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COMPUTERIZED NUTRIENT ANALYSIS
FOR FOODSERVICE INSTITUTIONS

By

Renee Ann Hart

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF SCIENCE

Department of Food Science and Human Nutrition

1983

ABSTRACT

COMPUTERIZED NUTRIENT ANALYSIS
FOR FOODSERVICE INSTITUTIONS

By

Renee Ann Hart

The Objective of this study was to assess what features
foodservice professionals perceive they need in a computerized
nutrient analysis system. Foodservice directors affiliated with
hospitals, nursing homes, colleges and universities, elementary
through secondary schools and correctional institutions were randomly
selected and interviewed about their perceived need for computerized
nutrient analysis. Fewer than half (37%) of the respondents. were
using computers in their department. Foodservice management software
was used most by these respondents who were primarily from educational
institutions; no nutrient analysis software was used currently.
Respondents (63%) who were not using a computer stated computerized
nutrient analysis would be useful. Most non-computer users were
affiliated with hOSpitals and nursing homes. Components of nutrient
analysis respondents thought would be useful were: plans menus based
on dietary requirements for individuals or groups (84%); analyzes
menus for nutrient content (82%); and analyzes percent Recommended
Dietary Allowance for a menu (82%). Respondents preferred a nutrient
data base of nine nutrients over larger or smaller data sets.
Information from this study can be used by foodservice professionals
to learn of features available in nutrient analysis programs and by

professionals designing and marketing nutrient analysis software.

 

ACKNOWLEDGEMENTS

The author extends sincere thanks to the following people:

To Dr. Kathryn Kolasa for her total support and guidance
throughout this research and my graduate program, despite the miles
between us. Her high expectations were Challenging and provided
encouragement for timely completion of this study and thesis.

To Jean McFadden for her practical advice and confidence in tne
research project. Her consistent thoughtfulness was very appreciated.

To Burness Wenoerg for offering insights and companionsnip during
the late hours Spent implementing the study and analyzing the results.

To Irene Hathaway for Sharing her expertise in microcomputers and
her encouragement to learn more about computer applications in the
home and classroom.

To Jonn and Josalee Bircnfield for their professional advice and
the opportunity to apply my knowledge and research results toward the
development of a nutrient analysis program.

To the study participants who tOOK time to answer the
questionnaires.

To the Department of Food Science and Human Nutrition for partial
financial support.

A special thank you to Linda Hansen for her excellent suggestions
and patience throughout my graduate program.

To Regina Mdncn, Alexis Alexander, Jonn Kallas and Grace Marquis
for providing emotional support, suggestions and friendsnip.

To my parents, Crystal and Ropert Hart, whose prior guidance and

support made this thesis possible.

Finally, to my dependable "sounding board", Ken Squire, for

helping me maintain perspective during my graduate program.

Page

Introduction ......................... . I
Literature Review ....................... 3
Computer Stored Nutrient Data Base ............. 3
Computerized Nutrient Analysis ............... 6
Review of Current Nutrient Analysis Software ........ l2
Methods and Procedures ..................... l5
Development of the Data Collection Instrument ....... l5
Sample Selection ........ . . . . . . ........ 2l
Data Collection . . . . . . . . . . . ........... 24
Approval of Researcn Involving Human Subjects ....... 25
Analysis . . . ....................... 26
Results and Discussion . . . . . ................ 27
Response and Participation Rates .............. 27
Sample Characteristics . . . . ............... 28
Computer Use and Availability ............... 36
Computer Users . . . . . . . ................ 37
Non-computer Users . . . . . . . . .......... 45
Components of Nutrient Analysis Software . . ‘ ........ 49
Results from Self- Administered Mail Questionnaire ..... 55
Selected Nutrient Analysis Programs ............ 57
Conclusion . . . . . . . . . . ............... 66
Summary . ...... . .................... 68
References . . ......... . .............. 73

Appendices
Appendix
Appendix
Appendix
Appendix

Appendix

TABLE OF CONTENTS

Nutrient Analysis for Foodservice Institutions . 80

Advance Letter to Respondents ......... 93
Consent Form . ................. 95
Nutrient Analysis Software Evaluation ..... 96

Review of Nutrient Analysis Software Brochures . 108

Table
Table
Table
Table
Table
Table
Table

Table

Table

Table

Table

Table

Table
Table
Table

Table

lO.
ll.

l2.

l3.
IA.
15.
16.

LIST OF TABLES

Institutions where Respondents were Employed .....
Type of Respondent, by Institution ..... . . . . .
Clientele Fed, by Institution
Source of Funding, by Institution ..........
Menu Cycle, by Institution ..............
Respondents Use of Computers ....... . . . . . .

Respondents Computer Availability, by Institution

Comparison of Foodservice Software: Reported by
Respondents with Computer Available to Department . .

Intention to Purcnase Nutrient Analysis Software,
by Institution ......... . ..........

What Inspires Respondents to Purcnase Software . . . .

Characteristics of Non-computer Users, by
Institution ..........
Components of Nutrient Analysis Software:
Perception . .

Respondents'

Statistically Different Software Components . . . . .
Nutrient Analysis Programs Selected, by Institution .
Selected Program Based on Cost, by Institution . . . .

Nutrients to be Analyzed, by Institution .......

Page
29

3O
32
33
35
37
38

4O

42
44

46

SO
52
60
62
65

Figure
Figure
Figure
Figure
Figure
Figure

Figure

5.

LIST OF FIGURES

Page

Directories for Sampling ............... 22
Measure Codes Selected by Respondents . . . . . . . . 56
Modification of Measure Codes ............ 57
Preferred Nutrient Analysis Program ......... 59
Modification of Nutrient Analysis Programs . . . . . . 6l
Respondents Selection of Programs Based on Cost . . . 63

Nutrients Selected to be Analyzed by Nutrient Analysis
Software . . . ...... . . ............ 64

INTRODUCTION

Computers have been used in the area of food and nutrition since
l958 (Hoover 198l). Initially the application of the computer was to
calculate recipe yields, assist with menu writing, simplify budgeting
and analyze nutrition research (Lowder and Medill l958; Callahan and
Aldrich l959; Caster l962; Goodloe, et al. l963; Hartman l964).
Through the years computer applications have become more refined and
flexible. Complex nutrition-related programs have evolved. Programs
are now available whiCh monitor the precise amount of liquid or solid
foods a patient consumes (Kissileff, et al. l980; Giacoia and Chopra
l98l). Programs are also available whiCh analyze the nutrients in an
individual's diet, in a menu, or in a recipe (Bell, Hatcher, Chan and
Fraser l979; Allington, et al. l980; Hoover and Perloff l98l, Brown,
et al. l982; Miller l982; Hoover l983; Hoover and Perloff l983;
Youngwirth l983). These programs are known as nutrient analysis and
were the focus of this study.

Computerized nutrient analysis has :nany applications. For
instance, the speed and reliability of some computerized nutrient
analysis programs make it a useful tool for institutions wnicn require
detailed nutrient information (Flook and AJford l974). In addition,
nutrient analysis software can be used for nutrition education, such
as simulated clinical encounters (Breese, et al. l977) or to teach
nutrition concepts to school children (Anonymous l978). Computerized
nutrient analysis can be used in foodservice kitChens and cafeterias
to display the nutrient content of foods served. With increased

public awareness of nutrition and health, foodservice arcnitects and

2

foodservice directors will have to design facilities whicn sell foods
based on attractiveness, good taste and the consumers' demand to know
the nutrient content of the food (Anonymous l98l; and. Bircnfield
l983). Nutrient analysis software also could be used to document for
state or federal government regulations the nutrient content of foods
served to patients or residents (Weyand l976; Roger 1983).

To the investigator's knowledge, there is no literature describing
the components or features of nutrient analysis software most
applicable to various institutions and their operations. Therefore,
this study was developed to systematically describe the
state-of-the-art of computerized nutrient analysis for foodservice
institutions. The investigator's Objective was to assess what
foodservice professionals perceive they need in computerized nutrient
analysis for hOSpitals, nursing homes, colleges and universities,
elementary through secondary schools and correctional institutions.
These various groups were interviewed to determine if there were
similarities and differences in their needs. Foodservice
professionals could utilize this information to determine whicn
features or components of a computerized nutrient analysis system may

be applicable to and functional for their institution.

LITERATURE REVIEW

Computers have been used for nutrient analysis since 1962
(Thompson and Tucker l962). In l983 there are at least 35
computerized nutrient analysis programs whiCh operate on micro- or
mainframe computers (Nutrition Information and Resource Center l982;
Brown l983; Freifeld 1983). These programs range in price from $20 to
$l,000. Nutrient analysis software is advertised and sold to three
target markets: (l) nutrition and foodservice professionals, (2)
educators, and (3) home computer users. The major component of

nutrient analysis software is the computer stored nutrient data base.

Computer Stored Nutrient Data Base

 

Computer stored nutrient data bases contain data on the nutrient
composition of foods. The data are usually derived from food

composition tables such as Agriculture Handbook No. 8: Composition of

 

Foods...Raw, Processed, Prepared (United States Department of

 

Agriculture, l975). All nutrient data bases are not alike; they
differ in the number of food items and nutrients whicn can be analyzed
(Anonymous l982).

Problems with computerized nutrient data bases have been reported
by Danford (l981) and Hoover (l983) such as differing nutrient
analysis results when a single day's diet is analyzed by ll
computerized nutrient analysis programs. This problem is being
monitored through the National Nutrient Data Bank Conferences
(NNDBC). One of the purposes of the NNDBC is “to promote the

maintenance of accurate nutrient data bases and the development of

4
reliable computer programs to use with the data bases" (Hoover and
Perloff 198l).

An accurate and comprehensive computerized nutrient data base is
important if a computer system is to perform various calculations
(Willard l982). For example, such a system would be able to
calculate: (l) nutrients for a recipe or menu; (2) nutrients on a per
serving or common measure oasis; (3) percent Recommended Dietary
Allowances for specified sex-age categories; (4) percent of total
daily intake of a specified nutrient from designated food groups; (5)
an Index of Nutritional Quality (INQ); (6) household measures to
metric equivalents; and (7) graphic display' of‘ output (Hoover and
Perloff l98l).

Several computerized data bases with multiple capabilities have
been developed. At this time the authors and users of these systems
are responsible for the accuracy and reliability of the data base
(Hoover and Perloff l983). Since users may not have the expertise to
assess the data base, Hoover and Perloff (l983) developed a review
model to assess computational procedures and evaluate the nutrient
data utilized in the computations. Perloff (l982) stated, a: data
base, consisting of United States Department of Agriculture (USDA)
food composition data, is accurate and current. At USDA trained
specialists evaluate the data based on sample selection, handling and
representativeness, date (Mi analysis, methodology, data reliability,
and if appropriate, validity of data. Other data sources Should be
investigated for reliability and accuracy using the review model or a

modified version.

5

Reviewing and assessing the data base accuracy of computerized

data base systems will help foodservice or nutrition professionals

begin

to select appropriate nutrient analysis software for their

institution. However, after reviewing literature, it: is clear other

factors must be considered including:

A definition of the type of nutrient analysis information the
staff and clients need.

Utilization of the analysis system for nutrition education, diet
evaluation, dietary risk screening and regulatory or legal
documentation.

An evaluation of existing nutrient analysis software. The
market should be researched to determined what is accurate and
inaccurate nutrient analysis software.

A determination of the type of hardware needed. Research that
would best meet the needs of the institution or department, find
out what similar institutions are using, consider the cost
effectiveness and flexibility of the hardware for accommoaating
future uses.

A determination of tne types of analysis desired suCh as recipe
analysis, individual diet analysis, percent Recommended Dietary
Allowances and nutrients per kilogram body weight.

A determination of the type of training necessary for
individuals who will use the software and hardware.

A decision should be made concerning the nutrients and foods to
be analyzed.

A determination of the type of print-out desired is necessary.

An estimation of the cost of the hardware and software is needed.

Computerized Nutrient Analysis

 

Nutrient analysis software can be defined as a set of step-by-step
instructions that tell the micro- or mainframe computer how to
calculate, using the nutrient data base, the nutrient content of a
diet, menu or recipe. Hardware is the computer and peripheral
equipment necessary for running the software. A computerized nutrient
analysis system consists of the data base, software and hardware
(Hillard l982). These systems can be developed in-house, purcnased
fronl a vender, leased or Obtained through a combination of these
options.

Foodservice and nutrition professionals affiliated with hOSpitals,
nursing homes, elementary through secondary scnools, colleges and
universities and correctional institutions have expressed interest in
computerized nutrient analysis programs (Neyand l976; Anonymous I978;
Wyse l979; Danford l98l; Finley and Simpson 1982; Seliger l98l;
Jonnson, et al. l982; Scnuler' and Fuller l982; Willard l982; Chin
l983; Youngwirth l983). Each institution's general uses for
computerized nutrient analysis will be outlined in the following
paragraphs.

Hospitals. Computers were first used in hospitals for foooservice
management. In l962, Tulane University designed the program,
Computer-Assisted Menu Planning (CAMP), to plan low cost and
nutritious menus (Balintfy and Nebel l966). Today, more sophisticated
inventory, purcnasing, forecasting, and production control programs
are being used in hOSpitals (Youngwirth l983). Reduced food costs
have resulted from using computer programs whicn ensure efficient

inventory management, recipe standardization, quantity and quality

7
control of food preparation, production and service (Bergaila and Pope
I977; Hart 1978; Tuthill l980; SChuster 198]). Bergaila and Pope
(l977) reported ccomputers can decrease labor costs tu/ reducing the
amount of clerical work and eliminating some positions.

Increasing attention is being given to nutrition-related computer
applications, specifically, computerized nutrient analysis (Willard
l982; Youngwirth l983). Flook and Alford (l974) have shown computer-
assisted nutrient analysis is less costly than nmnual calculations.
Computerized nutrient analysis can also relieve tne dietitian of
clerical ta5ks, resulting in more effective use of the dietitian's
time for nutrition education and patient counseling (Flock and Alford
l974; Miller l976; Dorea, et al. l981; Seliger l98l; Chin l983).

