplete psychic resources. Single parent families have fewer psychic resources available to them than two parent families, as they lack the support of another adult in the home. There are indications that single mothers experience higher stress levels than married mothers and have lower levels of psychological well-being (McLanahan & Booth, 1989). Children of single parents, or whose parents are separat- ed, are absent from school more than children from two parent families (Hetherington, Camara & Featherman, 1983; Reid, 1984). Families who experience chronic stressors may lack both physical and psychic resources. Chronic mental or physical illness of a family member is one such condition. Physical resources may be depleted because of continuing 22 medical expenses. Psychic resources will be depleted due to the stress of caring for the member and continued worry over the member's well-being. Lack of supportive interaction between parent and child may influence school attendance. Attending school is often the first time a child must depend on his or her own resources to be successful (Hersov, 1977). Children whose parents encourage dependence rather than independ- ence may find the school experience to be frightening and wish to stay home from school. At the same time, parents who enjoy their children's dependency may subconsciously encourage them to stay home from school (Little & Thompson, 1983). School Influence School systems are similar to family systems in structure and function. Both are open systems whose interactions are influenced by system values. A primary function of both systems is to socialize children (Carlson, 1992). The characteristics of the school system that are likely to influence attendance are congruent with those of the family system: openness of the system, goals for attendance, available resources and supportive inter- action. The openness of the school system will affect trans- actions between the family and the school. Schools that 23 make an effort to communicate with parents in a supportive manner may encourage parental involvement in the schools which may result in improved attendance for children (Sattes, 1984). The degree to which good attendance is prioritized as a system goal will influence attendance. In some elemen- tary schools, attendance records are kept by teachers only, with no effort made to methodically track attend- ance. Schools may call the home of a child who is absent, parents may be required to call the school when a child is absent, or a written excuse upon the child's return may be all that is needed. Schools may have strict attendance policies that are enforced, or there may be no policy in effect. Even schools with high standards for attendance may not have the resources to enforce them. Schools in which there is no in-school suspension room may use out of school suspension for severe behavior problems. School counselors and attendance officers may not be available to work with students and their families when there is an attendance problem. The way in which teachers interact with children is influenced by their perception of the child's ability to function within the school setting. They base their opinions on direct interaction with the child, previous experience with other members of the child's family 24 system, and other teachers' perceptions of the child (Paterson, 1989). Teachers interact more positively with children whom they perceive to be intellectually capable, physically attractive, socially competent with peers, and well-behaved in the classroom. A teacher's negative perception of a child can act as a barrier to a child's school attendance. Teachers who find a child to be disruptive in class may not want the child to attend school (Barth, 1984). They may thwart efforts to motivate a child to attend, and send them home, or suspend them at the slightest provocation (W. Schine, personal communication, January 1990; A. Rodesiler, per- sonal communication, October 10, 1992). Child Characteristics Even though there are multiple levels of environ- mental variables that influence behavior, school attend- ance cannot be explained by environmental characteristics alone. A child's characteristics will determine how he/she reacts to the school environment. Children who have difficulty learning, behaving in the classroom or making friends are likely to perceive themselves as failures at school. A child who experiences failure in one or more of these modes will be more likely to perceive going to school as a negative event than a child who is successful within the school environment. For a child who experiences repeated failure at school, 25 being absent from school may bring about a feeling of relief (Reid, 1982). The interaction between the school as a system and the child as a member of the system will result in the child developing a positive or negative perception of the school. This interaction takes place every time the child attends school. If the child perceives the interaction as positive, school attendance will be reinforced; if the child perceives the interaction as negative, motivation to attend school will diminish. No matter how motivated a child is to attend school, illness may act as a barrier to school attendance. Ill- ness is the reason given most often for school absence (Galloway, 1976). The conceptual model of school attendance described above is presented in Figure 1.2. While all variables are thought to be influential at all ages, the relative impor- tance of the variables will differ between young children and adolescents. For elementary school students, family variables are thought to be more influential, while child characteristics and school variables are likely to gain importance as a child progresses through the school system. 26 Chrono- Barriers system Natural weather Environment Macrosystem Dominant Sub-culture culture values values 1 Exosystem Enforcement of Compulsory Education laws ROOM 1 . Mesosystem School 4—» Family Microsystem goals goals poverty openness openness stress resources parent-child interaction interaction \M/ school behavior academic success health social relationships 1 child's motivation J_ School to attend school Attendance I'<<'1’(Dl--‘-OO£0 PUP-Hflmfinafll-i Figure 2 Conceptual Model 9: School Attendance 27 Theoretical Assumptions Assumptions from Lewin (1935) Interactions between the person and the environment influ- ence behavior. It is the person's perception that is important. Perception an of event/object/behavior/goal/environment as negative or positive motivates behavior. Perception results from direct experience with an event/object. Perception is a result of the influence of others. Motivation for behavior is tempered by barriers. Assumptions from Bronfenbrenner (1979; 1989) Development is a function of the characteristics of the person, characteristics of the environment and the inter- action between the two. Development takes place over time. Interaction between environments influences development. There are hierarchical levels of environments. Systems are embedded in their environments. Perception is what is important. Family is a major influence on development. Assumptions from Bubolz & Sontag (in press) Systems are interdependent with the natural environment. Families need resources to survive. Energy and resources are both physical and psychic. Families are goal-oriented and purposive. 28 Families base interactions with other systems on past experiences. 1 Systems are real and can be observed. Social system characteristics are analogous to real system characteristics. Human systems are open systems. Education is inherently good. Assumptions of this study School attendance is a necessary but not sufficient condi- tion to successfully participating in the educational system. Egg Empirical Mpggl Because data used in this study were collected as part of a larger study, data were not available on all variables included in the conceptual model. For this reason, the empirical model to be tested is less compre- hensive than the conceptual model. Specifically, school level variables and data on the child's motivation to attend school are not available. Figure 3 depicts the empirical model for this research. 29 Chrono- Barriers system P o s Macrosystem Community t values I 1 n Microsystem Family d goals poverty u openness stress 3 t 1 r Child i academic success health a school behavior 1 social relationships ——~““~->.School Attendance S o c i e t Y Figure 3 Empirical Model for Investigation 30 Propositions and Hypotheses The propositions and hypotheses listed below are statements of the relationships represented in the empiri- cal model (Figure 3). Proposition 1 The value that the community places on education will influence the school attendance of young children. HYP 1.1: There is a negative relationship between the value a community places on education and the number of days a child is absent from school. Proposition 2 Parents' attitudes toward the school will influence the children's attendance at school. HYP 2.1: There is a negative relationship between parents' attitudes toward education and the number of days a child is absent from school. HYP 2.2: There is a negative relationship between the number of years of school completed by the mother and the number of days a child is absent from school. Proposition 3 The degree to which a family values education has an influence on the school attendance of young children. 31 HYP 3.1: There is a negative relationship between the number of years of school the parent wants a child to complete and the number of days a child is absent from school. Proposition 4 The lack of physical resources in a family will act as a barrier to a child's school attendance. HYP 4.1: There is a negative relationship between level of family income and the number of days a child is absent from school. Proposition 5 The presence of stress in a family will act as a barrier to a child's school attendance. HYP 5.1: There is a positive relationship between the number of stressors experienced by a family and the number of days a child is absent from school. HYP 5.2: A child living in a single parent family will be absent from school more days than a child living in a two parent family. HYP 5.3: A child who lives in a family with a chronically ill member will miss significantly more days of school than a child who does not live in a family with a chronically ill member. 32 Proposition 6 A child's school performance influences school attendance. HYP 6.1: There is a negative relationship between a child's academic achievement and number of days absent. HYP 6.2: There is a negative relationship between a child's appropriate school behavior and number of days absent. HYP 6.3: There is a negative relationship between a child's social competence and number of days absent. Proposition 7 School attendance is influenced by child health. HYP 7.1: There is a positive relationship between the number of times a child is ill and number of days absent. Significance and Generalizability Absenteeism is one of the major problems facing our schools today (O'Bryan-Garland & Moore, 1987). At this time, little data are available on school attendance and the development of persistent absenteeism. This study will provide much needed empirical evidence which can be used to develop effective absenteeism prevention programs. The findings of this study will be generalizable to first 33 through third grade students who have experienced exces- sive absenteeism. Research findings will not be general— izable to urban students. II. LITERATURE REVIEW Historical Perspective In order to place the present day issues of school absenteeism in perspective, a cursory understanding of the development of compulsory schooling in this country is necessary. Knowledge of this process is important for understanding how compulsory school attendance became a societal norm and how societal values have influenced the study of school attendance over time. The beginnings of compulsory education are rooted in the Protestant Reformation (Rothbard, 1974, Ensign, 1921). Martin Luther and John Calvin both supported compulsory education as a means of suppressing dissent, encouraging obedience and educating the masses in the new Protestant religions. Luther likened compulsory education to mili- tary conscription. If citizens could be forced to bear arms in times of war, then certainly the state had the right to force parents to educate their children as a way of waging war against the devil (Rothbard, 1974). It was the Calvinist Puritans that brought the con- cept of compulsory education to America. The Puritan colony of Massachusetts Bay passed a compulsory literacy 34 35 law as early as 1642. The Puritans viewed the ability to read and study the Bible as necessary to their way of life. By 1647, the compulsory literacy law had been broadened to become a compulsory school law, and shortly thereafter many of the New England colonies followed suit. This early focus on public education was lost during the 1700's, as industrialization spread throughout America. Industrialists, politicians and families began to envision immediate monetary gains from the labor of young children. Industrialists hired children to perform menial repetitive tasks at very low wages which allowed them to lower production costs and increase profits. Politicians encouraged child labor as a way to increase the income of poor families and make them less of a burden on society. Working class parents needed their children's wages to subsist. Due to the immediate economic benefits of child labor, adherence to compulsory education laws was, for the most part, abandoned during this time. By the early to mid 1800's, the focus on education had resurfaced. Public education was seen as an effective equalizing agent for children from different social class- es and was espoused as a right of all children by social reformers, charity workers, teachers, clergy and unions (Thomas & Wilcox, 1987). In the northern states compulso- ry education was viewed as a way to Americanize immigrants (Rothbard, 1974), in the southern states as a way to 36 civilize blacks (Cooper, 1890), and in the cities as a way to socialize children of poor working class parents (Abbott & Breckenridge, 1917). It was hoped that the school experience would compensate for the "poor family environment" of these children (Abbott & Breckenridge, 1917), and "make the outlook and prospects of the child from the bad home as good as those from the good home" (Musgrove, 1966, p.20). Once the right of all children to become educated had been established, it was necessary to find a way to fi- nance the education of the poor. Legislation to tax property owners to fund public schools was introduced in many state legislatures. After lengthy political battles, the opposition of wealthy landowners, who would bear the biggest portion of the cost, was overcome and free public education became available to all children. Just because public schools were established did not mean that children of the working class attended school. The process of changing the child's role from worker to student was a slow one. Economic circumstances were the biggest obstacle to educating these children. Often, parents were reluctant to have their children leave work because the wages of the children were necessary for the family's subsistence. Employers also discouraged school attendance. They were accustomed to having children work for low wages and sometimes threatened parents with 37 termination if they did not bring their children to work with them. Many times there was an agreement between parent and employer to keep the child out of school and on the job, as both felt the child's labor was necessary for survival (Ellis, 1973). When taxpayers determined that working class families were not taking advantage of the opportunity that free schools provided, they were irate. Compulsory attendance at school became a controversial political issue. Undergirding the whole movement for compulsory educa- tion was a new ideological position that parental rights to the custody and control of their children were subordi- nate to those of the state. Under common law, parents had a moral, but not a legal, duty to maintain, protect, and educate their children. In return, the parent had a right to the custody and control of the child's person and to the child's earnings. During the 1800's, state legisla- tures began to enact laws that made parenting, as defined by the standards of the community, a legal obligation. In most states, laws were passed to protect children from malnutrition, parental cruelty, poor housing, inadequate clothing, child labor, and illiteracy (West, 1974). Sentiments for and against compulsory education ran deep. Supporters portrayed parents of children who were not in school as neglecting "to protect their children from the wrongs and evils of illiteracy ” and as regarding. 38 their children "as money making machines" (Abbott & Breckenridge, 1917, 47, 61). Opponents argued that forc- ing parents to send their children to school was against natural law and would undermine parental authority and weaken family ties (Cooper, 1890). The passage of compulsory school legislation brought about an adversarial relationship between parents and the schools. The moral duty of parents to provide their children with an education was now a legal obligation, enforceable by law, and punishable with fines, imprison- ment, or the removal of the child from the parental home. This resulted in antagonizing parents who felt that they, not society, should be able to choose the kind and amount of education their children should receive. Even after the passage of compulsory school laws, many children attended school irregularly or not at all. Legislation specifying attendance requirements was passed in all states by 1917 (Abbott & Breckenridge, 1917). These laws made parents legally responsible for their children's school attendance in order "to insure, through regularity of attendance, proper returns for the public investment in free education (Abbott & Breckenridge, 1917, p. 43). The first compulsory attendance laws were weak and ineffective. Over time, they grew stronger and were more stringently enforced. While each state's compulsory laws 39 were idiosyncratic, their patterns of development and en- forcement were similar. In the state of Illinois, the first compulsory law was passed in 1883 and required attendance at school for 12 weeks of the year for children ages 8-14 years. Within a few years the number of weeks of attendance increased to 16, and attendance for 8 of the 16 weeks had to be consecutive. Over the course of twenty years, there were several iterations of the law which required more weeks of total attendance, more weeks of consecutive attendance, and finally, that children be required to attend the entire time that school was in session, which was not to be fewer than 110 days (Abbott & Breckenridge, 1917). At the same time compulsory attendance laws were becoming more stringent, so were laws prohibiting child labor. Conditions under which children were working in factories were atrocious, and there was real concern about their well-being. Children often worked twelve hour days, six days a week. Their health suffered from breathing in fibers in the textile mills, from lack of exercise, and from seldom seeing the light of day. There was a general fear that the next generation of citizens from whom public officials would be elected would be physically unhealthy and undereducated (Ensign, 1921). It took both the legal compulsion to attend school and the legal prohibition of child labor to establish 40 school attendance as a societal norm. Enforcement of attendance laws only became feasible after the passage of child labor laws. As long as jobs were available to children, and families were giving up money income when a child went to school, employment was often chosen over education. .At the same time, forcing children out of the factories and onto the streets was cause for concern. (Abbott & Breckenridge, 1917). While education was in- trinsically valued by some, in effect schools became holding tanks for children until they were old enough to work (Spring, 1974). Employers, parents and children did not voluntarily comply with these new laws. In order to enforce them, attendance officers were hired to inspect the premises of factories for underage workers, to investigate cases of non- and irregular attendance, and to inform parents of their obligation to send their children to school. There was reluctance to enforce legal penalties when parents did not send their children to school because there was limited acceptance of state's right to force parents to send their children to school (Abbott & Breck- enridge, 1917). Attendance officers tried using “moral suasion" to persuade parents to comply. The City of Chicago took pride in the fact that no parental authority was breached in order to get a child to attend school. 