Dietary Self-Monitoring Through Calorie Tracking but Not Through a Digital Photography App Is Associated with Significant Weight Loss: The 2SMART Pilot Study—A 6-Month Randomized Trial

Switching diets after 6-months does not result in renewed weight loss: a secondary analysis of a 12-month crossover randomized trial

Weight change trajectory from diet and lifestyle interventions typically involves rapid weight loss followed by a weight plateau after approximately 6 months. Changing from one weight-loss diet to another at the time of the plateau could instigate renewed weight loss. Therefore, our secondary analysis aimed to assess trajectory of weight loss in a 12-month, randomized, cross-over study. Forty-two adults were randomized to eat a healthy low-fat or healthy low-carbohydrate diet for 6 months then switched to the opposite diet for an additional 6 months. Regardless of diet assignment, participants experienced rapid initial weight loss, which slowed between 3 to 6 months. After switching diets at 6 months, weight modestly decreased until 9 months, but at a rate slower than the initial 3 months and slower than the rate from 3 to 6 months. This suggests that the weight loss plateau typically seen at 6 months is physiological and cannot be overcome by simply switching to a different weight-loss diet.

Effect of using the snackability app on snack quality among US college students with overweight and obesity: A randomized controlled trial

OBJECTIVE

To determine if using the Snackability app improves snack intake among college students.

PARTICIPANTS

US college students with overweight/obesity were recruited in June 2020-April 2021.

METHODS

A randomized controlled trial was conducted to test the Snackability app use for 12 wk on snack scores (calculated from the app) compared to controls. We also explored the effect on diet quality (Healthy Eating Index-2015) and weight. Outcomes were compared between the intervention and the control groups at 4, 8, and 12 wk using repeated measures ANOVA.

RESULTS

Participants in the app group significantly increased snack score at week 4 (p < 0.001) and week 8 (p = 0.015) and increased HEI-2020 score (p < 0.001) at week 4 compared to controls. The first 4 wk had the highest app usage. No significant differences were seen in body weight.

CONCLUSIONS

The Snackability app can be used as a tool to help improve snack and diet quality in this group.

Characterization of adults concerning the use of a hypothetical mHealth application addressing stress-overeating: an online survey

BACKGROUND

About 40% of people respond to stress by consuming more unhealthy foods. This behavior is associated with increased energy intake and the risk of obesity. As mobile health (mHealth) applications (apps) have been shown to be an easy-to-use intervention tool, the characterization of potential app users is necessary to develop target group-specific apps and to increase adherence rates.

METHODS

This cross-sectional online survey was conducted in the spring of 2021 in Germany. Sociodemographic data and data on personality (Big Five Inventory, BFI-10), stress-eating (Salzburg Stress Eating Scale, SSES), and technology behavior (Personal Innovativeness in the Domain of Information Technology, PIIT; Technology Acceptance Model 3, TAM 3) were collected.

RESULTS

The analysis included 1228 participants (80.6% female, mean age: 31.4 ± 12.8 years, mean body mass index (BMI): 23.4 ± 4.3 kg/m2). Based on the TAM score, 33.3% (409/1228) of the participants had a high intention to use a hypothetical mHealth app to avoid stress-overeating. These persons are characterized by a higher BMI (24.02 ± 4.47 kg/m2, p < 0.001), by being stress-overeaters (217/409, 53.1%), by the personality trait "neuroticism" (p < 0.001), by having specific eating reasons (all p < 0.01), and by showing a higher willingness to adopt new technologies (p < 0.001).

CONCLUSION

This study suggests that individuals who are prone to stress-overeating are highly interested in adopting an mHealth app as support. Participants with a high intention to use an mHealth app seem to have a general affinity towards new technology (PIIT) and appear to be more insecure with conflicting motives regarding their diet.

TRIAL REGISTRATION

This survey was registered in the German Clinical Trials Register (Registration number: DRKS00023984).

Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity

BACKGROUND

Obesity is considered to be a risk factor for various diseases, and its incidence has tripled worldwide since 1975. In addition to potentially being at risk for adverse health outcomes, people with overweight or obesity are often stigmatised. Behaviour change interventions are increasingly delivered as mobile health (m-health) interventions, using smartphone apps and wearables. They are believed to support healthy behaviours at the individual level in a low-threshold manner.