Computerized nutrient analysis requires the appropriate hardware.
Programs are available which operate on mainframe computers,
microcomputers and programmable calculators. Dorea and coworkers
(l98l) have described a semi-automatic method for analyzing food
intake data using a programmable calculator. According to the
investigators, benefits of this method include: (l) less costly than
using a mainframe or microcomputer; (2) no sophisticated data
processing skills are needed; and (3) suited for small hospitals and
clinics. In addition, relatively inexpensive nutrient analysis
software for microcomputers can be purcnased from software vendors or
publishers. However, the accuracy and reliability of the data vary
widely.

Many computerized nutrient analysis programs can be purcnased.
These programs have different data. base characteristics suCh as:

editing availability ability' to plan menus, analyze) recipes and ‘to

8
graphically display the output. There is no literature describing the
features of computerized nutrient analysis hospital nutrition
professionals perceive as most functional, beneficial and neCessary.

Nursing Homes. Use of computerized nutrient analysis in nursing

 

homes is not well documented. However, Johnson and coworkers (l982)
have used computers to reduce tne time spent calculating dietary
intake from food composition tables. These researchers advocate using
a data base containing commonly eaten foods or core foods and
programmable calculators or microcomputers. Sucn a small computer
system could enable consulting dietitians to more easily transport a
nutrient analysis system to nursing homes to provide elderly and
geriatric persons with nutrition education and counseling.

The dietitian's role in nursing homes is expanding and includes a
focus on nutrition assessment (Madlin l983). -A small computerized
nutrient analysis systen1 may be useful to nutrition professionals
working ‘Hl nursing homes to analyze the nutrient. content. of 'foods
eaten by residents and to teach basic nutrition concepts to the
elderly. The program would be useful for calculating frequenly
prescribed dieabetic and restricted sodium diets. However, there is
no literature describing the type of computerized nutrient analysis
systenl most useful for’ diet planning, nutrient analysis, nutrition

counseling and education of nursing home residents.

Schools: Elementary through Secondany. Most computers in
foodservice departments of elementary through secondary scnools are
used for inventory, pre- and post-costing of menus, free and reduced-

price meal recording, revenue reporting, meal counts and menu planning

9
(Anonymous l976; Lewis l98]; McGlone l98l; Stephenson 198l; Snow l982;
SChuler and Fuller l982). Computerized nutrient analysis is used in
some schools for nutrition education (Lewis l98l; Miller l982; Scnuler
and Fuller l982) and to analyze menus and meal patterns for
nutritional quality and portion size (Schuler and Fuller l982).

Applebaum (l982) suggested that tne public's interest in
nutrition, along with parental demand, will encourage schools to
provide nutrition education to students. Software has been developed
to teacn selected nutrition concepts to school students (Anonymous
l978; Nutrition Education and Training l982).

Nutrient analysis software has been used tn/ teacners because it
provides a basis for making rational food choices through menu
planning (Lewis l98l; Miller l982). Learning to plan meals and
interpreting the nutrient analysis output involves working with
numerals, graphs, percentages and basic mathematic calculations.
Therefore, students need some skill in these areas before attempting
to use and understand nutrient analysis software.

However, scnool foodservice departments have low priority for
computerization; payroll, test correcting and student records are
priorities for school computer use (Stephenson l98l). In addition,
professionals from computerized school foodservice departments have
recommended thatnon-computerized school districts first computerize
the information that is high-volume and labor-intensive, sucn as
inventory records, or information that is needed on a timely basis

(Stephenson l98l; Schuler and Fuller l982).

10

Schools: Colleges and Lhfiversities. Foodservice departments in

 

many colleges and universities use some type of computer software for
recipe precosting, purChasing, inventory control, dining room access
control, payroll or accounts receivable and payable (Jacoos l982;
Finley and Simpson l982; Ricnie l983). Nutrient analysis software is
not commonly used in university or college foodservice.

In colleges and universities, computerized nutrient analysis is
used mostly by the academic departments to assist students in
analyzing diets, recipes and menus. Ohio State University was one of
the first universities to use Computer-Assisted Instruction (CAI).
The purpose of Ohio State's CAI program was to assist dietitians,
nurses and medical students in learning to evaluate the nutrient
content of diets or genus, calculate therapeuth: diets and nutrient
intake records, and analyze recipes (SChaum l973).

Computerized nutrient analysis has also been used to assist
students counseling patients on dietary needs (NltSChl, et al. l976).
Using a computer-based dietary counseling system designed to interview
patients about eating patterns and help them plan a l,500 kcal. weight
reduction diet.

Ricnie (l983) reported, that more university and (nullege
foodservice departments are demonstrating a commitment and
responsibility for food and nutrition education. Reports of college
and university foodservices posting the nutrient content of foods
served have been heard but the actual use of nutrient analysis
software in college cafeterias to teacn nutrition educathm1 has not
been documented. The use of computers in university foodservice has

been investigated by Finley and Simpson (l982). These investigators

ll
found 35 percent of 34 foodservice directors studied had a nutrition
analysis of their recipes. The researcners did not mention if the
recipes were analyzed within the department or by an external service.

Computerized nutrient analysis has been used for nutrition
education outside of the college classroom and cafeteria. For
instance, a study conducted by Texas Agricultural Extension Service
provided free, computerized nutrient analysis of 24-hour food recalls
to individuals 'U1 32 sites in Texas. The results of the study were
used to determine future nutrition education programs such as a weight
control program for teenage girls and a statewide program on
nutritious snacking (Ryan-Crowe, et al. l982). A similar program has
been used by Nfichigan State University Cooperative Extension Service
to help teacn homemakers basic nutrition concepts (Nutrition SpotcheCK
l981).

Computerized nutrient analysis also has been used by nmthers in
women, Infant and Children (NIC) clinics to assess their' diet and
their children's diets (DeSKins and Thorne l982). Where tne nutrient
analysis software was "user-friendly", foods did not have to be locked
up in a table, instead mothers could choose foods from a list on the
screen by typing I'yes" or "no". In addition, smiling or frowning
faces, colored graphic bar Charts and musical sounds were used to tell
the mother if she was choosing a good diet for herself and Children.
These are only a few example of applications in a nonformal

educational setting.

Correctional Institutions. Use of computers and computerized

 

nutrient analysis in correctional institutions is not well

12

documented. However, concern has been expressed regarding the
nutritional adequacy of food served in jails and prisons (weyand
1976). For instance, from 1854 until 1957, food served in the Utah
State Prison was seldom nutritionally adequate nor attractively
served; potatoes, gravy, beans, pasta, mush and bread were considered
a sufficient diet (Richardson 1980). In addition, many prison
foodservice departments do not prepare therapeutic diets for inmates
with diabetes or hypertension (Coani 1982). until recently inmates of
the Oklahoma State Correctional System on bland, low sodium or
diabetic diets were reportedly fed pureed food ‘thCh contained no
sodium or sugar (Coani 1982).

There are no reported studies assessing if foodservice directors
in correctional institutions need computerized nutrient analysis and
if they do, how would they use it. It is possible nutrient analysis
software could be used in correctional facilities as documentation
against accusations that inmatess received "cruel and unusual
puniShment“ by being served nutritionally inadequate food (Ricnardson

1980).

Review of Current Nutrient Analysis Software

 

There are at least 35 nutrient analysis software programs
currently marketed. These programs operate on mainframe computers,
microcomputers. Nutrient analysis software is advertised and sold to
three major tarket markets: (1) nutrition and foodservice
professionals, (2) educators, and (3) home computer users. Therefore,
features or components of the software may differ. For instance, a

program targeted for* a dietitian may contain 21 nutrients in the

13
nutrient data base, and a program marketed to an elementary school
teacner may have a nutrient data base consisting of five nutrients.

Nutrition professionals should know what types of nutrient
analysis software are being advertised and sold. One way to find out
is to evaluate the actual programs. A thorough evaluation is tedious,
time consuming and expensive. Obtaining the program can be costly.
However, some vendors or publishers do lend, rent or give away the
software. Nutrient analysis software run on different operating
systems. For an individual to evaluate 35 programs, they would need
access to various models of microcomputers and mainframe computers.

Another, more general method to find out what kind of software is
marketed is to write vendors, authors and publiShers for their
software brOChures or promotional materials. Seventeen nutrient
analysis programs have been reviewed based on' information Obtained
from promotional materials (Appendix 0). Most of the software
reviewed operated on microcomputers. Five of the programs were
nutrient analysis services which analyzed individual diets at £1 cost
ranging from $13 to $18. Only one program reviewed could immediately
be considered inappropriate and inaccurate; in addition to a diet
analysis, a hair analysis service also was promoted.

The number of foods in the data bases ranged from 136 to over
13,000. Total number of nutrients analyzed ranged from 13 to 74.
Almost all software used the 1980 Recommended Dietary Allowances (RDA)
(National Academy of Science 1980) as a standard for nutrition needs.
Specific tasks possible to perform with the software were rarely
included in the promotional brochure. In most cases this reviewer was

unable to determine if the programs provided suggestions to improve an

14
individual's diet, if it helped plan menus, or what food groups were
analyzed by the program.

Promotional brochures serve to outline and sell tne nutrient
analysis software or the service. It is fbr this reason the ggtggl
program must be evaluated. Inaccuracies in the explanation of
nutrition or data base sources are difficult to determine from a
brochure. In addition, the display of nutrient analysis results, the
quality print and ease of use can only be determined by evaluating the
actual program. Evaluation forms similar to the one in Appendix 0
should be develOped to thoroughly evaluate specific nutrition software.

A need for nutrition professionals to evaluate the nutrition
software sold to consumers, educators and colleagues exists. Members
of the Society for Nutrition Education are currently organizing a
computer software evaluation committee to meet this need (Journal of

Nutrition Education 1983).

METHODS AND PROCEDURES

Foodservice directors were randomly selected and surveyed about
computerized nutrient analysis. The survey instrument was a telephone
interview and a self-administered mail questionnaire. The foodservice
directors were affiliated with hOSpitals, nursing homes, elementary
through secondary schools, colleges and universities, and correctional
facilities throughout the United States.

Data were collected using an original telephone and mail
questionnaire. A pretest of the survey instrument was conducted with
‘two foodservice instructors and five foodservice directors or
dietitians representing nursing homes, scnools, correctional
facilities and hospitals.

The questionnaires were designed to collect information about the
«:omponents. of’ nutrient analysis software programs foodservice
department directors perceived as important for computerized nutrient
analysis. Specific areas of inquiry included institutional
(demographic characteristics, computer availability, computer software
used, nutrients, foods and measure codes desired for nutrient analysis

software.

Ilevelopment of the Data Collection Instrument
Description of the Data Collection Instrument. The instrument
used to collect data was a telephone questionnaire, Part A, and a

self-administered mail questionnaire, Part 8 (Appendix A).

15

16

The telephone questionnaire, Part A, contained 15 closed- and
Open-ended questions. The questionnaire had five areas of inquiry:
institutional characteristics, availability of computers, software
programs used, preference for computers, and opinions about usefulness
of nutrient analysis software components.

The mail questionnaire, Part B, was composed of closed- and
open-ended questions. The questions asked respondents to select
sample nutrient analysis programs. based (N1 the following: measure
codes, nutrients and foods to analyze, and cost of program. Two
open-ended questions aSKed respondents to modify or comment on sample
programs selected.

The first questions 'hi the telephone interview were demographic.
These questions described the random sample by identifying the
respondent's position 'h1 the institution, departmental name, type of
menu cycle, source of funding and clientele fed.

The availability of a computer to the foodservice directors was
studied to assess the types of computers and software used and the
functions currently performed on the computer. Respondents who used a
computer and nutrient analysis software were asked detailed questions
regarding use and likes and dislikes of the nutrient analysis
software. When a computer was not available, the respondents were
asked if they would want a computer and if computerized nutrient
analysis would be useful to their institution.

A series of questions about usefulness of components of nutrient
analysis software were asked to those respondents witn and those
without computers. A brief introduction was given to eacn respondent

explaining the questions and possible answers.

17

The components of nutrient analysis software studied were those
available in nutrient analysis software currently marketed.
Respondents were asked if there were components or features they would
like to add and to what degree of usefulness was the component.

A simple definition of hardware and software introduced
respondents to computer questions. The questions addressed
departmental and respondents' use of computers.

Three sample nutrient analysis "programs" were introduced in the
self-administered mail questionnaire (Appendix A). The first sample
"program" consisted (fl: eight nutrients and seven categories of food
whicn could be analyzed by nutrient analysis software. The next
"program" consisted of 19 nutrients and 10 categories of food for
analysis and "program" three consisted of 37 nutrients and twelve
categories of food which could be analyzed. The sample "programs"
were selected as representative of nutrient analysis software
currently marketed. ReSpondents were given the opportunity to modify

one of the nutrient analysis "programs".

Rationale for Selection of Data Collection Instrument. A

 

telephone interview is usually completed more quickly than the
face-to-face interview or mail questionnaire (Parten 1950; Kidder
1981). Hockstin: and Athanasopoulos (1970) and Dillman (1978) have
reported high numbers of desirable answers from telephone interviews.
Telephone interviews may have response rates as high as 84 percent to
95 percent (Berdie 1973; Dillman 1978). For this study the telephone
interview was selected as Part A of the survey because it is

relatively quick and response rate is high compared'to mail

18
questionnaires. These factors outweighed the disadvantages associated
with telephone interviews such as improper data. collection due to
deliberate: hang-ups (Parten 1950) and partially answered (open-ended
questions (Payne 1974).

This investigator asked most computer questions during telephone
interviews. Thus, it was possible to explain computerized nutrient
analysis, hardware, software and the subsequent self-administered mail
questionnaire to respondents.

The mail questionnaire, Part B, consisted of six questions. Four
close-ended questions included examples of measure codes commonly
found in nutrient analysis software; sample computerized nutrient
analysis programs; and 37 nutrients whiCh could be analyzed. Reading
measure code examples and a long list of nutrients over the telephone
could affect the response rate of the questionnaire since experts
suggest telephone surveys Should contain snort and nondemanding

questions (Warwick and Lininger 1975; Dillman 1978).

Methods Used to Reduce Error in Data Collection Instrument.
Questions asked in both Parts A and B of the questionnaire were
directed toward persons with foodservice knowledge and experience. A
definition of hardware and software was read to eacn interviewee.
Nutrient analysis was defined for those telephone questionnaire
respondents with the position of cnef, cock, corrections officer,
administrative secretary and respondents who requested a definition.