41 There was a new push to enforce compulsory attendance laws in the 1920's. During World War I, it was reported that those who had received systematic training by attend- ing school were better able to adapt to military life. Coupled with the fact that one in four men in the draft army were unable to read and write in English, a new importance was given to compulsory school attendance. The educational system was held responsible for not enforcing compulsory attendance laws and for the high rate of illit- eracy (Ensign, 1921). It was even suggested that school attendance should be enforced under national authority, in order to ensure that American youth would be better pre- pared to defend their country in the future. Today there are higher societal standards for school attendance. The change from an industrial to a post- industrial society has brought about a decrease in the number of jobs for unskilled workers and an accompanying increase in jobs for highly skilled workers (Blyth, 1991). Schools are no longer holding tanks for children. Educa- tion is a necessity for obtaining economic self— sufficiency. This change in the make up of the labor force, cou- pled with the knowledge that school failure puts a child at risk for many negative outcomes (early pregnancy, delinquency and welfare dependency), has captured the 42 attention of politicians. Once again school attendance has surfaced as a political issue. In 1988, the state of Wisconsin enacted a law that linked school attendance to welfare payments. Families in which students have more than the allotted amount of unexcused absences have their welfare payments reduced (washington Post, 1992). In Michigan, a similar bill was introduced in 1992 aimed at school attendance of elemen- tary children. Families receiving public assistance could lose up to $25 in benefits every month for each child who is identified as having too many absences (up to a maximum of $98 per month per family). Families not receiving assistance could lose $100 in state income tax exemptions per child (Lansing State Journal, 1992). Over one hundred years after the passage of compulso- ry attendance laws, it seems the issues remain the same. Taylor (1980, p.4) states "The questions that need most often to be asked about home-school relationships are . . . political and moral. They are concerned with the legitimacy and justification of the means by which the individual is inducted into the wider society . . . with the respective rights of the individual and family on one side and the school and society on the other." The struggle to enforce school attendance as a societal duty over the rights of the individual continues. 43 Review pf tpe Research The study of school attendance began shortly after the passage of compulsory attendance laws. Non-attendance at school was defined as a social problem in need of a solution. This necessitated determining the causes of absenteeism. The literature on school attendance reflects the changing focus of social scientists over the last 100 years and will be reviewed chronologically. Three dis- tinct paradigms have been used to explain absenteeism. Early studies focused on truancy as a social problem. In the next era of studies, a clinical paradigm was used to examine the differences between school phobics and tru- ants. The third stage of research on school absenteeism has moved toward an ecological paradigm in an attempt to integrate the effects of the home environment, individual characteristics and school environment on absenteeism. About two-thirds of the studies cited in this chapter are British; about one-third are American, and one is from the Netherlands. Because of the scarcity of American studies and the similarities between the American and British educational systems, the British studies were included in the review. Truancy as a Social Problem Early theories of truancy were based on the nature of children and their desire to be active. Kline (1898) 44 wrote of truancy as a result of man's need to wander, a remnant of hunting and gathering nomadic history. Burt (1925) viewed truancy as a natural result of "locomotor impulses." Children wanted freedom to move about and found it difficult to tolerate the inactivity of sitting at a school desk all day. Because public schools were viewed as a way to remedy poor parenting practices, the earliest studies of school attendance tended to focus on family characteristics as the most important influence on non-attendance. Primari- ly, it was viewed as the family's responsibility to socie- ty to ensure that a child attended school. Secondarily, it was the teacher's responsibility to the child to make school pleasant so that attendance was preferable to truancy (Burt, 1925). The only child characteristic explored in relation to absenteeism was illness. Ellis (1973) reviewed historical documents to deter- mine the influences on absenteeism in England in the mid .to late 1800's. He concluded that family characteristics were the biggest influence on school attendance. Lack of physical resources within the family seemed to be the major predictor of absenteeism. Sending children to school was costly for poor families; children in school were not able to work. The loss of wages plus payment of a small weekly school fee was more than many parents could afford. When children of the lower classes did go to 45 school, attendance was often irregular. Children didn't have proper clothing and didn't attend school in bad weather. If children were absent one or two days, some parents kept them home the rest of the week to avoid paying the fee for the entire week. Children from poor families who moved often in order to find seasonal work attended irregularly. In families where both parents worked, children stayed home to see to younger siblings. Ellis (1973) identified parent attitudes toward education as another important influence. Many parents were hostile about being forced to send their children to school and some even moved frequently to evade the compul- sory education act. Many working class parents were apathetic about sending their children to school as it was unclear how schooling would benefit their children. Employers also influenced school attendance. They viewed the cheap wages of child labor as necessary to keep costs down. Especially in agriculture, parents were threatened with dismisSal if they didn't bring their children with them to work on the farms. Ellis (1973) found evidence that teacher-child inter- action was a factor in absenteeism. Teachers reportedly neglected children who were unable to pay their fees and concentrated on those who could, a practice which discour- aged attendance of poor children. The overall quality of teaching also influenced attendance. In London in 1894, a 46 change in school staff led to an increase in the attend- ance rate from 70% to 90%. Childhood illness was a frequent cause of absences. Epidemics of small pox, diphtheria, cholera, tuberculosis and typhus closed many schools. In one school in Liver- pool in 1837, 90% of the children were absent with scarlet fever, while another school reported 78% absent with measles. Although there is no doubt that illness was a legitimate excuse for absence, school records show that most absences for illness were on Mondays, an occurrence for which there is no obvious explanation. In 1888-89, 1,329 families in 52 towns in Massachu- setts were visited to determine why children were absent from school. Poverty seemed to play a major role, with 44% of absences being caused by child employment and 7% by lack of proper clothing. Parental neglect, or lack of effort to ensure attendance, was listed as the cause of 34% of absences. Mental or physical disability of the child accounted for 13% of absences (Ensign, 1921). Booth (1902), stated in a report written in 1891, that underfeeding and irregular attendance were the major problems that teachers faced in teaching children from the poorer classes in London. He reported that 18-20% of the children had very bad attendance. The children whose attendance was the most irregular were from homes of extreme poverty where one or both parents drank. 47 Booth (1902) viewed the curriculum as an obstacle to school attendance. He wrote of the indifference with which children responded to the curriculum when it was not relevant to their situation. He found it inappropriate to require children who lived in appalling conditions to learn to diagram sentences properly and wrote of the "slum-look" on their faces when asked to do so. He re- ported that their faces brightened when basic skills that they could apply to their own lives were discussed and felt that school should be made more relevant to their situation. A thorough study of absences was completed in Chicago during the 1913-14 school year (Abbott & Breckenridge, 1917). Researchers investigated every absence of all children in two elementary schools for a three week peri— od. Every time a student was absent a home visit was made to determine the reason for the absence. Of the 3,192 children enrolled at the schools, 1,446 were absent at least one day during the three week period. Data are available on a total of 1,158 children. The two schools that were chosen were in overcrowded neighborhoods with high rates of poverty. The number of people per acre was 92 and 82 for the two schools, com- pared to 20 for the City of Chicago as a whole. Only 7% of the fathers of the children at either school were born 48 in the United States. The population of one school was predominately Polish, the other Italian. When attendance officers made home visits, they classified the homes as very poor, poor, comfortable or very comfortable. This designation was made based on the condition of the home, rather than on reported income. More than three-fourths of the homes were described as poor or very poor. Almost all of the children lived in two parent families (90%). During home visits, the reason most often given for absence was illness (48%). While there were legitimate cases of illness, often the child did not appear ill, and it was suspected that no effort had been made to get the child to school. Children often had to stay home because of family responsibilities and 26% of absences were due to working at home, taking care of ill family members, running er- rands, acting as an interpreter for parents and family emergencies. Lack of shoes or clothing accounted for 7% of absences. Abbott & Breckenridge (1917) concluded that poverty was the real reason for most absences, even illness. If proper medical care could have been obtained for minor illnesses, more serious illness and long periods of ab- sence could have been avoided. The authors concluded 49 that it was the parents, not the child or the school who were responsible for attendance problems. Family variables were the focus of early research studies and researchers concluded that the family was the most important influence on attendance. It appears that the major family variable related to absenteeism is lack of physical resources, or poverty. Some credence was given to the influence of school level variables of cur- riculum and teacher-child interaction. The only charac- teristic of the child that was examined in relation to attendance was illness, which.was a major reason for absenteeism. Figure 4 represents the Social Problem Model of Absenteeism in terms of the conceptual model developed in Chapter 1. 50 Chrono- Barriers system T R Natural weather A Environment N S I T I O N Exosystem Employers T J O Microsystem. School Family I curriculum attitudes poverty N teacher-child D interaction 1 stress U S T Child health R I A ‘7 School L Attendance I S M Figure 4 The Social Problem Model of School Attendance 51 School Phobia and Truancy as Clinical Issues The next era of studies on school attendance re- flected a change in the professional perception of the child's role in school attendance. From the 1920's through the 1940's, child guidance clinics were estab- lished in both the United States and Great Britain. The goal of the child guidance movement was to detect and treat difficulties in children ages 3-17 years (Long, 1989). .As children were referred for treatment of school absenteeism, the focus of the literature turned to clini- cal populations, rather than more general studies of absenteeism. The clinical paradigm explained absenteeism as a result of disturbed family relationships or a disordered personality. A distinction was made between two classifi- cations of absenteeism: school phobia and truancy (Broad- win, 1932; Clyne, 1966; Hersov, 1968). Students who have an adverse emotional reaction to school and exhibit somatic symptoms when faced with at- tending school are defined as school phobics. These students stay home with parental knowledge, but not neces— sarily with parental consent. Students are truant when they miss school for illegitimate reasons without their parents' knowledge (Cooper, 1966a; Hersov, 1960a). 52 Working from case studies, practitioners described school phobics as being anxious about school performance, having over-protective mothers, and coming from middle class families. The underlying cause of school phobia was identified as separation anxiety, with the child being afraid to leave the mother and go to school (Broadwin, 1932; Clyne, 1966; Hersov, 1960). Truants were described as having behavior problems, being involved in illegal activities, being below average achievers, having parents who ignored them and coming from working class families. Truancy was considered to be a symptom of conduct disorder (Cooper, 1966a; Hersov, 1960a). While both school phobia and truancy were identified in clinical populations, the literature focused on phobia, while truancy was relatively ignored (Tyerman, 1971). Over 40 articles on school phobia were published between 1932 and 1962 (Frick, 1964). Few of the articles dis- cussed empirical research because of the small number of identified school phobics. In a study by Galloway (1976), less than .1 percent of students were identified as school phobics. Three research studies were identified and are reviewed below. In a 1966 study comparing school phobics and truants, the children in the study were clients at a child guidance clinic in London. The groups consisted of 50 children 53 each and were compared on characteristics of the family environment and on child characteristics (Hersov, 1966a). School phobics were found to have over-protective mothers, have parents whose occupations were of a high social class, and were more likely to have family members with mental illness. They were likely to exhibit other symptoms of psychoneurosis such as eating disorders and somatic symptoms like abdominal pain and sleep disturb- ance. When children were asked why they didn't attend, 17 said they were afraid something would happen to their mother while they were gone, 14 said they feared academic failure, 14 were afraid of being teased or bullied and 11 were afraid of a teacher (Hersov, 1966b). Truants were more likely to come from homes where there was inconsistent discipline, and where either mater- nal or paternal absence had occurred. They exhibited symptoms of conduct disorder such as lying and running away from home, were more likely to have been enuretics and more likely to have been involved with juvenile court. Truants had changed schools frequently. Hersov concluded that there were two types of absentees, neurotics and conduct disordered. In another comparison of school phobics and truants, Cooper (1966b) gathered data on four groups of 40 students each. Group A was made up of students who had been re- ferred for psychological services as school phobics. 54 Group B consisted of referrals to the School Welfare Office as truants. Teachers rated students on several personality traits and appearance, and students responded to questions about attitudes toward school. School phobics differed from truants in that they were more intelligent, more anxious to respond to authori- ty and more affected by failure. The families of school phobics were smaller, of higher socioeconomic class and parents were over-anxious about discipline when compared to truants. In a recent study, Cooper (1986) compared a group of adolescent school phobics (n=37) and truants (n=39) at- tending special teaching units in London. His findings were congruent with earlier studies in regard to family dynamics. School phobics were more likely to have over- protective mothers and be immature, lonely and isolated, while truants were more likely to be rejected by their parents, come from a broken family and display additional anti-social characteristics. The focus during this time was in clarifying the description of school phobia. The differences between school phobics and truants were compared on parent-child interaction variables and child characteristics. Findings indicated school phobics were neurotic, anxious and had dependent relationships with their parents. Truants were considered to be suffering from conduct disorder and come 55 from lower class neglectful families. Figure 5 places the clinical model within the paradigm developed in Chapter 1. Chrono- Barriers system I Macrosystem Social Class N v 1 U S Microsystem Family T R parent-child I interaction A stress L 1 S Child O anxiety C delinquency I fear of failure ' E enuresis \ School T somatic symptoms Attendance Y Figure 5 Ecological Model of Absenteeism Over the last thirty years, several changes have taken place in the way that school attendance has been conceptualized and studied. There has been increased attention on the role of the school in all student out- comes, including absenteeism. Pressure to include school variables has come from two directions: concern about school failure in lower class students and concern about deviance in middle class students. 56 Concern about lower class students is based on two hypotheses from sub-cultural theory (Reynolds, Jones, St. Leger and Murgatroyd, 1980). The blocked opportunity hypothesis posits that lower class children are blocked from succeeding at school because they do not have the characteristics of the "good student" as defined by middle class values in the school. In the cultural conflict hypothesis, sub-cultural behaviors are seen to be in conflict. Student behavior is seen as adaptive in the neighborhood sub-culture, but is viewed as deviant in the sub-culture of the school. An increase in school failure of middle class stu- dents also focused attention on the role of the school (Reynolds, et al. 1980). It was recognized that middle class, as well as lower class, youths were failing at school, and doing so in increasing numbers (Franklin, 1992). It was no longer viable to look only to the family environment of lower class students for an explanation. The impact of these two forces brought about what is known as the "effective schools" literature. This trend in determining the relationship between school variables and poor pupil outcomes carried over to research on absen- teeism. At this time the blame shifted away from the child's mental health as the cause of absenteeism. Patterson (1989) describes this shift in research as changing from 57 truants as ”objects of inquiry" to thinking, feeling subjects who engage in social interaction. Using the terms "school phobia" and "truant“ place the blame for absenteeism on the individual, when in fact the community, family, school and individual can be involved (Kahn, Nursten & Carroll, 1981). The less judgmental term of absentee is more likely to be used to describe children with attendance problems (Reid & Kendall, 1982). Another change in the literature during this time was the identification of a third type of absenteeism, parent condoned. In these cases, students may be home to help with household tasks or because of general ambivalence about education and school attendance. Although parent condoned absences may account for up to 50% of absenteeism problems across all age groups (Galloway, 1976), very little research has been done in this area. The last major change in the study of absenteeism during this time is in the measurement of the dependent variable. The practice of measuring absenteeism subjec- tively, such as self-report of truancy or asking a teacher or parent to classify children as truants, is giving way to using more objective measures. In many of the studies reviewed here, the dependent variable was defined as the number of absences, number of episodes of absences, or attendance rate of the student. 58 The literature in this section is reviewed by re- search model. Of the studies listed below, seven explored only one domain (family, school or child). Six combined two domains (family and school, family and child, or school and child). Four included variables from the family and school systems and child characteristics. In addition, a few researchers included the macrosystem variable of sub-culture and the mesosystem variable of family-school interaction as research variables. 