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The Effect of Electronic Self-Monitoring on Weight Loss and Dietary Intake: A Randomized Behavioral Weight Loss Trial
Abstract
Technology may improve self-monitoring adherence and dietary changes in weight loss treatment. Our study aimed to investigate whether using a personal digital assistant (PDA) with dietary and exercise software, with and without a feedback message, compared to using a paper diary/record (PR), results in greater weight loss and improved self-monitoring adherence. Healthy adults (N = 210) with a mean body mass index of 34.01 kg/m2 were randomized to 1 of 3 self-monitoring approaches: PR (n = 72), PDA with self-monitoring software (n = 68), or PDA with self-monitoring software and daily feedback messages (PDA+FB, n = 70). All participants received standard behavioral treatment. Self-monitoring adherence and change in body weight, waist circumference and diet were assessed at 6 months; retention was 91%. All participants had a significant weight loss (P < 0.01) but weight loss did not differ among groups. A higher proportion of PDA+FB participants (63%) achieved ≥5% weight loss in comparison to the PR group (46%) (P < 0.05) and PDA group (49%) (P = 0.09). Median percent self-monitoring adherence over the 6 months was higher in the PDA groups (PDA 80%; PDA+FB 90%) than in the PR group (55%) (P < 0.01). Waist circumference decreased more in the PDA groups than the PR group (Ps = 0.02). Similarly, the PDA groups reduced energy and saturated fat intake more than the PR group (Ps < 0.05). Self-monitoring adherence was greater in the PDA groups with the greatest weight change observed in the PDA+FB group.
INTRODUCTION
Research has demonstrated a consistent relationship between dietary self-monitoring and success in losing weight and maintaining weight loss (1–4). Estimates from the 2008 National Health Interview Survey show that the prevalence of overweight/obesity has plateaued; however, it is still at the level of an epidemic (5). The extremely high rate of relapse following weight loss treatment magnifies the seriousness of this public health problem (5–7). An important challenge is to identify practical strategies that individuals can use to increase awareness of their energy intake and expenditure, which can help them with long-term weight management.
Self-monitoring increases individuals' awareness of their behavior and the circumstances that precipitate or surround the behavior (8). However, the most often-used method of self-monitoring continues to be the paper record (PR), which is time consuming and tedious to complete. Moreover, the feedback that is received from a PR is only present to the degree that the person records and calculates sub-totals. Furthermore, PRs do not permit immediate, real-time external feedback to support and motivate the individual. The addition of the tailored feedback message is a logical next step and is based on evidence supporting the role of feedback in reinforcing motivation for behavior change when delivered in relation to goal achievement (9, 10). Emerging technologies may improve self-monitoring and the success of weight-loss treatment through the feedback mechanism.
Several recent studies have focused on the use of the Internet for weight loss (4, 11–13). In a study that tested the use of an Internet-delivered behavioral weight loss program, Tate and colleagues showed that the number of weekly diaries submitted online was significantly related to weight loss (4). A later study by this same group examined e-mail feedback for weight loss (12). Individuals in two intervention groups received weekly reminders to complete the online diary. One group received a pre-programmed computer message on a webpage and the other group received an e-mail message from a weight loss counselor; diary submission was significantly related to weight loss in both groups. Weight loss between the groups was comparable at 3 months; however, the group that received the e-mail message lost significantly more weight at 6 months. These studies laid the foundation for technologically-supported behavioral weight loss programs that have the potential to reach a large portion of the population. However, for many individuals, use of an online diary may limit accessibility and does not permit one to check the nutrient content of foods prior to eating. In a pilot study where women in a diet modification trial were given personal digital assistants (PDAs) for self-monitoring with feedback, participants significantly increased their self-monitoring and more often achieved dietary goals (14). In a 4-week, diet-focused weight loss trial that compared PDA for self-monitoring to PR, dietary adherence was significantly higher in the PDA group (43%) compared to the PR group (28%) (15); adherence to the self-monitoring method was not reported. Despite the proliferation of hand-held devices, no one has examined the use of PDAs with dietary and exercise software for self-monitoring in behavioral weight loss treatment. Moreover, no clinical trials have examined the use of a PDA to deliver a tailored feedback message in response to the recorded behavior.