Closed-ended and open-ended questions were used in both Parts A
and B of the questionnaire. Both types of questions have inherent
advantages and disadvantages. Open-ended questions elicit a wide

variety of responses and the respondent is not limited to a

l9
pre-selected answer (Tull and Hawkins 1980). Since there have been no
prior reported investigations regarding foodservice directors'
perceptions of computerized nutrient analysis, more exploratory
information could be obtained using open-ended questions.

A disadvantage of open-ended questions is respondents“ answers to
questions may be too brief or incomplete (Tull and Hawkins, 1980).
Therefore, the mail questionnaire, Part B, contained fewer open-ended
questions than the telephone questionnaire, Part A. The investigator
could "probe" respondents for a more complete answer during telephone
interviews.

In this study the average time to conduct one telephone interview
was planned to be 10 minutes. This time corresponds with reports that
telephone interviews should range from 10 to 30 minutes (Berdie 1973;
Tull and Hawkins 1980; Kidder 1981). Part B, self-administered mail
questionnaire, was five pages long with one to two questions per
page. Both front and back. of’ the: questionnaire were used so the
questionnaire would appear to be three pages long. Little or no
correlation between mail questionnaire length and response rate have
been reported (Berdie 1973; NiCKensw et. al. 1980; “Mill and Hawkins

1980; Tedin and Hofstetter 1982).

Methods Used to Nbximize Response Rates. Response rate has been
defined as the percentage of the original sample interviewed (Tull and
Hawkins 1980). Telephone questionnaire response rates can be
increased by proper timing of phone calls and callbacks (Tull and
Hawkins 1980; Vidgerhous 1982). The investigator scheduled telephone

calls around peak production and serving hours characteristic of

20
foodservice departments. Peak hours were identified in Eastern
Standard Time as breakfast-~6z30AM to 8:00AM, luncn--10:30AM to
1:00PM, dinner--4:30PM to 5:30PM. These hours were adjusted for
Central, Mountain and Pacific times.

To maximize response rates the investigator planned up to three
callbacks to potential telephone interview respondents. If the
potential respondent was not in the office, a message was left. The
message included the investigator's name, reason for calling, time and
date the phone call would be returned.

A letter (Appendix B) was sent to notify potential respondents of
the forthcoming interview. This advanced letter was typed on Micnigan
State University letterhead. Letters and envelopes were individually
printed. Advance letters were individually signed by the investigator
and a business card enclosed.

Prhmc to sending advance letters, the investigator contacted by
telephone eaCh prospective institution to Obtain appropriate address,
telephone number and foodservice director's name.

To maximize responses, the mail questionnaires were sent only to
telephone interview respondents. At the completion Of the telephone
interview respondents were reminded Part B of the questionnaire would
be arriving in the mail along with a consent form (Appendix C). Eacn
respondent was asked to return Part B as soon as possible.

Part B, mail questionnaire, contained the message that it was to
be completed by the same individual who participated in the telephone
interview. The message asked respondents to return completed
questionnaires to the investigator using the enclosed addressed and

stamped envelope. Consent forms were sent with Part B. The consent

21
form and return envelope were mailed first class mail to each

telephone questionnaire respondent.

Pretesting and Critiquing. The questionnaire, Parts A and B, was

 

revised several times for clarity and precision. The questionnaire
was pretested by five foodservice professionals representing nursing
homes, schools, hospitals and correctional institutions. In addition,
the research committee Chairperson, a graduate committee member and
the investigator also participated in pretesting the telephone
questionnaire. As a result, the questionnaire was more precise and

relevant.

Interview Training. Interview training sessions were conducted by

 

Kathryn Kolasa, Ph.D. and Carolyn Lackey, Ph.0., Food Science and
Human Nutrition associate professors, Micnigan State University. This
researcher participated in those sessions to refine interviewing

skills.

Sample Selection

 

Rationale for Sample Selection Method. Foodservice directors were

 

selected as the target population. As administrators they best
represent the foodservice department in hospitals, nursing homes,
elementary ‘through secondary' schools, colleges and universities and
correctional institutions. Foodservice directors would most likely be
familiar with computers and nutrient analysis. If unfamiliar with
these subjects, the foodservice director would be in a position to

select a departmental person who would better understand computers and

22
nutrient analysis and the individual selected by the foodservice
director would be asked to participate in the study.

No single directory exists with a complete listing of hOSpitals,
nursing homes, elementary to secondary schools, colleges and
universities and correctional institutions which have foodservice
departments. Therefore, four directories were used as sources to
identify these five types of institutions.

The sampling frame included the current edition of the following
directories. The type of institution randomly selected from eacn

directory is also listed (Figure 1).

 

Type of Institution

 

 

 

 

 

 

 

Randomly Selected Sampling Frame
hospitals American HOSpital Association Guide to
nursing homes HeaTth Care Fields 1982. American
Hospital AssociatiOn, Chicago, IL.
(n = 8,274)
elementary to Patterson's American Education 1982.
secondary schools EducatiOnal Directors, Inc.,
Prospect, IL.
(n = 14,814)
colleges and Education Directory, Colleges and
universities Universities 1982. National Center
for Educational Statistics,
WaShington, DC.
(n = 3,253)
correctional Juvenile and Adult Correctional
institutions Department; Institutions, Agencies

 

and Paroling, Authorities 1981.
American Cbrrectional Association,
College Park, MD.

(n = 1,600)

 

Figure 1. Directories for Sampling

23

The American Hospital Association Guide to Health Care Fields

 

provides addresses for every known hospital in the United States,
including medical centers, county hospitals, veterans administration
hospitals and private hospitals. This investigator did not
distinguisn between hospitals accredited or not-accredited by the
Joint Commission for Accreditation of Hospitals. An address and
telephone number was listed for each hospital.

Accredited nursing homes (long term care facilities) in the United

States were listed in the American Hospital Association Guide to

 

Health Care Fields. Non-accredited nursing homes were not selected

 

for the study since they may not maintain organizational and health
care standards and are probably too small to have a fOOOservice
department. An address was listed for eacn accredited nursing home.
NO telephone numbers were provided.

Patterson's American Education provides addresses for known

 

elementary through secondary SChools and SChOOl districts in the
United States. No telephone numbers were listed in the directory.
The investigator did not distinguish between elementary, middle and
secondary schools. The school district address was used for
correspondence.

The Education Directory’ Colleges and Universities provides
addresses and telephone numbers for known colleges and universities in
the United States. The investigator did not distinguisn between two
year schools, four year schools, business scnools, theological
seminaries, private or public schools.

The correctional institutions in the United States are listed in

Juvenile and Adult Correctional Department: Institutions,' Agencies

24

and Paroling Authorities. This investigator selected samples from

 

institutions since a foodservice department would most likely be
located in an institution and not an agency or paroling Office.

Addresses and telephone numbers were provided.

Subject Population. A random table of numbers was used to select

 

the names and addresses of five groups of institutions for the study.
An estimated number Of institutions in eacn group was determined by
counting the number of institutions in the directory: hospitals
7,080, nursing homes 1,194, elementary through secondary scnools
14,818, colleges and universities 3,253 and correctional institutions
1,600.

The investigator planned to over-sample. A sample size of 145
institutions was generated. There were 29, 29, 28, 33 and 26,
respectively, in hospitals, nursing homes, elementary to secondary
scnools, colleges and universities, and correctional institutions
selected.

Institutions outside the coterminous United States were excluded
from the sample. Exclusion was based on the high cost of business
hour telephone calls to Hawaii and AlaSKa.

The sample institutions were called to Obtain telephone numbers
for the foodservice department and the name of the foodservice

director or person responsible for feeding the people.

Data Collection
Advance letters enclosed with the investigator's business card

were mailed to 145 foodservice directors Marcn 28, 1983. Telephone

25
interviews began April 11, 1983 and concluded April 20, 1983.
When a telephone interview was completed, a 9 x 12 envelope
containing the consent form, mail questionnaire (Part B) and the
addressed and stamped return envelope was sent to the telephone

questionnaire respondent.

Nutrient Analysis Software Evaluation. A nutrition analysis

 

software evaluation form was developed by the investigator (Appendix
0). Using this evaluation, form, nutrient analysis software is
reviewed and evaluated on eight major points: (1) identifying
information such as title, publiSher, computer used, disclaimers; (2)
quality Of documentation; (3) key features sucn as nutrition
definition, graphics, analysis Of diets based on RDA, use as nutrition
education tool; (4) consistency and reliability; (5) nutrient data
base information; (6) food data base information; (7) design and
quality of program and documentation; and (8) summary statement.

The evaluation tool has only been used by the investigator. It

will be submitted to the Journal of Nutrition Education Office,

 

Pennsylvania State University, as a nmdel for further development of

nutrition software evaluation materials.

Approval of Researcn Involving Human Subjects

 

An abstract of this study, explanation of tne subject population,
the risk/benefit ratio, consent procedures and data collection
instrument were approved by the Michigan State University Committee on

Research Involving Human Subjects on January 3, 1983.

26

Analysis

For this study, Statistical Package for the Social Sciences (SPSS)
(Nie, Hull, Jenkins, Steinbrenner, and Bent 1975) was used to analyze
apprOpriate> data. The investigator ran FREQUENCIES, CROSSTABS, and
T-test programs. These programs generated appropriate statistics such
as mean, median, mode, percentages, chi square and Students t-ratio.

Other data were analyzed descriptively. The data did not warrant

further statistical analysis.

RESULTS AND DISCUSSION

Response and Participation Rates

 

Foodservice directors were randomly selected and surveyed about
computerized nutrient analysis. The survey instrument was a telephone
interview and a self-administered mail questionnaire. Foodservice
directors were affiliated with hospitals, nursing homes, elementary
through secondary SChOOlS, colleges and universities, and correctional
facilities throughout the United States.

The response rate was 58 percent for telephone interviewed
subjects. These subjects were given at least five weeks to respond
with the questionnaires. Of the 58 percent who participated in the
telephone interview, 68 percent returned the self-administered
questionnaires. This response rate was better than the expected 30 to
54 percent from mail questionnaires only (Berdie 1973; Jones and Linda
1978; NiCKens, et a1. 1980). Seven more responses were received after
the deadline. Only those received by the deadline were included in
this analysis.

Early in 1983, 145 advanced letters were sent to foodservice
directors. Two letters were returned because of incorrect addresses.
Four letters were sent to institutions whicn had no foodservice
department. These six institutions were deleted from the sample,
leaving a sample of 139 potential subjects. Fifty-eight (42%)
subjects refused participation and were not interviewed, 29 of these,
cnose not to participate for the following reasons: 76 percent were
not interested, 17 percent did not have time, three percent were on

strike and three percent were retiring.

27

28

Fifteen (26%) of the 58 non-participants were telephoned at least
three times but there was no answer. Fourteen (24%) Of the
non-participants cancelled three scneduled interviews. I

The refusal rate was high. However, because the sample was a
random selection of people from a population, the distribution of
preferences in the sample is approximately tne same as the
distribution in the population. Since the sample size is small,
results are generalized with less certainty than if a larger sample

existed.

Sample Characteristics

 

Affiliation. The 81 respondents, several with more than one

 

affiliation, were employed by various institutions: 25 percent with
hospitals, 22 percent nursing homes, 21 percent colleges and
universities, lSl percent correctional institutions, 17 percent
elementary through secondary scnools; other institutions included
contract foodservice companies and State Department Of Education.
Table 1 shows the institution respondents were affiliated with. There

was no difference in number of respondents in each group.

29

Table l. Institutions where Respondents were Employed

 

 

Institution N_ Percenta
Hospitals 20 25
Nursing Homes 18 22
Colleges and Universities 17 21
Correctional Institutions 15 19

Elementary through Secondary

 

SChOOls 14 17
Other 10 12
TOTAL 94 116

 

aTotals do not equal 100% because several respondents
had more than one affiliation.

Type Of Respondents. There were four types of respondents:

 

foodservice directors, dietitians, production managers, and
foodservice supervisors (Table 2). Of the 81 respondents, 47 percent
were foodservice directors. There were approximately an equal number
Of respondents who were foodservice or production managers,
dietitians, and foodservice supervisors, 17 percent, 12 percent, and
10 percent, respectively. In addition, 45 (55%) of the respondents
were female and 36 (44%) were male.

Most respondents, who participated in the study, were foodservice
directors affiliated with colleges and universities (67%), hospitals
(60%), and nursing homes (45%) (Table 2). These respondents seemed
knowledgeable about nutrient analysis. This is probably because
nutrient analysis is often used in hospitals and nursing homes for

documenting and calculating patient calorie counts and nUtritional

3O

 

 

 

 

mm __ op v_ o_ om 4<HOH

co. 9. mm m om m om .m o 0 RN q Poozum Acmucoomm
canoes» Acmucmsm_m
co. m. m. m om m ow o o 0 Km v co_g:uwum:H
_mco_uumccou
co. m_ __ N o 0 mm c o o No __ mm_upmem>wc:
use mumm__ou
co. om m _ ON 4 a _ mm m me m ago: m:_mcaz
co. m. N _ o o o 0 mm m om m Poupamoz

E a :3 a E a :3 a :3 .z. E m
cmcuo Lomw>cmazm Lamaze: cm_u_umwo couumc_o copu:u_umc~

4<Hoh mu_>cmmooom copuuzooem muw>cmmuood

A_m n cv cowu:u_umcfi An .ucmucoqmmm yo maxh .m Open»

31
status from dietary data. With increasing public awareness about
health and nutrition, some college students are requesting foodservice
directors to post caloric and nutrient content of cafeteria foods
(Krause 1983). In the interview, it was necessary to explain the term
“nutrient analysis" to production managers and foodservice supervisors
affiliated with correctional institutions (60%) and elementary through
secondary schools (40%). These foodservice directors have had little
need to understand nutrient analysis because diets are seldom analyzed
for nutrient content and school students may have little interest in
nutrient content of meals eaten at scnool. Therefore, with these
distributions of respondents and their apparent familiarity with
nutrient analysis one could anticipate differing responses to tne

questions about computerized nutrient analysis.

