Evaluation of a PDA-based Dietary Assessment and
Intervention Program: A Randomized Controlled Trial
Jeannette M. Beasley, PhD, MPH, RD, William T. Riley, PhD, Amanda Davis, BS, RD, Jatinder Singh, BS
Personal Improvement Computer Systems, Inc., Reston, Virginia
Objective: To evaluate the capability of DietMatePro, a PDA-based dietary assessment program, to monitor
dietary intake and to improve adherence to a dietary regimen.
Design: Randomized controlled trial.
Subjects. Overweight and obese (Body Mass Index (BMI) 25–40) participants without dietary restrictions.
Intervention: Participants (n ? 174) were randomized to record usual dietary intake using either Diet-
MatePro or a paper food diary for one week to compare concordance with 24-hr recall. At the week 1 visit,
participants were individually counseled to follow the diet recommendations of the Ornish Prevention Diet for
three weeks and continue monitoring food intake using the assigned method to estimate adherence to the
intervention by monitoring condition.
Outcome Measures: Spearman correlations between week 1 24-hr recall and the assigned recording method
were compared to assess validity. Mean pre-post changes in intake measured by 24-hr recall were compared
according to monitoring condition to measure adherence to the Ornish diet.
Results: Correlations of energy and nutrient values reported on the food label ranged from 0.41 to 0.71 for
the DietMatePro condition versus 0.63 to 0.83 for the paper-based diary. Diet adherence was higher among
DietMatePro (43%) compared to the paper diary (28%) group (p ? 0.039).
Conclusions/Applications: DietMatePro does not appear to produce more valid data than paper-based
approaches. DietMatePro may improve adherence to dietary regimens compared to paper-based methods.
Lack of adherence to dietary regimens is a pervasive prob-
lem in both clinical nutrition and nutrition research. In research,
lack of adherence to assigned interventions yields an intention-
to-treat analysis biased towards null findings. One effective
strategy for increasing adherence is self-monitoring of dietary
intake [1–3]. Though self-monitoring is an indirect marker of
motivation, evidence suggests that monitoring intake also di-
rectly leads to behavior change [4,5]. Traditional self-monitor-
ing involves writing down everything one eats and drinks, and
often includes referencing tables to calculate energy and/or
nutrient goals . This process is time-consuming and incon-
venient for patients and study participants, especially when
eating away from home, which can result in retrospective
completion of paper-based food diaries.
Paper-based food records are also cumbersome when used
in clinical practice or nutrition research because they require
researchers to enter foods and portions into a nutrient database
for tabulation. As prospective measures of food intake, how-
ever, they may be one of the better measures of dietary assess-
ment compared to 24-hr recalls or food frequency question-
naires [7,8], though no single measure of energy and nutrient
intake can be considered acceptably adequate . When com-
pleted during or immediately after a meal, food diaries mini-
mize memory recall errors. Recall methods such as 24-hr recall,
however, are less reactive than prospective recording which
tends to influence food consumption.
Address reprint requests to: Jeannette M. Beasley, PhD, MPH, RD, Center for Health Studies, Group Health Care Cooperative, 1730 Minor Ave., Suite 1600, Seattle, WA
98101. E-mail firstname.lastname@example.org
Dr. Riley is now with the Behavior Change Research Program, National Institute of Mental Health, Bethesda, Maryland.
All authors were employed at PICS at the time of the study, and PICS is the developer of DietMatePro. This study was funded by NINR Grant# R44NR008443.
A related abstract was presented at the Second International Congress of Epidemiology held in Seattle, WA in June 2006.
Journal of the American College of Nutrition, Vol. 27, No. 2, 280–286 (2008)
Published by the American College of Nutrition
Technological advances have facilitated the process of cal-
culating energy and nutrient intakes from food records. Web-
based programs allow end-users to enter food intake and re-
ceive feedback regarding energy and nutrient intake. A more
portable option is Personal Digital Assistant (PDA)-based pro-
grams that provide tracking of intake against daily energy and
nutrient goals . Dietary data can be automatically and
immediately uploaded for the researcher or clinician to analyze.