OBJECTIVES

To assess the effects of integrated smartphone applications for adolescents and adults with overweight or obesity.

SEARCH METHODS

We searched CENTRAL, MEDLINE, PsycINFO, CINAHL, and LILACS, as well as the trials registers ClinicalTrials.gov and World Health Organization International Clinical Trials Registry Platform on 2 October 2023 (date of last search for all databases). We placed no restrictions on the language of publication.

SELECTION CRITERIA

Participants were adolescents and adults with overweight or obesity. Eligible interventions were integrated smartphone apps using at least two behaviour change techniques. The intervention could target physical activity, cardiorespiratory fitness, weight loss, healthy diet, or self-efficacy. Comparators included no or minimal intervention (NMI), a different smartphone app, personal coaching, or usual care. Eligible studies were randomised controlled trials of any duration with a follow-up of at least three months.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methodology and the RoB 2 tool. Important outcomes were physical activity, body mass index (BMI) and weight, health-related quality of life, self-efficacy, well-being, change in dietary behaviour, and adverse events. We focused on presenting studies with medium- (6 to < 12 months) and long-term (≥ 12 months) outcomes in our summary of findings table, following recommendations in the core outcome set for behavioural weight management interventions.

MAIN RESULTS

We included 18 studies with 2703 participants. Interventions lasted from 2 to 24 months. The mean BMI in adults ranged from 27 to 50, and the median BMI z-score in adolescents ranged from 2.2 to 2.5. Smartphone app versus no or minimal intervention Thirteen studies compared a smartphone app versus NMI in adults; no studies were available for adolescents. The comparator comprised minimal health advice, handouts, food diaries, smartphone apps unrelated to weight loss, and waiting list. Measures of physical activity: at 12 months' follow-up, a smartphone app compared to NMI probably reduces moderate to vigorous physical activity (MVPA) slightly (mean difference (MD) -28.9 min/week (95% confidence interval (CI) -85.9 to 28; 1 study, 650 participants; moderate-certainty evidence)). We are very uncertain about the results of estimated energy expenditure and cardiorespiratory fitness at eight months' follow-up. A smartphone app compared with NMI probably results in little to no difference in changes in total activity time at 12 months' follow-up and leisure time physical activity at 24 months' follow-up. Anthropometric measures: a smartphone app compared with NMI may reduce BMI (MD of BMI change -2.6 kg/m2, 95% CI -6 to 0.8; 2 studies, 146 participants; very low-certainty evidence) at six to eight months' follow-up, but the evidence is very uncertain. At 12 months' follow-up, a smartphone app probably resulted in little to no difference in BMI change (MD -0.1 kg/m2, 95% CI -0.4 to 0.3; 1 study; 650 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in body weight change (MD -2.5 kg, 95% CI -6.8 to 1.7; 3 studies, 1044 participants; low-certainty evidence) at 12 months' follow-up. At 24 months' follow-up, a smartphone app probably resulted in little to no difference in body weight change (MD 0.7 kg, 95% CI -1.2 to 2.6; 1 study, 245 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in self-efficacy for a physical activity score at eight months' follow-up, but the results are very uncertain. A smartphone app probably results in little to no difference in quality of life and well-being at 12 months (moderate-certainty evidence) and in little to no difference in various measures used to inform dietary behaviour at 12 and 24 months' follow-up. We are very uncertain about adverse events, which were only reported narratively in two studies (very low-certainty evidence). Smartphone app versus another smartphone app Two studies compared different versions of the same app in adults, showing no or minimal differences in outcomes. One study in adults compared two different apps (calorie counting versus ketogenic diet) and suggested a slight reduction in body weight at six months in favour of the ketogenic diet app. No studies were available for adolescents. Smartphone app versus personal coaching Only one study compared a smartphone app with personal coaching in adults, presenting data at three months. Two studies compared these interventions in adolescents. A smartphone app resulted in little to no difference in BMI z-score compared to personal coaching at six months' follow-up (MD 0, 95% CI -0.2 to 0.2; 1 study; 107 participants). Smartphone app versus usual care Only one study compared an app with usual care in adults but only reported data at three months on participant satisfaction. No studies were available for adolescents. We identified 34 ongoing studies.

