scholarly journals Adherence to Self-monitoring of Dietary Intake During a Weight Loss Intervention: Does a Personalized Approach Maintain Adherence? (FS11-04-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Collin Popp ◽  
Mark Butler ◽  
David St-Jules ◽  
Lu Hu ◽  
Paige Illiano ◽  
...  
Keyword(s):  
Weight Loss ◽  
Dietary Intake ◽  
Repeated Measures ◽  
Heart Association ◽  
Behavioral Approach ◽  
Self Monitoring ◽  
Behavioral Counseling ◽  
Weight Loss Programs ◽  
Session Attendance ◽  
Personalized Approach

Abstract Objectives We compared self-monitoring adherence in participants randomized to two weight loss programs: a STANDARDIZED, one-size-fits-all, low-fat diet, or a diet PERSONALIZED to minimize the postprandial glycemic response. Methods Participants were adults with pre-diabetes or type 2 diabetes, and a BMI >27 k/m2. Both groups were instructed to restrict total calories, monitor dietary intake with the Personal Nutrition Program (PNP) smartphone app, and attend videoconference behavioral counseling sessions on the same intervention schedule. STANDARDIZED (n = 12) received app feedback about intake of total calories and dietary fat. PERSONALIZED (n = 20) received app feedback about intake of total calories plus a meal-specific predicted glycemic score. Total meal entries were measured at 1, 2 and 3 months. Self-monitoring adherence was defined as logging >50% of expected meals each month into the PNP app, assuming 3 meals/day. Session attendance was also measured. Repeated measures binomial logistic regression analysis was used to assess change in adherence due to treatment group, time (i.e., months), and the interaction between treatment and time, adjusting for age, gender and BMI. Results Proportion adherent was 75.0%, 41.7% and 8.3% in the STANDARDIZED group and 85.0%, 80.0% and 75.0% in the PERSONALIZED group during months 1, 2 and 3, respectively. The repeated measures model demonstrated a significant effect of month (P < 0.001) and a treatment*month interaction (P = 0.011). After adjusting for covariates, these effects remained significant, showing a significant reduction in odds of adherence by month (OR [95%CI]: 0.13 [0.05, 0.37]; P < 0.001). Moreover, compared to the STANDARDIZED, PERSONALIZED participants had greater odds of adherence over time (OR [95%CI]: 5.12 [1.49, 17.6]; P = 0.009). Higher BMI was significantly associated with lower adherence (OR [95%CI]: 0.92 [0.87, 0.98]; P = 0.006). The proportion of attendance at videoconference sessions was similar between groups (STANDARDIZED: 77.1%; PERSONALIZED: 77.5%). Conclusions Two weight loss programs having similar calorie targets, behavioral approach, and contact schedule resulted in similar session attendance. However, adherence to self-monitoring was better when feedback was personalized. Funding Sources American Heart Association.

scholarly journals Randomized Controlled Pilot Study Testing Use of Smartphone Technology for Obesity Treatment

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Jerilyn K. Allen ◽  
Janna Stephens ◽  
Cheryl R. Dennison Himmelfarb ◽  
Kerry J. Stewart ◽  
Sara Hauck
Keyword(s):  
Weight Loss ◽  
Pilot Study ◽  
Behavioral Interventions ◽  
Pilot Trial ◽  
Smartphone Application ◽  
Self Monitoring ◽  
Behavioral Counseling ◽  
Counseling Intervention ◽  
Smartphone Technology ◽  
Smartphone Intervention

Background. The established interventions for weight loss are resource intensive which can create barriers for full participation and ultimate translation. The major goal of this pilot study was to evaluate the feasibility, acceptability, and preliminary efficacy of theoretically based behavioral interventions delivered by smartphone technology.Methods. The study randomized 68 obese adults to receive one of four interventions for six months: (1) intensive counseling intervention, (2) intensive counseling plus smartphone intervention, (3) a less intensive counseling plus smartphone intervention, and (4) smartphone intervention only. The outcome measures of weight, BMI, waist circumference, and self-reported dietary intake and physical activity were assessed at baseline and six months.Results. The sample was 78% female and 49% African American, with an average age of 45 years, and average BMI of 34.3 kg/m2. There were trends for differences in weight loss among the four intervention groups. Participants in the intensive counseling plus self-monitoring smartphone group and less intensive counseling plus self-monitoring smartphone group tended to lose more weight than other groups (5.4 kg and 3.3 kg, resp.).Conclusions. The results of this pilot trial of a weight loss intervention provide preliminary support for using a smartphone application for self-monitoring as an adjunct to behavioral counseling.