PDA-based programs such as DietMatePro (PICS, Version
1, 2003, Reston, VA,) offer tailored feedback and features
designed to improve adherence to dietary regimens. Diet-
MatePro provides individualized intake recommendations,
comparison of actual intake with targeted intake, reminders to
record meals, and meal plans and recipes that meet diet spec-
ifications. However, it is unclear whether PDA-based programs
are feasible alternatives to written food records, given that PDA
programs require additional participant training and shift the
burden of data entry from the health care professional to the
Researchers have examined both the validity and utility of
using PDA-based programs for dietary research [11,12]. Un-
controlled studies using PDA-based dietary assessment pro-
grams to improve adherence to dietary regimens has provided
data to support the feasibility of the approach in diverse pop-
ulations and over periods of up to six months [13–16]. To the
best of our knowledge, this is the first report in the literature of
a randomized, controlled trial comparing the utility of elec-
tronic versus paper-based food diaries in a large sample.
The purpose of this 4-week randomized, controlled trial was
to evaluate the effectiveness of DietMatePro. Two primary
aims were to 1) compare concordance of reported energy and
nutrient intakes obtained from DietMatePro and paper food
diaries with 24-hr recall; and 2) compare adherence to a strict
dietary regimen among users randomized to use DietMatePro
versus a paper-based food record.
MATERIALS AND METHODS
Participants (n ? 174) were recruited from November 2003
to March 2004 from print ads placed in the health section of the
Washington Post seeking volunteers for a four week diet study
of food intake recording methods (Fig. 1). Eligible participants
were overweight (BMI 25–40) adults who were computer
literate (reported using computers at least 3 times per week)
and able to read the standard displays of a Palm Zire 21.
Physician approval to follow a very low fat, vegetarian diet was
also required to participate in the dietary intervention period.
Participants reporting following a special diet for any health
condition were excluded from the study.
A security deposit of $50 was obtained from each partici-
pant at the beginning of the study and was returned when the
study materials were returned. Participants received $100 for
completing the study. The PICS Institutional Review Board
approved the study, and all participants provided written in-
Potential participants called the research office in response
to newspaper ads and were screened for eligibility. A research
assistant next contacted the potential participant’s physician to
obtain approval to follow the Ornish Prevention Diet, a very-
low fat, vegetarian diet. The Ornish diet was selected because
it is diet with considerable research support  but is also a
restrictive diet that is difficult for most to follow .
At the baseline visit, participants completed the demo-
graphic questionnaire and a trained research assistant measured
weight using a Detecto triple beam physician’s scale and waist
circumference using a tension-controlled tape measure. Partic-
ipants were then randomly assigned to receive either the Diet-
MatePro program or the paper-based food diary as their food
recording method based on a randomization table generated by
the first author. Research staff that made assignments based on
this randomization table were not masked to randomization at
the baseline visit but eligibility determinations were made
based on phone screenings prior to the baseline visit.
Participants were provided instructions for their assigned
recording method and asked to record intake of all food and
drink consumed throughout the entire 4-week study period. All
participants were provided with a food portion education pam-
phlet to assist in determining appropriate food portion sizes for
recording using either assessment method. Study participants
were instructed not to make any dietary changes during the
initial week they were in the study.
Fig. 1. Study Participant Flow.
Evaluation of a PDA Diet Assessment Program
JOURNAL OF THE AMERICAN COLLEGE OF NUTRITION281
Those in the paper-diary condition received a 31 page, 5.5?
by 8.5? food diary booklet that was based on a review of other
food diaries used by dietary researchers. Each page had spaces
for entries of all foods eaten at breakfast, lunch, dinner, and
snacks for each day and the estimated portions for each food
eaten. Participants were instructed to record an amount and
detailed description of all food and drink consumed as close to
the eating occasion as possible throughout the 4-week study
Those in the DietMatePro condition received a Palm Zire 21
loaded with the DietMatePro program. The participant could
access the program at any time from the DietMatePro icon but
was also prompted by an auditory alert to record meals at the
times the user was most likely to eat these meals each day.
After selecting the meal to record, foods from version 15 of the
USDA database, augmented with common packaged and res-
taurant foods, could be selected using either a search function
or selecting within food category lists. After each selection, the
program prompted the user to enter the unit of measure and the
amount of each food selected. Foods from meals could be saved
and later modified and reused for subsequent recording if
similar to a prior meal, thus reducing food entry time. Foods
not listed in the program could be entered individually along
with all of the information on the nutrition label. This database
included a time and date stamp for each recording, the time and
date of the meal as recorded by the participant, the foods eaten
at each meal, their portion size, and the nutrient values asso-
ciated with this dietary intake. During the first week of Diet-
MatePro use, participants recorded food amounts and the pro-
gram displayed food amounts without any energy or nutrient
At the week 1 visit, the participant returned the recording
method provided and the data were either uploaded (Diet-
MatePro) or collected by the research assistant and later entered
into the ESHA Food Processor SQL 9.1.2 (ESHA, Version
9.1.2, Salem, OR) to determine nutrient values. A research
assistant reviewed paper-based food diaries to insure complete
entries and appropriate portion estimations. Research assistants
were aware of the participant’s randomization assignment dur-
ing the assessment. Participants completed subjective ratings of
the recording method used.