Clientele Fed by Respondents. Most foodservice directors were

 

responsible for feeding more than one type Of clientele (Table 3).
Respondents from hOSpitals (87%), nursing homes (68%) and colleges and
universities (65%) fed staff and employees along with patients,
residents and students. Catered groups were also fed by respondents
from colleges and universities (29%) and hospitals (7%). Respondents
affiliated with elementary through secondary scnools (100%) fed only
students or residents age five to 19 years. Since more than one type
Of clientele are usually fed in an institution, the foodservice
director should determine if clientele demand or desire nutrient
analysis. This is important for justifying nutrient analysis software
and determining components sucn as nutrients and foods to analyze,

special dietary requirements and regulations, the level of nutrition

.mmmcoamwe m_qpapae cu wan acoucma oo— _o:ao yo: ass m—aaopo

 

 

 

32

cc. a m 9 ~_ m. .m mm hm 4<pop
co. m. o o co m o o o o o o oe c o o o o copuauwumc~
.ocopuuoccou
mwm mm mm m o 0 mm m co. m. o o o o o 0 mo .# aawmco>wc=
uco emu—Fog
2: a o o o o o o c o o ,o 8. A: o o o o .85”
Acaocouum cmaoczu
Agoucm5m_u
2... R o o o o o o o o 8 m o o 8. 2 8 2 28: 8.55:
oo. mm RN v o o N _ o 0 mm c. o o ow m Rm m. .ou_gmo:
:3 m 3: a. a: m :3 m :3 m s: m E m as m E m
meow»
egos co m. manage mucmoaum mwm< a. cu m mm< meomcma mmwxo_qem
o4<hop cacao Om< mm_oeou omcmuou Au_mLO>w:= mc_xco> we mucmupmmz upcuopco¢ a wwoum copuaupumc_
ace mm_oz a vamp—cu mucOPuoq co mucouzum

 

=o_u=»_umc_ an .omu m_mucmw_u .m m_nap

33
knowledge needed to use the software and, if software is 111 be used

for nutrition education.

Funding of Institution. It was expected that the institution's

 

source of funding could influence type Of hardware and software
purcnased and amount Of computerization. For instance, government
funded institutions may receive funds or grants toward
computerization, such as, office mechanization or computer education.
Table 4 snows most non-profit institutions were elementary through
secondary scnools (73%), hospitals (67%) and nursing homes (63%).
Thirty two percent Of nursing homes, 29 percent colleges and
universities and 27 percent hospitals were profit institutions. Most
government funded institutions included correctional institutions

(93%), elementary through secondary scnools (53%) and colleges and

Table 4. Source of Funding, by Institution

 

Non- Government Don't TOTALa
Institution Profit Profit Funded Know
N (%) N (%) N (%) N (%) N (%)

 

Hospital 10 67 4 27 l 7 O 0 15 101
Nursing Home 12 63 6 32 2 ll 1 5 21 111
Elementary

through Secondary

Scnool ll 73 O O 8 53 0 0 19 126
College and

University 5 29 5 29 7 41 l 6 18 105
Correctional

Institution 2 13 O O 14 93 O O 16 106

 

aTotals do not equal 100 percent due to multiple responses.

34
universities (41%). Nursing homes, colleges and universities, and

correctionals institutions had more than one source of funding.

Type of Menu Cycle. The institution's menu cycle is important

 

because this can influence amount of data storage needed for menu
substitutions and changes. Table 55 snows hospital respondents (80%)
used either three week or one to two week menu cycle (p_<_ .OOl).
Menu cycles used by nursing home respondents were three week (32%),
four week (26%), five week (21%) or one to two week (16%). Sixty
percent of elementary through secondary SChool respondents used a four
week cycle and 20 percent used no cycle. Seventy two percent college
and university respondents equally reported using four week, five week
or no menu cycle. Most reSpondents fron1 correctional institutions
(36%) used a six week to six month menu cycle, 29 percent did not have
a menu cycle, and 21 percent used a five week cycle.

A usable nutrient data base must contain the same or similar foods
as those in the inventory. If there is frequent intrOduction of new
foods or menu substitutions, the data base might not be useful.
Therefore, an appropriate question to a5k would be now frequently menu
substitutions were made and new fOods introduced. If frequent, the
user snould have the ability to edit the data base. This is
especially important if no menu cycle exists and meals are planned
week 1x1 week. An institution whicn seldom introouces or suostitutes
foods may need to analyze menus only once. In this case, it may be

cost effective to have menus analyzed once by an external organization.

35

.mmmcoammc m_O_u_:e on was HOOOLOO oo_ _O:cm no: Owe ONOOONO

 

 

 

 

OO O __ O O_ N. O. NN O<NON
OO. O. O O ON O OO O O .O _N O O O O_ N OO_OOO_OOOH
.Ocowuumccou
NO_ N_ O _ ON O N_ N O O ON O N. N ON O NONWLOONOO
ocm mmmppou
NO. O_ O O ON m N N N . O O m. N OO O .OOOOO
Ocmucoumm cmsoccu
Ocmucm5m_m
OO_ ON O _ O O O _ O. m ON O .N O NO O mac: OONOLO:
NO_ O. ON O O O O O OO O O O O: O N _ NOONOmo:
a: z c: z E z :3 z E z E z c: z a: :
m>wuum—mm m_oau space m . _ OowuzuwamOH
OO<NON \_mcommmm 0: on gum; o :mmz NTN xmmz m :mmz m xmmz v
OONHOONNOOH an .m_uxu 3cm: .m m_OON

36

Computer Use and Availability

 

Questions about computers were introduced by first asking
respondents if they ever used a computer. A significant number, forty
five respondents (56%) had never used a computer (p 5; .05). Of the
44 percent who had used computers, 11 respondents used them for
foodservice management, 10 1km: a college class or company worksnop,
five respondents used a computer for dietetic functions sucn as diet
analysis and diet Office procedures, five used a computer in another
job, and five reported using personal computers. Based on this
information, foodservice management software for purChasing,
inventory, and food production may be more frequently used by
fOOdservice departments with computers than nutrient analysis software.

Table 6 shows most respondents (87%) who never used a computer
were affiliated with correctional institutions. These respondents
were head cooks and chefs who probably had less Opportunity to use a
computer in a company workshop or college class. Also, these
respondents would not be in the position to use the computer for
foodservice management since this function is prooably performed by
the state-level foodservice director. Since other respondents (42%)
have used a computer, they may realize how a computer can benefit
their department. Therefore, these respondents may have some interest
in computerized nutrient analysis.

The percentage of foodservice departments in hospitals, nursing
homes, schools and correctional institutions whicn have computers
available or not available is Shown in Table 7. Most respondents
affiliated with nursing homes, correctional institutions and hospitals

were not using computers. Computers may be unavailable) to these

37
institutions because residential care and budget constraints have
priority over computerized foodservice. The greater percentage of
computers were available to foodservice departments in educational
institutions. Justification for computers may be easier for
foodservice directors affiliated with scnools since many school
districts and colleges and universities may have access to main frame
computers or have state or federal funds for computer education
(Stephenson 1981; Schuler and Fuller 1982; WierzoiCKi 1983; Freiberger

1983).

Table 6. Respondents Use of Computers

 

 

Yes, N0.
Institution Have Used Have Not Used TOTAL
(%) (%): (%)

Hospital 67 33 100
College and

University 59 41 100
Nursing Home 42 58 100
Elementary through

Secondary School 40 60 100
Correctional

Institution 13 87 100

 

Computer Users (n = 30)

The following results were derived from data supplied only by
respondents with computers available to them. Respondents were asked
if they were using software for food inventory, food and supply
purchasing, menu tally, recipe precosting, recipe expansion, nutrient

analysis and payroll.

.mcwucaoL ca use acmueaa co. Nazca «o: cu upouoho

 

 

38

 

com amw mm mm mm mm m_ 4<NON
mm mm m. m. NN m_ o _oocum Agoucoumm
sauces» Acuucweopm
oo. MN 0 o . om N o m:o_u:u.umc_
.ocowuumegou
.o. .o N. N. cw m. o mm_upmcm>wc=
can mmmw__ou
co. cm 0 m m. o o 98: 9.3.52
oo. me n. o o o m. _oupnmo:
a a a a a a
com: “oz u:o&~:oawa
OO<NoN cmuansou O_OO__O>< mmazucam go» On ouczo uoz coaaaeou gouaqsou copu=u_um=~
oz emuzgsou nmuoooam cousasou m_am__o>< LOOOOEou pou=OEucOamo .ocoOcom

 

A_O u OV OO_OOO_OOOO NO .NOO_NOO__O>< LOOOOEOO OOOOOOOOOOO .N «NOON

39

The distribution in Table 8 snows foodservice management software
used most frequently. This agrees. with previous information; most
respondents who used a computer used it for foodservice management.
Although no respondents in this survey used nutrient analysis
software, 13 percent reported planning to use it. Therefore,
questions about computerized nutrient analysis were answered only by
respondents planning to use this software. These respondents may laCK
knowledge and hands-on experience using nutrient analysis software.
Thus, responses to these questions may have been answered differently
if respondents were using nutrient analysis software.

Respondents using foodservice software were asked the type of
computer and name of software used. Some respondents (31%) used
various models Of IBM computers, 27 percent did not know what computer
they used. The other 42 percent respondents repOrted using one Of the
following computers: Apple, Borroughs, Commodore, Honeywell, North
Star, Osborne, Texas Instruments, TRS 80, VACS or Xerox. Most
respondents (75%) did not know the name of software they were using.
However, 25 percent used one of the following types of software:
Dynamic Control, Visicalc, Concept Systems, "government“ software, and
software developed in-house. From this information, it appears
respondent may not have been involved in purchasing or writing
specifications for departmental software or hardware. Thus,
reSpondents seem to lack sensitivity about importance of knowing the
type of computer and software being used. If the type of software is
unknown, the user would not know what data base sources were used; the
accuracy and reliability Of the nutrient analysis program would be

difficult to determine.

4O

.mcwuczoe o» man ucmugma oo. .Ozcm ac: on O.Ouo»O

 

 

.O. N. O O. NO O O.OO.OO< OOO.LOOZ.
OO. O O. O. OO O OO.OOOOxO O0.000
OO. O O. N. OO N. OOOOOLO OO.OOO
OO O O. O. OO O. N..O. OOO:
oo. o O ON mO ON mcwmwcuczm
O.OOOm OOO coon
.O. O. O O. mm mm ..OLOOO
.O. O O OO NN .O OLOOOO>O. OOOO
.O. .NO .:O .NO .OO .Nv
O.OOOO mm: com ewuzaeou m.OO..O>< cam: OO: Low umscomcmm OOELOOOOO
umccmpa uoz OP Egowcma u.:oz cmccm.a poz gmuzqsou

 

3 292.53. LOOOOEOQ 5.... 38383: .3 Steam:

Aom u :v newspcmawo

”mcmzfiom mowimmuoom No OOOCOOEOQ .m 32.;

41

Nutrient Analysis. The following information was supplied by

 

respondents who would use nutrient analysis software, if they used tne
available computer and those planning future use of nutrient analysis
software (n = 5). No percentages are given since very few respondents
supplied the information.

Most respondents were foodservice directors in schools, therefore,
nutrient analysis software use was not limited to diet analysis. For
instance, respondents reported they would use nutrient analysis
software to analyze menus and recipes for nutrient content, adjust
menus using the output, display output in cafeteria dining areas to
inform clients Of nutrient content of foods served, and they would
place output in medical records to document calorie counts and

nutrition care.

Intent to Purchase Nutrient Analysis Software. Respondents

 

affiliated with hOSpitals (33%) and correctional institutions (25%)
had some intention to purchase nutrient analysis software (Table 9).
Respondents from hospitals probably hand calculate nutrient analysis
daily, and thus, realize possible time saved using computerized
nutrient analyses. Increasing operating costs experienced by most
hospitals (Johnson 1983; Division of Economic Studies 1983) is
probably why 33 percent respondents said they had no intent to
purchase nutrient analysis software and 33 percent said it depends on
cost of software. In addition, some dietitians and foodservice
directors know the nutrient content of foods served or know where to
find the nutrient values. Therefore, there maybe little reason to buy

nutrient analysis software.

42

Table 9. Intention to Purchase Nutrient. Analysis Software, by
Institution (n = 26)

 

Institution NO Yes Depends Gathering Don't Totala
on Cost Information Know

(%) (%) (%) (%) (%) (%)

 

College and

University 78 ll 0 ll 0 100
Elementary through

Secondary School 75 13 O O 13 101
Hospital 33 33 33 0 O 99
Nursing Home 50 0 0 50 0 100
Correctional

Institution 25 25 O 25 25 100

aTotals do not equal 100 percent due to rounding.

Respondents (25%) affiliated with correctional institutions may
purchase nutrient analysis software to document, for the state,
nutrient content of theals served to residents. In addition, some
respondents expressed difficulty contacting the dietitian when a
resident required a special diet. These respondents stated it would
be easier and faster to use a computerized nutrient analysis program
than to rely on the dietitian.

Many respondents had no intention to purchase nutrient analysis
software, eSpecially those affiliated with elementary through
secondary schools (75%) and colleges and universities (78%). As
previously stated, these reSpondents are more interested in
foodservice management software than in nutrient analysis. There may
be some demand for nutrient analysis software in colleges and

universities since 11 percent Of respondents are intending to purchase

43
nutrient analysis software and 11 percent are gathering more
information about the software. Because of age, nutrient content of
foods, especially calories, is probably a greater concern among

college students than elementary or high school students.

What Inspires Respondents to Purchase Software. Respondents were

 

asked what would inspire them to purcnase new software (Table 10). It
appears respondents from hOSpitalS (80%) and elementary through
secondary schools (78%) believe software should be beneficial and
acceptable to their department or institution and reduce labor and
food costs. Software wthh fits these specifications would be easy to
justify. Respondents affiliated with elementary and secondary schools
(22%), colleges and universities (10%) and correctional institutions
(25%) Specifically said they would be inspired to purcnase good
foodservice software; software whicn is accurate, easy to use and
meets specified needs. Many respondents (50%) from colleges and
universities would be inspired to purcnase software for the following
reasons: if there was demand from residents; if software was
recommended by a person using it; and if dietitian was unavailable and
in-house programmer' could not write good programs. Based on this
information, foodservice directors may purcnase software that is
beneficial and acceptable to the department, and capable Of reducing

labor and food costs.

Like Using Computer. Respondents were asked if they liked using
the computer. Most (90%) liked using the computer because it was fast

and convenient. Ten percent did not like using the computer because

44

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45
they seldom used it or the computer they were using could not handle
all necessary information.
Based on this information, computers could be integrated into
foodservice departments as fast and convenient equipment. However,
adequate training of employees is important for acceptance and proper

use of computers (Stokes 1983).