The aim of this study was to determine if self-monitoring diet and exercise using a PDA, with or without tailored feedback (PDA or PDA+FB), was superior to using a PR for promoting and maintaining weight loss. We conducted a 3-group randomized clinical trial to examine the efficacy of using a PDA as a means to improve adherence to self-monitoring as part of a standard, 24-month behavioral intervention for weight loss. This paper presents the initial results of the study at 6 months. We hypothesized that the groups using the PDA would achieve greater weight loss for the short-term (6 months) than those who use the PR. We also hypothesized that those assigned to the PDA+FB group would show better self-monitoring adherence than either of the other two treatment groups, and that the PDA groups would show better self-monitoring adherence than the PR group.
METHODS AND PROCEDURES
Study design
The methods of the SMART Trial have been detailed elsewhere (16). Briefly, SMART was a single-center, randomized clinical trial of behavioral treatment for weight loss. All participants received a 24-month standard behavioral weight loss treatment and were randomly assigned to use 1 of 3 self-monitoring tools: (1) PR, (2) PDA or (3) PDA+FB (Figure 1). Outcome data were collected at semi-annual assessments. This report focuses on the results from the 6-month assessment.
PR, paper record; PDA, personal digital assistant; PDA+FB, personal digital assistant plus feedback.
Participants and randomization
Participants were recruited from the community in 3 cohorts from 2006 to 2008. Eligible individuals were between 18 and 59 years of age and had a body mass index (BMI) between 27 and 43 kg/m2. We excluded individuals with conditions that required medical supervision of diet or exercise and those who participated in a weight-loss program in the 6 months prior to recruitment or planned an extended vacation or relocation during the 24-month study period (16).
Of the 704 individuals screened for eligibility, 210 were enrolled in the trial. The participants were randomly assigned, stratified by gender and ethnicity, to 1 of the 3 different modes of self-monitoring. All participants provided written informed consent. The study protocol was approved by the University of Pittsburgh Institutional Review Board. Participants were compensated only for their time in completing the 6-month assessment.
Intervention
All 3 treatment groups received the same standard behavioral intervention, which has been successfully used in multiple studies (8, 17, 18). The intervention included: (1) daily self-monitoring of eating and exercise behaviors, (2) group sessions, (3) daily dietary goals and (4) weekly exercise goals.
Self-monitoring
Participants in the PR group were given standard paper diaries and instructed to record all foods eaten, the calories and fat grams, as well as minutes of exercise. At the first group session, they were given a reference book that contained nutrition information and were trained in how to determine the calorie and fat gram content of their foods. Participants in the PDA and PDA+FB groups were provided with Palm Tungsten E2™ PDAs with self-monitoring software that tracked energy and fat consumption and displayed current intake related to daily goals and also provided easily accessed nutrition information (Dietmate Pro© ) (15, 19) and CalculFit© (PICS, Reston, VA). Participants in the PDA+FB group had a custom software program on their PDAs with a feedback algorithm that provided daily messages tailored to their entries and provided positive reinforcement and guidance for goal attainment. Participants in the PDA and PDA+FB groups were trained in how to use the PDA and self-monitoring software in the first 2 group sessions.
The feedback messages varied by the time of day and conditions of reported intake, e.g., if between 10:00 AM and noon, a participant had reported consuming > 40% of the calorie allowance but only 20–40% of the fat goal, a sample message could be “Good job making choices low in fat. Watch portion sizes to control calories”. The feedback messages focused on diet could be delivered between 10:00 AM and 9:00 PM. The details of the feedback messages and algorithm are published elsewhere (16).
At each session, PR participants submitted their diaries and received new ones to use until the next session. The interventionist reviewed those diaries, provided written feedback and returned the diaries at the next session. The PDA and PDA+FB participants turned in their PDAs at the beginning of the session, the self-monitoring data were uploaded into the study database and the PDAs were returned to participants at the end of the session. The interventionists received printed reports that appeared similar to the standard paper diaries for their review and wrote comments, which were returned to the participants at the next group session.
Group Sessions
There were 16 weekly and 4 bi-weekly group sessions during the first 6 months. Sessions focused on nutritional and behavioral counseling and practical hands-on experiences to develop skills to implement a healthy lifestyle.