The research assistant next conducted a 24-hr dietary recall
with the participant. The week 1 24-hr recall served as the
criterion measure for assessing concurrent validity while the
purpose of the week 4 24-hr recall was to measure adherence to
the dietary intervention. Prior to study initiation, a registered
dietitian trained the research assistants to conduct a multiple
pass 24-hr recall, using the USDA five-step multiple-pass
method as a framework [19,20]. Following the training session,
each research assistant conducted a mock 24-hr recall interview
to insure consistency among interviewers. Food models were
used to assist in portion-size estimation of consumed foods.
A research assistant followed a script to describe the very
low fat diet to each participant. Each participant was provided
with an individualized target calorie level based on the Harris-
Benedict calculation using NIH guidelines for weight loss ,
a fat goal of 10–15% of calories, saturated fat ?7% calories,
and cholesterol less than 200 mg. All participants were pro-
vided with Eat More, Weigh Less by Dean Ornish  and Fat
Free and Easy by Jennifer Raymond . Participants in the
DietMatePro condition received a version of the program that
displayed personalized target values for energy based on the
Harris-Benedict calculation using NIH guidelines for weight
loss  as well as fat, saturated fat, and cholesterol goals
based on Ornish Prevention Diet recommendations. Additional
DietMatePro program features to assist in adhering to the
dietary regimen included feedback of comparisons between
actual and target intake by meal and by day as well as recipes
and meal plans consistent with the assigned diet. Research
assistants instructed DietMatePro participants on these addi-
All participants were asked to continue recording all foods
and drinks consumed until they returned for their week 4 visits.
At the end of the fourth week, participants returned their
assigned recording method. Data collection at the final visit
included a 24-hr recall, self-report of recording practices,
weight, and waist measurements.
Two registered dietitians and one research assistant having
previous experience with dietary research entered 24-hr recall
and food diary information into ESHA Food Processor SQL
(Version 9.1.2, Salem, OR). For quality control, 10% of the
data were independently verified. Correlations between the two
entries were high for energy, fat, saturated fat, and cholesterol,
ranging from 0.91 to 0.97. Both the ESHA Food Processor and
the DietMatePro system rely on the USDA Nutrient Database
SR, and database differences were negligible . Question-
naires were scanned using teleforms and data were verified by
a research assistant.
Independent t-tests for continuous variables and chi-squared
tests for categorical variables were used to compare baseline
values between conditions and between study participants who
completed the study versus those who discontinued. Dietary
variables with non-normal distributions were analyzed using
non-parametric Wilcoxon rank sum tests.
To evaluate dietary monitoring capabilities of DietMatePro,
week 1 median and inter-quartile ranges (25thand 75thpercen-
tile) reported by assigned recording method were calculated. To
assess statistical significance between conditions, values were
ln-transformed to improve normality and compared using in-
dependent t-tests. Concordance between week 1 24-hr recall
and assigned recording method data were compared by Spear-
man correlations and compared using independent t-tests after
Evaluation of a PDA Diet Assessment Program
282 VOL. 27, NO. 2
Dietary monitoring adherence via the DietMatePro diary
and the paper-based food record was determined by calculating
the percentage of days with plausible energy intake ranges (500
to 3500 calories for women and 800 to 4,000 calories for men)
 by sampling the last three days, including weekend days if
within this three day period, of week 1 and week 4. We
sampled only six days out of the four-week intervention period
due to the resources required to enter four weeks of paper-
based food entries for each of the diary participants.
Reporting plausible energy intake ranges was used as a
proxy for recording a “complete” day of intake and inclusion in
subsequent analyses. Adherence to the prescribed diet regimen
was analyzed using both the diary and 24-hr recall data. The
percentage of recorded days during week 4 for each dietary
monitoring system in which the participant remained at or
under the total calories, fat, saturated fat, and cholesterol pre-
scribed was calculated. Sensitivity analysis using worst and
best case scenarios for missing data were performed.