Non-computer Users (n = 51)

 

The following results were derived from data supplied only' by
respondents not using a computer.

Respondents were asked if they would want a computer in their
department. Preference for a computer was distributed between
respondents who said yes (41%), no (26%) and those who were uncertain
(33%).

Table 11 shows most respondents affiliated with colleges and
universities (57%), correctional institutions (55%) and hospitals
(50%) want a: computer in their department. Respondents from nursing
homes (47%) were uncertain about wanting ea computer. These results
are somewhat evenly distributed and may reflect respondents' lack of
knowledge regarding the use of computers in foodservice. Respondents
who wanted a computer did not know what type computer they wanted.
Respondents did not want a departmental computer or were uncertain
about having a computer for the following reasons: institution was
too small, computers were too expensive, no need for computers, they
lacked computer knowledge, and administration would not support use of
computers. This information may indicate a need to inform foodservice

directors and employees of computers' role in foodservice and the

116

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47
hardware and software available before they are in a position to
determine what may be useful in their institution (Schuler and Fuller
1982; Snow 1982). 1

Computer Use. Those 21 respondents wanting a computer were asxed

 

what they would use it for. Most (73%) would use computer for
management functions. Fewer respondents (23%) would use computer for
nutrition assessment and nutrient analysis. Based on this
distribution, more respondents would use the computer for foodservice
management than for nutrition assessment and analysis. However, Table
11, shows computer use depends on institution respondent is affiliated
with. Several respondents would use the computer for more than one
task. For instance, more respondents affiliated with hospitals (4)
would use> computers for» nutrition assessment and nutrient analysis
than for foodservice management. Respondents from colleges and
universities (ll), elementary through secondary SChOOlS (4), nursing
homes (5) and correctional institutions (7) would use a computer for
foodservice management functions sucn as, food purchasing and
production, meal planning, cost containment, work scnedules and
reports (p 5;_ .01). Therefore, one could anticipate the first
software purchased by a new computer-user would be a type of
foodservice management software. AS expected, respondents have some

differing needs and uses for computers depending on their institution

affiliation.

Nutrient Analysis Software. The 51 non-computer users were aSKed

 

if computerized -nutrient analysis would be useful to their

department. Sixty three percent said yes, 20 percent said no and 18

48

percent were uncertain. Unlike computer users, it appears
non-computer users believe computerized nutrient analysis can be
useful. This is expected Since many non-computer users are affiliated
with hospitals and nursing homes and would use computers for nutrition
assessment and nutrient analysis. Sixty three percent of respondents
perceived computerized nutrient analysis useful for six reasons:
(1) it would ensure nutrition standards were met; (2) nutrition
assessment would be easy and accurate; (3) analysis of nutrients in
menus and recipes could be possible; (4) would not have to rely on
other sources for nutrition information; (5) could Share program with
other interested institutions; and (6) would be useful because
information can be stored and retrieved. These non-computer users
appear to have some understanding of uses for computerized nutrient
analysis even though they were not using nutrient analysis software.
However; many' seemed to believe all nutrient analysis software is
accurate and computer information is always correct. These
respondents need to be aware of data bases, measure codes and
nutrition standards used in nutrient analysis programs. TO assure
accurate information respondents need to exercise judgment when
selecting nutrient analysis software.

Thirty eight percent of non-computer users were uncertain or
believed nutrient analysis software was not useful for the following
reasons: department was too small, computerized nutrient analysis was
unnecessary; external agency performed computerized nutrient analysis;
and some expressed limited knowledge about nutrient analysis. From
this information and previous information, there are two obstacles

confronting computerization of foodservice and nutrition departments.

49
These are: (l) respondents believe their institutions or departments
are too small in Size for computers and (2) there is limited knowledge

about computers and nutrient analysis.

Components Of Nutrient Analysis Software

The following results are derived from data supplied by telephone
interviewed respondents (n = 81).

Respondents were aSked what components Of nutrient analysis
software would be very useful, useful, little use <n~ not useful to
their department or institution.

Seventy five percent respondents found all components of nutrient
analysis software very useful or useful (Table 12). Previous
information indicates respondents do not have e1 great interest in
computerized nutrient analysis. However, this distribution suggests
respondents believe nutrient analysis software is useful. Perhaps by
reading and explaining software components, respondents learned nmre
about computerized nutrient analysis and answered questions
accordingly.

Statistically different responses were given for nutrient analysis
software which can identify nutrient deficiences or excesses and
provide suggestions to improve an individual's diet (Table 13).
Respondents affiliated with hospitals (94%), correctional institutions
(94%) and nursing homes (84%) believed software which analyzed
deficiencies or excesses in diet or menu would be very useful or
useful. Analyzing nutrition deficiencies and excesses is also a
component of nutrition care in hospitals and nursing homes.

Therefore, these respondents probably believe software With this

50

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51

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52

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54

component would simplify and speed this taSK. Respondents from
correctional institutions are head cooks and chefs with little
nutrition training. Therefore, a software component identifying
nutrient deficiencies or excesses in a diet or menu would be very
useful or useful to a cock responsible for feeding residents on
special diets (Coani 1982). Also, obtaining nutrient deficiencies or
excesses from the computer may be quicker than waiting for the
dietitian's visit.

Elementary through secondary school respondents (67%) believed
identifying nutrition deficiencies and excesses in diets or menus was
useful. This information is helpful if a student requires a special
diet. Respondents would also be able to identify deficient nutrients
in a menu and modify the menu to meet requirements. Most college and
university respondents (70%) believed the component was either useful
or little use. It could be useful if a student had Special dietary
needs. However, determining nutrient deficiencies cu“ excesses irl a
menu would be impractical Since college cafeterias do not have one
menu but serve different foods whicn can be combined to form many
menus.

Respondents from hOSpitals (100%), correctional institutions (94%)
and nursing homes (90%) believe nutrient analysis software whicn
suggests improvements to irmHvidual diets is very useful or useful.
This is expected since respondents could use the information to modify
diets and instruct patients and residents on diet Changes.
Respondents fronn correctional institutions may find this component
useful because using the suggestions, they can help residents on

special diets more quickly than contacting and waiting for a dietitian.

55
Respondents. fron1 elementary 'through secondary schools (80%) and
colleges and universities (48%) rarely' counsel individual students.
Therefore, there is little need for a nutrient analysis program whicn

suggest improvements to individual diets.
Results from Self-Administered Mail Questionnaire (g = 51)
The following results were derived from data supplied by 51

respondents who returned mail questionnaires.

Selected Measure Codes. The self-administered questionnaire began

 

with an explanation of measure codes to aid the respondent in
selecting one of the given measure code examples. The examples were
based on codes used in nutrient analysis Software currently marketed
and the Michigan State University Nutrient Data Bank (Zabik and Morgan
1979). This question was important because it provided information on
the measure codes respondents perceived as useful. Thirty nine
percent respondents selected the sample nutrient analysis program with
21 coded units of measure, 37 percent selected 10 coded units of:
measure, and 24 percent selected 5 coded units of measure (Figure 2).
There is au1 almost even distribution between reSpondents preference
for "Program F“ and "Program E".

Respondents were given the opportunity to make modifications on
selected measure code examples. Thus, they were not limited to
questionnaire nmasure code examples. More appropriate measure codes
could be added or less appropriate ones deleted.

Figure 3 Shows the codes deleted and added by respondents. Thirty
one percent reSpondents modified "Program E“, 27 percent modified

"PrOgram D", and 24 percent modified "Program F".

56

 

Percent Respondents

 

 

39% 37% 24%
"PROGRAM F" "PROGRAM E" "PROGRAM 0“
Coded Units of Coded Units of Coded Units of
Measure Measure Measure
01 Cup 01 Cup 01 Cup
02 Half Cup 02 Half Cup 02 Tablespoon
03 Glass (6 oz) 03 Glass (6 oz) 03 Teaspoon
04 Bottle/Can O4 Tablespoon . O4 Ounce
05 Tablespoon 05 Teaspoon 05 Fluid Ounce
O6 Teaspoon O6 Ounce
O7 Ounce O7 Fluid Ounce
08 Fluid Ounce 08 Small (2 3/8“ diameter)
09 Piece (2 oz) 09 Medium (2 5/8" diameter)

10 Scoop (1 oz, 4 oz) 10 Large (3 1/16” diameter)
11 Cube (1 oz)

12 Wedge (1 oz)

13 Ring (3“ diameter)

14 Stalk (1 1/2" x 8")

15 Strip (2")

16 Small (2 3/8" diameter)
17 Medium (2 5/8" diameter)
18 Large (3 1/16" diameter)
19 Gram

20 Milliliter

21 Liter

 

Figure 2. Measure Codes Selected by ReSpondentS (n = 51)

57

 

 

PROGRAM ADD DELETE
"Program F“ pound, scoop Sizes: milliliter, liter,
21 coded units #8, #10, #16, #20 bottle, can, ring
Of measure
“Program E“ gram, milliliter, liter,
lO coded units liter, scoop (1 oz, 4 oz),
of measure wedge, 1/4 cup, pint, --

quart, gallon, bottle, can,

pound
“Program 0" gram, liter, milliliter, fluid ounce
5 coded units 1/2 ounce, 1 ounce, pound,
Of measure quart, #10 can, dozen,

gallon

 

Figure 3. Modification of Measure Codes (n = 51)

Preference for other codes varied from small codes such as fluid
ounce, to large food codes like pound or #10 can. Metric measurements
were frequently preferred. Although the respondents did respond to
the question, they did not seem to know what measure codes they want,
need or find useful. Because of this, no recommendation can be made
since respondents did not seem knowledgeable about measure codes.

Therefore, further research is indicated.

Selected Nutrient Analysis Programs

Respondents were given three sample nutrient analysis "programs".
"Program A“ consisted of eight nutrients and seven categories of food,
“Program 8" nine nutrients and 10 food categories, and “Program C" 37
nutrients and 12 categories of food.

Forty-eight percent respondents selected the sample nutrient

analysis program with 21 nutrients and 10 food categories, 35 percent

58

selected program with eight nutrients and seven food categories, and
17 percent selected the program with 37 nutrients and 12 food
categories (Figure 4). This question was important since respondents
were able to select the nutrients and foods perceived as most
functional to the department or institution. Table 14 shows
respondents affiliated with nursing homes (69%) and hospitals (50%)
prefer "Program 8“. Most (50%) respondents affiliated with colleges
and universities and elementary through secondary scnool (55%)
selected "Program A". Respondents affiliated with correctional
institutions had no preference.

This distribution characterizes the most functional programs for
institutions in the study. Since nutrient analysis is a major
responsibility in hospitals and nursing homes, respondents affiliated
with these institutions need a somewhat extensive nutrient data base
to perform accurate and quick nutrient analysis. An extensive data
base would enable the dietitian to analyze specific nutrients such as
amino acids for patients with inborn errors of metabolism or Specified
nutrients for test diets controlling for a vitamin or mineral.
Nutrient analysis is not a major responsibility in schools. Instead
it is something requested by students or the State Board of Education
or United States Department of Agriculture. Therefore a small data
base is most functional. ReSpondentS from correctional institutions
reported an even distribution among sample programs. It appears these
respondents realize a need for computerized nutrient analysis. Their
limited nutrition and computer knowledge may have affected their

responses.

59

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60
Table 14. Nutrient Analysis Programs Selected, by Institution

(n = 51)

 

 

Institution Program 8 Program A Program C Totala
N (%) N (%) N (%) N (%)

Nursing Homes 3 23 8 69 1 7 12 99

Hospitals 7 50 3 20 4 30 14 100

Elementary through

Secondary School 4 55 4 46 0 0 8 101

Correctional _

Institution 3 33 3 33 3 33 9 99

College and

University 4 50 2 25 2 25 8 100

Total 21 20 10

 

aTotals do not equal 100 percent due to rounding.

Respondents were asked to modify the program they selected (Figure
5). Most respondents (67%) made no modifications to the program
selected. Figure 5 shows a list Of nutrients added or deleted by
respondents. There were no modifications on "Program C". The
additions and deletions may indicate the need for a user edit function

for nutrition analyis data bases.

61

 

 

Program ADD DELETE
Program A saturated and polyunsaturated fat
vitamin C, vitamin A
folacin
cholesterol none offered
fiber

thiamine, niacin, riboflavin
potassium, sucrose

Program 8 folacin magnesium
vitamin D potassium
vitamin 812 phOSphorus
vitamin K kilocalories
copper

crude fiber
dietary fiber
biotin

iodine

water
caffeine

Program C none Offered none offered

 

Figure 5. Modification of Nutrient Analysis Programs (n = 51)

Cost of Sample Program. Based on cost, reSpondents were aSked to

 

select one of the sample nutrient analysis programs, Program “A", "B“,
or “C". "Program A", was less expensive than “Program 8", whicn was'
less expensive than "Program C". Fifty percent respondents selected
"Program B", 38 percent selected "Program A“, and 13 percent selected
"Program C” (Figure 6). Respondents selected "Prograhl B" as Ihost
functional and most economical. Table 15 shows "Progrmn B“ as most
economically accepted by respondents from hospitals, nursing homes and
schools. Respondents from correctional institutions were extreme in
their selection. ReSpondents (50%) selected the least expensive

program and 33 percent selected the most expensive program. From

62

Table 15. Selected Program Based on Cost, by Institution (n = 51)

 

 

Institution Program 8 Program A Program C Totala
N (%) N (%) N (%) N (%)

Hospital 10 70 l 10 3 20 14 100

Nursing Home 7 62 5 39 O O 12 101

Elementary through

Secondary Scnool 4 55 4 46 O O 8 101

College and University 3 38 3 38 2 25 8 101

Correctional

Institution 1 l7 4 50 3 33 8 100

TotalD 25 17 8

 

aTotals do not equal 100 percent due to rounding.

DTotal does not equal 51 due to rounding.

their other responses, it is reasonable in) assume these respondents
may not know how much a computer and software cost.