Dietary and exercise goals
Each participant received a daily energy and fat gram goal based on their gender and baseline weight consistent with standard behavioral weight loss treatment (18). The daily energy intake goal was between 1200 and 1500 calories for females and between 1500 and 1800 for males; the fat allowance was 25% or less for all. They were counseled to reach a weekly goal of 150 minutes of moderate intensity exercise by the sixth week.
Outcome measures
Our primary outcome was change in weight at 6 months. We measured weight on a digital scale with the participant in light clothing and not wearing shoes. Secondary outcomes included adherence to self-monitoring, waist circumference and diet. Adherence to self-monitoring diet was measured on a weekly basis and analyzed as a binary variable based on whether a participant completed daily recordings of food, energy intake and fat grams (adherent: self-monitored, non-adherent: did not self-monitor). If the weekly record indicated that a participant consumed more than 50% of the weekly calorie goal, the participant was defined as adherent to self-monitoring for that week. For example, a participant with a daily calorie goal of 1200 (weekly goal = 8400 kcal) would be adherent to self-monitoring if the person recorded consuming ≥ 4200 calories for that week. If a diary was not returned, adherence to self-monitoring was coded as non-adherent for that week. However, if a PR participant missed a group session, the completed diary could be mailed or brought it in at the next session to be counted for self-monitoring. Since all the recordings on the PDA were stored, the days /weeks of previous recordings were included in the adherence measure. Adherence to self monitoring physical activity was determined by the number of entries reporting physical activity. Waist circumference was measured at the umbilicus with a Gulick II measuring tape at baseline and 6-month assessments. Dietary intake was assessed through 2 unannounced 24-hour dietary recalls (1 weekday and 1 weekend day) at baseline and 6 months and the data were analyzed using the Nutrition Data System for Research software (Nutrition Coordinating Center, University of Minnesota).
Statistical analysis
Statistical analyses were conducted using SAS version 9.1.3 (SAS Institute, Inc., Cary, NC). The significance level was set as P≤ 0.05. Analyses were performed using the intention-to-treat principle regardless of the participant's adherence and retention. Missing data were handled by a baseline value carried forward imputation approach. Summary statistics were reported as mean (SD) and frequency count (%). For those continuous variables having outliers, the median (inter-quartile range, IQR) was also reported. Changes from baseline to 6 months were used in the analyses. Successful (clinically meaningful) weight change was defined as > 5% weight loss. The F-test from a one-way analysis of variance or the Kruskal-Wallis test for continuous variables and chi-square test of independence for categorical variables were used to compare the baseline characteristics, anthropometric and dietary variables as well as the change scores for dietary intake and waist circumference and average adherence to self-monitoring diet and physical activity over 6 months. A dependent t-test was used to examine the changes from baseline to 6 months within each treatment group. Hypotheses regarding changes from baseline to 6 months across the treatment groups were tested using planned comparison via specified linear contrasts: [1) PDA, PDA+FB vs. PR and 2) PDA vs. PDA+FB] for weight loss and adherence to self-monitoring.
Mixed-effect logistic regression modeling was applied to assess the effect of treatment groups and time on self-monitoring adherence. Both linear and nonlinear functions of time (e.g., square root and squared function of time) were considered. We used the likelihood ratio test to assess treatment group and time effects to achieve more parsimonious models. Sensitivity analyses were conducted for outliers identified through graphical methods. When outliers were omitted via sensitivity analysis, the results did not change, supporting the robustness of our findings.
RESULTS
The sample was predominantly female (85%) and White (79%). We found no significant differences in baseline demographic and anthropometric characteristics among the 3 treatment groups (Table 1). We also did not find statistically significant differential attrition/retention among the 3 treatment groups. Ninety-one percent (n = 192) completed the 6-month assessment with no differences in race, gender, age, weight or BMI between completers and non-completers.