Pre-post intervention changes in energy and nutrient intake
were calculated by subtracting week 4 24-hr recall estimates
from week 1 estimates. With 160 participants, the study pro-
vided over 90% power to detect a 10g (Standard Deviation
(SD) 25g) difference in daily total fat intake with a 2-sided
alpha level of 0.05 (PS Power and Sample Size, Version 2.1.3,
2003, Nashville, TN). We used SPSS version 12 (SPSS Inc,
Chicago, II) for statistical analyses, and the level of statistical
significance was set at p ? 0.05.
Despite randomization, mean BMI was 2 units lower in the
DietMatePro condition than the paper diary condition (p ?
0.02). There were no other significant differences between
groups by randomization assignment (Table 1). At week 1,
median energy intake reported by 24-hr recall was 1852
(IQR ? 1437 to 2297) calories in the DietMatePro compared to
1605 (IQR ? 1350 to 2015) in the paper diary group. This
difference in intake between conditions was also observed
comparing week 1 diary data. For the three main nutrients
targeted in the intervention (fat, saturated fat, and cholesterol),
reported intake was between 17% and 33% greater in the
DietMatePro compared to the paper diary condition (Table 2).
Compared to the 159 participants who completed the inter-
vention, the 15 participants who dropped out had a higher mean
BMI (35.05 versus 30.63, 95% CI for difference 1.64 to 7.20)
and waist circumference (38.06 vs. 35.72 in), 95% CI for
difference 0.73 to 3.96 in). Completers did not differ from
drop-outs in age, gender, level of education, employment sta-
tus, or race.
Concordance of Week 1 Paper Based and
DietMatePro Diaries to Week 1 24-hr Recall
Despite similar summary measures of intake reported by
both paper-based and DietMatePro food diaries, Spearman
correlation coefficients measuring the association between
24-hr recall and the corresponding time period for the food
diary assessed at week 1 were higher for the paper-based diary
compared to DietMatePro (Table 2). The week 1 median dif-
ference between the paper diary and the recall was only 5
calories (IQR ? ?365 to 204) compared to 137 calories
(IQR ? ?487 to 371) for the DietMatePro condition, but this
difference was not statistically significant. For both conditions,
the diary reflected higher energy and nutrient intake compared
to the 24-hr recall.
Adherence to Dietary Monitoring between
Plausible caloric intake was defined as 500 to 3500 calories
for women and 800 to 4,000 calories for men . For the
week 1 concordance analysis, data with missing or implausible
energy intakes were reported for a larger proportion of Diet-
MatePro participants (20%) compared to those assigned to the
paper-based diary condition (8%) (p ? 0.03). Over the 6 day
sampling period, on days where participants reported any in-
take, 93% of daily summaries from DietMatePro records (n ?
80) and 95% of paper diary (n ? 75) days (p ? 0.37) fell within
range. Sensitivity analyses were performed to address the pos-
sibility that informative missing data may lead to incorrect
inferences. Adherence was 78% for both conditions assuming
drop-outs were completely non-compliant to recording (p ?
0.99) and 95% for DietMatePro versus 96% for the paper diary
under the assumption that all drop-outs were completely ad-
herent to recording (p ? 0.30).
Table 1. Baseline Characteristics of Study Participants by
(n ? 89)
Mean ? SD* or %
(n ? 85)
Mean ? SD or %
Employed full-time (%)
52 ? 12
29.9 ? 4.3
36.2 ? 4.9
54 ? 10
32.1 ? 4.4
38.6 ? 5.6
* SD ? standard deviation, y ? years, BMI ? Body Mass Index, kg ?
kilograms, m ? meters, in ? inches.
** p ? 0.02, unpaired t-test.
Evaluation of a PDA Diet Assessment Program
JOURNAL OF THE AMERICAN COLLEGE OF NUTRITION283
Adherence to the Dietary Intervention between
Daily adherence to the intervention diet was defined as
reported intakes via assigned recording method below the pre-
scribed calorie intake, ?15% total calories from fat, ?7%
calories from saturated fat, and cholesterol intake below
200mg. Using these criteria, mean percent adherence to all four
dietary criteria during the last three days of the intervention was
43% (n ? 72) for the DietMatePro condition versus 28% (n ?
69) for the paper diary condition (?2(1) p ? 0.039). Including
missing data under the extreme assumptions that missing data
indicated non-adherence reduced the difference between
groups from 15% to 14% whereas assuming missing values
indicated adherence to the dietary regimen reduced the differ-
ence further to 10% between groups.