Nutrients for Analysis. ReSpondentS were aSked to select 11

 

nutrients from a possible 37 to be analyzed by a nutrient analysis
program. Results Show respondents preferred nine nutrients to be
analyzed by computerized nutrient analysis (Figure 7). All but two of
the nutrients are used for U.S. Recommended Dietary Allowance
labeling. The nutrients not required on nutrition labels are sodium
and potassium. Eighty one percent respondents selected sodium and 65
percent selected potassium (p f;_ .05). In Table 16 respondents
affiliated with hospitals and nursing homes wanted sodium and
potassium analyzed. This is prooably because these respondents care

for patients who must monitor their blood sodium and potassium and

63

..O u c. OOOO co OOOOO EOLOOLO NO OOOOOO.OO OOOOOOOOOOO .O OLOO.N

 

OOOOO O.ccuo LO .OOO..OOLO.:.
OOOON OcOLO OEO:

OOOOO O.OOOOOLO:u
OOOOLOOOOOL SOLO OOOOO .OOO.
.Ocou.o

mummnm

ONO.

OOOOOOLO .OmLou OcO OOOLO
OO.:LO

OO.OO.OOO>

ONOOOOLO x..E OOO x..E
OO.OO..OOOO “Owe OOO .OOE

 

auN>O<z< moooO mo mm.mooN»<u

 

OOOOIO

OOOO

OOOOOOLO .OOLOO oco OOmLO
OO.:LO

OO.OOOOOO>

OOOOOOLO x..e OOO g..e
OO.O...OO:O «Owe OOO .Owe

 

:O~>Oqz< maooN mo mu_mouwp<u

 

..0.0 .O.OOOLO 3O.
.OOO.OOO. was“. OOOOO O.OOOOOLOOO
OOOOLOOOOOL EOLO .OOOO .OOO.
.OOOO.O
Ouoozn
OOOO
OOOOOOLO .OOLOO OcO OOOLO
OO.:LO
OO.OO.OOO>
OOOOOOLO x..e oco x..E
OO.:..OOO:O “Owe OOO .Owe

 

3ON>.<2< woos; no mu.¢OOON<u

 

 

OOOOOOOOOOO OOOOLOO

LOO.O
ac..O> .OLOOO.OOO
congeaaxLu < .N.) u_uo u..oO
OO.:OOLO. E:.OOOOOe ”e:.O.OO OOOO OOOLOOOO
Oc.cO.O.OOO:O OOLOOOOOOO ”5:.O_OO c.OO.O
oc.:o.zuoe E:.OOO.OO Om .O:.xOO.LOO
OO.OO. 5:.OOO NO .c.>O..OO.L
Oc.u:O.OO. OOLOOOOOOO .O .OOEOOOO
x .O.» LOOOOO < .O.)
O .O.) EOOOOOOOE EOOOOOOOE
o .O.» cOL. e:.OOO
O.OO u.OLOOOO OO.OO. EOOOOOOOO
0.00 O.cO:OOOcOO E:.O.OO OOL.
:.OO.O Lmqu 5:.OOO OOLOOOOOOO
.OO.OOO. OOOLOOO 5:.OOOOOO EOOO.OO
0.00 O..O. OOOLOOOOOLOO OOL. OOOLOOOOOLOO

c..O.O OOOOLOOOOO=O_OO- OO.O.OO OOOOLzuOOOOO.OO-

N_O .:.E..OOOOOOOOO OOOOLOOOO- OOOLOOOOOLOO OOOOLOOOO-
om .Oc.xOO.LOO .OO you uOO
NO .O.>O_.OO.L :.OOOLO c.OOOLO OOOOOLO
.O .:.EO.c. OO.LO.OOO..O OO.LO.OOO..O OO.LO.OOO..O
OON.O<z< O.zO.¢.=z OON>O<2< O.zO.aO:z OON>O<z< OOzO.m.:z

O. OO OO
OO zOOOOOOO O< z<mOOOOO Om z<100¢Oa

 

 

64

 

NUTRIENT

Carbohydrate

25

PERCENT

50 75 100

 

Fat

 

Protein

 

Kilocalories

9O

 

Iron

81

 

Sodium

 

Calcium

79

 

Vitamin A

67

 

Potassium

65

 

Polyunsaturated Fat

 

Ascorbic Acid

 

Saturated Fat

 

Thiamine

 

Riboflavin

 

Vitamin D

 

Calcium: PhOSphorus

 

Niacin 19
Water 17
Sucrose 15
Vitamin E
Iodine
Magnesium
Calcium: Magnesium 8
Folic Acid
Vitamin K
Cyanocobalamin
Pyridoxine 4
Pantothenic Acid 4
Phosporus .2
Inositol
Isoleucine
Lysine
Methionine
Phenylalanine
Threonine
Tryptophan

OOOOOOO

 

Figure 7.
Software (n = 51)

Vi

Nutrients Selected to be Analyzed by Nutrient Analysis

65

Table 16. Nutrients to be Analyzed, by Institution

 

 

 

 

 

 

Institution Sodium Potassium
(%) (%)
HOSpital
Yes 90 80
No 10 20
Total 100 100
Nursing Home
Yes 92 92
No 8 8
Total 100 100
Elementary through
Secondary SChool ~
Yes 64 36
NO 36 64
Total 100 100
College and University
Yes 100 50
NO 0 50
Total 100 100
Correctional Institution
Yes 50 50
NO 50 50
Total 100 100

 

66
they must know the sodium and potassium content of foods. Respondents
affiliated with schools want sodium analyzed and not potassium.
Sodium is the more familiar nutrient since it found in foods often
eaten by students, such as, snack foods, fast foods and convenience
foods. Half the respondents fron1 correctional institutions wanted
sodium and potassium analyzed. This fifty-fifty split may indicate a

lack Of sensitivity to why these nutrients would need analyzed.

Conclusion

 

Foodservice directors' perceived need for' computerized nutrient
analysis does seem to differ depending on the type of institution the
progranu will be used in. For instance, hospital and nursing home
respondents were interested in using and purchasing nutrient analysis
software. Respondents affiliated with scnools were more interested in
foodservice inanagement software rather than nutrient analysis
software. Correctional institution respondents were interested in
nutrient analysis software because it can analyze diets quicckly.

Most respondents preferred a "medium size" nutrient analysis
program with a data base consisting of 21 nutrients, 10 food
categories and a variety of measure codes, especially metric measures.

Many respondents sated they lacked knowledge about computers and
nutrient analysis. There is also a lack Of hands-on computer
experience among these respondents since most had never used a

computer.

67

Finally, respondents interested in purchasing, writing or leasing

a computer nutrient analysis system, Should consider four points:

(1)

They must determine if their clientele are interested in
nutrient analysis, and if so, what nutrients and foods Should
be analyzed; a small needs assessment Should be conducted.
This will also help when writing the justification for the
system.

A nutrition or foodservice specialist or consultant should be
contacted to help describe the type of computer and nutrient
analysis program most suited to the institution.

The persons using the computer and nutrient analysis program
must be trained to use the new equipment.

Whatever program is purchased, leased or written, there must
be good documentation describing the use of the software and a
user's guide explaining computer functions and problems.

Food and nutrition professionals should know what types of
nutrient analysis software are being advertised and review the
software for accuracy so they can recommend to perspective
buyers an accurate nutrient analysis system whicn best meets

their needs.

SUMMARY

The Objective of this study was to assess what foodservice
professionals perceive they need 'H1 a computerized nutrient analysis
system. Foodservice directors affiliated with hospitals, nursing
homes, colleges and universities, elementary through secondary scnools
and correctional institutions were randomly selected and surveyed
about their perceived need for computerized nutrient analysis.
Respondents (37%), most from educational institutions, were using
computers in their department. Foodservice management software was
used most by these respondents; no nutrient analysis software was
used. Respondents (63%) not using a: computer stated computerized
nutrient analysis would be useful. Most non-computer users were
affiliated wdth hOSpitalS and nursing homes. Components Of nutrient
analysis found most useful were: plans menus based on dietary
requirements for individuals or groups (84%), analyzes menus for
nutrient content (82%), and analyzes percent RDA for a menu (82%).
Respondents preferred a nutrient data base Of nine nutrients.
Information from this study can be used by fOodservice professionals
to learn of features available in nutrient analysis programs.

Foodservice: directors affiliated with hospitals, nursing homes,
colleges and universities, elementary ‘through secondary' scnools Iand
correctional institutions have expressed interest in computerized
nutrient analysis (Weyand 1976; Anonymous 1978; Wyse l979; Danford
1981; Finley and Simpson 1982; Seliger 1981; JOhnson, et a1. 1982;
Schuler and Fuller 1982; Willard l982; Chin l983; Youngwirth 1983).

Nutrient analysis programs in hospitals have been used to analyze

68

69

patient dietary intake (Dorea, et al. 1981; Youngwirth 1982) and
nutrient content of parenteral nutrition fluids (Giacoia and Chopra
1981). In nursing homes computerized nutrient analysis has been used
to reduce the time spent calculating dietary intake from food
composition tables (JOhnson, et a1. 1982). Colleges and elementary
through secondary schools use nutrient analysis software to teach food
and nutrition to students and professionals (Scnaun1 1973; Molleson
l976; Welch and Breeze 1977; Lewis 1981; Nutrition Education and
Training 1982; Smiciklas-Wright, et al. 1983; DeSKins and Thorne
1983). Foodservice directors in correctional institutions may be
interested in computerized nutrient analysis to avoid accusations of
"cruel and unusual puniShment“ for serving nutritionally unbalanced
meals to residents (Weyand 1976; RiChardson 1980).

The documented uses Of nutrient analysis programs have been mostly
research oriented. However, this researcner's experience and
information from this study shows that many foodservice professionals
do not know what they want from a nutrient analysis program or
understand the implementation or potential Of various programs.

There are at least 35 nutrient analysis software programs
currently Inarketed (Nutrition Information and Resource Center 1982;
Brown 1983; Freifeld l983). Eacn program has different
characteristics or components. For instance, software is generally
Specific for a hardware system; may analyze from 6 to 74 nutrients and
from 600 to 3,000 foods; may provide percent Recommended Dietary
Allowances and recommendations for an improved diet; may assist in
menu planning; results may be graphically displayed; and the program

may or may not be easy to learn and use (user-friendly). It requires

70

time and money to effectively and thoroughly review available nutrient
analysis software. Many interested foodservice professionals do not
have the time or money to perform this task. Therefore, this
researcher's objective was to assess what foodservice professionals
perceive they need in a computerized nutrient analysis program.

In this study, respondents' use of computers and availability of a
computer to their department was examined. Fifty Six percent Of the
respondents had never used a computer, most of these (87%) were
affiliated with correctional institutions. Many respondents from
nursing homes (90%), correctional institutions (73%) and hOSpitals
(63%) did not have a computer available to their department.
Respondents from elementary through secondary scnools (53%) and
colleges and universities (48%) had computers available to their
departments or a computer was budgeted for purchase.

Respondents using computers, especially those affiliated witn
hospitals and correctional institutions, were interested in purChasing
nutrient analysis software. Computer users from colleges and
universities and elementary through secondary schools had no intention
to purcnase nutrient analysis software.

Respondents were aSked what components of nutrient analysis
software would be very useful, useful, or little use or not useful; 75
percent respondents found all components of nutrient analysis software
very useful or useful. Different responses were given for nutrient
analysis software whiCh can identify deficiencies or excesses and
provide suggestions to improve an individuals diet.

The need for computerized nutrient analysis seems to differ

depending on the type of institution the program will be used in. For

71

instance, respondents affiliated with hospitals and nursing homes were
interested in using computerized nutrient analysis mostly for
nutrition assessment and to analyze nutrients in menus and recipes.
Respondents from colleges and universities and elementary through
secondary SChOOlS seemed more interested in foodservice management
software than nutrient analysis software. Those interested in
nutrient analysis software would use it in) adjust menus so they are
nutritionally adequate, to analyze menus and recipes for nutrient
content and to display output in cafeteria dining areas. Correctional
institution reSpondents were more interested in foodservice management
software but thought computerized nutrient analysis would be useful
for calculating Special diets.

A smaller nutrient data base was preferred by respondents.
Besides nutrients used for U.S. Recommended Dietary Allowance
labeling, respondents also wanted sodium and potassium as nutrients
analyzed by the software. A nutrient data base containing 9 to 21
nutrients was perceived as useful and affordable fin: most
respondents. Many respondents preferred a veriety Of measure codes,
especially metric units of measure.

To the investigator's knowledge, there are no other studies
assessing what foodservice directors perceive they need in a
computerized nutrient analysis program. A linntation cfi’ this study
was the small random sample of 81 subjects. Tnus, to generalize
results with greater certainty, Similar researCh Should be conducted
using a larger random sample. In addition, further research Should
focus on subjects' computer knowledge. Subjects could be grouped

according to their computer knowledge level, instead of computer use

72
and non-use. This would help nutrition educators develop education
strategies for teaChing computer literacy and food and nutrition
computer applications to students, foodservice employees and

colleagues.

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75

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APPENDICES

APPENDIX A.

Code No.

NUTRIENT ANALYSIS FOR FOODSERVICE INSTITUTIONS

Part A.

1.

"First I'm going to ask about your position and about the

institution you are affiliated with.“

What type of institution are you
affiliated with?

E] hospital
[:1 college/university

[ l elementary/secondary
school

DUDE

What is the name of your department?

Nutrition Department

DD

Food Service Department

is your position or job title?
food service director
administrative dietitian

assistant director

consultant C)

DDDDUEIMJ
EDD

supervisor | 1 other

currently working in or

nursing home

consultant in

 

correctional institution

other

 

Dietetics Department

Other

 

administrator
Clinical dietitian
nutritionist

management engineer

 

What type of clientele do you feed? You can respond to more than

one category.

[::] students, age 5-10 years [:Z]
[:Z] students, age 10-14 years [:Z]
1:] students, age 13-16 years 1:]
[3 students, age 16-19 years 1:]
[j college/university students 1:]

80

geriatrics, elderly
convalescent persons
inmates

patients of varying ages

other

 

5.

. [:l 4 weeks

81

IS your institution classified as:
I | profit E] government funded

[:3 non-profit [Z] other

 

 

What type of menu cycle do you have?

C] 2 weeks

 

 

[j 6 weeks
D seasonal
[:1 other

"Now we're going to talk about you or your department's current
use of computers. I'll be talking about software and hardware.
Software is the computer program and hardware is the machine; the
computer."

 

 

 

Have you ever used a computer?

[:Z] Yes. What did you use it for?

 

 

[::] NO. Any specific reason why you have not used a computer?