Table 1
Baseline characteristics by treatment groupsa
| Variable | PR (n = 72) | PDA (n = 68) | PDA+FB (n = 70) | Total (N = 210) |
|---|---|---|---|---|
| Demographics | ||||
 Age (years) | 47.4 (8.5) | 46.7 (9.2) | 46.4 (9.5) | 46.8 (9.0) |
| Women, n (%) | 61 (84.7) | 58 (85.3) | 59 (84.3) | 178 (84.8) |
| White, n (%) | 55 (76.4) | 55 (80.9) | 55 (78.6) | 165 (78.6) |
| Married, n (%) | 55 (76.4) | 42 (61.8) | 47 (67.1) | 144 (68.6) |
| Employed full time, n (%) | 62 (86.1) | 58 (85.3) | 54 (77.1) | 174 (82.9) |
| Education (years) | 15.9 (3.1) | 15.5 (2.9) | 15.5 (3.0) | 15.7 (3.0) |
| Anthropometry | ||||
| BMI (kg/m2) | ||||
| Women | 33.9 (4.6) | 33.5 (3.8) | 34.2 (4.8) | 33.9 (4.4) |
| Men | 32.9 (4.4) | 36.3 (5.4) | 35.5 (4.4) | 34.9 (4.8) |
| Waist circumference (cm) | ||||
| Women | 104.3 (11.4) | 102.4 (10.1) | 103.4 (13.2) | 103.4 (11.6) |
| Men | 114.7 (11.7) | 120.2 (12.0) | 118.9 (10.3) | 117.9 (11.2) |
| Dietary intake | ||||
| Energy intake (kcal/d)b | 1970 (1533, 2483) | 1931 (1705, 2579) | 1990 (1688, 2362) | 1970 (1608, 2458) |
| % kcal total fat | 33.2 (7.3) | 34.3 (6.9) | 33.9 (7.4) | 33.8 (7.2) |
| % kcal SFAb | 11.3 (8.9, 13.4) | 12.0 (9.0, 14.2) | 11.1 (9.9, 13.8) | 11.4 (9.2, 13.8) |
| % kcal MUFA | 12.1 (2.8) | 12.7 (2.9) | 12.6 (3.3) | 12.5 (3.0) |
| % kcal PUFA | 7.1 (2.6) | 7.2 (2.5) | 6.8 (2.4) | 7.0 (2.5) |
PR, paper record; PDA, personal digital assistant; PDA+FB, personal digital assistant with the added customized feedback program; BMI, body mass index; SFA, saturated fatty acids; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids.
At 6 months, the percent mean [SD] weight loss was statistically significant (P< 0.01) for all treatment groups (PR 5.3% [5.9]%; PDA 5.5% [7.0]%; and PDA+FB 7.3% [6.6]%), with no significant differences among the groups. However, a higher proportion of participants in the PDA+FB group (63%) achieved ≥ 5% weight loss in comparison to the PR (46%) (P=0.04) and PDA (49%) (P=0.09) groups while there was no significant difference in the proportion between the combined PDA groups and the PR group (P = 0.17). Post hoc analyses revealed a significant difference in the proportion that achieved a ≥ 5% weight loss between the PDA+FB group and the combined PDA and PR groups (P = 0.03).
The overall median adherence to self-monitoring for the entire study period of 6 months was better in the PDA groups than in the PR group; the proportion of sample adherent was 90%, 80% and 55% in the PDA+FB, PDA and PR groups, respectively (P < 0.01). The pattern of adherence to self-monitoring over time among the treatment groups is displayed in Figure 2. Adherence was highest in the second week (PDA 97%; PDA+FB 96% and PR 85%); however, self-monitoring began to decline by the third week. At 6 months, 53% of the PDA and 60% of the PDA+FB groups were adherent to self-monitoring while only 31% of the PR group was. There was no significant difference between the PDA and PDA+FB groups in adherence to self-monitoring over time (P = 0.11); however, adherence to self-monitoring over time was significantly higher in the PDA (P < 0.01) and PDA+FB (P < 0.01) groups compared to the PR group.
PR, paper record; PDA, personal digital assistant; PDA+FB, personal digital assistant with the added customized feedback program.
Based on the nonlinear mixed effects modeling, adherence to self monitoring decreased over time in all treatment groups (P < 0.001). The PDA+FB group was more adherent than the PR group (P = 0.003) and the PDA group was more adherent than the PR group (P < 0.001). There was no significant difference between the PDA and the PDA+FB groups (P = 0.11).