scholarly journals Expert Opinions on Reducing Dietary Self‐Monitoring Burden and Maintaining Efficacy in Weight Loss Programs: A Delphi Study

2021 ◽  
Author(s):  
Rebecca A. Krukowski ◽  
Jean Harvey ◽  
Janna Borden ◽  
Melissa L. Stansbury ◽  
Delia Smith West
Keyword(s):  
Weight Loss ◽  
Delphi Study ◽  
Self Monitoring ◽  
Expert Opinions ◽  
Weight Loss Programs

scholarly journals The effect of adherence to a smartphone app use on long-term effectiveness of weight loss in developing and OECD countries (Preprint)

2019 ◽  
Author(s):  
Sang Youl Rhee ◽  
Myeung Hee Han
Keyword(s):  
Weight Loss ◽  
Developing Countries ◽  
Body Weight ◽  
Repeated Measures ◽  
Oecd Countries ◽  
Smartphone App ◽  
Self Monitoring ◽  
Significant Difference ◽  
Over Time

BACKGROUND Behavioral change interventions using smartphone applications (apps) have rapidly increased worldwide to prevent non-communicable diseases. However, most previous studies on the use and effectiveness of apps have been conducted in OECD countries, and rarely in developing countries. OBJECTIVE The purpose of this study was to compare the characteristics of long-term use of an app and examine the effects of app use on body weight changes over time between developing and OECD countries. METHODS Secondary data analysis was conducted with the repeated measures. Data were collected from users (n=312) in developing countries and users (n=8041) in OECD countries who used the app for 12-month. The app provided programs for self-monitoring of physical activity, dietary intake, and body weight. Descriptive statistics, independent T-tests, Chi-square tests and linear mixed models were used for analysis. RESULTS Body weight of overall users significantly decreased over time (-1.79kg, P <.001), however, there was no statistically significant difference in the change of body weight for 12-month between developing and OECD countries (β= -.16, P=.189). The changes in body weight over time (from baseline to 12 months) differed by gender (β= -19.01, P <.001). In addition, users who frequently monitored their lunch (β= -0.1, P <.001), dinner (β= -0.1, P <.001), body weight (β= -0.1, P <.001), evening snack (β= -0.1, P <.001), and exercise (β= -0.03, P <.001) showed significant weight loss over time. CONCLUSIONS This study found that smartphone app could be effective tools for self-monitoring of health-related behaviors and achieving weight loss regardless of the level of development of the user’s country of residence.

Evaluation of a portable device to record dietary intake in women using commercial weight-loss programs

2013 ◽  
Author(s):  
Matthew J. Burns ◽  
Philip M. Wilson ◽  
Diane E. Mack ◽  
Jenna D. Gilchrist ◽  
Lindsay S. Meldrum ◽  
...  
Keyword(s):  
Weight Loss ◽  
Dietary Intake ◽  
Portable Device ◽  
Weight Loss Programs

scholarly journals Weight-Related Information Avoidance Prospectively Predicts Poorer Self-Monitoring and Engagement in a Behavioral Weight Loss Intervention

2020 ◽  
Author(s):  
Leah M Schumacher ◽  
Mary K Martinelli ◽  
Alexandra D Convertino ◽  
Evan M Forman ◽  
Meghan L Butryn
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Body Weight ◽  
Treatment Engagement ◽  
Treatment Discontinuation ◽  
Behavioral Weight Loss ◽  
Self Monitoring ◽  
Information Avoidance ◽  
Related Information ◽  
Session Attendance