Pre-post intervention reductions in energy intake, measured
by 24-hr recall, were 2.1 times greater for DietMatePro com-
pared to the paper diary condition (p ? 0.005). Median reduc-
tion in total fat intake was 31g (IQR 8, 62) among DietMatePro
versus 22g (IQR ?13,45) among paper diary participants (p ?
Although the intervention period was too short to expect
differential anthropometric changes from these dietary mon-
itoring conditions, there were trends towards larger anthro-
pometric changes in the DietMatePro versus paper diary
condition over the 3-week intervention period. Mean weight
decreases were 3.5 (SD ? 4.9) pounds in the electronic
compared to 2.9 (SD ? 4.8) pounds in the paper diary
condition (p ? 0.39). Waist circumference decreased by 1.0
(SD ? 1.2) inch in the DietMatePro compared to 0.5 (SD ?
1.5) inch in the paper diary (p ? 0.04). These findings were
robust to adjustment for baseline BMI using linear regres-
Self-Reported Adherence and Usability of the
Paper-Based and DietMatePro Diaries
Though food record data suggested participants adhered to
the prescribed dietary regimen for well under half of the meals,
by questionnaire the DietMatePro diary group reported 60%
adherence and the paper diary group reporting adhering to
dietary recommendations for 63% of the meals. There were no
significant differences between groups on 5-point Likert-Scale
ratings of how closely the diet was followed, ease of following
the diet, or utility of the recording method.
The results of this trial suggest that paper-based food diaries
may be more concordant with 24-hr recall data than Diet-
MatePro food diaries. The DietMatePro record was moderately
correlated with the 24-hr dietary recall on calories and major
macronutrients, but these correlations were generally lower
than those found for the paper-based food diary. Since 24 hour
recall data may be incomplete due to memory problems or the
interview situation  and the DietMatePro food record en-
tries reported higher intakes than recall reports on average, it is
unclear whether the paper-based diary is more accurate than
DietMatePro, or just more similar to potentially incomplete
A prior study of DietMatePro produced higher correlations
with 24-hr recall data, i.e. 0.713 for energy compared to 0.542,
than in the present study . This prior study, however,
involved participants who used DietMatePro for only a three
day period, the last day of which was compared to 24-hr recall.
Therefore, the additional recording burden prior to the 24-hr
recall period (i.e. 7 days) and the anticipation of another three
weeks of recording may have resulted in a less careful and
Table 2. Effectiveness of Dietary Monitoring as Measured by Week 1 Median (IQRa) and Spearman Correlations by
Energy or NutrientDietMatePro
(n ? 71)
(n ? 78)
(n ? 71)
Paper Diary Correlations
(n ? 78)
Total Fat (g)
Saturated Fat (g)
Vitamin A (IU)b,c
Vitamin C (mg)
1872 (1376, 2511)
60 (46, 96)
22 (13, 33)
193 (100, 342)
232 (168, 322)
17 (10, 25)
79 (54, 97)
3676 (1831, 8250)
79 (28, 135)
693 (459, 952)
13 (9, 19)
1671 (1344, 2173)
57 (41, 77)
19 (14, 30)
163 (83, 321)
214 (172, 266)
17 (13, 24)
75 (50, 94)
4877 (2632, 9373)
72 (35, 111)
734 (423, 1133)
12 (9, 17)
aInter-quartile range (25th %, 75th %), kcal ? kilocalories g ? grams, mg ? milligrams.
bLn-transformed energy and nutrients compared by monitoring condition using unpaired t-test. Significant difference for vitamin A (p ? 0.025).
cFisher-transformed correlations compared by unpaired t-test. Significant difference (p ? 0.05) between monitoring conditions for energy, fiber, protein, vitamin A,
calcium, and iron.
Evaluation of a PDA Diet Assessment Program
284VOL. 27, NO. 2
complete recording on the day corresponding to the 24-hr recall
period. The percentage of days with missing or implausible
food records was greater than twice as high among Diet-
MatePro compared to paper diary data. One possible explana-
tion for this difference is that it takes approximately 8 minutes
to record each meal using the PDA program  which is
presumably longer than it would take to use a paper food diary.
If so, then it is important to note that computerized food diary
recording methods are not immune from inaccuracies resulting
from participant recording burden.
Although DietMatePro did not correlate as well with 24-hr
recall as did the paper-based diary in this study, DietMatePro
participants adhered better to the diet prescription than paper
diary participants, maintaining intake under stringent energy,
fat, saturated fat, and cholesterol restrictions 43% of the days
sampled compared to 28% among the paper diary participants.