AUTHORS' CONCLUSIONS

The available evidence is limited and does not demonstrate a clear benefit of smartphone applications as interventions for adolescents or adults with overweight or obesity. While the number of studies is growing, the evidence remains incomplete due to the high variability of the apps' features, content and components, which complicates direct comparisons and assessment of their effectiveness. Comparisons with either no or minimal intervention or personal coaching show minor effects, which are mostly not clinically significant. Minimal data for adolescents also warrants further research. Evidence is also scarce for low- and middle-income countries as well as for people with different socio-economic and cultural backgrounds. The 34 ongoing studies suggest sustained interest in the topic, with new evidence expected to emerge within the next two years. In practice, clinicians and healthcare practitioners should carefully consider the potential benefits, limitations, and evolving research when recommending smartphone apps to adolescents and adults with overweight or obesity.

Why more successful? An analysis of participants' self-monitoring data in an online weight loss intervention

BACKGROUND

Self-monitoring is crucial for behavioral weight loss. However, few studies have examined the role of self-monitoring using mixed methods, which may hinder our understanding of its impact.

METHODS

This study examined self-monitoring data from 61 Chinese adults who participated in a 5-week online group intervention for weight loss. Participants reported their baseline Body Mass Index (BMI), weight loss motivation, and engaged in both daily quantitative self-monitoring (e.g., caloric intake, mood, sedentary behavior, etc.) and qualitative self-monitoring (e.g., daily log that summarizes the progress of weight loss). The timeliness of participants' daily self-monitoring data filling was assessed using a scoring rule. One-way repeated measurement ANOVA was employed to analyze the dynamics of each self-monitoring indicator. Correlation and regression analyses were used to reveal the relationship between baseline data, self-monitoring indicators, and weight change. Content analysis was utilized to analyze participants' qualitative self-monitoring data. Participants were categorized into three groups based on their weight loss outcomes, and a chi-square test was used to compare the frequency distribution between these groups.

RESULTS

After the intervention, participants achieved an average weight loss of 2.52 kg (SD = 1.36) and 3.99% (SD = 1.96%) of their initial weight. Daily caloric intake, weight loss satisfaction, frequency of daily log, and the speed of weight loss showed a downward trend, but daily sedentary time gradually increased. Moreover, regression analysis showed that baseline BMI, weight loss motivation, and timeliness of daily filling predicted final weight loss. Qualitative self-monitoring data analysis revealed four categories and nineteen subcategories. A significant difference in the frequency of qualitative data was observed, with the excellent group reporting a greater number of daily logs than expected in all categories and most subcategories, and the moderate and poor groups reporting less than expected in all categories and most subcategories.

CONCLUSION

The self-monitoring data in short-term online group intervention exhibited fluctuations. Participants with higher baseline BMI, higher levels of weight loss motivation, and timely self-monitoring achieved more weight loss. Participants who achieved greater weight loss reported a higher quantity of qualitative self-monitoring data. Practitioners should focus on enhancing dieters' weight loss motivation and promote adherence to self-monitoring practices.

Metrics for weight management success: an examination of the lifestyle score

Multiple weight loss attempts, and weight regain are common. Various lifestyle changes are often required for success, but just diet and exercise are often promoted. The amount of lifestyle changes needed for successful weight management is still unclear. Lifestyle metrics, such as the Lifestyle Score (LS) of The Lifestyle Questionnaire for Weight Management (LQ-WM), may provide clarification and predict success rates. The range of possible scores on this measure is from -49 to 77, where higher scores suggest healthier lifestyles. Hypotheses are that higher lifestyle scores will be found with successful weight management outcomes. Method: 1,007 online participants completed the LQ-WM and other items related to weight management. Results: 90.7% (39/43) of participants with an LS of 50 + reported successful weight loss, while just 5% (2/40) reported weight regain. 35.7% (20/56) of those with LS below zero reported weight loss success, and 39.4% (13/33) reported weight regain. Significant (p < .001) mean LS differences existed between those with healthy BMI versus the obese range (m = 22.2, SD = 15.51; m = 6.70, SD = 15.97) and those reporting success versus those not reporting success (m = 26.92, SD = 17.03; m = 13.68, SD = 14.95). Discussion and Conclusions: Future studies should employ more diverse samples and use causal designs. The LS from the LQ-WM may be a helpful tool in research and clinical interactions to raise patients' awareness of behavioral patterns, increase the likelihood of success, and prevent future weight gain.