Abstract Background Self-monitoring is a key component of behavioral weight loss (BWL) interventions. Past research suggests that individuals may avoid self-monitoring in certain contexts (e.g., skipping self-weighing after higher-than-usual calorie intake). However, no studies have attempted to quantify individuals’ inclination to avoid information about their weight control (“weight-related information avoidance”; WIA) or prospectively examined its implications for treatment engagement and outcomes in BWL programs. Purpose Characterize WIA using a validated questionnaire among adults enrolled in BWL treatment and examine whether WIA prospectively predicts self-monitoring adherence, session attendance, treatment discontinuation, or weight loss. Methods Participants (N = 87; MBMI = 34.9 kg/m2, 83% female) completed a measure of WIA prior to starting a 12 week, group-based BWL intervention. Participants were given digital self-monitoring tools and instructed to self-monitor their food intake daily, physical activity daily, and body weight weekly (Weeks 1–10) and then daily (Weeks 11–12). Session attendance and treatment discontinuation were recorded. Weight was measured in-clinic pretreatment and posttreatment. Results While mean WIA was low (M = 2.23, standard deviation [SD] = 0.95; potential scale range: 1–7), greater WIA predicted poorer attendance (r = −.23; p = .03) and poorer self-monitoring of physical activity (r = −.28; p = .009) and body weight (r = −.32; p = .003). WIA did not predict food monitoring (p = .08), treatment discontinuation (p = .09), or 12 week weight loss (p = .91). Conclusions Greater WIA, as assessed via a brief questionnaire, may place individuals at risk for poorer self-monitoring and treatment engagement during BWL. Further research on the implications of WIA in the context of weight management is warranted, including evaluation of correlates, moderators, and mechanisms of action of WIA. Clinical Trial Registration NCT03337139.

scholarly journals Adapting evidence-based behavioral weight loss programs for emerging adults: A pilot randomized controlled trial

2017 ◽  
Vol 24 (7) ◽  
pp. 870-887 ◽  
Author(s):  
Jessica Gokee LaRose ◽  
Deborah F Tate ◽  
Autumn Lanoye ◽  
Joseph L Fava ◽  
Elissa Jelalian ◽  
...  
Keyword(s):  
Weight Loss ◽  
Emerging Adults ◽  
Controlled Trial ◽  
Behavioral Weight Loss ◽  
Self Monitoring ◽  
Web Based ◽  
Face To Face ◽  
Weight Losses ◽  
Weight Loss Programs ◽  
Intent To Treat

Emerging adults are at high risk of obesity but behavioral weight loss programs do not meet their needs. Emerging adults ( N = 52, age = 22.3 ± 2 years, body mass index = 34.2 ± 5.5 kg/m2, 46.2% non-Hispanic White) were randomly assigned to one of three behavioral weight loss programs adapted based on formative work: face-to-face behavioral weight loss, web-based behavioral weight loss, or web plus optional community sessions (Hybrid). Assessments occurred at 0 and 3 months. Engagement and self-monitoring were highest in Hybrid. Intent-to-treat weight losses were −2.8 ± 2.9 percent in face-to-face behavioral weight loss, −2.2 ± 4.5 percent in web-based behavioral weight loss, and 4.8 ± 4.9 percent in Hybrid. Percent achieving ⩾5 percent weight loss was highest in Hybrid (63%). Findings suggest potential for adapted behavioral weight loss to promote engagement and weight loss in emerging adults.

scholarly journals The Effect of Electronic Self-Monitoring on Weight Loss and Dietary Intake: A Randomized Behavioral Weight Loss Trial

Obesity ◽  
2011 ◽  
Vol 19 (2) ◽  
pp. 338-344 ◽  
Author(s):  
Lora E. Burke ◽  
Molly B. Conroy ◽  
Susan M. Sereika ◽  
Okan U. Elci ◽  
Mindi A. Styn ◽  
...  
Keyword(s):  
Weight Loss ◽  
Dietary Intake ◽  
Behavioral Weight Loss ◽  
Self Monitoring

scholarly journals Examination of Nutrition Literacy and Quality of Self-monitoring in Behavioral Weight Loss

2018 ◽  
Vol 52 (9) ◽  
pp. 809-816 ◽  
Author(s):  
Diane L Rosenbaum ◽  
Margaret H Clark ◽  
Alexandra D Convertino ◽  
Christine C Call ◽  
Evan M Forman ◽  
...  
Keyword(s):  
Weight Loss ◽  
Caloric Intake ◽  
Secondary Analysis ◽  
Behavioral Weight Loss ◽  
Food Record ◽  
Obese Adults ◽  
Baseline Measure ◽  
Self Monitoring ◽  
Session Attendance