Adherence to self-monitoring physical activity followed a pattern similar to adherence to self-monitoring dietary intake. On average, the PR group recorded 2.2 (1.8) entries per week over the 6-month period compared to the PDA group recording 2.7 (1.8) and the PDA+FB group recording 3.2 (1.8) entries per week (P = 0.006). Post hoc analyses revealed that the PR group was significantly less adherent than the combined PDA and PDA+FB groups (P = 0.007).
Table 2 shows changes within and between groups. Percent median [IQR] waist circumference also decreased significantly (P < 0.01) within each group (PR −4.0% [−8.4, 0.0]%; PDA −5.0% [−8.5, −1.7]% and PDA+FB −6.4% [−11.5, −1.8]%) and was significantly different among groups (P = 0.03). Post hoc analyses revealed a significant difference in percent waist circumference change between the PDA groups and the PR group (P = 0.02).
Table 2
Percent changes in weight, waist circumference, and dietary intake by groups at 6 months
| Variable | PR (n = 72) | PDA (n = 68) | PDA+FB (n = 70) | P valuea |
|---|---|---|---|---|
| Weightb | ||||
| median (IQR) | −4.6 (−8.6, −0.5) | −4.8 (−9.3, −0.5) | −6.5 (−10.4, −2.7) | 0.12 |
| mean (SD) | −5.3 (5.9) | −5.5 (7.0) | −7.3 (6.6) | |
| Waist circumferenceb,a | ||||
| median (IQR) | −4.0 (−8.4, 0.0) | −5.0 (−8.5, −1.7) | −6.4 (11.5, −1.8) | 0.03 |
| mean (SD) | −4.6 (6.0) | −5.5 (5.4) | −6.9 (5.8) | |
| Energy intakeb,c | ||||
| median (IQR) | −12.5 (−34.7, 0.0) | −19.9 (−39.2, −1.6) | −23.3 (−40.6, −8.3) | 0.05 |
| mean (SD) | −11.9 (31.9) | −16.7 (31.7) | −24.0 (22.4) | |
| trimmed mean (SD) | −17.4 (22.7) | −20.8 (25.3) | −26.6 (19.1) | |
| % kcal total fatb | ||||
| median (IQR) | 0.0 (−21.3, 8.7) | −9.2 (25.4,−0.1) | −12.6 (−32.8, 0.0) | 0.12 |
| mean (SD) | −5.5 (27.0) | −9.2 (20.7) | −14.0 (25.0) | |
| trimmed mean (SD) | −7.7 (23.9) | −10.2 (19.0) | −14.0 (25.0) | |
| % kcal SFAb,c | ||||
| median (IQR) | 0.0 (−31.5, 17.7) | −11.3 (−31.9, 4.5) | −17.5 (−36.1, 0.0) | 0.08 |
| mean (SD) | −1.9 (36.3) | −7.8 (36.4) | −14.4 (32.0) | |
| trimmed mean (SD) | −6.7 (28.4) | −15.5 (22.3) | −15.9 (29.5) | |
| % kcal MUFAb | ||||
| median (IQR) | −5.4 (−23.4, 15.2) | −8.9 (−26.8, 4.2) | −11.5 (−31.6, 8.2) | 0.37 |
| mean (SD) | −2.9 (33.5) | −8.8 (25.6) | −11.6 (30.5) | |
| trimmed mean (SD) | −8.0 (26.0) | −11.2 (21.9) | −13.0 (28.6) | |
| % kcal PUFAb | ||||
| median (IQR) | −4.3 (−33.1, 11.0) | −3.3 (−29.9, 9.5) | −15.4 (−40.9, 15.4) | 0.42 |
| mean (SD) | −4.6 (41.3) | −2.8 (35.3) | −8.6 (43.4) | |
| trimmed mean (SD) | −9.5 (34.3) | −9.5 (26.9) | −13.8 (35.1) |
PR, paper record; PDA, personal digital assistant; PDA+FB, personal digital assistant with the added customized feedback program; SFA, saturated fatty acids; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids; IQR, interquartile range.
Trimmed mean (SD) is calculated by excluding outliers.