Need analysis of a dietary application among caregivers of patients with disorders of amino acid metabolism (AAMDs): A mixed-method approach

BACKGROUND

A dietary application can assist the caregivers of AAMDs children in auto-calculating the protein intake, hence improving dietary compliance. However, existing dietary application for patients with AAMDs only focus on delivering the nutritional content of food and monitoring the dietary intake but were lacking in other educational components.

OBJECTIVE

To assess the uses, needs and preferences towards a dietary application among the caregivers of AAMDs patients.

METHODS

We conducted a mixed-method study comprising focus group discussion (FGD) and a quantitative questionnaire survey among caregivers of patients aged between 6-month-old to 18-year-old with AAMDs who are receiving active treatment, both medical and dietetic treatment in the genetic clinic, Hospital Kuala Lumpur (HKL).

RESULTS

A total of 76 and 20 caregivers participated in the survey and FGD respectively. All the caregivers (100%) possessed a smartphone and most of the caregivers (89.5%) had the experience of using smartphone or other technological devices to search for health or medical information. However, majority of the participants were not aware of the existence of any web-based or mobile application related to AAMDs (89.5%). While for the qualitative part, three themes emerged: (1) experience with current source of information; (2) needs for supporting self-management educational contents and needs for technological design application. Most of the caregivers used the nutritional booklet as sources of reference but some of them searched for web-based information. Features perceived by the caregivers included a digital food composition database, sharing diet recall with healthcare providers, self-monitoring diet intake as well as low protein recipes. Besides that, user-friendly and ease to use were also perceived as the important features by the caregivers.

CONCLUSION

The identified features and needs by the caregivers should be integrated into the design of the apps to promote acceptance and usage.

MyDietCam: Development and usability study of a food recognition integrated dietary monitoring smartphone application

Background

Diet monitoring has been linked with improved eating habits and positive health outcomes such as prevention of obesity. However, this is often unsustainable as traditional methods place a high burden on both participants and researchers through pen and paper recordings and manual nutrient coding respectively. The digitisation of dietary monitoring has greatly reduced these barriers. This paper proposes a diet application with a novel food recognition feature with a usability study conducted in the real world.

Methods

This study describes the development of a mobile diet application (MyDietCam) targeted at healthy Malaysian adults. Focus group discussions (FGD) were carried out among dietitians and potential users to determine ideal features in a diet application. Thirty participants were recruited from a local university to log their meals through MyDietCam for six days and submit the Malay mHealth Application Usability Questionnaire (M-MAUQ) at the end of the study.

Results

The findings from the FGD led to the implementation of the main features: individualised recommendations, food logging through food recognition to reduce steps for data entry and provide detailed nutrient analyses through visuals. An average overall usability score of 5.13 out of a maximum of seven was reported from the M-MAUQ which is considered acceptable.

Conclusion

The development of a local (Malaysian) mobile diet application with acceptable usability may be helpful in sustaining the diet monitoring habit to improve health outcomes. Future work should focus on improving the issues raised before testing the effectiveness of the application for improving health outcomes.

A Review of Digital Innovations for Diet Monitoring and Precision Nutrition

This article provides an up-to-date review of technological advances in 3 key areas related to diet monitoring and precision nutrition. First, we review developments in mobile applications, with a focus on food photography and artificial intelligence to facilitate the process of diet monitoring. Second, we review advances in 2 types of wearable and handheld sensors that can potentially be used to fully automate certain aspects of diet logging: physical sensors to detect moments of dietary intake, and chemical sensors to estimate the composition of diets and meals. Finally, we review new programs that can generate personalized/precision nutrition recommendations based on measurements of gut microbiota and continuous glucose monitors with artificial intelligence. The article concludes with a discussion of potential pitfalls of some of these technologies.