9.121.414.1491 Attendance patterns by age of child have been ad-1 dressed in two major studies. In an early study by Sten- nett (1967), attendance histories of rural junior and senior high school students were plotted from kindergarten to twelfth grade. Absences were highest in kindergarten and declined through fourth grade where they stabilized. There was a decrease in absences in Grade 7, and an in- crease in the last two years of high school. Easton and Engelhard (1982) replicated this study using attendance records of 617 eighth graders in Chicago public schools. Attendance patterns were remarkably similar to those in Stennett's study; kindergartners missed the most school, with attendance increasing through fourth grade. Attend- ance was stable through seventh grade, with a slight increase in absenteeism in Grade 8. Both studies reported 59 higher absences for girls than boys, but Easton and Engel- hard stated the difference was not significant. Mitchell and Shepherd (1967; 1980) studied the atti- tudes and attendance patterns of a random sample of over 6000 students aged 5 to 15 years from Buckinghamshire, England. Parents were asked to rate their children on behavior and on how well they liked school: likes school very much, likes school about as much as other children, or dislikes going to school. The percentage of boys and girls who were said to like school very much decreased with age, while the percentage reported to like school about as much as other children increased. The percentage who disliked going to school remained relatively constant at 5% of boys and 3% of girls, with a slight increase for both genders after age 12. . For both boys and girls, the lower the level of academic achievement the higher the percentage who didn't like school. Boys described as having uncooperative behavior were more likely to dislike school, but this did not hold true for girls. Parents were more likely to rate children who didn't like school as being worried and having more frequent headaches than children who did like school. Even though this was a statistically significant difference, the practical difference was small; only 7% of the children who didn't like school reported weekly head- aches compared to 3% of children who did like school. 60 Dislike of school was found to be related to attend- ance; twice as many children who disliked school missed more than 10 days in a term then children who liked school. This relationship did not hold across age groups, however. For primary school students, there was no sig- nificant association between how much a student liked school and attendance. These data indicate that attend- ance of young students is controlled by parents, but as students reach adolescence, they are more likely to make their own decisions to attend school independent of their parents' wishes. School Mgggl In research that focused on school variables, attend- ance rates for eight secondary schools in South Wales were studied from 1966-7 through the 1972-3 school years (Reynolds, Jones, St. Leger & Murgatroyd, 1980). Attend- ance rate is defined as the average percentage of students in attendance. An attendance rate of 90% can indicate that 10% of students never come to school, or that all students attend 90% of the time. Student variables of reading and mathematics test scores, and personality test scores on extroversion and neuroticism were used as con- trol variables. Only reading scores were correlated with absenteeism. School attendance rates were found to be higher in schools where students wore uniforms, where the level of 61 control over student activity was lower, where there was less strict enforcement of rules, where pupils were uti- lized in decision-making and management roles. There was no relationship between school size, class size, or build- ing age or facility and absenteeism. Higher attendance rates also were found to be related to the mesosystem variable of better school-parent relationships, which was measured by the proportion of parents visiting the school in a term. Teacher-student interaction variables were studied in relation to mean attendance for 19 classrooms from one college preparatory high school in California. Classes included math and algebra, foreign language, biology, English, art and bookkeeping. Students and teachers were asked to complete the Classroom Environment Scale. Aver- age attendance was better in classrooms rated by students as less competitive and having less teacher control, and in classrooms rated by teachers as having high levels of teacher support (Moos & Moos, 1978). A 1990 study examined the influence of school charac- teristics on attendance in the Netherlands (Bos, Ruijters & Visscher, 1990). Attendance data were collected on Monday, Wednesday and Friday of one week in April, 1988 at 36 schools in Holland. The schools all have a high per- centage of low SES students. Variables that were not correlated with truancy rate are school size and degree of 62 teacher support. Significant correlations were reported between degree of centrality of attendance records and accuracy with which attendance records were kept by teachers. Family Mgggl Brown (1987) interviewed 28 parents of truants and 28 parents of controls who were matched on sex, school year, class set and neighborhoods to learn more about the rela— tion between parental attitudes and absenteeism. Parents were asked about their own school experience, their views of their child's school, and their support of their child's education. In general, attitudes of parents of truants were similar to parents of controls. Parents of truants reported positive views of their own schooling and their child's school. The only exceptions were that fathers of truants were less likely to view their own schooling as related to later success and mothers of truants were more likely to have negative attitudes about their own schooling. Parents of truants were less likely to visit their child's school and more likely to keep their children home from school for illegitimate reasons than parents of controls. The attitudes of the 14 parents of truants who were most negative toward their children's schools were exam- ined in more depth. It was found that these parents did 63 not have negative attitudes about their own schooling, but had developed negative feelings because of their children's school experiences. These parents felt that the school failed to support their child in two ways: some parents believed schools were too lax in dealing with their child's school behavior and needed to be more au— thoritarian; other parents complained that teachers treat- ed their children badly because they were poor. Family-School Model The National Child Development Study followed all children born in England, Scotland and Wales in the first week of March, 1958. The children were studied at the time of birth and at ages 7, 11 and 16 years. School personnel filled out questionnaires and tested the chil- idren; the child had medical examinations and parents were interviewed. At ages 11 and 16, children completed ques- tionnaires. Data were collected on family characteris- tics, family value of education, and school characteris- tics. The dependent variable was measured by asking teachers to designate a child as truanting or not (Fogel- man, Tibbenham & Lambert, 1980). In a comparison of the percentage of students in five social class levels, it was found that there was a higher percentage of truants at each level, from managerial and professional to unskilled manual workers. This held for both boys and girls at ages 7, 11 and 16. Children from 64 families who owned their own home were less likely to be truants than those who lived in rented housing. Students living in families with four or more children were more likely to be identified as truants than children from smaller families. The value parents placed on education was found to be related to truancy. At age 11, parents of truants were more likely to have had no contact with the school and to want their children to leave school as soon as possible. Teachers reported that fathers of truants did not care about their children's education. At age 16, students were asked to rate their parents' level of concern about their school performance. For children classified as working class, a significantly higher percentage of truanting children than non-truanting children reported their parents did not care about school achievement, or they didn't know their parents level of concern. No difference was found for middle class chil- dren because all students, truants and non-truants, reported that their parents showed concern about their education. These results indicate that the effect of parental attitude on attendance differs by sub-culture. The relationship between school level variables and truancy was explored and separate analyses were completed by gender. The school variables were use of corporal punishment, ability grouping policy, student-teacher 65 ratio, teacher turnover, size of school and whether or not the school was co-educational, required school uniforms or held parent-teacher meetings. Because the relationships between school characteristics and percentage of truants were weak and inconsistent, the authors concluded that school variables had little influence on truancy rates. The authors described a typical truant at age 16 as being from the working class, living in poor housing, and having parents who were not concerned about school. They concluded that truancy was a social problem, not an educa- tional one. A 1983 study by Little and Thompson illustrates the move away from the perception of absenteeism as a child problem_and towards a systems perspective. They state that the focus of absenteeism research should be on the interactions between parent and child or teacher and child which influence how receptive a child is to the school experience, rather than on the child as sick or incom- plete. Data were collected from parents and teachers of 103 habitual absentees from four middle schools in Kentucky. A control group was matched by sex, grade, geographic loca- tion (as a control for social class) and remedial or special class membership. Habitual absenteeism was defined as having 10 or more unexcused absences during the school year. 66 Parents and teachers were asked to complete the Little Parental Valuing Styles Scale and the Little Teacher Valuing Styles Scale, respectively. Parents of absentees scored higher on overprotection and overindul- gent scales. Teachers rated their relationships with absentees as higher on rejection and overprotection. The authors concluded that parents who over indulge and over- protect their children foster dependency and allow chil— dren to set standards for behavior. The authors speculat- ed that teachers who view children as less able to succeed in school feel overprotective of the child and view the child as special. As the child continues to perform poorly, the teacher gets frustrated and may reject the child, thus a dysfunctional cycle of teacher-child inter- action is perpetuated. In both cases, children are less receptive to school and more likely to be absent. Family-Child Model Investigators in St. Louis in 1958 examined child and family characteristics related to absenteeism. (Brooks, Buri, Byrne & Hudson, 1962). A random sample of 476 parents of children from 135 elementary schools was chosen. The dependent variable consisted of three catego- ries, children with above average, average, or below average attendance. 67 Level of physical resources was measured by income and home ownership, both of which were related to attend- ance level. Stressors identified as being related to attendance were number of years in the neighborhood and number of moves in the previous two years. Whether or not a child lived in a single parent family was not related to attendance. Family size was related to attendance with a higher percentage of children from large families having below average attendance. Parent attitude toward education was measured using three sub-scales: attitude toward attendance, attitude toward the school, and attitude toward education. Attitude toward attendance consisted of items about the importance of attending regularly. Attitude toward educa- tion was defined as how important education was as a family goal. Attitude toward the school measured feelings about school personnel, discipline, and educational stand- ards. An overall attitude toward education score was computed by summing the three sub-scales. The attitude toward school sub-scale and the total score were found to be related to level of child's attendance. Child characteristics measured were gender, race, and age of child. There were no differences between boys and girls or black and white children on level of attendance. There was a significant relationship between age of child 68 and level of attendance with younger children missing more school than older children. The Cambridge Study of Delinquent Development (Farrington, 1980) included truancy as an outcome variable in research on 411 males. The boys were first contacted in 1961, when they were eight years old. Teachers com- pleted questionnaires when the boys were ages 8, 10, 12, and 14. When teachers were asked to indicate why they thought 135 boys with low attendance rates missed school, they gave the following reasons: illness (59), truancy/school refusal (50), parental unconcern (12), trouble at home (11) and parents' holiday (4). Additional information was gathered from families and teachers of boys who were identified as frequent truants or whose attendance rates were 90% or less. These absen- tees lived in low socioeconomic class, low income families with marital disharmony. They were more likely to be from large families with five or more children and live in poor housing. On a general measure of parenting, parents were rated as having poor child rearing skills and having a lack of interest in their children's education. Teachers described primary school truants as lazy, restless, difficult to discipline, lacking concentration, not caring about being a credit to their parents, and not clean and tidy. These descriptors were also used for 69 secondary level absentees. On standardized tests, absen- tees scored lower on vocabulary and IQ tests than regular attenders. In a study of 204 children who entered nursery school in Texas from 1972-78, researchers hypothesized that children who were rated high on peer sociability would have fewer illness related absences than children with low peer sociability scores (Pennebaker, Hendler, Durrett & Richards, 1981). This hypothesis was based on the theory that illness can be stress induced and that the first year of school can be disruptive and stressful for a child. Since a positive social environment can ameliorate the effect of stress on health, children with positive peer relationships should find school less stressful and have fewer illness related absences than those with poor peer relationships. Control variables included socioeconomic class and divorce, which were significantly associated with illness related absences, and gender and health history, which were not. Peer sociability, as rated by the parents, was related to absences after controlling for the above named variables. School-Child Model Data were collected on 3,246 students at six middle schools in Boston in 1982-83. Students were placed into two categories, problem absence students (PAS) or non- 70 problem absence students (NPAS). A student was identified as a problem absence student if they 1) missed six or more consecutive days in a quarter; 2) missed 10 or more non- consecutive days; or 3) had patterned absences and missed half or more days of a particular day of the week. One- third of the students were designated problem absence students. There was significant variation in the percentage of problem absence students by school, ranging from 26% to 42.8%. The only school variable measured, school size, was not related to absentee rate. Child variables of age and academic failure were related to the designation of problem absence student. Younger students were less likely to be rated as a PAS than older students. Almost 50% of students who were two years behind grade level were designated PAS compared to 20% who were at appropriate grade level. The relationship between special education status and problem absence status was significant, but contributed the least of all variables to the discrimination between the two groups. Attendance varied by sub-culture. White students were one and a half times as likely to be labeled PAS as black or Hispanic students. The authors felt that this was related to busing and desegregation. The percentage of white students attending these middle schools had dropped from 54% to 29% since desegregation and busing had 71 been instituted, 10 years before the study. The high percentage of white PAS was linked to the departure of middle class whites from the Boston school system and continuing ambivalence of whites toward desegregation. Family-School-Child Model One source of data on school attendance during this time period was the National Survey of Health and Develop- ment (Douglas, 1964). This longitudinal study took place in Great Britain and included all children of agricultural and non-manual workers and one-quarter of the children of manual workers born in the first week in March, 1946. When these children were aged six and one-half to ten and one-half years, their school attendance was tracked by their teachers. Attendance was measured by number of episodes of absence rather than number of days absent. Of the 1,399 children who showed excessive episodes of ab- sence from six and one-half to eight and one-half years, 21% had excessive absences in all four years. During these four years, the children missed an average of 11.6 weeks of school. The highest number of absences was recorded between ages six and one-half and seven and one-half, with 4.0 weeks missed while for the latter three years the average number of absences was between two and one-half and three weeks. 72 The relationship between sub-culture and attendance was explored. There was no difference between rural and urban schools. There were differences among geographic regions. Students with attendance problems in all four years ranged from 5.5% to 13.1% of the school population, however no pattern was discernible. It was hypothesized that attendance would be worse in the northern regions because of weather conditions, but this was not supported by the data. Social class was found to be related to episodes of absence; percentage of children with excessive absences from upper middle class families was 4.6%, from lower middle class families 7.3%, from upper manual class fami- lies 9.9%, and from lower manual class families 11.2%. Children from families with four or more children were more likely to have attendance problems in all four years, as were children whose parents had a low level of interest in their education. The only school level variable measured in this study was the ranking of schools by overall academic achievement of student—body. Schools with poor academic records had a higher percentage of students with attendance problems in all four years. Teachers rated children on a five point scale on their attitude toward school work. Of children who were rated as very hard workers, only 2.6% had attendance 73 problems in all four years, while 23.4% of those rated as lazy had excess episodes of absence in all years. No group difference was found between boys and girls. Several research articles have been published from a large scale study of absentees in South Wales (Reid, 1982, 1983, 1984a, 1984b). The research population consisted of three groups of 128 students each. The first group was made up of students who had been absent at least 65% of the time in the previous school year. The second was a control group of good attenders from the same academic track as the absentees matched by age and sex. The third group also was a control group of good attenders matched to the absentees by birth date and by sex but from a higher academic track. The three groups were compared on social background variables. The absentees were more likely to come from single parent homes and to have fathers with lower status occupations. One quarter of absentees said they missed school because of domestic reasons (Reid, 1983). There were significant differences between academic controls and the two other groups on family size, birth order and type of housing, but there were no differences between the two groups from the lower forms (Reid, 1984a). Reid (1982) found that there were more parent-school conflicts reported in the files of absentees. Their parents were less likely to show an interest in their 74 school work or visit school than either of the two control groups (Reid 1984a). Intelligence of the absentees, as measured by tests at age 11, was significantly lower than for a normal population. Their grades were lower and continued to get worse the longer they stayed in school. In the year prior to the study, the absentees' grades averaged to "D", the control group from the same form a "C", and the academic controls a ”B”. The school files of the absentees showed they had taken more remedial and special education tests, had been demoted more, and been underachievers (Reid, 1982; 1984a). Self-concept was compared across groups in another study by Reid (1982). The Brookover Self-Concept of Academic Ability Scale, which measures self-concept in relation to school learning, and the shortened version of the Coopersmith Self-Esteem Inventory, which measures general self-concept, were administered to the three groups. The absentees had significantly lower self-esteem scores on both scales than either of the two control groups. It was found that absentees rated their school work lower than students in the other two groups regard- less of how teachers graded their work. The control groups also differed significantly; students from the lower academic forms scored lower than those from the higher forms. 