Total energy intake (median [IQR]) decreased significantly among the three groups (PR −12.5 [−34.7, 0.0]%; PDA −19.9 [−39.2, −1.6]%; and PDA+FB −23.3 [−40.6, −8.3]% (P = 0.05). The combined PDA group reduced total energy (P = 0.03) and saturated fat (P = 0.03) intake more than the PR group.
DISCUSSION
This study demonstrated that participants who used a PR, a PDA with dietary and exercise software or a PDA with the same software and a daily, tailored feedback message achieved significant weight loss at 6 months. A higher proportion of the PDA+FB group achieved a ≥ 5% weight loss than the PR and PDA groups, suggesting that the daily tailored feedback messages may have enhanced the effect of standard behavioral weight loss treatment. Overall, the weight loss was good in all 3 groups, which might be explained by the frequent group sessions during the first 6 months. The attention and guidance received through the standard behavioral intervention facilitated weight loss across all groups and thus the difference by method of self-monitoring was less pronounced than what was expected. We also demonstrated that those in the PDA and the PDA+FB groups were significantly more adherent to self-monitoring than those in the PR group. While the findings do not support our hypothesis that the PDA+FB group would be more adherent to self-monitoring than the PDA group, they do support our hypothesis that the groups who used a PDA would be more adherent than the PR group.
This was the first large randomized clinical trial to compare different methods of self-monitoring in a behavioral weight loss intervention and to compare the use of PDAs to conventional paper diaries. Two previous studies addressed self-monitoring methods and reported a significant association between the number of diaries completed and weight loss; however, neither of them reported a group difference in weight loss (20, 21). Because of the methodological limitations in both studies, one cannot definitively conclude that approaches to self-monitoring other than the use of paper diaries result in better adherence or weight loss outcomes. However, our findings from this randomized trial with excellent retention do provide preliminary data to suggest that there is improved adherence to self-monitoring with the use of a PDA.
Tate and colleagues reported previously on a weight loss study that used a feedback system (12). While the group receiving the automatic computer feedback messages was comparable in weight loss to the human e-mail counseling group at 3 months; at 6 months, the e-mail counseling group had significantly greater weight loss than the computer-automated feedback group or no counseling group. The main difference between that study and our trial is that the computer feedback message in their study was delivered on a weekly basis and our PDA-delivered feedback message occurred daily (16). The significantly greater weight loss in our PDA+FB group suggests that the combined self-monitoring and feedback message delivered in real-time and on a daily basis might have provided the reinforcement and sustained motivation that was needed to improve weight loss.
The findings supported the difference in adherence to self-monitoring between the combined PDA groups and the PR group but the adherence in the two PDA groups was similar. As can be seen in Figure 2, the slope of the adherence curve began to decline at 3 weeks and steadily declined thereafter with only 30% of the PR group self-monitoring at 6 months. However, adherence for the two PDA groups was sustained by over 70% of the participants in these groups until the 12th week. At 6 months, it was still above 50%. This decline in self-monitoring over time has been a consistent finding in several studies (12, 22). The decline that we observed in this study is slightly less than what we observed in a previous trial (23) and most important, the decline in the PDA groups was significantly less than what was observed in the PR group.
While the study demonstrated that the use of the PDA improved adherence to self-monitoring in both groups (90% in PDA+FB and 80% in PDA), it was unclear why the improved adherence in the PDA without feedback group did not lead to a greater weight loss than what we observed. This may suggest a more central role for individualized feedback to goal attainment. This finding is consistent with the behavioral principles that document that feedback, both reinforcing feedback and corrective or redirective feedback, enhances motivation toward goal attainment. The feedback message functioned as a compass that enabled the individual to stay on course toward the goal; it also functioned as a source of more frequent attention that `someone' was noticing what the participant was doing, which was another powerful reinforcer, regardless of the nature of the feedback.
The goal of teaching an individual to self-monitor is that the person will learn to use the tool to provide information (feedback), and will use the information to self-correct behaviors (e.g., eating or food intake). However, many individuals do not make that connection easily, which probably contributes to their stopping self-monitoring, since they never used the strategy in a way that made a difference or sense to them. The addition of a programmed, tailored feedback message may have helped them make that connection (24).