Detailed Versus Simplified Dietary Self-monitoring in a Digital Weight Loss Intervention Among Racial and Ethnic Minority Adults: Fully Remote, Randomized Pilot Study

BACKGROUND

Detailed self-monitoring (or tracking) of dietary intake is a popular and effective weight loss approach that can be delivered via digital tools, although engagement declines over time. Simplifying the experience of self-monitoring diet may counteract this decline in engagement. Testing these strategies among racial and ethnic minority groups is important as these groups are often disproportionately affected by obesity yet underrepresented in behavioral obesity treatment.

OBJECTIVE

In this 2-arm pilot study, we aimed to evaluate the feasibility and acceptability of a digital weight loss intervention with either detailed or simplified dietary self-monitoring.

METHODS

We recruited racial and ethnic minority adults aged ≥21 years with a BMI of 25 kg/m² to 45 kg/m² and living in the United States. The Pacific time zone was selected for a fully remote study. Participants received a 3-month stand-alone digital weight loss intervention and were randomized 1:1 to either the detailed arm that was instructed to self-monitor all foods and drinks consumed each day using the Fitbit mobile app or to the simplified arm that was instructed to self-monitor only red zone foods (foods that are highly caloric and of limited nutritional value) each day via a web-based checklist. All participants were instructed to self-monitor both steps and body weight daily. Each week, participants were emailed behavioral lessons, action plans, and personalized feedback. In total, 12 a priori benchmarks were set to establish feasibility, including outcomes related to reach, retention, and self-monitoring engagement (assessed objectively via digital tools). Acceptability was assessed using a questionnaire. Weight change was assessed using scales shipped to the participants' homes and reported descriptively.

RESULTS

The eligibility screen was completed by 248 individuals, of whom 38 (15.3%) were randomized, 18 to detailed and 20 to simplified. At baseline, participants had a mean age of 47.4 (SD 14.0) years and BMI of 31.2 (SD 4.8) kg/m². More than half (22/38, 58%) were identified as Hispanic of any race. The study retention rate was 92% (35/38) at 3 months. The detailed arm met 9 of 12 feasibility benchmarks, while the simplified arm met all 12. Self-monitoring engagement was moderate to high (self-monitoring diet: median of 49% of days for detailed, 97% for simplified; self-monitoring steps: 99% for detailed, 100% for simplified; self-monitoring weight: 67% for detailed, 80% for simplified). Participants in both arms reported high satisfaction, with 89% indicating that they would recommend the intervention. Weight change was -3.4 (95% CI -4.6 to -2.2) kg for detailed and -3.3 (95% CI -4.4 to -2.2) kg for simplified.

CONCLUSIONS

A digital weight loss intervention that incorporated either detailed or simplified dietary self-monitoring was feasible, with high retention and engagement, and acceptable to racial and ethnic minority adults.

TRIAL REGISTRATION

ASPREDICTED #66674; https://aspredicted.org/ka478.pdf.

Capacity Strengthening Undertaking-Farm Organized Response of Workers against Risk for Diabetes: (C.S.U.-F.O.R.W.A.R.D. with Cal Poly)-A Concept Approach to Tackling Diabetes in Vulnerable and Underserved Farmworkers in California

In our project herein, we use the case of farmworkers, an underserved and understudied population at high risk for Type-2 Diabetes Mellitus (T2DM), as a paradigm of an integrated action-oriented research, education and extension approach involving the development of long-term equitable strategies providing empowerment and tailored-made solutions that support practical decision-making aiming to reduce risk of T2DM and ensuing cardiovascular disease (CVD). A Technology-based Empowerment Didactic module (TEDm) and an Informed Decision-Making enhancer (IDMe) coupled in a smart application (app) for farmworkers aiming to teach, set goals, monitor, and support in terms of nutrition, hydration, physical activity, sleep, and circadian rhythm towards lowering T2DM risk, is to be developed and implemented considering the particular characteristics of the population and setting. In parallel, anthropometric, biochemical, and clinical assessments will be utilized to monitor risk parameters for T2DM and compliance to dietary and wellness plans. The app incorporating anthropometric/clinical/biochemical parameters, dietary/lifestyle behavior, and extent of goal achievement can be continuously refined and improved through machine learning and re-programming. The app can function as a programmable tool constantly learning, adapting, and tailoring its services to user needs helping optimization of practical informed decision-making towards mitigating disease symptoms and associated risk factors. This work can benefit apart from the direct beneficiaries being farmworkers, the stakeholders who will be gaining a healthier, more vibrant workforce, and in turn the local communities.