75 In 1984, Reid compared the three groups of students on school behavior. Teachers completed the Rutter Children's Behavior Questionnaire; the main scale and the anti—social and neurotic sub-scales were used. On all three scales, there were significant differences between the absentees and each of the two control groups. There were no differences between the two control groups on any of the scales. It was noted that 39% of the absentees showed signs of neurotic behavior and 35% showed signs of anti-social behavior. School files indicated that absen- tees were more disruptive at school than the other two groups (Reid, 1982). When absentees were asked why they did not attend school, they often gave school-related reasons. Slightly more than 15% stated it was because of curriculum and examinations and 14% said it was because of teachers. When asked about their feelings about school, absentees were more likely to feel confused, to think they were unable to protect their own interests and to like fewer classes than the other two groups. Wanting to leave school was one of the reasons given by absentees for missing school (Reid, 1983). Absentees had significantly fewer friends at school than the controls from the same form. Data collected from school records provided evidence that absentees were more often bullied at school than other students. Almost 20% 76 of absentees reported that being bullied at school was the reason they did not attend (Reid, 1983). A second major British study of school attendance was completed by Galloway, who examined the attendance records of all 36 comprehensive schools in Sheffield, England and their feeder primary schools (Galloway, 1976, 1980, 1982, 1983, 1985). Data were collected on reasons for absences, school level variables, family resources and stressors, and child characteristics. The dependent variable, iden- tification as a persistent absentee or not, was defined as missing more than 50% of possible attendance days during the fall term of 1975 (seven weeks). Less than 1% of primary students and approximately 2% of comprehensive school students were identified as persistent absentees. Attendance officers were asked why they thought the persistent absentees had missed school (Galloway, 1976). The following categories were provided to attendance officers for classifying student absences: illness, absent with parental consent, parents unable or unwilling to insist on child's attendance, school phobia, truancy, socio-medical reasons (e.g. scabies), psychosomatic ill- ness and miscellaneous reasons. It is important to note that these preset categories did not include any school- related reasons. The 35% of primary level and 23% of comprehensive level students who were absent mainly due to illness were excluded from additional analyses. 77 Of primary level absentees, slightly more than 40% were absent for mixed reasons, 16% because the parent was unable to insist on return, 10% socio-medical reasons, and less than 5% psychosomatic illness, truancy, and school phobia. For secondary students, 27.8% were absent for mixed reasons, 26% parents unable to insist on attendance, 11.2% truancy and less than 5% school phobia, psychosomat- ic illness and socio-medical reasons. Almost one-quarter of students in both age groups were absent with parental consent. Younger children were more likely to be absent because of socio-medical reasons and mixed reasons than older students, and less likely to be absent due to truan- cy and parents unable to insist on child's attendance. The author commented that the school phobia category probably was under-counted because some of the children with psychosomatic illness and who were out for mixed reasons were school phobics. Two school level variables, size of student body and percent of students receiving free lunches, were correlat- ed with percentage of persistent absentees. The correla- tion between size of school and attendance was small (-.22) and not statistically significant. The correlation between attendance and percent of children receiving school lunches was larger (.8) and significant (p <.001). In a subsequent analysis, comparisons were made across four groups of students: persistent absentees from 78 one secondary school (n=39) and its feeder primary schools (n=20), persistent absentees who had been referred for psychological reasons (n=20), and a representative group of regular attenders from the same class as the secondary and primary absentees. The groups were compared on family characteristics, family stressors and individual charac- teristics of the students. In over half of the families of all three groups of absentees neither parent was em- ployed, compared to 9% of regular attenders. There were no significant differences among the four groups in family size, overcrowding, or intact families (Galloway, 1982, 1985). The mothers of absentees scored significantly higher on a screening questionnaire used for psychiatric disor- ders. In fact, their scores were similar to women in another part of England who had been diagnosed as suffer- ing from psychiatric disorders. In interviews with stu- dents, many more absentees reported feeling anxious about their parents' well-being than regular attenders. It seems that their concerns were realistic, considering the mothers' high scores on the screening questionnaire (Galloway, 1982, 1985). Galloway (1982) also looked for group differences on number of family stressors experienced by students. These stressors included poor housing, overcrowding, illness of family members, single parent family and separation from 79 either parent. He found that the primary and referred groups of absentees experienced significantly more stres- sors than the regular attenders. When parents were asked if school factors contributed to their children's attendance problems, parents of sec- ondary absentees were more likely to report that their children were afraid of one or more teachers, or had an extreme dislike of a particular class, than the others groups. There were no differences between groups on parental report of boredom at school. Comparisons of IQ and reading scores were made across groups. IQ and reading scores were low for all groups (Galloway, 1982). No differences were found on parental report of sense of academic failure. There were no differences among the groups on paren- tal report of being bullied or teased at school. Parents of absentees who had been referred for services reported their children as having difficulty with social relation- ships at school (Galloway, 1982; 1985). There were no differences among groups on children's current health status or medical histories (Galloway, 1985). In an attempt to gain knowledge about the difference between parent-condoned absentees and truants, Galloway classified the referred and non-referred secondary absen- tees as "other absentees" or "truants". The parents of 80 other absentees knew where their children were when not at school, usually at home. The parents of truants seldom knew of their children's whereabouts when not at school. Many of the differences between the two groups point to a more stressful home life for other absentees. A significantly higher percentage lived in families who were receiving social assistance, had mothers who were chroni- cally ill, and had lost a parent through death. There also were differences between the groups associated with parent-child interaction. More other absentees reported warm, satisfactory relationships with their parents, and were over-protected by, and over-dependent on, their parents than were truants. Sommer (1985) studied 25 truants and 25 non-truants in eighth grade in a semi-urban junior high school in California. The groups were matched for gender, grade in school, ethnicity and neighborhood. Truants were identi- fied as students with ten or more absences from September to March and being listed on the irregular attendance list. Data were collected from school records, interviews with students and counselor ratings. Truants were found to be less likely to have a telephone, more likely to live in a single parent home and to have more siblings living 1 at home. Truants scored lower on academic achievement tests, had lower GPA's and had more disciplinary actions than 81 non-truants. When students were asked what they thought about school, fewer truants made positive statements than did non-truants. Counselors were asked to indicate what they thought were the major factors that caused truants to miss school. The three factors they felt contributed most to absentee- ism.were ineffective parenting, home problems, and the students disinterest in the curriculum. Summapy 9: recent studies. Because of the large number of independent variables discussed in the ecological studies, a summary is present- ed below. Variables are discussed by system level and by constructs within the system. Macrosystem. The influence of sub-culture values as measured by social class were shown to have an effect on school at- tendance in several studies (Douglas, 1964; Fogelman, et al., 1980; Pennebaker, et al., 1981). It has been hy- pothesized that working class families do not value educa- tion as highly as do middle and upper class families. This relationship was clearly illustrated by Fogelman, et al.'s examination of the relationship between parents' concern about their children's education and attendance when broken down by social class. The degree of parental concern was related to truancy in working class families. This was not true for middle class families, however, 82 because all middle class parents were concerned about their children's education. Mesosystem. Three studies reported that the parents of absentees were less likely to visit their children's schools than control groups (Brown, 1987; Fogelman, et al. 1980; Reid, 1984a). Reid (1982) also reported that the files of absentees indicated more parent-school conflicts than other students. Family Microsystem. Family physical resources. Level of physical re- sources was measured by income level, home ownership, and telephone in the home. In every study that examined the relationship between economic deprivation and attendance, a significant relationship was found (Brooks, et a1. 1962; Farrington, 1980; Fogelman, et al., 1980; Galloway, 1982; Sommer, 1985). There were consistent findings that indi- cated absentees are more likely to live in large families (Brooks, et a1. 1962; Douglas, 1964; Fogelman, et al., 1980; Sommer, 1985). Only one researcher reported no link between family size and attendance (Galloway, 1976). Family stress. Researchers measured family stress in both general terms and as specific events. Students reported that they often missed school because of domestic problems (Reid, 1983). Counselors and teachers cited home 83 problems as a reason for absenteeism (Farrington, 1980; Sommer, 1985). Galloway (1985) reported that unemployment and mother's level of psychological well-being were relat- ed to attendance. He also found that persistent absentees lived in families that experienced a higher number of stressors than did regular attenders (Galloway, 1982). There were conflicting findings on the relationship between living in a single parent family and absenteeism. Three studies report a significant relationship (Sommer, .pa1985; Fogelman et al., 1980; Pennebaker, 1981), and two reported no relationship (Galloway, 1982; Brooks, 1962). Education pg family gga_. Students' reports of parents' level of concern about school was related to attendance for working class only (Fogelman et al., 1980); teachers reported that fathers of truants did not care about their children's education (Fogelman et al., 1980; Reid, 1984a), and parents of absentees reported they wanted their children to leave school as soon as possible. Parents of absentees were less likely to show an interest in their children's school work (Douglas, 1964; Fogelman et al., 1980; Reid, 1984a). In a study where education as a family goal was measured as a sub-scale of parent's attitude toward education, no significant relationship was identified (Brooks et al., 1962). 84 Family perceptions. Feelings about school personnel, discipline and educational standards were reported to be related to school attendance for elementary level students (Brooks, 1962). Brown (1987) reported that fathers of truants felt their education was not related to future success, and mothers of truants viewed their own school experience negatively. Parent-child interaction. Few studies during this time period addressed parent-child interaction as a cause of absenteeism. Parents of elementary level absentees were reported to be overprotective and overindulgent (Little & Thompson, 1983). Middle school counselors felt ineffective parenting was a major contributor to absentee- ism (Sommer, 1985), and parents scored poorly on child rearing skills (Farrington, 1980). School Microsystem. School resources. No study measured school resources related to facilitating attendance (e.g. availability of transportation) or enforcing attendance policies (e.g. student-attendance officer ratio). It is not surprising that the resources measured, such as building age or facility and student-teacher ratio, were not related to school attendance rates. School attitudeslopenness. Attendance rates were found to be related to better school-parent relationships. 85 School yglgg pf Attendance. Attention given to school attendance policies by school personnel is an indication of how much a school values attendance. The accuracy of attendance records and whether or not attend- ance records were kept in a central location were related to school attendance rates in the Netherlands (Bos, et al. 1990). Teacher-child interaction. Parents of persistent absentees reported that their children disliked one or more of their teachers (Galloway, 1982; 1985), and that teachers were not supportive of their students because of lax discipline and negative attitudes toward economically deprived children. A Moos & Moos (1978) identified the classroom variables of competition and teacher support as being positively related to attendance. Schools with less strict discipli- nary practices and classrooms where teachers used less control had better attendance (Reynolds et al., 1980; Moos & Moos, 1978). Curriculum. Secondary level students reported that curriculum was a reason for absenteeism (Reid, 1984), as did middle school counselors (Sommers, 1985). Qphg; school variables. Although many school varia- bles were measured in studies of attendance, they seem to have been chosen for reasons of convenience rather than theoretical reasons. There is no apparent theoretical 86 reason to anticipate that wearing of school uniforms or whether a school is co-educational would impact school attendance rates. If variables that were more closely related to attendance policies had been included, more informative findings may have been forthcoming. Child Characteristics Academic success. Intelligence level, grades, achievement test scores, retentions and special education testing and placement have all been identified as signifi- cantly related to absences (Farrington, 1980; Weitzman, 1985; Reid, 1982). The child's perception of him/herself as a student also is related to absenteeism. Absentees score lower on academic self-concept than other students, regardless of how teachers rate their work (Reid, 1982). ggiig behavior. Absentees are more likely to be rated as neurotic and anti-social (Reid 1982) and lazy (Douglas, 1964; Farrington, 1980). The school files of absentees indicate they are more likely to be disruptive and be involved in more disciplinary actions than regular attenders. Social Relationships. Four studies addressed the association between social relationships and attendance. A significant relationship was found between peer socia- bility and number of illness related absences in nursery school children (Pennebaker, et al., 1981) and being bullied at school and number of friends for secondary 87 persistent absentees (Galloway, 1982, 1985; Reid, 1983). Qpilg attitude. For middle and secondary level stu- dents who disliked school, desired to leave school, or made negative statements about school, there was a rela- tionship between attitude and attendance (Sommer, 1985; Reid, 1983; Mitchell & Shepherd, 1967; 1980). For primary level students there was no association between attendance and a child's dislike of school. Qpilg 3gp. Consistent patterns between age and attendance have been identified by two studies. Kinder- garten children miss the most school. The level of absen- teeism drops from kindergarten through the end of elemen- tary school and then increases from about age 12 through the end of secondary school (Easton & Engelhard, 1982; Stennet, 1967). When researchers examined attendance patterns for elementary students only (Douglas, 1964) or middle school only (Weitzman, 1985), the findings were consistent with the previously cited studies. Chilg gender. No significant relationships were reported between gender and number of absences or classi- fication as a persistent absentee. Child health. One of the most interesting contrasts in the research findings is between the percentage of absences attributed to illness and the relationship be- tween child health and attendance. Attendance officers report that most absences are because a child is ill 88 (Galloway, 1976). In a study of nursery school children, there was no relationship between child health history and illness related absences (Pennebaker, 1981). Galloway (1985) reported that there was no association between medical history or current health status and being identi- fied as a persistent absentee. The recent studies on school attendance do not all utilize an ecological paradigm. Some authors have contin- ued to examine variables from only one domain, such as the research by Brown (1987), Mitchell and Shepherd (1967; 1980), and Reynolds et a1. (1980). When the independent variables from all the studies are combined into a model, an ecological model, much like the conceptual model for this study, is the result. Discussion Table 1 lists the variables identified using the social problem, the clinical, and ecological paradigms. In the social problem model, child variables were omitted. The clinical model then focused on the child as disor- dered, which is inconsistent with the social and ecologi- cal paradigms. In the ecological model, the family and school are emphasized once again. The view of the child has changed from deficient to interacting with other systems. It is interesting to note the similarities between the social problem and ecological models. If researchers 89 had continued to build on the social problem model, in- stead of using the clinical model to investigate absentee- ism for 30 years, it is likely that there would be a more complete understanding of school absenteeism by this time. 90 Table 1 Independent Variables Identified py Three Research Paradigps pf Absenteeism Paradigm Social System Problem Clinical Ecological Natural weather Macro social class social class Exo employers Meso parent-school interaction Family poverty stress poverty stress parent/child stress attitude interaction attitude goal parent/child interaction School curriculum curriculum teacher/child attendance policy interaction teacher/child interaction Child health anxiety academic success fear of failure school behavior delinquency peer relations enuresis age attitude toward school III. METHODOLOGY An objective of this research is to test the model of school attendance in Figure 6, and to assess the influ- ence of community, family and child characteristics on number of absences. Chrono- ggrriers system P o s Macrosystem Community t values I J n Microsystem Family d goals poverty u openness stress 8 l t r Child i academic success health a school behavior -_________ 1 social relationships ‘—> School Attendance S o c i e t Y Figure 6 . . Empirical Model for Investigation 91 92 Research Design The data for this research were gathered as part of an evaluation study of the Absenteeism Prevention Program (Werner & Paladina, 1984) supported by the Michigan De- partment of Mental Health, Prevention Services Division. Data were collected from parents, teachers, and children over four years at two sites in Michigan. Initial data consisted of attendance data only and were used to identi- fy children with attendance problems. Intake data were collected at the point in the school year when an attend- ance problem was identified, sometime between October and May. Posttest data were collected approximately 12 months and 24 months after intake. At Intake, Posttest 1 and Posttest 2, data were collected on family demographics, teacher's perception of the child as a problem student, child's self-concept, parent's educational goal for the child, and parent's attitude toward education. Attendance data were collected for all four years of the study. Table 2 is a summary of the data collection at the two sites. 