Glanz et al. reported on a pilot behavioral intervention study
among 33 participants of the Women’s Health Initiative using
PDA’s to reduce fat intake to less than 20% of caloric intake
and increase fruit and vegetable intake found that participants
met fat and produce goals on 60% of days . Therefore,
PDA-based dietary monitoring and feedback programs appear
to have a positive impact on adherence to low-fat diets.
Though both conditions received books and individual in-
structions to improve adherence, the DietMatePro program also
included several features compared to the paper diary designed
to improve adherence (e.g. calorie and nutrient feedback fol-
lowing recording of a meal, comparison of actual intake to
target intake, preplanned recipes and meals consistent with
diet). Future research could assess the relative importance of
individualized feedback and meal plans, recipes that are readily
available, and the platform for the food recording method in
encouraging change in dietary intake.
Further support for increased adherence to the dietary reg-
imen was provided by the 24-hr recall data showing a mean
calorie pre-post difference of 490 calories in DietMatePro
participants compared to 226 calories among paper-based diary
participants. Mean reductions in fat intake were similar to the
10.9% decrease reported during the first year of the Women’s
Health Initiative intervention . Although study duration
was too short to expect differential changes in anthropometric
measures, those in the DietMatePro condition experienced sig-
nificantly greater reductions in waist circumference compared
to those in the paper-based diary condition.
There are a number of study limitations that should be
considered in interpreting the results of this study. The study
participants were mostly women and were selected for access
to health care and computer literacy that could limit the exter-
nal validity of these findings. Sampling three days of food
records before and after the intervention may not be an accurate
reflection of adherence, as participants may have increased
recording close to the study visits or decreased recording due to
fatigue. Selection factors may have influenced study comple-
tion, as 18 DietMatePro compared to 7 paper diary participants
had implausible food record data for the concordance analysis.
The concordance analysis was based on the final day of record-
ing before the week 1 visit, so the difference between groups
may be due to greater retrospective recording in the paper-
based condition, not necessarily to poorer recording adherence
in the DietMatePro condition. We performed sensitivity anal-
ysis under best and worst-case scenarios of adherence to insure
findings were not due solely to selection bias.
Though we modeled 24-hr recall procedures after a five-
step, multiple-pass method, this dietary assessment technique is
subject to measurement error that increases random error in
comparing the 24-hr recall data with food diary data. Further-
more, the 24-hr recalls may have been influenced by the prior
recording since it is not typical for participants to prospectively
record and also retrospectively report food intake for the same
time period. The study design could have been improved by
masking research assistants to treatment assignment for 24 hour
recalls and other assessment procedures.
Other studies have investigated the use of PDA programs to
improve adherence to complicated dietary regimens as a result
of chronic disease. A six-month crossover trial designed to
evaluate the effect of using a handheld self-monitoring program
and found a mean HbA1C reduction of 0.825% after a 3-month
intervention compared with control periods . Another pilot
study that tested the feasibility of using a PDA program among
five individuals following a hemodialysis dietary regimen de-
scribed trends of increased albumin, but larger studies are
required to draw inferences . These studies suggest PDA
based programs can improve adherence to dietary regimens
leading to improved clinical outcomes, and a study lasting 6
months suggested changes may be sustainable . The utility
of PDA-based dietary assessment software programs such as
DietMatePro will be highly dependent upon both the accuracy
and comprehensiveness of the food and nutrient database and
the ease with which foods may be searched and selected by the
This study provides evidence regarding the feasibility of
using DietMatePro as a tool for improving short-term adher-
ence to dietary regimens. Studies are needed to assess patterns
of long-term use and impact of using this self-monitoring and
dietary adherence tool on clinical outcomes.
DietMatePro food records may provide valid assessment of
dietary intake. Though PDA programs require additional train-
ing compared to food diaries, the information returned does not
need to be entered into a nutrient analysis program by another
person, thereby improving time efficiency and reducing possi-
bilities for error in transferring the information from paper to
database. Immediate tailored feedback as well as other PDA
program features may enhance adherence to dietary regimens
compared to paper-based monitoring of food intake.
Evaluation of a PDA Diet Assessment Program
JOURNAL OF THE AMERICAN COLLEGE OF NUTRITION285
ACKNOWLEDGMENTS Download full-text
This work was funded by a NINR Grant#: R44NR008443.
The authors would like to thank Gunnar DeMarco for his
instrumental role in the design and development of Diet-
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Received November 5, 2006; revision accepted January 23,
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