A Tailored Gender-Sensitive mHealth Weight Loss Intervention (I-GENDO): Development and Process Evaluation

BACKGROUND

Given the increase in the prevalence of overweight and obesity worldwide, the number of digital weight loss interventions has also risen. However, these interventions often lack theoretical background and data on long-term effectiveness. The consideration of individual and gender differences in weight-related psychological parameters might enhance the efficacy and sustainability of mobile-based weight loss interventions.

OBJECTIVE

This paper presented an introduction to and the process evaluation of a 12-week gender-sensitive mobile health (mHealth) weight loss intervention (I-GENDO) combining computer-based and self-tailoring features.

METHODS

Between August 2020 and August 2021, individuals with overweight (BMI 25.0-29.9 kg/m²), those with obesity class I (BMI 30.0-34.9 kg/m²), and those with obesity class II (BMI 35.0-39.9 kg/m²) were recruited to the I-GENDO project, a multicenter study in Germany. The mHealth intervention aimed at targeting individual psychological factors associated with the development and persistence of overweight and obesity (eg, emotional eating) using computer-based tailoring. Moreover, the intervention took a gender-sensitive approach by implementing self-tailoring of gender-targeted module versions. The computer-based assignment of the main modules, self-selection of gender-targeted module versions, and use patterns were evaluated while considering gender. Moreover, gender differences in the usability assessment were analyzed.

RESULTS

Data from the intervention arm of the study were processed. A total of 116 individuals with overweight and obesity (77/116, 66.4% women; age mean 47.28, SD 11.66 years; BMI mean 33.58, SD 3.79 kg/m2) were included in the analyses. Overall, the compliance (90/109, 82.6%) and satisfaction with the app (mean 86% approval) were high and comparable with those of other mobile weight loss interventions. The usability of the intervention was rated with 71% (5.0/7.0 points) satisfaction. More women obtained the main module that focused on emotion regulation skills. Most men and women selected women-targeted versions of the main modules. Women used the app more frequently and longer than men. However, women and men did not differ in the progress of use patterns throughout the intervention.

CONCLUSIONS

We developed a tailored gender-sensitive mHealth weight loss intervention. The usability of and engagement with the intervention were satisfactory, and the overall satisfaction with the intervention was also high. Gender differences must be considered in the evaluation of the effectiveness and sustainability of the intervention.

Sustainability of Weight Loss Through Smartphone Apps: Systematic Review and Meta-analysis on Anthropometric, Metabolic, and Dietary Outcomes

Background

Evidence on the long-term effects of weight management smartphone apps on various weight-related outcomes remains scarce.

Objective

In this review, we aimed to examine the effects of smartphone apps on anthropometric, metabolic, and dietary outcomes at various time points.

Methods

Articles published from database inception to March 10, 2022 were searched, from 7 databases (Embase, CINAHL, PubMed, PsycINFO, Cochrane Library, Scopus, and Web of Science) using forward and backward citation tracking. All randomized controlled trials that reported weight change as an outcome in adults with overweight and obesity were included. We performed separate meta-analyses using random effects models for weight, waist circumference, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, blood glucose level, blood pressure, and total energy intake per day. Methodological quality was assessed using the Cochrane Risk of Bias tool.

Results

Based on our meta-analyses, weight loss was sustained between 3 and 12 months, with a peak of 2.18 kg at 3 months that tapered down to 1.63 kg at 12 months. We did not find significant benefits of weight loss on the secondary outcomes examined, except for a slight improvement in systolic blood pressure at 3 months. Most of the included studies covered app-based interventions that comprised of components beyond food logging, such as real-time diet and exercise self-monitoring, personalized and remote progress tracking, timely feedback provision, smart devices that synchronized activity and weight data to smartphones, and libraries of diet and physical activity ideas.