93 Table 2 Schedule 9; Data Collection 1986-87 1987-88 1988-89 1989-90' 1990-91 Site 1 Initial Intake Posttest Posttest attendance data one two data Site 2 Initial Intake Posttest Posttest attendance data one two data 2gp; Collection Parents were contacted by telephone or letter (Appen- dix A). The goals of the study were explained to them, and an appointment was made to collect intake data. Upon meeting with parents, the data collector asked the parent to sign a consent form (Appendix B). By signing the consent forms, the parents agreed to allow the data col- lector to interview their child at school and to collect data from their child's teacher. The data collection procedures described below were repeated for posttest one and posttest two. All data from parents and children were collected through personal interview. This was done in an attempt to insure understanding of the questions and as a way to avoid problems resulting from illiteracy. Parent interviews took place in the home. At the completion of the interview the parents were paid $10.00 94 pain cash or received $10.00 in restaurant coupons, based on their preferences. Children were interviewed at school. The data col- lector received permission from teachers to take children from the classroom. The interviews took place in any available area in the school that provided privacy. Teacher surveys were placed in teacher mail boxes with a note that requested the teacher complete the survey on a specific child. Teachers returned completed surveys to the data collector's mail box which was set up for this purpose. In schools where attendance was tracked by the school secretary, attendance data were gathered through office records. In schools where the only attendance record was kept by the teacher, the data collector examined the records from each classroom. Instruments Instruments used to collect data were Children's Stressful Life Events (Appendix C, pp. 153-4), Family Face Sheet (Appendix C, pp. 158-9) Revised Parent Attitude toward Education (Appendix C, pp. 155-7), the Teacher- Child Rating Scale (Appendix C, p. 160) and the Self- Perception Profile for Children (Appendix C, pp. 161-4). Two of these instruments, the Children's Stressful Life Events and the Family Face Sheet were developed by the Michigan Department of Mental Health, Prevention Services ‘95 Division, as part of ongoing program evaluation efforts. The Children's Stressful Life Events Scale includes chron- ic and acute stressors and indicators of family stability. The Family Face Sheet was used to collect demographic information from families. The Revised Parent Attitude toward Education Scale was developed by Medinnus (1962) and revised by the De- partment of Mental Health, Prevention Services Division, with permission of the author. This instrument was de- signed to measure the parent's attitude toward his/her own educational experience and the parent's evaluation of the importance of education. The revised form consists of 26 items, 22 items from the original Medinnus instrument and 4 items (#3, #10, #17, #20) added for the purpose of evaluating the Absenteeism Prevention Program. The Teacher-Child Rating Scale (Hightower, Spinell & Lotyczewski, 1986) was developed by the Primary Mental Health Project. It consists of two parts; Part I has 18 items which assess problems a child has in the classroom and Part II has 20 items which assess strengths. In this study, only Part I was utilized. The constructs measured include 1. Acting-out: aggressiveness, disruptiveness and impulsivity. 2. Shy-Anxious: shy, withdrawn dependent behaviors. 3. Learning Skills: skills needed to succeed aca- demically in school. 96 Each of the sub-scales consists of 6 items rated on a 5-point scale. The Self-Perception Profile for Children consists of 36 items which form six sub-scales that measure self- concept (Harter, 1985). Each item consists of two con- trasting statements. Children are asked to pick which statement is most like them. After they choose a state- ment, they indicate whether the statement is "really true for me" or "sort of true for me." The three sub-scales used in this study are 1. Scholastic Competence: child's perception of competence for scholastic performance. 2. Social Acceptance: child's perception of how well liked by peers. 3. Behavioral Conduct: Child's perception of the appropriateness of behavior. This instrument was developed for children eight years and older. (In this study it was used for slightly younger children, but completed in an interview format, so that children did not have to be able to read the ques- tions. Conceptual 29g ngggtigpgl Definitions The dependent variable of this study is absenteeism. The independent variables of interest in predicting absen- teeism are community environment, family perception of school, education as a family goal, level of family 97 resources, stress, child's health and child's academic success, classroom behavior and social competence. Dependent Variable Absenteeism is defined as the number of days absent over four school years (ABSENT). Independent Variables Community yglgg pf Education. The school drop-out rate and the percentage of par- ents attending parent-teacher conferences are representa— tive of the value a community places on education. In this study the drop-rate was lower and the percentage of parents attending conferences higher at Site #1 than at Site #2, indicating that Site #1 valued education more highly than Site #2. The variable of community (COMMUN) is a dichotomous variable. Site #1 is coded as 0 and Site #2 is coded as 1. Family Perception 9; School Family perception of school is defined by two compo- nents. The parent's attitude toward the school system as it relates to home-school interaction, fairness, and ability to teach children is one measure of the family's perception of the school. This variable is measured by the Parent Attitude Toward Education Scale. The scale consists of 14 positive and 12 negative statements about schools. Negatively stated items were reverse coded and 98 the scores of all items were summed. The higher the score, the more positive the parent's attitude toward education. The scores for three years were summed to provide a stable measure of parent attitude (PARATT). Thus the scores could range from 0 to 234. The mother's level of education is the second compo- nent of the family's perception of education. This varia- ble is measured as the number of years of school completed by the mother (CGED). For two parent and single mother families, the mother's level of education was used. For single father families, the father's level of education was used. Education pp p Family Egg; The goal of academic attainment for individual chil- dren was measured by asking parents' how many years of schooling they would like their children to complete (GOAL), which is item #29 on the Parent Attitude Toward Education Scale. Level 9; Resources For this study, level of physical resources is meas- ured by family income. Income is item # 10 on the Family Face Sheet and was recorded as a categorical variable with unequal intervals between categories. Income was recoded pausing the mid-point of each category to represent the dollar amount of annual income for the family (INCOME). 99 Stress Thomson and Vaux (1986), suggest using an unweighted sum of negative events to measure family stress. The life events as listed on the Children's Stressful Life Event Scale were summed for three years to give a total stress score (STRESS). Items #2 and #4 were not included in the stress score because they were used as individual predic- tors in the regression model. Single parent families were defined as a family with only one parent figure. Two parent families were defined as having two parent figures, including step-parents and unmarried partners of parents who were living with the family. The number of parent figures in the family was determined using the information listed in items 13.1., 13.2, and 13.11 of the Family Face Sheet. Single parent family was Operationalized by creating a dichotomous variable (SINGLE) in which families with only one parent were coded as 1 and families with two parents were coded as 0. Chronically ill family member (CHRONIC) is item #4 on the Children's Stressful Life Event Scale. It is a di- chotomous variable and coded as 1 for families in which there was a chronically ill or handicapped member reported at intake, and 0 for families in which there was not a chronically ill member. 100 Academic Success, Behavior gpg Social Relationships Child's academic success, behavior and social rela- tionships were operationalized using sub-scales of the Self-Perception Profile for Children and the Teacher Child Rating Scale (TCRS). Academic success was measured using the academic self-concept of the child (ACAD) and the teacher's perception of the child's learning skills (LEARN). Behavior was measured by the behavioral self- concept of the child (BEHAVE), the teacher's perception of the child's acting out behavior (ACT) and the teacher's perception of the child's shy/anxious behavior (SHY). Social relationships were measured by the child's social self-concept (SOCIAL). Table 3 indicates the items in- cluded in each sub-scale. For the self-concept sub- scales, higher scores indicate higher levels of self- concept, for the TCRS sub-scales, higher scores are indic- ative of more severe problems. For each of the sub-scales, scores were added across the three years, i.e. the scores for the academic sub- scale for years one, two and three were summed to give a total academic sub-scale score. This was done to decrease measurement error. With young children, self-concept related to school performance is still forming, and scores across three years are likely to be more stable. A com- posite of three teachers' opinions of classroom behavior is likely to be less biased than the perception of one 101 Table 3 Items 9: the ACAD, BEHAVE, SOCIAL, ACT, LEARN and SHY Sub-scales Instrument Variable Items Self-Perception Profile ACAD 1, 7, 13, 19, 25, 31 for Children BEHAVE 5, 11, 17, 23, 29, 35 SOCIAL 2, 8, 14, 20, 26, 32 Teacher-Child Rating ACT 1, 4, 7, 10, 13, 16 Scale LEARN 2, 5, 8, 11, 14, 17 SHY 3, 6 9, 12, 15, 18 Child Health At each interview, parents were asked how many times their children had experienced major illness or injury in the past year (Children's Stressful Life Events, item #2). The number of illnesses and injuries were summed for the three years. Table 4 provides an overview of the instruments used to collect data on the constructs measured. 102 Table 4 Data Sources, Instruments and Variables for the Study Source Instrument Variable School Records Absences Parent . Family Face Income InterView Sheet Single Parent Family Teacher Survey Child Interview Stressful Life Events Parent Attitude Toward Education Scale Teacher-Child Rating Scale Self-Perception Profile Mother's Education Stressors Chronically Ill Member Child Illness/Injury Parent Attitude Toward Education Educational Goal for Child Learning Skills Acting-out Behavior Shy/Anxious Behavior Academic Self-Concept Social Self-concept Behavioral Self-concept 103 The Study Population Intake data were collected on 66 children from 59 families. All children included in the study were identi- fied as having attendance problems and were selected to participate if they met one or more of the following conditions: 1. the student had missed 15 or more days in the prior school year; 2. the student showed a pattern of absences, e.g. missing every Monday, in the current school year; 3. the student missed more than three days in a month in the current school year; 4. the student missed 15 or more days in the current school year. Attrition Complete data are available for 34 children from 33 of the original 59 families. Almost one-half of the study population was lost over the four years of data collec- tion. Chi-square tests and t-tests were computed for categorical and interval level variables, respectively, to determine if the children with complete data were repre- sentative of the original sample. There was no difference between the two groups on the initial measurement of absences. Mean days absent for the children who completed data collection and those who did not were 20.5 and 16.3, respectively. The families who completed data collection were significantly different from those who dropped out in two ways: family income and 104 mothers' employment status. Of the 86% of families who reported annual income of under $25,000, 52% did not complete data collection, while only 15% of those with incomes of $25,000 or more dropped out. In families where mother's were employed full time, only 19% dropped out, while in families where mother's were not employed, or were employed part-time, 67% dropped out. The Communities Data were collected on children in grades one through three from three elementary schools in two counties in Michigan. Two schools were located at Site 1, a city of about 16,000 residents. One school was located at Site 2, in a town of 1,800 residents. The drop-out rates for the two school districts were disparate. For site 1, the drop-out rate was 3%, while at Site 2, it was slightly more than 13%. The percentage of parents attending par- ent-teacher conferences for the two schools at Site 1 were 76% and 87%, and 48% for Site 2. Both the dropout rate and the percentage of parents attending parent teachers conferences indicate that education is valued more highly in community #1 than in community #2. The Families Over 65% of the families reported annual income of under $25,000 and 26% had income of $10,000 or less. Slightly more than 35% of the families were headed by 105 single parents; one single parent was a father. In slightly less than one-quarter of the households, there was no one employed outside the home; in almost 40% there was one employed adult, and in slightly more than 35% there were two wage earners. Mothers' education level ranged from seven to thir- teen years. Slightly less than 40% of the mothers did not complete high school. One-fifth of the mothers completed from one to three years of college; none of them completed a four year college degree. When asked how many years of school they wanted their children to complete, all parents wanted their children to graduate from high school, 10% wanted their children to complete a two year college degree, 45% wanted their children to complete four years of college and 10% wanted their children to attend gradu- ate school. Over the three years of data collection, the parents of 75% of the children indicated they wanted their child to complete at least some college. Table 5 provides a summary of demographic characteristics of the families. 106 Table 5 Description pf Study Population Percentage Variable of Families Family Structure single parent 35 two parent 65 Caregiver's Education < 12 years 40 12 years 40 13-15 years 20 Income up to $10,000 26 $11,000-25,000 39 over $25,000 35 Adults Employed none 25 one 40 two 35 The families that completed data collection experi- enced ongoing instability and stress over the three years. Slightly more than 60% reported a decrease in income, 30% moved to a new home, over three-quarters experienced changes in employment, 36% added new members to the house- hold and over half had member leave. Slightly less than two-thirds reported that a member experienced serious illness or injury. The Children The study sample was almost evenly divided between boys and girls. They ranged in age from six to 10 years 107 at pretest. There were three African American children in the sample, and the rest of the sample was white. The possible range, minimum, maximum, and mean for the sub-scales of the TCRS and Self-Perception Profile for Children are presented in Table 6. Table 6 Values for ACAD, BEHAVE, SOCIAL, ACT, LEARN, and SH Variable Possible Minimum Maximum Mean Range ACAD l8 - 72 30 71 48.8 BEHAVE 18 - 72 27 70 52.7 SOCIAL l8 - 72 38 70 55.0 ACT 20 - 80 18 78 31.2 LEARN 20 - 80 18 71 38.4 SHY 20 - 80 20 50 32.9 The Teacher-Child Rating Scale provides profiles for urban and suburban students by sex. Scores of the study population were examined in relation to the profiles provided for suburban children, as there were no norms for rural children. Mean scores for each child were computed to determine the percentage of children who scored above the 85th percentile on the profile. For the sub-scales of ACT, SHY and LEARN, the percentage of boys scoring above the 85th percentile was 12%, 18% and 24% and for girls 15%, 8% and 23%, respectively. A higher percentage of both boys and girls had scores above the 85th percentile 108 on learning skills. It appears that students with attendance problems are more likely to have problems with learning skills than the general population. No defini- tive conclusions can be drawn, however, because no pro- files are available for small town or rural students. Means for academic, behavioral and social self- concept were compared to the means of the population on which the Self-Perception Profile for Children was normed. The means for the study sample were almost identical with the means provided by Harter (1985). This suggests the self-concept of children identified as having absenteeism problems does not differ from the self-concept of other children. The maximum, minimum and mean number of absences for each year and the total for all four years are shown in Table 7. On average, children missed about 20 days, or four weeks of school each year. The average for four years was 84.4 days, or almost 17 weeks of school. Total weeks of school missed for the four years ranged from 8 (40 days) to almost 31 (154 days). 109 Table 7 Posttest Posttest Initial Intake One Two Total Minimum. 6 4.5 4 3 40 Maximum 69 42.5 40 55.5 154 Mean 23 20.5 21.7 19.3 84.4 Data Analysis Multiple regression analysis is a statistical tech- nique used to determine the relationship between a contin- uous dependent variable and a set of independent varia- bles. Using multiple regression, a statistical model was built which tests the empirical model for this study. The multiple regression equation is Y-A+B1X1+B2X2+. . .kak where Y is the estimate of the dependent variable, A is the Y intercept and Bi are the values by which xi are multiplied to obtain the best possible prediction line for Y. The equation describes a line which most closely represents the points on a scatterplot for each case. The distance between the actual values of Y for each case and the estimated point on the regression line is the residu- al. The regression line is calculated to minimize the sum of the squared residuals. The standard error of estimate is the square root of the squared residuals and gives an 110 indication of the average error in predicting Y from the regression line (Lewis-Beck, 1980). R2 is the proportion of the variance in the dependent variable explained by the independent variables. Each independent variable entered into the regression equation will increase R2. The law of diminishing returns takes effect, however, and each additional variable explains less of the variance. When variables that account for little variance in Y are entered into the equation, R2 will rise slightly, but so will the standard error of estimate. The Adjusted R2 is calculated to take into account the variability in the independent variables in relation to the dependent variable. It is computed mathe- matically by drawing different samples from the study population and determining the variance in R2 for these samples. Assumptions of Regression There are six common problems of regression which need to be addressed during the process of analyzing data: specification error, non-normality, non-linearity, collin- earity, non-standard error variance and influential cases (Lewis-Beck, 1980; Fox, 1991). Each is discussed briefly, with a description of appropriate diagnostics and solu- tions. lll Specification Error The first assumption of regression is that the theo- retical model being tested is accurate and that no extra- neous variables are included in the equation and no rele- vant variables are excluded. Because R2 increases with each additional independent variable, including extraneous variables will over estimate R2. Significance tests are used to identify any variables that should not be included in the model and extraneous variables are dropped from the model. If variables are excluded from the model, beta coef- ficients may be inflated. The only way to determine if important variables have been omitted is to examine R2. If a great deal of variance in the dependent variable is left unexplained, important predictor variables have not been included in the model. The only was to rectify this problem is to respecify the model including additional variables (Lewis-Beck, 1980). Non-normality .A second assumption of regression is that the distri- bution of Y is normal. The skewness statistic can be computed as a measure of normality. If the distribution of Y is highly skewed, transformations on Y can decrease the problem (Lewis-Beck, 1980). 112 Non-linearity A third assumption of regression states there is a linear relationship between X and Y. In order to deter- mine if the relationship between each x and Y is linear, partial residuals are computed and then plotted against Xi. The equation for computing partial residuals is ei=e+BiXi where e is the least squares residual, B is the estimated slope coefficient for xi, and Xi is the value of X for case i. If the relationship between X and Y is not lin- ear, transformations on x to bring about linearity can be computed (Fox, 1991). Collinearity Multicollinearity is the result of two highly corre- lated variables being included in the same model. This causes the coefficients of x to be unstable and may cause the null hypothesis to be accepted, when in fact there is a significant relationship between a predictor and the independent variable. Two indicators of collinearity are the condition indices and correlations of regression coefficients. Condition indices of over 30 are indicative of serious problems of collinearity. Additional evidence of collin- earity comes from highly correlated regression coeffi- cients (Wilkinson, 1988). 