 

 

Does your department or do you currently own a computer or have
one budgeted for purchase but haven't received it to date?

yes, person has their own computer (complete questions 9-11)
yes, departmental computer (complete questions 9-11)

computer is available to department, but not owned by
department (complete questions 9-11)

no, person does not have their own computer
(go to questions 12-14)

no departmental computer nor one available to department
(go to questions 12-14)

[11313131313

budgeted for purchase but not received to date (complete
questions 9-11)

82

"lf_il§§L answer 0" #8. if computer is available for use or if'
computer is budgeted, then continue to #9."

“If 'NO' answer on #8 (no computer) complete #12-14."

I'm going to read seven computer functions to you; please answer
if they are or are not performed by the computer you are using.
If you answer yes to any function, please state the software used
and the machine you are using. (If a computer is in the budget,
then ask if the functions are being planned for use on the
computer.)

|:] food inventory
If yes: a. software used

 

b. maChine used

 

C] food and supply purchasing
If yes: a. software used

 

b. machine used

C] menu tally

If yes: a. software used

 

 

b. machine used

 

I | precost system for recipes
If yes: a. software used

 

b. maChine used

 

[:3 recipe expansion
If yes: a. software used
b. machine used

 

 

[:| payroll

If yes: a. software used
b. machine used

 

 

83

"The next few questions are about nutrient analysis."

1:] nutrient analysis
If yes: a. software used
1. What do you like best about the software?

 

 

 

2. What do you like least about the software?___

 

 

3. How often do you use it?

 

 

b. What all do you use the nutrient analysis for?___

 

 

 

c. What do you do with information (output) you
receive from the computer?

 

 

 

d. machine used

 

e. who uses the nutrient analysis program most?

 

If no nutrient analysis software:

a. is there any intention to purchase nutrient
analysis software?

 

b. if so, how soon will it be purchased?

 

84

10. In general, Since you have a computer, what would inspire you to
purchase a new piece of software?

 

 

 

11. Do you like using the computer?

C] Yes, why

 

 

[:] No, why not

 

 

12.

13.

14.

85

"If 'NO' answer on #8 (no computer), complete #12-14."

Would you want a computer in your department?

[:1 Yes

a. What type of computer would you want?

 

 

b. What would you use it for?

 

 

I: no, why not

 

 

 

[:1 uncertain, why

 

 

 

In your Opinion, would a computerized nutrient analysis program
be useful to your department or institution?

[:1 yes, why

 

 

C] no, why not

 

 

B uncertain, why

 

 

If your department owned a computerized nutrient analysis
program, who would use the program?

1:] food service director [:1 students
1:] nutritionist, dietitian [:| food service employee

[:1 technician 1:] patients
a other

 

15.

86

"The next series Of questions are about computerized nutrient
analysis. The questions deal specifically with different com-
ponents (or features) a computerized nutrient analysis program
may offer."

I am going to read some components or features that are available
on some computerized nutrient analysis software. I want to know
how useful these would be to .your institution (N’ department.
Please state if they would be: VERY USEFUL, USEFUL, of LITTLE
USE, or NOT USEFUL. It may be beneficial to write these down so
they can easily be referred to when each component is read.

Possible Components of Nutrition Analysis Software:

a. provides analysis of percent Recommended Dietary Allowances
for an individual.

 

Very Useful Useful Little Use Not Useful

b. provides analysis of percent Recommended Dietary Allowances
for a menu.

Very Useful Useful Little Use Not Useful
C. identifies Specific nutrient deficiencies or excesses. This
is in relation to the Recommended Dietary Allowances, to a
prescribed diet, or to federal or state dietary requirements.
Very Useful Useful Little Use Not Useful

d. plans menus based on specific dietary requirements for an
individual or group.

Very Useful Useful Little Use Not Useful
e. analyzes recipes for nutrient content.

Very Useful Useful Little Use Not Useful
f. analyzes mepge for nutrient content.

Very Useful Useful Little Use Not Useful

9. analyzes individual diets for nutrient content based on
Specific requirements or dietary prescriptions.

Very Useful Useful Little Use Not Useful

h. able to recognize established state and federal requirements
and regulations for a nutritionally adequate diet for an
individual or group.

Very Useful Useful Little Use Not Useful

15.

87

(continued)

1.

provides suggestions to improve an individual's diet based on
information put into the computer.

Very Useful Useful Little Use Not Useful

to use as a nutrition education tool; for instance, to allow
peOple to use the computer and nutrition software to
understand their nutrient needs, meal planning, digestion and
absorption of foods, and the nutrient value of foods.

Very Useful Useful Little Use Not Useful

uses bar graphs, along with numbers to represent and explain
the nutrient analysis output (or results).

Very Useful Useful Little Use Not Useful
Are there any components I have not mentioned that you want

to add? If yes, please state the component and the degree of
usefulness based on the scale we have been using.

[::] no

[:Z] (yes: Very Useful

 

 

Useful

 

 

Little Use

 

 

Not Useful

 

 

88

Code NO.

This section of the questionnaire is to be completed by the same

individual

participating

in the telephone

interview. Please

return Part B of the questionnaire with your reSponseS to Renee

Hart.
convenience.
Part B
16.

An addressed and stamped envelope is enclosed for your
Thank you for your participation.

Some computerized nutrient analysis programs use specific measure

codes for inputting data.

measure (i.e., pound, cup).
codes which may be used
programs.

Please

department or institution.

[:1 "PROGRAM 0"

Coded Units of

Measure

Cup
TableSpoon
Teaspoon
Ounce

Fluid Ounce

:1 "PROGRAM E"

Coded Units of

Measure

Cup
Half Cup
Glass (6 oz)
Tablespoon
TeaSpoon
Ounce
Fluid Ounce
Small

(2 3/8" diameter)
Medium

(2 5/8" diameter)
Large

(3 1/16" diameter)

A measure code represents a unit of

Below are three examples of measure
in three different nutrient analysis
select the one most functional

for your

1:] "PROGRAM F"

Coded Units of
Measure

Cup

Half Cup
Glass (6 oz)
Bottle/Can
Tablespoon
Teaspoon
Ounce

Fluid Ounce
Piece (2 oz)

Scoop (1 oz, 4 oz)
Cube (1 oz)
Wedge (1 02)
Ring (3” diameter)
Stalk (1 1/2" x 8")
Strip (2")
Small

(2 3/8" diameter)
Medium

(2 5/8" diameter)
Large

(3 1/16" diameter)
Gram
Milliliter
Liter

17.

89

Please write any modifications you would make on the coded units
of measure used in the program .you selected in question 16.
Modifications refer to deletions and additions of units of
measure you would want for inputting your data.

 

Modification of Coded Units
of measure for the “Program“ Comments or Suggestions

selected in question 16

 

 

9C1

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OOOOLOOOOOL EOLN OOOON OOOOO

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OuooxO
OOO.

OOOOOOLO .OOLOO ucO OOOLO

OO.OLN
OO.OOOOOO>

OOOOOOLO x..e OOO x..e
OOOOO.OOOOO ”Owe OOO OOOE

 

ouN>4<z<

mooou mo mm.¢oump<u

we..O>
OOOOOOOOLO
OO.OOOLOO
OOOOO.O.OOOOO
OO.:OOOOOE
O0.00.
ac.u:0.00_

x .u.>

u .u.>

a .u.>

0.00 O.OLOOOO
0.00 u.cO:OOOOOO
c.OO.:

.OO.OO:.

0.00 u..om
:Ouo.a

N.O .O.E0.000000000
Om .mc.xOO.LOO
NO .O.>O..OO.L
.m .c.EO_:u

< .u.>

5:.OOOOOE ”E:.u.Ou

OOLOOOOOOO ue:.u.Ou

E=_OOOOOO

EO.OOO

OOLOOOOOOO

LOOOOO

EOOOOOOOE

:OL.

OO.OO.

5:.O.OO

LOOO:

OOOLOOO

OOOLOOOOOLOO
OOOOLOOOOOO0.00-
OOOOLOOOO-

OON

c.0uOLa

OO.LO.OOO..O

 

awN>4<z< mhzm.mhzz

O .U

..Oum

.O.OOOLO 3O. .OOO.OOOO
menu. OOOON O.OOOOOLOOO
OOcOLOOOOOL SOLO OOOOO OOONO
.OOOO.O
mumuxm
OOON
OOOOOOLO .OOLOO OOO OOOLO
OO.:LO
OO.OO»OOO>
OOOOOOLO x..e OOO x..e
OOHOO.OOOOO qu5 OOO .OOE

 

cmN>4<z<
OQOON mo mm.mouwh<u

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.OLO»OO.OOO
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O.OO u.OLOOOO
c.uO.O
OO .O:.xOOOLOO
NO .O.>O.NOO.L
.O .O.OO.OO
< .O.)
5:.OOOOOE
EOOOOO
EOOOOOOOO
OOL.
OOLOOOOOOO
EO.O.OO
OOOLOOOOOLOO
OOOOLOOOOOOO.OO-
OOOOLOOOO-
HO»
:.OuOLO
OO.LO.OOO..x

 

om~>4<z< mhzm.ah:z

O .U

mummN—
uuxnzzmm

OOOOxO

OOON

OOOOOOLO .OOLOO OOO OOOLO
Ou.=LN

OO.OOOOOO>

OOOOOOLO x..e OOO x..s
OOOOO.OOOOO “Owe OOO que

 

nmN>4<z<
mooou no mm.¢ocuh<u

EO.OOO
5:.OOOOOOO
cOL.

e:.0.00
OOOLOOOOOLOO
OON

c.0uOLO
OO.LO.OOO..3

 

om~>4<z< mhzm.¢h:z

O..|I_

.OO.uau.uOc. LO OOOEOLOOOO LOOO LON OEOLOOLOO .Oco.uuczu umoe

Ogu OOO.OO OOOO.O .OOOOO OOO OOOO.LOOO OOO.LO> ONO.OOO OO.O: OeOLOOLO OOOO.OOO OOO.LOOO NO OO.OerO OOLOO
OLO so.OO .OOOON NO OO.LOOOOOO OOO OOOO.LOOO OOO.LO> ONO.OOO :OO OEOLOOLO O.OO.OOO OOO.LOOO OO~.LOOOOEOO

xx\:m

.m.

9l
l9. Please write any modifications you would make on the "program"

you selected in question l8. Modifications refer to deletions
and additions of nutrients and categories of foods to be analyzed.

Modification of Nutrients Modification of Food Categories

 

 

Comments and Suggestions

 

20.

21.

92

To answer this question, please refer back to question l8.

Computerized nutritional analysis is expensive. Therefore, it
the cost of “Program 8" was twice the cost of "Progrmn A"; and
the cost of “Program C" was three times the cost of "Program A";
which "program" would you choose for your institution?

|:] Program A C] Program 8 [3 Program C

Assume you have been offered $3000 to spend on a computer and
nutrient analysis software program. This amount of money will
enable you to select as many as ll nutrients to be analyzed by
the computer. From the nutrients given below, select those you
want in your nutrient analysis program.

Possible Nutrients for Analysis (Please check as many as ll
nutrients you want your program to analyze.)

1:] kilocalories [:1 thiamin, B]

[:3 protein 1:] riboflavin, 82

[3 fat I: pyridoxine, B5
[3 -saturated C] cyanoc0balamin, 812
D -polyunsaturated [:l biotin

[:] folic acid

I: inositol

[:l niacin

[j carbohydrate

[:3 magnesium
[:I c0pper
[:l phOSphorus
[3 sodium
[:1 potassium
[:3 calcium:
[:1 calcium:
[:3 vit. A

phOSphorus

magnesium

[:J pantothenic acid
E] ascorbic acid
[:J vit. D

l:] vit. E

1:] vit. K

[:I isoleucine
|:| lysine

C] metheonine
C] phenylalanine
[:3 threonine
|:| tryptophan

[_—_| valine

APPENDIX B.
ADVANCE LETTER TO RESPONDENTS

MICHIGAN STATE UNIVERSITY

 

DEPARTMENT or soon SCIENCE AND HUMAN NUTRITION EAST LANSING . MICHIGAN - 4332a

HUMAN ECOLmY BUILDING

March 8, l983

_ Dear

 

Within the next two weeks I will be calling you from East Lansing,
Micnigan to a5k your help in a researcn study. It is a nation-wide
survey to find out if computerized nutrient analysis is important to
foodservice departments in hospitals, nursing homes, scnools and
correctional institutions. In a telephone interview I will aSK for
your professional opinion about the Characteristics of a computerized
nutrient analysis program useful to your department. This information
will be used to guide other foodservice directors and nutritionists in
selecting apprOpriate nutrient analysis software for their
departments. We are studying, not selling, computerized nutrient
analysis systems.

 

This survey of "Nutrient Analysis for Foodservice Institutions" is
conducted by Dr. Kathryn M. Kolasa, R.D., adjunct Associate Professor,
Ms. Jean McFadden, Cooperative Extension/Foodservice Specialist, and
Renee Hart, R.D., Researcn Assistant, Department of Food Science and
Human Nutrition, Micnigan State University.

Nnen I call, I will ask to scnedule a telephone interview with you or
a qualified person appointed by you. The appointment will be
scheduled after you have agreed to participate in the study. A
consent form will be sent to you. Enclosed with the consent form will
be Section II of the questionnaire. This consists of some snort
answer questions and is to be reutrned to me after the telephone
interview. Section II of tne questionnaire should take about l0
minutes to complete. Tne interview Should take about 15 minutes to
complete. If I call at an inconvenient time, please tell me and we
can reschedule the interview. Tne information you provide will be
confidential.

93

MSU i: an Allin-naive Anion/Equal Opportunity Institution

94

Your help and that of others being asked to participate in this effort
is essential to the study's success. The results of the study will be
available upon request.

If you have any questions, contact me by phone at (5l7) 355-7730 or by
mail. I will be calling you within the next two weeks to schedule an
appointment for the telephone interview.

Cordially,

6442/4. W, m.

Renee A. Hart, R.D.
Research Assistant

APPENDIX C.
CONSENT FORM

I consent to take part in a survey of "Computerized Nutrient
Analysis for Food Service Institutions" conducted by Renee A. Hart,
R.D. under the supervision of Kathryn M. Kolasa, Ph.D., R.D. The
research is through the Department of Food Science and Human Nutrition
of Micnigan State University.