Conclusions

Smartphone weight loss apps are effective in initiating and sustaining weight loss between 3 and 12 months, but their effects are minimal in their current states. Future studies could consider the various aspects of the socioecological model. Conversational and dialectic components that simulate health coaches could be useful to enhance user engagement and outcome effectiveness.

Trial Registration

International Prospective Register of Systematic Reviews (PROSPERO) CRD42022329197; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=329197

Expert opinions on reducing dietary self-monitoring burden and maintaining efficacy in weight loss programs: A Delphi study

Objective

Dietary self-monitoring is consistently related to both short- and long-term weight loss, but typically declines over time. Adopting an abbreviated approach to self-monitoring might reduce burden and potentially increase engagement while maintaining efficacy.

Methods

Using a Delphi-type study, experts were queried about abbreviated self-monitoring approaches that might best balance efficacy and burden and asked to identify when these approaches might best be implemented within a behavioral weight loss program. Experts were surveyed three times until consensus was reached.

Results

Experts identified three main categories of promising strategies for abbreviated self-monitoring regardless of whether individuals have been successful with weight loss or full dietary self-monitoring: (1) self-weighing only, (2) reducing the foods/beverages self-monitored to those that are often less routine and higher in caloric density, and (3) reducing the number of days per week to engage in full dietary self-monitoring. Experts recommended transitioning to abbreviated self-monitoring after 2 weeks of no self-monitoring among individuals who were struggling and after reaching 5%-10% weight loss among successful individuals.

Conclusions

These expert opinions offer a foundation to experimentally manipulate promising strategies for reducing burden and increasing long-term engagement in self-monitoring, with a goal of enhancing long-term weight control.

Patient-Generated Health Photos and Videos Across Health and Well-being Contexts: Scoping Review

Background

Patient-generated health data are increasingly used to record health and well-being concerns and engage patients in clinical care. Patient-generated photographs and videos are accessible and meaningful to patients, making them especially relevant during the current COVID-19 pandemic. However, a systematic review of photos and videos used by patients across different areas of health and well-being is lacking.

Objective

This review aims to synthesize the existing literature on the health and well-being contexts in which patient-generated photos and videos are used, the value gained by patients and health professionals, and the challenges experienced.

Methods

Guided by a framework for scoping reviews, we searched eight health databases (CINAHL, Cochrane Library, Embase, PsycINFO, PubMed, MEDLINE, Scopus, and Web of Science) and one computing database (ACM), returning a total of 28,567 studies. After removing duplicates and screening based on the predefined inclusion criteria, we identified 110 relevant articles. Data were charted and articles were analyzed following an iterative thematic approach with the assistance of NVivo software (version 12; QSR International).

Results

Patient-generated photos and videos are used across a wide range of health care services (39/110, 35.5% articles), for example, to diagnose skin lesions, assess dietary intake, and reflect on personal experiences during therapy. In addition, patients use them to self-manage health and well-being concerns (33/110, 30%) and to share personal health experiences via social media (36/110, 32.7%). Photos and videos create significant value for health care (59/110, 53.6%), where images support diagnosis, explanation, and treatment (functional value). They also provide value directly to patients through enhanced self-determination (39/110, 35.4%), social (33/110, 30%), and emotional support (21/110, 19.1%). However, several challenges emerge when patients create, share, and examine photos and videos, such as limited accessibility (16/110, 14.5%), incomplete image sets (23/110, 20.9%), and misinformation through photos and videos shared on social media (17/110, 15.5%).

Conclusions

This review shows that photos and videos engage patients in meaningful ways across different health care activities (eg, diagnosis, treatment, and self-care) for various health conditions. Although photos and videos require effort to capture and involve challenges when patients want to use them in health care, they also engage and empower patients, generating unique value. This review highlights areas for future research and strategies for addressing these challenges.

A pilot randomized trial of simplified versus standard calorie dietary self-monitoring in a mobile weight loss intervention

OBJECTIVE

This study tested the efficacy of a lower-burden, simplified dietary self-monitoring approach compared with a standard calorie monitoring approach for self-monitoring adherence and weight loss in a mobile-delivered behavioral weight loss intervention.