113 The possible solutions for dealing with this problem are not usually feasible. Fox (1991) suggests collecting new data or, when possible combining two related variables into one. The solution of last resort is to delete a variable from the model. While this may solve the problem with collinearity, deleting a relevant predictor creates the problem of specification error. Non-standard Eppgp Variance (Heteroskedasticity) A fifth assumption of regression is that the error terms are equally distributed around the regression line. If error terms increase with increasing values of X or Y, significance tests will be inaccurate. In this analysis, no diagnostics were computed to identify heteroskedasticity. In general, regression is robust to violations of the assumption of homoskedasticity, and no transformations are needed unless the non-standard error variance is extreme (Fox, 1991). Influential ggggg Influential cases are individual cases which have a large influence on B. Studentized residuals are plotted against fitted values of Y to identify influential cases. If, when examining the scatterplot, influential cases are noted, they should be deleted (Fox, 1991). 114 Hypothesis testing The null hypothesis in regression analysis is that B=0. The t statistic is used to test the null hypothesis for individual variables. The F statistic can be used to test the hypothesis that B=0 for two or more variables simultaneously. For this study, the significance level for rejecting the null hypothesis is p <.05. Building the model Because the estimate of the coefficients is not accurate if any major predictors are excluded from the model, the preferred method of model building is to test the full theoretical model. All variables are included in the equation and variables for which the null hypothesis cannot be rejected are systematically discarded. Varia- bles can be eliminated one at a time based on the t statistic, or groups of variables can be eliminated by comparing the F statistic of a full equation to the F statistic of a reduced equation. The number of independent variables that can be included in the equation is constricted by sample size. Neter, Wesserman & Kutner (1991), state that there must be six to ten cases per independent variable. Because of the small sample size in this study (n=34), a maximum of five independent variables can be included in the regression equation. This constraint made it impossible to test the IV. RESULTS The multiple regression analysis was completed in two stages. First the individual hypotheses were tested and variables were identified for inclusion in the final model. The second phase consisted of the testing of the empirical model. Tests pf Hypotheses Stage one of the analysis had two purposes: to test the hypotheses from Chapter 1 and to complete the first stage of model building. The first step in the analysis was to compute the skewness statistic, to determine if the distribution of ABSENCE was normal. The distribution was only slightly skewed (.468), and no transformation on ABSENCE was necessary. Regression analyses were completed for each of the seven propositions with each analysis testing one or more related hypotheses. The results of the stage one analysis are reported for each proposition. 115 116 Macrosystem Propositions Community yglpg pf Education Proposition 1 states that the degree to which a community values education will influence the school , attendance of young children. To test this relationship ABSENCE was regressed on the dichotomous variable COMMUN (Table 8). The variable of community was not a signifi- cant predictor of number of absences but was retained for further analysis (p<.10). Proposition 1 and Hypothesis 1.1 were neither rejected or accepted at this time. Table 8 Regression p; ABSENCE pm COMMUN VARIABLE COEFFICIENT T P(1 TAIL) CONSTANT 61.757 4.058 <.000 COMMUN 16.068 1.578 <.100 DEP VAR: ABSENCE N: 34 MULTIPLE R: .269 R2: .072 ADJUSTED R2: .043 STANDARD ERROR OF ESTIMATE: 29.212 Family System Propositions Four propositions suggest a relationship between family system variables and school attendance. Parent's Perception Q; School Proposition 2 states that parents' perception of the school will influence school attendance. Of the two variables that measure parent perception of the education 117 system, caregiver's level of education (CGED) and parent's attitude toward school (PARATT), CGED is a significant predictor of ABSENCE and was retained for stage two of the analysis (Table 9). Table 9 VARIABLE COEFFICIENT T P( 1 TAIL) CONSTANT 219.107 4.698 (.000 PARATT “0.099 -0.586 (.300 DEP VAR: ABSENCE N3 30 MULTIPLE R: .566 R2: .320 ADJUSTED R2: .270 STANDARD ERROR OF ESTIMATE: 24.383 Proposition 2 was partially supported. Hypothesis 2.1 was rejected: no significant relationship between parent's attitude toward school and number of days absent was found. Hypothesis 2.2 was accepted: there is a negative relationship between mother's education level and number of days absent. Education pg Family Goal Proposition 3 suggests the degree to which a family values education influences school attendance of young children. When ABSENCE was regressed on GOAL, the number of years of school parents want their child to complete was not a significant predictor of ABSENCE (Table 10). 118 Table 10 Regression pi ABSENCE pm GOAL VARIABLE COEFFICIENT T P( 1 TAIL) CONSTANT: 105.662 2.838 <.005 GOAL -1.525 -0.611 <.300 DEP VAR: ABSENCE N: 29 MULTIPLE R: .117 R2: .014 ADJUSTED R2: .000 STANDARD ERROR OF ESTIMATE: 29.314 Proposition 3 was not supported. Hypothesis 3.1 was rejected: no significant relationship was found between number of years parents want their child to complete and number of days absent. Family Income Proposition 4 indicates lack of physical resources in a family will act as a barrier to school attendance. When ABSENCE was regressed on INCOME, INCOME was found to be a strong predictor of ABSENCE with p=.000 (Table 11). Table 11 Regression g; ABSENCE gm INCOME VARIABLE COEFFICIENT T P(1 TAIL) CONSTANT 110.281 14.781 <.000 INCOME -0.001 -4.182 <.000 DEP VAR: ABSENCE N: 34 MULTIPLE R: .594 R2: .353 ADJUSTED R2: .333 STANDARD ERROR OF ESTIMATE: 24.387 119 Proposition 4 is supported. Hypothesis 4.1 is accepted: there is a negative relationship between income and number of days absent. Family Stress Proposition 5 states that the presence of stress in a family will act as a barrier to school attendance. The variables STRESS, SINGLE, and CHRONIC, representing number of stressors, single parent status and chronically ill family member, were entered simultaneously to represent level of family stress. The two dichotomous variables, SINGLE and CHRONIC, are significant predictors of ABSENCE and were retained for further analysis. Number of stres- sors is not a significant predictor of absences (Table 12). Table 12 Regression p; ABSENCE gm STRESS, SINGLE and CHRONIC VARIABLE COEFFICIENT T 9(1 TAIL) CONSTANT 67.090 6.096 <.000 STRESS 0.209 0.223 <.450 SINGLE 17.897 1.793 <.050 CHRONIC 29.073 2.590 <.010 DEP VAR: ABSENCE N: 33 MULTIPLE R: .535 R2: .286 ADJUSTED R2: .212 STANDARD ERROR OF ESTIMATE: 26.896 Proposition 5 was partially supported. Hypothesis 5.1 was rejected: there is no relationship between number 120 of stressors and number of days absent. Hypothesis 5.2 was accepted: children living in single parent families are absent more days than children living in two parent families. Hypothesis 5.3 was accepted: children living in families with a chronically ill member are absent more days than children living in families where no member is chronically ill. Child Characteristics Propositions 6 and 7 relate child characteristics to school attendance. School Performance Proposition 6 states that a child's school perform- ance influences school attendance. ABSENCE was regressed on all six variables that represent school performance, child's academic self-concept, teacher's perception of the child's learning skills, child's social self-concept, child's behavioral self-concept, teacher's perception of the child's acting out behavior and teacher's perception of the child's shy/anxious behavior. Of the six varia- bles, only shy/anxious behavior is a significant predictor of number of absences (Table 13). 121 Table 13 ABSENCE Regressed pm ACAD, LEARN, SOCIAL, BEHAVE, ACT and SHY VARIABLE COEFFICIENT T P(1 TAIL) CONSTANT -11.651 -0.260 <.400 ACAD -0.067 -0.088 <.450 LEARN -0.176 -0.374 <.400 SOCIAL -0.293 -0.527 (.350 BEHAVE 1.051 1.069 <.150 ACT 0.154 0.287 <.400 SHY 1.791 2.506 <.010 DEP VAR: ABSENCE N: 34 MULTIPLE R: .556 R2: .309 ADJUSTED R2: .155 STANDARD ERROR OF ESTIMATE: 27.449 Diagnostics for collinearity were conducted. Condi- tion indices indicated a problem with collinearity (index 7=37.073). Correlations of regression coefficients were moderate for the three self-concept variables (ACAD, SOCIAL, BEHAVE) and for acting-out behavior and learning skills (ACT, LEARN). Two new variables were created: The self-concept variables were combined into one variable (SELF) as were ACT and LEARN (ACTLRN). A second regression analysis was computed using the two new variables of SELF and ACTLRN, along with SHY as predictors. Collinearity was no longer a problem, as the highest condition index was 20.818. The significance tests for the two new variables still indicated they were not predictors of ABSENCE (Table 14). 122 Table 14 Regression p; ABSENCE pm SELF, ACTLRN and SHY VARIABLE COEFFICIENT T 9(1 TAIL) CONSTANT 9.065 0.238 <.450 ‘ SELF 0.132 0.649 <.300 ACTLRN -0.127 -0.637 <.300 SHY 1.930 3.089 <.050 DEP VAR: ABSENCE N: 34 MULTIPLE R: .524 R2: .275 ADJUSTED R2: .202 STANDARD ERROR OF ESTIMATE: 26.678 A hypothesis test was computed to determine if the variables of SELF and ACTLRN could be dropped from the equation simultaneously. Since p=.555 (Table 15), the combined self-concept variable and acting out-learning skills variables were omitted from the model. Table 15 Hypothesis test for effects pi SELF and ACTLRN SOURCE SS DF MS F P HYPOTHESIS 854.230 2 427.115 0.600 0.555 ERROR 21352.254 30 711.742 Proposition 6 was partially supported. Hypothesis 6.1 was rejected: there is no relationship between meas- ures of academic success and number of days absent. Hypothesis 6.2 was rejected: there is no relationship between child's social self-concept and number of days absent. Hypothesis 6.3 was partially supported: No 123 relationship was found between child's behavioral self- concept or teacher's perception of the child's acting out behavior and number of days absent. A positive relation- ship between shy/anxious behavior and number of days absent was identified. Cgimg Health Proposition 7 states that school attendance is influ- enced by child health. ABSENCE was regressed on ILL, the number of serious illnesses or injuries a child experi- enced. ILL is not a significant predictor of number of days absent (Table 16) and was not retained for further analysis. Table 16 Regression p; ABSENCE gm ILL VARIABLE COEFFICIENT T P(1 TAIL) CONSTANT 79.000 11.756 (.000 ILL 13.231 1.236 (.150 DEP VAR: ABSENCE N: 33 MULTIPLE R: .217 R2: .047 ADJUSTED R2: .016 STANDARD ERROR OF ESTIMATE: 30.051 Proposition 7 was not supported. Hypothesis 7.1 was rejected: There was no relationship between number of illnesses or injuries and number of days absent. 124 Summary of Stage One In the first stage of model building, six variables were identified as predictors of number of absences: community, income, caregiver's education, single parent status, chronically ill family member, and shy/anxious behavior. Test _: the Empirical Model To test the empirical model, number of absences was regressed on the six remaining variables. For both INCOME and SINGLE, p >.10 (Table 17). Table 17 Regression Analysis 9; the Full Model VARIABLE COEFFICIENT T P(1 TAIL) CONSTANT 92.151 2.256 <.025 COMMUN 13.888 1.683 <.100 INCOME -0.000 -0.586 <.300 CGED -5.085 -1.362 <.100 CHRONIC 17.866 1.762 <.050 SINGLE 7.776 0.573 <.300 SHY 0.896 1.731 <.050 DEP VAR: ABSENCE N: 34 MULTIPLE R: .741 R2: .548 ADJUSTED R2: .448 STANDARD ERROR OF ESTIMATE: 22.188 In order to determine how to better specify the model, studentized residuals were plotted against fitted values of ABSENCE and examined for influential cases (Figure 7). One case with a residual less than —3 was deleted from the data set. 125 Figure 7 Scatterplot of Studentized Residuals Against Fitted Values of ABSENCE a l I l 2 + . 1 — +¥+ '+':+' + _ + + + + ++ + I- 0 _ + + _ E + ,4!- + + o + + E -1 ~ + + ++ — + + + _ -2 _. -3 _. + -4 I l I O 50 100 150 200 ATT A second analysis was run with the 33 remaining cases. After deleting the one influential case, only the variable INCOME was not a significant predictor of ABSENCE (Table 18). 126 Table 18 Regression Analysis 9; the Full Model with Influential Case Deleted VARIABLE COEFFICIENT T P(1 TAIL) CONSTANT 122.082 3.361 <.001 COMMUN 13.448 1.894 <.050 INCOME 0.000 0.678 <.300 CGED -9.541 -2.731 <.010 SINGLE 27.863 2.107 <.025 CHRONIC 30.938 3.220 <.005 SHY 0.868 1.948 <.050 DEP VAR: ABSENCE N: 33 MULTIPLE R: .821 R2: .674 ADJUSTED R2: .598 STANDARD ERROR OF ESTIMATE: 19.084 Diagnostics for collinearity were examined at this time. Condition indices for the full model indicated serious problems with collinearity, with one index over 35. In examining the correlations of the regression coefficients, income was found to be highly related to single parent status (.811) and to caregiver's education level (-.735). At this point, a decision was made to drop INCOME from the model. A third regression analysis was run on the reduced model with ABSENCE regressed on the five remaining inde- pendent variables: COMMUN, CGED, SINGLE, CHRONIC and SHY. All of the independent variables in this model are highly significant predictors of number of absences (Table 19). At this point hypothesis 1.1 was accepted: There is a relationship between the degree to which a community values education and the number of days a child is absent. 127 . Table 19 Reggession Analysis 9: the Reduced Model VARIABLE COEFFICIENT T P(1 TAIL) CONSTANT 114.873 3.341 <.005 COMMUN 11.962 1.789 <.050 CGED -7.800 -3.326 <.005 SINGLE 20.592 2.686 <.010 CHRONIC 27.357 3.443 <.005 SHY 0.870 1.972 <.050 DEP VAR: ABSENCE N: 33 MULTIPLE R: .817 R2: .668 ADJUSTED R2: .606 STANDARD ERROR OF ESTIMATE: 18.893 Regression diagnostics for collinearity for the reduced model were examined. After deleting INCOME from the model, the highest condition index was 28, indicating there was no longer a problem with highly related predictors. Tests for linearity were computed for the relation- ships between ABSENCE and CGED and ABSENCE and SHY. Partial residuals were calculated for CGED and SHY and plotted against Xi. The relationship between ABSENCE and CGED was found to be linear, but the relationship between ABSENCE and SHY was not. Fox (1991) indicates that trans- formations of x should be attempted to improve the linear- ity of the relationship and increase R2. Two transforma- tions on SHY were calculated, SHY2 and SHY3. Two addi- tional regression analyses were completed with the trans- formed variable. Since neither resulted in a perceptible 128 increase in R2, the model presented in Figure 4.2 was accepted as the final model. Intempmetation f the Model The coefficients for four of the five predictor variables are easily interpreted. For the variable COMMUN, the coefficient is 11.962 and indicates that children at Site #2 missed almost 12 more days of school (two and one-half weeks) than children at Site #1 over a four year period. The coefficient for CGED, -7.8, sug- gests that for each additional year of mother's education, a child misses almost eight fewer days of school in four years. Children living in single parent families miss slightly more than twenty days, or four weeks, of school over four years than children living in two parent fami- lies (b=20.592). Children who live in a family with a chronically ill member miss 27 more days, or five and one- half weeks, of school than children who live in families without a chronically ill member. There is a positive relationship between shy/anxious behavior and number of absences. The coefficient for SHY is .87, which implies that for each additional point on the shy/anxious sub- scale, a child misses eight-tenths of a day of school over four years. There is no practical interpretation for this coefficient because the score is not an observation of the characteristics of the child, but is an artifact of the research. 129 The R2 for the model is .668; almost 70% of the variance in ABSENCE is explained by the five predictor variables remaining in the model. Figure 8 represents the final regression model of school attendance. Chrono- Barriers system P o s Macrosystem Community t values I 1 n Microsystem Family Stress d caregiver's single parent u education chronic illness 8 1 t r Child ;: School i shy/anxious behavior Attendance a l S o c i e t Y Figure 8 Regression Model 9: School Attendance V. DISCUSSION The results presented in Chapter 4 have little mean- ing until they are applied to real world situations. This chapter provides a summary of the results by each of the three research question stated in Chapter 1. Research Question #1 Do elementary students identified as having poor school attendance in the early elementary grades continue to exhibit this behavior in subsequent years? As expected, not all young children who were identi- fied as absentees continued to experience attendance problems. Attendance in the first few years of school may be temporary and reflect a period of adjustment to the child's new role as student. Twelve of the 34 students missed more than 15 days each of the four years. While 15 days per year may seem a liberal measure of absenteeism, for these 12 students, it added up to the equivalent of a minimum of 12 weeks of school over a four year period, certainly enough of a reduction in time on task to hinder academic progress. For an additional seven students, attendance was a problem in three out of the four years. The data provide evidence 130 131 to support that for almost half of young children with attendance problems, these problems seem to work out without intervention. Research Question #2 Can predictors of absenteeism be identified by examining selected characteristics of the community and home envi- ronments and individual child characteristics? Seven propositions and related hypotheses were developed to answer this question. The results of the analysis as they related to each proposition are discussed below. Proposition 1 The value that the community places on education will influence the school attendance of young children. The values of the dominant culture set standards for school performance such as dropout rate, participation rate for parent-teacher conferences, and attendance. The values of the sub-culture determine how well communities perform on these measures. The findings of this study support the theory that the cultural values of the community influence school attendance. While sites were not chosen to represent different sub-cultures in relation to educational values, it appears that the sites did represent different sub- cultures. The analysis indicates that children living at Site #2, with a dropout rate of 13% and 48% of parents attending parent-teacher conferences, missed more school 132 than children at Site #1, where the dropout rate is slightly less than 3% and the percentage of parents at- tending parent-teacher conferences is over 80%. The community characteristics that are related to a devaluing of educational attainment at Site #2 are not known. If higher levels of education are not necessary for entry into the job market, placing less importance on education is adaptive. If this is not the case, and the educational needs for entry into the job market are simi- lar to those at Site #1, the devaluing of education at site #2 is likely to be maladaptive. Proposition 2 Parents' attitudes toward the school will influence the children's attendance at school. Two measures, the Parent Attitude Toward Education Scale and mother's level of education, were used to assess the influence of parents' perceptions of school on attend- ance. The scores on the Parent Attitude Toward Education Scale were not predictive of number of days absent. The reason no relationship was identified may be because of the wording of the scale items. Many of the items do not directly solicit the attitude of the parent. Instead, the items ask what most parents think, or what most children feel. Rewording the items so that they are specific to 133 parents' attitudes or children's situations at school might improve the validity of this instrument. Mothers' education level represents how well mothers navigated through the educational system. Those that were unsuccessful are likely to view their own education nega- tively. They are likely