Abstract Background Few have examined nutrition literacy (i.e., capacity to process and make informed nutritional decisions) in behavioral weight loss. Nutrition literacy (NL) may impact necessary skills for weight loss, contributing to outcome disparities. Purpose The study sets out to identify correlates of NL; evaluate whether NL predicted weight loss, food record completion and quality, and session attendance; and investigate whether the relations of race and education to weight loss were mediated by NL and self-monitoring. Methods This is a secondary analysis of 6-month behavioral weight loss program in which overweight/obese adults (N = 320) completed a baseline measure of NL (i.e., Newest Vital Sign). Participants self-monitored caloric intake via food records. Results NL was lower for black participants (p < .001) and participants with less education (p = .002). Better NL predicted better 6-month weight loss (b = −.63, p = .04) and food record quality (r = .37, p < .001), but not food record completion or attendance (ps > 0.05). Black participants had lower NL, which was associated with poorer food record quality, which adversely affected weight loss. There was no indirect effect of education on weight loss through NL and food record quality. Conclusions Overall, results suggest that lower NL is problematic for weight loss. For black participants, NL may indirectly impact weight loss through quality of self-monitoring. This might be one explanation for poorer behavioral weight loss outcomes among black participants. Additional research should investigate whether addressing these skills through enhanced treatment improves outcomes. Clinical trial information NCT02363010.

Abstract P506: Dietary Self-monitoring Using An App: Are Frequency, Consistency And Completeness Related To Weight Loss?

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Jason E Payne ◽  
Melanie T Turk ◽  
Christine A Pellegrini ◽  
Melissa A Kalarchian
Keyword(s):  
Weight Loss ◽  
Linear Regression ◽  
Dietary Intake ◽  
Weight Change ◽  
Linear Regression Analysis ◽  
T Test ◽  
Self Monitoring ◽  
Paired Sample ◽  
Percent Weight Loss ◽  
Increased Risk

Background: Approximately 70% of the U.S. adult population has obesity and/or overweight and thus increased risk for heart disease, stroke, and type II diabetes mellitus. Standard obesity treatment includes a behavior modification technique, dietary self-monitoring, which entails recording all foods and beverages consumed with calorie amounts and time of consumption. Greater adherence to dietary self-monitoring using a paper diary is associated with weight loss. Self-monitoring via a mobile phone application (app) is an appealing, convenient alternative to paper-based techniques; however, few studies have examined the relationship between adherence to a dietary self-monitoring app and weight loss. Objectives: The objectives of the study were to 1) examine if there is an association between app-based dietary self-monitoring and weight change and 2) explore the relationships between the frequency, consistency, and completeness of app-based dietary self-monitoring and weight change at 8 weeks among adults with overweight or obesity. Frequency was the percentage of days that any self-monitoring occurred during the study; consistency was the recording of any dietary intake on > 3 days each week; completeness was the recording of 50% or more of the weekly individual calorie goal. Methods: Ninety participants interested in weight loss were recruited to self-monitor dietary intake for 8 weeks using the app Calorie Counter by FatSecret. Participants were assigned a daily calorie goal to achieve a one-pound weight loss per week. Paired sample t-test and linear regression were used to examine the relationships between app-based self-monitoring and weight change as well as the frequency, consistency and completeness of self-monitoring and weight change at 8 weeks. Results: The sample [N = 90, mean ( M ) age = 42 ± 10 years (SD)] was employed (100%), primarily female (96.7%), White (90%), and married (63.3%) with a Bachelor’s or Associate’s degree (60%). Paired-sample t test revealed a significant mean difference [ t (89) = 6.59, p < .001] between baseline and 8-week weight in pounds ( M = -3.26 ± 4.70). Linear regression analysis revealed an association [ F (1, 88) = 7.18, p = .009] between total weeks of consistently self-monitoring ( M = 4.44 ± 2.77) and percent weight loss ( M = -1.54 ± 2.26) as well as an association ( F (1, 88) = 6.42, p = .013] between the frequency of self-monitoring ( M = 50.14 ± 33.0) and percent weight loss. Completeness of self-monitoring was not associated with percent weight loss. Conclusion: Results suggest that consistent ( > 3 days/week) and frequent ( > 50% of days) app-based self-monitoring aids weight loss. Clinicians may wish to emphasize frequent and consistent self-monitoring, rather than complete self-monitoring, when providing weight loss counseling. Future research should examine app-based self-monitoring in men as well as ethnically and racially diverse populations. .

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