Our findings showed that the participants in the PR group were consistently less adherent to self-monitoring over the 6 months. This might have been explained by the disadvantages to using a PR (25). Individuals who use a PR are faced with the labor of maintaining handwritten records, searching for the nutrient composition of foods in a pocket manual, and calculating subtotals for nutritional intake. In a previous study of participants who used PR, participants reported that self-monitoring was often time-consuming and burdensome (26), which often led them to record at the end of the day or days later (27). This practice eliminated the opportunity to take corrective action if one was close to the daily energy or fat goal. In contrast, benefits of using the PDA included its portability and immediate access to a U.S. Dept. of Agriculture database containing 5000 to 6000 food items including brand and restaurant foods, real-time calculation and display of dietary subtotals in relation to daily goals, and saving commonly eaten meals. Participants reported that its use was socially acceptable and thus reduced the uneasiness that might have accompanied self-monitoring in social settings. Finally, advances in wireless technology now permit transmittal of monitoring and feedback, which provide opportunities for intervention delivery (28).
There could be limitations to using a PDA. Use of technological devices might have been a barrier for some individuals; however, participants who were technologically naive were able to learn how to use the device. It is still unclear if a person saves time with a PDA (19), as this may vary depending on the software being used and the screen design.
The major strengths of our study included the randomized trial design with objective measures of the anthropometric measures and its innovative approach to examining the use of a technology that is becoming ubiquitous. It was the first large trial to compare the efficacy of PDAs with combined diet and exercise software to the traditional PR in improving weight loss and adherence to self-monitoring. An additional strength was our 91% retention rate at 6 months and the 21.4% minority representation. An important limitation was that we achieved only 15.2% male representation despite extra efforts that were made to recruit men. Additionally, the study design was for a 24-month final testing of the hypothesis; the results presented here were for 6 months and thus only revealed the short-term outcomes.
In summary, in our study that used 3 different approaches to self-monitoring diet and exercise, each group achieved a significant weight loss. Moreover, a higher proportion of the PDA+FB group achieved a clinically significant weight loss (5%) than the PDA and PR groups. The daily tailored feedback appears to have enhanced the effect of the behavioral treatment. Our study revealed that a significantly greater proportion of participants in the PDA and the PDA+FB groups self-monitored compared to those in the PR group. Also, there were significant within and between group differences in waist circumference and energy intake at 6 months. These findings suggest that use of an electronic diary facilitates improved self-monitoring; however, the use of an electronic diary plus a daily feedback message that was tailored to what had been entered in the diary was related to the best weight loss.
ACKNOWLEDGMENTS
We gratefully acknowledge the participants in this study who so willingly gave of their time to complete the assessments.
This study was supported by National Institutes of Health grants #RO1-DK71817 and partial support for LE Burke by NIH K24 Award, NR010742. The conduct of the study was also supported by the Data Management Core of the Center for Research in Chronic Disorders NIHNINR #P30-NR03924 and the General Clinical Research Center, NIH-NCRR-GCRC #5MO1-RR00056 and the Clinical Translational Research Center, NIH/NCRR/CTSA Grant UL1 RR024153 at the University of Pittsburgh.
Footnotes
DISCLOSURE None to disclose.
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Funding
Funders who supported this work.
NCATS NIH HHS (1)
Grant ID: UL1 TR000005
NCRR NIH HHS (5)
Grant ID: M01 RR000056-38
Grant ID: UL1 RR024153
Grant ID: M01 RR000056
Grant ID: UL1 RR024153-04
Grant ID: 5MO1-RR00056
NIDDK NIH HHS (9)
Grant ID: R01 DK071817-01
Grant ID: R01 DK071817-04S1
Grant ID: R01 DK071817
Grant ID: R01 DK071817-05S1
Grant ID: R01 DK071817-02
Grant ID: R01-DK71817
Grant ID: R01 DK071817-03
Grant ID: R01 DK071817-04
Grant ID: R01 DK071817-05
NINR NIH HHS (7)
Grant ID: K24 NR010742
Grant ID: K24 NR010742-01
Grant ID: K24 NR010742-02
Grant ID: K24 NR010742-03
Grant ID: P30-NR03924
Grant ID: P30 NR003924
Grant ID: P30 NR003924-11