to feel anger about their own experience, be concerned that their children will have a negative school experience, and feel ignorant when faced with communicating with school staff (Wissbrun & Eckart, 1992). This may affect attendance in several ways. Lewin (1935) suggests that children's perceptions of an event as positive or negative will be influenced by parents' perceptions of the event. Children who are aware of mothers' negative feelings about school may be less motivated to attend school. Mothers who were unsuccessful in school may fear their children will fail and be unhappy at school. If their children are reluctant to go to school, mothers may allow them to stay home and avoid what is perceived to be a negative experience, rather than encourage regular school attendance. Family ecology theory suggests that interactions between family members and a system viewed as antagonistic will be limited (Kantor & Lehr, 1975). Mothers' negative perceptions of school may influence both the quantity and quality of home-school transactions; they may be reluctant 134 to interact with the school system and the interactions that take place may be strained. Negative interactions between the family and school systems will cause conflict for the child and affect school performance (Bronfenbren- ner, 1979; 1989; Wissbrun & Eckart, 1992). Proposition 3 The degree to which a family values education has an influence on the school attendance of young children. PrOposition 3 was not supported by this study. Theory predicts that a family expends energy and resources on family goals. .Asking parents how many years of school they want their child to complete may not be an accurate measure of education as a family goal. A better measure might include direct evidence of the amount of energy and resources invested in educational activities. Proposition 4 The lack of physical resources in a family will act as a barrier to a child's school attendance. Even though income was the single most powerful predictor of absences, the relationship between income and absences, relative to other predictors, could not be ascertained by this study. This was an artifact of the statistical analysis and the high correlation between income and mothers' education level and single parent status. These correlations are not surprising, as educa-. tion level has been shown to be a major predictor of 135 _income (McCarthy, 1992), and the annual income of single parent families ranges from one-quarter to one-half of that of two parent families (Laosa, 1988). Family ecology theory predicts that lack of material resources such as lack of appropriate clothing, lack of transportation, and lack of medical care act as a barrier to school attendance. A direct measure of these specific resources would provide a more valid measure of lack of resources as a barrier to school attendance and, hopeful- ly, would decrease the collinearity problem. PrOposition 5 The presence of stress in a family will act as a barrier to a child's school attendance. It appears that acute temporary stress is not relat— ed to persistent absenteeism, but that chronic stress does predict long term attendance problems. The number of stressors experienced by a family is not a predictor of number of absences, but two chronic stressors, single parenthood and having a chronically ill family member, are. Chronic stress may cause family goals to supersede educational goals for the individual. For example, goals that relate to maintaining the health of a chronically ill member may be more important to survival of the family system than supporting children's school success. 136 Proposition 6 A child's school performance influences school attendance. This proposition covers three constructs of school performance: academic success, social relations and behavior. Academic success Academic success was measured by two variables, academic self-concept and teacher's perception of learning skills. Since neither measure was a predictor of ab- sences, it appears that at this age, academic success is not related to attendance. Studies that identify low academic performance as a predictor of absenteeism in older children may, in fact, be interpreting the relation— ship incorrectly. Academic failure may be a result of absenteeism, not a cause. Behavior Behavioral self-concept and teachers' perceptions of acting out behavior both measure behaviors which are likely to get negative attention from parents and teachers and lead children to perceive themselves as failures in the school environment. Neither measure was related to attendance. An unexpected result of this study is that shy, withdrawn behavior predicted number of absences. Since there is no way to know what is causing this behavior, it 137 is difficult to interpret this finding. There are two likely explanations for this relationship. Shy, withdrawn behavior may be the of result of stress in the family system. Kashani, Ray & Carlson (1984) reported depression in young children was related to chaotic family life, physical and/or sexual abuse, neglect, psychopathology of a parent, or parental alcohol or substance abuse. It is also possible that there is something in the school envi- ronment that is causing these children to withdraw. This finding indicates a need for change in the way children are identified for special services. Because children who are disruptive in the classroom interfere with the teacher's ability to teach other children, they are identified for and receive special services. Children who are shy and withdrawn do not interfere with the teacher's goals for the class, are not referred for spe- cial services, and get little attention. Social relationships For this group of children, there is no relationship between social self-concept and school absences. Newson and Newson (1977) stated that how well young children like school is directly related to how well they like their iteachers. Perhaps peer relationships are relatively less important than the student-teacher relationship at this young age. 138 Proposition 7 School attendance is influenced by child health. Although it was hypothesized that illness and in- juries would influence school attendance, no relationship was identified. This supports previous findings by Gallo- way (1985). While illness may be the main reason for absence with regular attenders, it does not seem to be related to attendance of children identified as absentees. Perhaps it is not the main reason for absences at all, but only the main excuse used by parents when their children do not attend school. WW1; Can an ecological model of absenteeism be developed which aides in identifying students who may be in need of inter- vention for attendance problems? The ecological model of school attendance developed in this study provides a means for identifying those in need of intervention and for developing apprOpriate inter- ventions. The macrosystem variable of community was found to be a predictor of number of days absent. When indicators of school performance for an entire school district are low relative to other districts, community level interventions may be beneficial. Family level variables indicate that children who live in families with single parents, with chronically ill members, or with mothers with low educational levels should be targeted for intervention and that the family system should be included 139 in the intervention. The model also indicates a need for child-centered interventions to work with shy, withdrawn children. The interpretation of the model implies that the school system also should be a target of intervention in order to change the way the school perceives and inter- acts with absentees and their families. The fact that income is not included in the final model is not thought to be detrimental to the usefulness of the model. Since 86% of the original sample reported annual income of under $25,000, using income to identify absentees for intervention would over identify the number of children needing intervention. Since two variables that are highly related to income, mother's years of school and single parent family, are included in the model, most of the low income families would still be targeted for intervention. There are three major limitations in this study: attrition, sample size and specification error. Almost half of the sample was lost over four years which resulted in a high percentage of low income families being lost from the final analysis. The group that dropped out of the study differed significantly from those who completed the study on two variables: income and mother's employment status. Families with low annual incomes and mothers who 140 were not employed full-time were more likely to move out of the school district. The results can be generalized only to absentees whose residence is stable. The small n which resulted from attrition reduced the power of the statistical analysis. With a larger sample, additional variables might have been identified as signif- icant predictors of number of days absent. The sample size also limited the number of independent variables that could be included in the regression model and made it impossible to test the entire model using one equation. The original research for which these data were collected was based on an assumption that absenteeism in young children is the result of family problems. Because of this family focus, school level data were not collect- ed. This made it impossible to test the full conceptual model and led to specification error, i.e. not all varia- bles believed to be important in predicting school attend- ance were included in the empirical model. Mime for Tater‘s-mg If education is inherently good and one goal of the dominant culture is to improve school attendance of young students so that they can become better educated, then the practical implications of this research lie in using the findings to work toward this goal. Research results can be used to suggest interventions at the macro-, exo-, 141 meso- and microsystem levels, as well as child-centered interventions. Macrosystem Interventions In order to bring about change in attendance, one of two things must take place, the forces for change must be increased or the resistance to change must be decreased (Lewin, 1958). The goal of a macrosystem intervention would be to decrease the community resistance to regular school attendance by changing sub-culture values. One of the most effective ways to instigate change in attitudes is through a media campaign, or what Rutter (1982) de- scribes as propaganda. The change in the way Americans view cigarette smoking is an example of how well this can work. Community resources could be use to develop a media campaign that would stress the importance of education and attendance at school. The private sector could contribute by talking with students and parents about the types of skills that are needed to become employed (Wissbrun & Eckart, 1992). Exosystem Interventions Using the legal means available to enforce attendance creates change through forced compliance rather than reducing resistance. It is likely that some of the parents who now show little concern about their children's school attendance would be more compliant if they feared a 142 penalty for non-compliance. For these families, learning that there is a willingness to prosecute for non-attend- ance could improve attendance. For families where chil- dren are out of school because of chronic stress, the threat of prosecution, or actual prosecution, is not likely to be effective. Forced change brings about addi- tional stress (Lewin, 1958), which would be likely to exacerbate the family situation and could start a spiral of increasing absenteeism and additional prosecutions. Mesosystem Interventions Teachers and parents often blame each other for children's problems at school and children get caught in the middle of these hostilities. These students become responsible for their own school performance, as they receive little support from the school or the family system (Wissbrun & Eckart, 1992). Intervention is needed to help the school and family systems focus on the needs of children, rather than view each other as the cause of children's problems. One way to decrease resistance to change on the part of parents and school staff would be to add a home—school liaison to the school staff. A liaison could act as an advocate for children with both parents and teachers, an advocate for parents within the school environment, and an advocate for teachers within the home. 143 .A home-school liaison could provide in-service train- ings which focus on helping teachers and administrators understand the ramifications of parents' attitudes and family stress on school performance. They can be encour- aged to make parents feel welcome at school, to show respect of parents' knowledge of their children, to assume parents are interested in their children's well-being, and to communicate with parents in such as way that parents feel good about the interaction. A.home-school liaison can provide a positive link to the school for parents who have previous negative interac- tions with school staff. When a parent is openly hostile about the school, the emphasis should be on the children's needs to succeed in school and the necessity of good home- school relations in accomplishing this task. Microsystem Interventions School System Interventions The ways in which schools deal with attendance prob- lem vary widely. In many schools, policies only cover unexcused absences (M. Moreland, personal communication, December, 1992). Research findings indicate that both unexcused and excused absences should be considered when defining an attendance problem. While illness is often given as the excuse for absence, it may not be the reason. 144 Family System Interventions A.home-school liaison could provide direct interven- tion with families. Children and families who are experi- encing chronic stress are in need of support, or help in accessing support. Information on community resources should be available and parents should be referred to appropriate helping agencies for clothing, emergency assistance, medical care, or counseling services. It is important that parents learn how to be suppor- tive of their children's school experience. A home-school liaison can help parents understand how to support regular school attendance, appropriate classroom behavior, comple- tion of homework assignments and the importance of being responsive to school communications. (Wissbrun & Eckart, 1992). Child Centered Interventions Since little is known about the cause of shy, with- drawn behavior in the classroom, it is difficult to determine what intervention strategies should be used to address this problem. If these children are troubled by family issues, some type of home-based intervention may be appropriate. If their behavior is related to the school, then changes in the school environment may help. No matter what the cause of this behavior, teaching children coping skills may be helpful. In a 1980 study, two inter- vention conditions, one placebo condition, and a control 145 condition were compared for effectiveness in working with fifth and sixth graders who were withdrawn and depressed. It was found that depression scores and classroom behavior improved for children who participated in 10, one-hour role playing sessions which addressed problems such as peer rejection, success and failure, self-blame, and loneliness (Butler, Meiziti, Friedman & Cole, 1980). Suggestions _9; Future Research Although this study represents a small step in under- standing absenteeism in the early elementary years, some of the knowledge gained from the literature review and the research results suggests changes in methodology and in directions for future research. The findings of this study indicate that longitudinal research provides a more accurate picture of school attendance of young children than would data collected for one school year. Future research needs to include the means to track students who move to other school systems. This would enhance the generalizability of the research and provide data on children whose families are transient. Macrosystem Research The study identified a relationship between community level variables that measure school performance and at- tendance. More information is needed on how characteris- tics of the community are related to attendance problems. 146 Research that examines school performance over time in relation to an ecological assessment of the community (e.g. employment opportunities, characteristics of the school environment, demographics of the population) would add to the understanding of how sub-cultures come to place a high or low value on education. Exosystem Research Accurate information on the use of legal enforcement of compulsory attendance laws is needed. While it is often reported that Children's Protective Services will not deal with cases of educational neglect (T. Welke, personal communication, April, 1992; M. Moreland, personal communication, January, 1990) no empirical data seem to be available. Research that describes the use of prosecution to enforce compulsory attendance laws and the effectiveness of the procedure would be helpful in making future policy recommendations. Mesosystem Research Home-school interactions need to be measured direct- ly. Ways to measure the number of interactions, the reasons for the interaction and the tenor of the interac- tion need to be developed. Information needs to be gath- ered from parents, teachers and administrators to better understand what takes place at the home-school interface. 147 Microsystem Research School System.Research No research was identified that examined the rela- tionship between school level variables and elementary school attendance. In order to test a truly ecological model of attendance, without specification error, school system variables that measure system openness, attendance as a school goal, and school resources need to be included. Family System Research Several instruments need revising to measure varia- bles of interest with more accuracy. The Parent Attitude Toward Education Scale needs to be revised and items need to be specific to the experiences of the parent and the child. Family educational goals need to be measured in terms of resources as energy invested in education, a measure of actual behavior. A direct measure of lack of resources necessary for school attendance needs to be developed. Two chronic stressors were identified as predictors of absenteeism. Future research needs to focus on addi- tional chronic stressors such as conflict between family members, physically abusive family relationships, alcohol or substance abuse, and a reHuction in family income level to determine their influence on attendance. 148 The relationship between mother's educational attain- ment and child's attendance is a cause for concern. It indicates that there may be an intergenerational cycle of school failure which keeps families in poverty and sup- ports a two class system (Finn, 1987). Research that explores the intergenerational aspects of school attend- ance would clarify the importance of this finding. Research on Child Characteristics When Reid (1982; 1984) studied absenteeism, he asked secondary students why they were absent from school. Primary level children should be asked this same question. Barrett (1989) suggests that five to seven year olds are very aware of what they like and dislike about the educa- tional process, but that adults choose to ignore them as sources of information. Personal interviews with young absentees would undoubtedly add insight into why they were absent from school. More research to determine why children are withdrawn in the classroom is needed to design appropriate interven- tions for these children. It is necessary to determine if this behavior is most often caused by family problems, the school environment, or is related to personality charac- teristics of the child. 