The study has been explained to me and I understand the
explanation. What my participation involves is also understood. I am
aware that further explanation of the study after my participation is
completed is available to me upon request.

I understand that I am free to discontinue my participation in the
study at any time.

I am aware that my answers will be treated in strict confidence
and that I will remain anonymous. Within these restrictions, results
of the study will be made available to me at my request.

I understand that my participation in the study does not guarantee

any benefit to me nor to the institution I am affiliated with.

Signed

 

Date

 

95

APPENDIX D.

NUTRIENT ANALYSIS SOFTWARE EVALUATION

IDENTIFYING INFORMATION

 

Fill in spaces with checks or comments.

5 (A) N -—‘
o o n 0

Title Nutritionist

 

Author(s) or Producer n2 Computing

 

Professional Assistance (specify) none

 

Publisher n 2 Computing

 

Address 53l8 Forest Ridge Rd., Silverton, 0R 9738l
Telephone (503) 873-5906
Copyright a l982
Disclaimer not responsible for any damages caused by using the
software. Not to specify or recommend any type or amount of
nutrient or food
Guarantee

 

List of Components:

 

 

 

computer Apple III or Apple IIe
disk drives l or 2

languages BASIC

number of disks 2

 

documentation manual yes

 

data base: source(s) USDA #8, Bowes and Church, Home and

 

Garden #72, RDA l980, Krause l978 for sodium, fat and

 

 

 

 

cholesterol
number of foods 730
number of nutrients l8
edit data base (§E§)or no food and nutrient

 

other ability to change RDA standard

 

 

 

97

DOCUMENTATION

Cheek if present, make appropriate comments.

 

 

 

 

l. Table of contents yes if' - ‘ j

2. Index yes fig

3. Bibliography ,yes

4. Appendix: ‘Xes .Ng
data base included in package _§__ ____
abbreviation list _X_- I___
glossary .___ ._5_
index of nutritional quality ____ _3£_
food cost ____ _JL_
food excnange groups ____ _JL_
measure codes (specify) .___ ._5_

some codes are included in an abbreviation listing; little
explanation about measure codes is given

 

 

 

food and nutrition information ____ _§_
(INQ, RDA) (specify)

energy expenditure information ____ .___
other ._§_

 

 

 

5. User Knowledge Level:
Enter necessary information, Check when appropriate.
l. Knowledge level indicated by author/publisher for personal and
(professional use; some knowledge of nutrition
2. Knowledge as determined by reviewer Basic nutrition knowledge
is necessary for interpreting graphic display of results andigfi
for changing RDA types. To use tne program to its fullest,
professional nutrition knowledge is needed for creating special
diets and interpreting results or explainingresults to

patients

 

98

Evaluations conducted using software; group or individuals

involved in evaluation:
none specified

reviewer has conducted none

6. Objectives/Goals/Purposes or Intended Outcomes: (Briefly)
User has ability to create nutritionally balanced diets for in-

dividual needs and preferences--also for special diets such as low
sodium,rdiabetic, pregnancy or lactating or low calorie. By com-

Aparing analyses of foods, meals and diets, tne user(s) can select
optimum choices for their needs and goals

Stated in user's guide or manual

Inferred by reviewer

KEY FEATURES

 

-Check if present in the software.

Features:

I.

_'__2.
_X_3-
_4.
__5
__6.
_7.
__8.
_X_9-
l0

Nutrition defined

Physical activity defined
Number of diets which can be
stored

Food cost

. Shopping list

Recipe file

Stores personal information
Monthly cnarts (specify)
Graphics (specify)

. Uses food exchange lists

specify

6320? no

yes orfigfi

Comments:

 

 

3O

 

 

 

 

 

fihigh resolution graphics,
displays RDA for food, diets,
recipe

 

99
Feature: Comments:

_X_ ll. Analyzes percent RDA for an
individual

 

12. Analyzes RDA for a menu

 

l3. Plans menus based on dietary
requirements for an individual
or group

 

X 14. Analyzes recipes for nutrient
content

 

l5. Analyzes menus for nutrient
content

 

X l6. Analyzes individual diets for
nutrient content based on specific
requirements or regulations can edit RDA standards pp

 

l7. Recognizes state and federal
requirements for an adequate
diet

 

l8. Provides suggestions to improve
an individual's diet

 

 

 

 

_JX_ l9. Identifies nutrient list foods which will provide
deficiencies or excesses a balanced diet

___ 20. Can be used for nutrition too detailed and complex for
education patient education

 

X 2l. Uses bar graphs along with
numbers to represent output

 

CONSISTENCY AND RELIABILITY

Check appropriate spaces. .XES .gg SOMEWHAT
1. Objectives are realistic ____ .___ ._X_

confusing if little
nutrition knowledge

Content supports Objectives _3:_ ____ ____

Topics are presented in a generally

accepted scientific context '_X_ ____ ____
4. Terminology is used correctly _}L_ ____ ____
5. More than one view on controversial

issues is presented _X_

TOO

‘VES ‘gg SOMEWHAT

6. Only proven theories are presented as I

fact i _ __
7. Personal viewpoints are presented as

views, not facts ‘_X_ ____ ____
8. Appropriate generalizations are drawn

from information presented _JX_ ____ ____
9. Recommendations will not result in ____ ____ __X_

harmful effects Disclaimer
l0. Data bases used are referenced in

manual X

NUTRIENT DATA BASE

 

l. Source(s) USDA Handb00k #8; Bowes and Church, Food Values of
Values of Portions Commonly Used ; Garden BUTTetin #72; Catherine
Adamp, Nutritive Value of AmeriCan Foods

2. NutFients analyzed: Check appropriate spaces.

Yes
Kilocalories
Protein
Fat
Carbohydrate
Vitamins, number of 5
Minerals, number of 5
Amino acids
Other (list): cholesterol

saturated fat

No
_L

oleic fatty acid
linoleic fatty acid

3. Can use multiple or
fractional serving sizes X

TOR

FOOD DATA BASE

 

 

 

 

 

 

 

 

 

 

 

 

 

Check appropriate spaces Y§§_ Np_ Comments

I. Ethnic or internationalfoods “___ _3L_

2. _Mixed or combination dishes ._5_ ____ very few

3. Therapeutic foods ____ _JL_

4. Fast foods ____ ._X_

5. Edit Data Base ._X_ ____

DESIGN AND QUAEITY

Check appropriate spaces ‘Ygg .Np Comments

I. Readable type in manual ____ _1L_ difficult to

read

Readable type on CRT i _
Organized diSplay of information/ cramped, hard
nutrient analysis output .___ ._X_ to read

4. Quality graphics _JL_ ____ small size
Backup disks available or can
be copied by user _J§_ ____ copy by user

 

SUMMARY STATEMENT
This program may be difficult to use and confusing if the user has

 

 

littlepnutrition knowledge. To use the program to its fullest, nutri-
tion knowledge is helpful. The program isn't intended to recommend or

 

specify certain foods to be eaten (disclaimer). Documentation is
difficult to follow, there is no index and nutrition terms are not

 

explained, such as "oleic fa" (meaning oleic fatty acid). Thispprogram

 

would be most useful to dietitian or nutrition professional who calpu-
late patient diets

 

 

 

 

 

 

 

REVIEWER
Name Renee A. Hart, R.D. Position/Title Nutrition Consultant
Affiliation/Business Micnigan State University
address Room l Human Ecology
Michigan State University, East Lansing, MI 48824
telephone (5l7) 353-4357 #47
Date August 3, l983

 

Prepared by: Renee A. Hart, R.D., Michigan State University, 8/l983.

Adopted from: Profiling; Nutrition Education Materials, Instructors
Manual. Oakland, CA: Society for Nutrition Education -
Center for Nutrition Education, l983.

 

102

NUTRIENT ANALYSIS SOFTWARE EVALUATION
IDENTIFYING INFORMATION

 

Fill in spaces with checks or comments.

I. Title ,, EAT FOR HEALTH

 

2. Author(s) or Producer Genesee Intermediate School District

 

Nutrition, Education and Training Center

 

3. Professional Assistance (specify) Foodservice consultant, Home

 

Economist, Dairy Council of Michigan

 

Y

4. Publisher Genesee Intermediate School District
Address *24l3*West Maple Avenue, Flint, MI 48507*

 

Telephone (313) 767-43I0
5. Copyright l982

 

6. Disclaimer --

 

7. Guarantee --

 

Vi

8: List of Components:

 

 

 

 

 

 

 

 

 

 

computer Apple II plus, Apple IIe

di5k drives I

languages pp? BASIC

number of disks l

documentation manual X

data base: source(s) not specified
number of foods 500
number of nutrients l6 (documentation says l7)
edit data base yes orCE§

 

other

A

 

103
DOCUMENTATION

 

Check if present, make appropriate comments.
l. Table of contents X
2. Index no

3. Bibliography resources X

 

 

 

 

 

 

4. Appendix: .Yes .Np
data base ‘_X_ “___
abbreviation list .___ '_X_
glossary .___ __X_
index of nutritional quality .___ ._5_
food cost _ _L
food exchange groups ____ ._§_
measure codes (specify) ____ _Jg’

but appears household measures

are used - no separate listing

is found. I
food and nutrition information _1L_ ____
(specify) pre-post nutrition

tests; food recall worksheets;

activipy levels
energy expenditure information ____ ____
other note to parents explaining, _1L_

 

nutrition program; food descrip-
tions; comppter instructions

5. User Knowledge Level:
Enter necessary information, cheek when appropriate.

I. Knowledge level indicated by author/publisher students with
fifth grade reading level, ability to read bar graphs and
percentages

2. Knowledge as determined by reviewer could be used with younger

 

students if results are explained to them; same as above but
can also be used by older students and adults

104

3. Evaluations conducted using software; group or individuals
involved in evaluation:
none stated

 

6. Objectives/Goals/Purposes or Intended Outcomes: (Briefly)
To aid students in identifying the nutritional content of their
daily diet as compared to their daily needs. To be used by
students in grades 5-8; it is also appropriate for older ages.
A pretest is given before students use the program, this will

determine students minimalvnutrition knowledge.

Stated in user's guide or manual (yes or no
Inferred by reviewer yes or’po

KEY FEATURES

Check if present in the software.

Features: Comments:

.LX. l. Nutrition defined Instructor's activities include
teaching nutrition concepts

 

prior to using program

 

 

 

 

 

 

 

_XL_2. Physical activity defined
.___ 3. Number of diets which can be
stored _fi
l___ 4. Food cost
'___ 5. Shopping list
___ 6. Recipe file
___ 7. Stores personal information
___ 8. Monthly charts (specify)
'_X_ 9. Graphics (specify) diSplays RDA for nutrients in

 

diet
l0. Uses food exchange lists
(specify)

 

Feature: Comments:

_1L_ll. Analyzes percent RDA for an
individual

 

12. Analyzes RDA for a menu

 

13. Plans menus based on dietary
requirements for an individual
or group

 

14. Analyzes recipes for nutrient
content

 

15. Analyzes menus for nutrient
content

 

X 16. Analyzes individual diets for
nutrient content based on specific
requirements or regulations

 

 

17. Recognizes state and federal
requirements for an adequate
diet

 

fi—f —‘

X 18. Provides suggestions to improve
an individual's diet very brief and accurate

 

l9. Identifies nutrient deficiencies
or excesses

Ix

 

X 20. Can be used for nutrition
education intended purpose

 

._X_ 21. Uses bar graphs along with
numbers to represent output

 

CONSISTENCY AND RELIABILITY

 

Cheek appropriate spaces. YE§_ .np SOMEWHAT
1. Objectives are realistic __X_ ____ ‘___
2. Content supports objectives ._X_ ____ ____
3. Topics are presented in a generally
accepted scientific context _}L_ ____ ____
4. Terminology is used correctly _1L_ ____ .___
5. More than one view on controversial
issues is presented _J£_

106

.YES .np ' SOMEWHAT

6. Only proven theories are presented as

fact _ __ _
7. Personal viewpoints are presented as

views, not facts i _ _
8. Appropriate generalizations are drawn

from information presented -_X_ ____ ____
9. Recommendations will not result in

harmful effects _2L_ ____ ____
10. Data bases used are referenced in ____ ____ _3£_

manual no clear reference

NUTRIENT DATA BASE
l. Source(s) not defined - resources include: NET Resource Centepp
Dairy Council of Micnigan, Food, Home and Garden Bulletin #228,
Cooperative Extension
2. Nutrients analyzed: cneCK appropriate Spaces.
Yes No
Kilocalories
Protein
Fat
Carbohydrate
Vitamins, number of 6
Minerals, number of 5

Amino acids
Other (list): fiber

 

 

 

3. Can use multiple or fractional
serving sizes X

107

FOOD DATA BASE

 

 

 

 

 

 

 

 

 

 

 

 

Check apprOpriate spaces Y§s_ Np_ Comments
1. Ethnic or international foods _3L_ ____ Italian; Mexi-
can,pChinese
2. Mixed or combination dishes _JX_ ____
3. Therapeutic foods -___ _JL_
4. Fast foods _1L_ ___
5. Edit data base ____ _3£_
DESIGN AND QUALITY
Check appropriate spaces Ygs_ Np_ Comments
1. Readable type in manual ._1_ ‘___
2. Readable type on CRT _JL- ___
3. Organized display of information/
nutrient analysis output _X_ ____ very clear
4. Quality graphics _JX_ ____
Backup disks available or can no informa-
be c0pied by user ‘___ ._5_ tion provided

 

SUMMARY STATEMENT
This program is an excellent nutrition education teaChing tool.

 

Teachers using this program should have basic nutrition knowledge.

 

The pretest and nutrition education materials included with the pro-
gram are accurate and applicable to students. Data base references

 

are not included. Some food servings are not specified or appear in

 

unusual amounts; i.e. "juice" = 5/8 cup, "soup" = 1 serving.
REVIEWER
Name Renee A. Hart, R.D. Position/Title Nutrition Consultant

 

 

Affiliation/Business Michigan State University

 

address Room 1 Human Ecology
Michigan State University, East Lansing, MI 48824
telephone (517) 353-4357

Date August 3, 1983

Prepared by: Renee A. Hart, R.D., Michigan State University, 8/1983.
Adopted from: Profiling Nutrition Education Materials, Instructors

 

Manual. Oakland, CA: SocTety for Nutrition Education -
Center for Nutrition Education, 1983.

 

 

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