149 Conclusions In the post-industrial society in the United States, a great deal of emphasis is placed on regular school attendance. This is a relatively new phenomena that has developed over the last century as education as become more important to gaining entry into the job market and becoming economically self-sufficient. While a majority of young children have little prob- lem complying with compulsory education laws, there is concern about those who often are absent from school. The results of this study indicate that absenteeism may start in the early elementary years and, for a majority of young absentees, irregular attendance is a continuing problem. The results of this study supported part, but not all of the proposed empirical model of school attendance. The community in which children live, chronic stress in the family in the form of single parenthood and chronic ill- ness, the mother's own school attainment are environmental influences on school attendance. While it was hypothe- sized that a child's perception of success or failure in the school environment would lead to persistent absentee- ism, the only child level variable identified as influenc- ing school attendance was shy, withdrawn behavior. Findings indicate that several systems level inter- vention may improve school attendance for persistent 150 absentees. Community level interventions to change sub- culture values, enforcement of compulsory education laws, improving home-school relations and working with shy, withdrawn students to learn the source of their behavior and teach them coping skills may help young absentees experience school success and become self-sufficient adults. APPENDICES 151 Appendix A Letter to Parents Dear : A new program is under development in the elementary schools to encourage children's school attend- ance. In order to make sure that the School Success Program meets the needs of our students, we need to know more about the reasons children are absent from school. is working with us and would like to visit with you in your home and meet with in school to gather information on issues related to school attendance. IN exchange for you time and coopera- tion, you will receive a $10.00 food certificate. He will talk with you and your child again next year, and you will receive an additional $10.00 certificate at that time. (Please note: The $10.00 amounts are from a special state fund for this project. The money Lg pg; coming from the Schools' budget.) will be calling or writing you within the next week or two to schedule a meeting time. We look forward to your participation in our efforts to learn more about school attendance. Sincerely, Principal 152 Appendix B Consent Form Sometimes a child has a hard time getting to school on time or getting to school at all. The Schools and the School Success Program are working together to collect information about such children and we need your help. In order to increase our understanding of the reasons a child may be tardy or absent from school, we need input from parents and children. We will be interviewing you and your child at the following times: 1. Fall 1987 2. Fall 1988 3. Fall 1989 Your child's teacher will be requested to supply us with information on your child's progress in the classroom these times. Each time you are interviewed, you will receive food certificates worth $10.00. All information is gathered in a way that is sensi- tive and respectful of your family. The information will be kept strictly confidential unless you give written permission authorizing its release. When reports are made about the project, only group information will be provid~ ed. Your name and other identifying information will not be revealed. Remember that your participation is volun- tary and that you may withdraw at any time. Acceptance Agreement I authorize you to interview my child about how s/he feels about things that relate to school attendance. I have read and understand the above description of the School Success Program in the Schools. Parent Date School Success Staff Date 153 Appendix C Research Instruments CHILDREN'S STRESSFUL LIFE EVENTS I am going to ask you about some things that may have happened in the last year. Some might be difficult to recall exactly, just give your best estimate. 1. Did any of the following events happen to your child? How many times? a. move to a new home 0 1 2 3 4 5+ b. change schools 0 1 2 3 4 5+ c. have someone close die 0 1 2 3 4 5+ How many times did your child experience serious illness or injury? 0 1 2 3 4 5+ How many household members experienced serious illness or injury? 0 1 2 3 4 5+ Are any household members chronically ill or handicapped? 0 1 2 3 4 5+ How many new members have been added to your household? 0 1 2 3 4 5+ How many household members left either temporarily or permanently? 0 1 2 3 4 5+ Was there a major increase in the amount of fighting or conflict between household yes no members? How many marital separations were there between the child's parents in the last year? 0 1 2 3 4 5+ How many reconciliations were there between the child's parents last year? 0 1 2 3 4 5+ 10. 11. 154 Appendix C How many times did household members experience changes in employment (layoffs, new jobs, etc.)? 0 1 2 3 4 5+ Has the financial state of the household gotten worse? yes no 155 Appendix C PARENT ATTITUDE TOWARD EDUCATION SCALE I would like to learn how you feel about your child's education. When I read the following statements, please tell me if you agree strongly, agree somewhat, disagree somewhat, or disagree somewhat. Strongly Somewhat Somewhat A9ree Agree Disagree 1. On the whole schools do a good job in cooperating with parents. 2. Parent should back up the school in matters of discipline. 3. What children learn in the first years of school is the basis for future school success. 4. Most teachers let parents know when their child is having a problem at school. 5. Many school principals and teachers are too bossy in their attitude toward children. 6. Schools teach a lot of things that don't work out when you actually get on the job. 7. If a child doesn't do well in school it's probably the teacher's fault. 8. Some boys and girls are always getting tough breaks in school. 9. Teachers provide regular feedback about the progress a child is making in school. 10. In the early school years most classroom activities are. recreational (drawing, pictures, playing games, singing songs). Strongly Disagree 3 2 l 3 2 l 3 2 1 3 2 1 3 2 1 3 2 l 3 2 l 3 2 1 3 2 1 3 2 l 11. 12. 13. 16. 17. 18. 156 Appendix C Some teachers ask parents too many questions about how they treat the child at home. Teachers usually do the best they can in trying to teach what they are supposed to. There are times when teachers can't be blamed for losing patience with a pupil. Children should listen to the teacher and do what he/she says. It doesn't do any harm for pupils to skip school once in a while. Most boys and girls like to go to school every day. When parents try to explain why a child was absent or tardy, school staff usually don't listen. Most schools don't let the parents know enough about what's going on. 19. 20. 21. 24. Many teachers don't explain enough in their teaching. Even in the first years of school it is important for children to go to school every day unless they are ill. Parents feel free to contact teachers about their child at anytime. Most teachers treat the children in their classrooms fairly. The main reason I can see for going to school is that the law requires it. The best way to get a good job is to a good education. 157 Appendix C 25. The school is often to blame when 3 2 1 students don't like school. 26. Most parents share information with 3 2 1 teachers about family situations that may influence a child's school performance. I also would like to know what you would like your child to achieve in school. 27. What grades would you like your child to bring home on his/her report card? 28. What grade do you think your child will bring home on his/her report card? 29. How many years of school would you like your child to complete? 30. How many years of school do you think your child will complete? M" "M" 158 Appendix C 1 1 PREVENTION SERV'CES _ FAMILY LIMVWNO. Wmmlmmnl ACOSTGNTER NO. I z . . . I 1: ) I 1 l , 7 I srmsncu. race SHEET " mm” "mm" m "M” 4. O'ENING DAT! 1m- DAY. YR. B. 11an 1004“!!!“ _ L3_JL_:__JL_1_.’ 1 am 01: m m 1. uroarzoncomecnoumo- cum) I. nun oouuwovnesmncz gram 3 LEI-eon Comenan 'w.':‘:'L-_Jl_.i'l.-_J Code-LJ‘ LJ__'_-._1_‘ IQMIMYNOOH ILNTACT Imvmm) 12.3m6u"nuur rmwmm) 1,_C lam” owl—1.1 1!,D1am LBW Lamas... LDFMM 1105mm“ «Cm-com. u. , u. n n. n. n. n. 20. momma. sums At nmmou M Hun-u III-u ea... m 21. 22. 23. m hue-ca Elvin Lad (Bunion-1 m ”‘0'... h (m 1 - Ibis on. Day. w.) Gnu (m Sum m. 7m m “I. no or Gno- (3.. To (Ma. Dov. W.) and mom z-hmuo Cod" m 0040' fllflLlI-L a... ”*0 C3 113112] L_.__JL_L_JL_1_J L_J 1.1—J 1.1—J 1.1—1.4.1.44 Ll L_:_l LLJI—LJLJJ “""D C] 92:13 l—LJLJ—JLJ—J LJ L1._.1 L_L_J 1—L..1_.u_1_1__1 LJ l_:._.1 L4_1L_1_JL_'__1 “*0 CI CM] l_1_1L_1_.|L.z_J LJ L_:_J 1_.I__11—-L_.I__I_J_.L_1 L_J LLJ L_:_JL_.L_JL_1_J AND :1 'CJIU L1_.iL1_.ll_1_J LJ L..1_1 1_.I_Jml-—-l——L—_I_J_l__1 LJ L1_1 LLJL—LJL—J—J mu :1 cm L_1_ll_._Jl_:_J LJ L4_JL_L_J.L—1_I_L_1_s_l must—4L4. 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OM! or com (M... 001.?” LCM Lamas-n 1.DM CoorL-LJ L—LJL—H'l—J—J m MCHIGAN COUNTY CODES 01Alcona 159 Appendix C 18 Clare 35 losco 02 Alger 19 Canton 38 Iron 03 Alaqan 20 CraMord 37 Iaabela O4 Aloena 21 Delta 38 Jackson 05 Antnrn 22 Dickinson 39 Kalamazoo 08 Anna: 23 Eaton 40 Kalllaaka 07 Baraga 24 Emmet 41 Kent 08 Barry 25 Geneeee 42 Kaweenaw 09 Bay 28 Gladwin 43 Lake 10 Hanan 27 Gogebic 44 Lancer 11 Ben'ien 28 Grand Traverse 45 Leelanau 12 Branch 29 Gratiot 48 Lenawee 13 Calhoun 30 Hilledale 47 Livingston 14 Case 31 Houqhton 48 Luca 15 Chanevolx 32 Huron 49 Mackinac 18 Cheboygan 33 lngham 50 Macornb 17 Clippewa 34 1001. 51 Manistae '11 recipient is from REFERRAL SOURCE/REFERRED TO 52 53 54 55 56 57 56 59 60 61 62 63 64 65 68 67 68 Marguette 59 013990 Mason 70 Ottawa Mecoata 71 Presoue lala Menorninae 72 Roscommon Midland 7 Saglnaw Mieaaukee 74 St. Clair Monroe 75 St. Joseph Montcalm 78 Saniac Montmorency 77 Schoolcratt Muanqon 78 Shieweeaee Newaygo 79 Tuacola Oakland 80 Van Baron Oceana 81 Washtenaw Oqernaw 92 Wayne Ontonagon 83 Waxiond Osceola 84 Michigan County Oacoda Not Known out-of-state use county of service. 01 Agency-initiated loaned“ 02 Sell 03 Famiy or Frienda 04 Carey 08 Non-Psychiatric MO/DO 08 Police 07 Through Employment 08 School 09 (immunity Hospital 10 JailIPneon ETHNIC GROUP CODE 1 White 2 Black 3 Am. lnd'nn 4 Hispanic 5 Asian 8 Other (Enterthecodeonly onttlefirstllneif itiatheaarnetoral MW) 12 Other Community Agency 13 Other Community Mental Health Services Board: 14 Deoartmant of Social Services 15 Local Health Department 18 Vocational Rehabilitation Services 17 Department Living Facility 18 Slate MR Fatality 19 State MI Hospital 20 Court 21 Other 22 Not Referred EMPLOYMENT STATUS Currently Employed 01 Fol Time 02 Part Time 03ShelteredEmoloyment Unemplgyed 04 On Level: or Strike 05 Looking for Work (available last 4 weeks) 08 Not Looking for Work Not in Labor Force 07 Homemaker 08 Child 09 Student 10 Never Worked. Nonsmdent 11 Disabled 12 Retired 13 Other GROSS ANNUAL INCOME CODES 01 Less than 51.000 02 510004.999 03 32000-2399 04 53.000.3399 05 540004.999 06 $5.000-5.999 O7 36000-6399 08 $7.000-7.999 09 58000-8999 10 53000-9399 11 51000041399 12 51200044999 13 $1 5.000-24.999 14 $25,000-49.999 15 550.000 or more PRESENTING SITUATION CODES 01 Fri-Marriage 02 Mental 03 Divorce Related 04 Second Marriage 05 Intent lO-2 yr.) 08 Child (3-11 yr.) 07 Adolescent (12.18 yr.) 08 Adult Child (17+) 09 Retirement 10 Death 11 Disaster 12 Employment 13 Parenting 14 Other 160 Appendix C teacher-Child Rating Scale (T-ClSl Child‘s in , om 1mm Final (Last) (First) (circle one) Student‘: School 104 TeeCher School I. Please rate this child on the following v.ry ital-is hy circling the manner union ‘10! a Serious corresponds to this sciTe: Proolen Mild Moderate Serious Problem 1. Disruotive in class- ~ - - — - - - - ~ . - l 2 3 4 5 2. Hithdraln- - - - - . ~ - - - - - - - - - - 1 2 3 4 5 3. UnnereChievihg (not working to lbility)- - I 2 3 4 5 4. Fidgety, difficulty sitting still- - - 4 - l 2 3 4 5 S. Shy. tinid . - - - - - - — - . - - - - - - l 2 3 4 5 8. Poor work habits - - - - - - - . - - - - - I 2 3 4 5 7. Disturb: others while they are working . - l 2 3 4 S 6. Maimrs.~nrried---o~ooo----- 1 2 3 4 S 9. Poor concentration. limited IEZQHLlon soon I 2 3 4 S In. Constantly seeks attention - - - - - . - - l 2 3 '4 5 ll. Heryous. frightened. tense . - - - - - - - l 2 3 4 a 12. "lVIICuIty following directions- - - - - - 1 2 3 4 5 l3. Overly aggressive to peers (fightsl- - ~ . 1 2 3 4 S 14. fines not express feelings --------- l 2 3 4 3 15. Poorly activated to achieve- ~ ------ l 2 3 4 a 16. Defiant.-ohstinate. stubborn . - - - - . . l 2 3 4 S 17. Unhappy, sad - - - . . - . - . - . - - . - I 2 3 4 5 IR. Learning ecanenic sunjects - . - - . - - - l 2 3 4 S ' Problem Scale Ac:-0ut Shy-4h: Learn. Rae Score ll. “lease rate the following items according Not a: 4 Hooeretely Very to how sell they deserihe 52: child: 511 (51331; Bell Bell ‘2211 1. Accent: things not going his/her say - - . l 2 3 4 s 2. Oe'enns own vlees under group pressure ~ - l 2 3 4 S 3.‘Co~letesvortcoco-ro-o-oo-- I. 2 3 4 S 4. Has aany friends ; . . - - . . . - - . — . I 2 3 4 5 5. Ignores teasinq- - - - - - - . ----- . I Z 3 4 S 4. Confortanle as a leader- - . - . . - - - - l 2 3 4 S 7. Hell organized - - . - - ~ . - - - . ~ - - l 2 3 4 5 4. Is friendly toward deer: - - - - ----- I Z 3 4 5 9. Accents inoosed limit: . - - - ----- - l 2 3 4 5 10- "articlnates In class discussions. ~ - - - l 2 3 4 5 11. Function: well even eith distrec:ioh:- - - l 2 3 4 S 12. 4see: friends easily . - - . - . - - - - - 1 2 3 4 5 13. Cones well with failure- - - ~'- - - . - - l 2 3 4 5 I4. Exoresses ideas ellllnqu- - ~ - . - - . - l 2 3 4 5 15. Hort: well without adult suooorz - - - - . l 2 3 4 5 18. Classmates with to sit near this child - - l 2 3 4 5 l7. Tolerate: frustratidh- - - - - - - — - - - 1 Z 3 4 5 IS. Questions rules that seen unfair/unclear - 1 2 3 4 . S 19. 4 self-starter - - . - - - . - . - - - - - 1 Z 3 4 5 20. Hell liked by classaetes - - - - - - - - - 1 Z 3 4 S Conscience Scale Frust. - Assert. Task 0. ’eer Soc. Rae Score Cooyrignt©1988 by Prinary Hental Health Project. Inc. All right: reserved. Name 161 Appendix C What I Am Like Age Boy or Girl (circle which) Really Sort of True True for me for me (a) IJJD F J Birthday Month Day SAMPLE SENTENCE Some kids would rather play outdoors in their spare time Some kids feel that they are very good at their school work Some kids find it hard to make friends Some kids do very well at all kinds of sports Some kids are happy with the way they look Some kids Often do nor like the way they behave Some kids are Often unhappy with themselves Some kids feel like they are just as smart as as other kids their age Some kids have slot of inends BUT BUT BUT BUT BUT BUT BUT BUT BUT Other kids would rather walcn T.V. Other kids worry about whether they can do the school work assigned to them. Other kids find it’s pretty easy to make friends. Other kids don't feel that they are very good when it comes to sports. Other kids are not happy with the way they look. Other kids usually like the way they behave. Other kids are pretty pleased with themselves. Other kids aren't so sure and wonder if they are as smart. Other kids don't have very many friends. 162 Appendix C Really Sort ol True True S1ort of Fleelly for me for me forge is”; 10. 11. 12. 13. 14. 16. 17. 18. 19. 20. JDDH "'1' Some kids wish they could be alot better at spons Some kids are happy with their height and weight Some kids usually do the right thing Some kids don’t like the way they are leading their life Some kids are pretty slow in finishing their school work Some kidswould like to have alot more friends Some kids think they could do well at just about any new sports actlvity they haven't tried before Some kids wish their body was different Some kids usually act the way they know they are supposed to Some klds are happy with themselves as a person Some kids often forget what they learn Some kids are always doing things with alot of kids BUT BUT BUT BUT BUT BUT BUT BUT BUT BUT BUT BUT Other kids feel they are good enough at sports. Other kids wish their height or weight were different. Other kids often don't do the right thing. Other kids do like the way theyl are leading their life. Other kids can do their school work quickly. Other kids have as many friends as they want. Other kids are afraid they might not do well at sports they haven't ever tried. Other kids like their body the way it is. Other kids often don't act the way they are supposed to. Other kids are often not happy with themselves. Other kids can remember things easily. Other kids usually do things by themselves. 21. 23. 24. 25. 26. 27. 28. 30. 31. 32. 163 Appendix C Really Sort of True True 5:21;” “13:? for me for me for me for me .__‘, Some kids feel that they are better than others BUT their age at sports Some kids wish their physical appearance (how BUT they leek) was different Some kids usually get in trouble because of BUT things they do Some kids like the kind of person they are BUT Some kids do very well at their classwork BUT Some kids wish that more people their age BUT liked them . in games and sports some kids usually watch BUT instead of play Some kids wish something about their BUT face or hair looked different Some kids do things they know they BUT shouldn't do Some kids are very happy being the way BUT they are Some kids have trouble figuring out the answers BUT in school Some kids are popular with others their age BUT Other kids don't feel they can play as well. Other kids like their physical appearance the way it is. Other kids usually don't do things that get them in trouble. Other kids often wish they were someone else. Other kids don 't do very well at their classwork. Other kids feel that most people their age do like them. Other kids usually play rather than just watch. Other kids like their face and hair the way they are. Other kids hardly ever do things they know they shouldn't do. Other kids wish they were different. Other kids almost always can figure out the answers. Other kids are not very popular. Really Sort of True True for me for me 34. 36. Susan Harter. Ph.O.. Univ 1 6 4 Appendix C Some kids don't do well at new outdoor games Some kids think that they are good looking Some kids behave themselves very well Some kids are not very happy With the way they do alot of things ersity of Denver, 1985 BUT BUT BUT BUT Other kids are good at new games right away. Other kids think that they are not very gooo looking. Other kids often find it hard to behave themselves. Other kids think the way they do things is fine. Sort of True for me Really Tnte for me iii 165 Appendix D MICHIGAN STATE UNIVERSITY OFFICE Of VICE PRESIDENT fOI RESEARCH EAST LANSING ° MICHIGAN 0 “Bu-l0“ AND DEAN OF THE GRADUATE SCHOOL January 12. 1993 TO: Ms. Cynthia A. Cameron PO. Box 111 Mulliken. MI 48861 RE: .IRB 1: 92-625 TITLE: THE INFLUENCE OF FAMILY CHARACTERISTICS ‘ON ELEMENTARY SCHOOL ATTENDANCE: A FAMILY ECOSYSTEMS MODEL REVISION REQUESTED: N/A CATEGORY: l-E APPROVAL DATE: 01/12/1993 The University Committee on Research Involving Human Subjects' (UCRIHS) review of this project is complete. I am pleased to advise that the rights and welfare of the human subjects appear to be adequately protected and methods to obtain informed consent are appropriate. Therefore. the UCRIHS approved this project including any revision listed above. UCRIHS approval is valid for one calendar year. beginning with the approval date shown above. Investigators planning to continue a project beyond one year must seek updated certification. Request for renewed approval must be accompanied by all four of the following mandatory assurances. I. The human subjects protocol is the same as in previous studies. 2. There have been no ill effects suffered by the subjects due to their participation in the study. 3. There have been no complaints by the subjects or their representatives related to their participation in the study. 4. There has not been a change in the research environment nor new information which would indicate greater risk to human subjects than that assumed when the protocol was initially reviewed and approved. There is a maximum of four such expedited renewals possible. Investigators wishing to continue a project beyond that time need to submit it again for complete review. UCRIHS must review any changes in procedures involving human subjects. prior to initiation of the change. Investigators must notify UCRIHS promptly of any problems (unexpected side effects, complaints. etc.) involving human subjects during the course of the work. If we can be of any future help, please do not hesitate to contact us at (517) 355-2180 or FAX (517) 336-1171. ‘ +— Sincerely. avid 5. Wright. Ph.D. UCRIHS Chair DEW:pjm cc: Dr. Robert Griffore "SC is on Al/rmarr’r'e Action/Equal Opportunity Institution 166 Appendix E March 25, 1993 Cynthia Cameron Prevention Services Michigan Department of Mental Health Lewis Cass Building Lansing, MI 48913 Dear Ms. Cameron: As Director of the Primary Mental Health Project, I give you permission to include a copy of The Teacher-Child Rating Scale (T-CRS) in the appendix of your report we discussed. Also, thank you for observing the copyright laws and I would very much like to receive a copy of that report for our files. Sincerely, A. Dirk Hightower, Ph.D. Director 167 Appendix E Dwmdmndoffiyfidqm March 24, 1993 Ms. Cynthia Cameron Prevention Services Michigan Department of Mental Health Lewis Cass Bldg. Lansing, MI 48913 Dear Ms. Cameron, This letter is to give you permission to use the Self-Perception Profile for Children in your project. You may copy the instrument as needed for your project. I hope that you have found this instrument useful for your project. Sincerely yours, Ari“: Susan Harter Professor BIBLIOGRAPHY Abbott, E. & Breckinridge, S. (1917). Truancy ggg Egg; attendance Lg the Chicago Schools, Chicago: The University of Illinois Press. Alwin, D. Thornton, A. (1984). Family origins and the schooling process: Early versus late influence of parental characteristics. American Sociological Review, 49, 784-802. Andrews, M., Bubolz, M., & Paolucci, B. (1980). An ecological approach to study of the family. Marriage 5 Family Review, 3(1/2) 29-50. Barrett, G. (1989). A child's eye-view of schooling. In G. 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