METHODS

Participants (n = 72) with overweight or obesity who had children 2 to 12 years of age living in the home were randomly assigned to a group that used simplified dietary self-monitoring of high-calorie foods (Simplified) or a group that tracked calories (Standard). Both groups received a wireless scale, Fitbit trackers, and a 6-month intervention delivered via a smartphone application with lessons, text messages, and weekly personalized feedback messages.

RESULTS

Percentage weight loss at 6 months was 5.7% (95% CI: -8.3% to -3.2%) in the Standard group and 4.0% (95% CI: -5.7% to -2.3%) in the Simplified group, which was not significantly different. Similar proportions reached 5% weight loss at 6 months (43.2% in Standard and 42.9% in Simplified). There were no differences in number of dietary tracking days or change in average daily caloric intake between groups.

CONCLUSIONS

Two mobile-delivered weight loss interventions produced clinically meaningful levels of weight loss at 6 months, with no differences in dietary tracking adherence or dietary intake. The results suggest that simplified monitoring of high-calorie foods could be a promising alternative to calorie monitoring.

Executive summary of evidence and consensus-based Clinical Practice Guidelines for management of obesity and overweight in midlife women: An AIIMS-DST initiative

BACKGROUND AND AIMS

Weight gain is an independent risk factor for decline in cardiometabolic and overall health-related quality of life in midlife women. The AIIMS-DST initiative aims to develop and validate stepwise recommendations specific for weight management in midlife women.

METHODS

The key clinical questions specific to weight management in midlife women were finalised with the help of a multidisciplinary team of experts in the guideline development group (GDG). Phase I included a systematic and/or narrative review to gather evidence, grading of evidence and expert opinion was sought to develop clinical practice recommendations for each clinical question. Phase II focused on validation of clinical practice recommendations using the peer-review, Delphi method and GRADE approach.

RESULTS

-The guidelines provide clinical practice points to address challenges encountered by midlife women in their attempts to manage obesity via lifestyle modification techniques. The initiation of discussion would help the healthcare provider to identify the weight management needs of the women, educate women on different modalities of weight management, and empower them to incorporate corrective lifestyle behaviours. Before initiating the management, a comprehensive assessment of clinical and lifestylerelated parameters should be completed. A personalised behavioural lifestyle modification program addressing the midlife specific barriers for optimal metabolic, musculoskeletal, and mental health should be planned. A consistent follow-up is required for maintenance of corrective eating and activity habits by addressing midlife specific barriers for sustenance of healthy weight.

CONCLUSION

These recommendations will be useful in opportunistic screening and management of obesity in midlife women across healthcare settings.

Executive summary of evidence and consensus-based clinical practice guidelines for management of obesity and overweight in midlife women: An AIIMS-DST initiative

Weight gain is an independent risk factor for decline in cardiometabolic and overall health-related quality of life in midlife women. The AIIMS-DST initiative aims to develop and validate stepwise recommendations specific for weight management in midlife women. The key clinical questions specific to weight management in midlife women were finalized with the help of a multidisciplinary team of experts in the guideline development group. Phase I including a systematic and/or narrative review, grading of evidence, and expert opinion was sought to develop clinical practice recommendations for each clinical question. Phase II focused on validation of clinical practice recommendations using the peer-review, Delphi method, and GRADE approach. The guidelines provide clinical practice points to address challenges encountered by midlife women in their attempts to manage obesity via lifestyle modification techniques. The initiation of discussion would help the health-care provider to identify the weight management needs of the women, educate women on different modalities of weight management, and empower them to incorporate corrective lifestyle behaviors. Before initiating the management, a comprehensive assessment of clinical and lifestyle-related parameters should be completed. A personalized behavioral lifestyle modification program addressing the midlife-specific barriers for optimal metabolic, musculoskeletal, and mental health should be planned. A consistent follow-up is required for maintenance of corrective eating and activity habits by addressing midlife-specific barriers for sustenance of healthy weight. These recommendations will be useful in opportunistic screening and management of obesity in midlife women across health-care settings.

Adherence to mobile‐app‐based dietary self‐monitoring—Impact on weight loss in adults

Objectives

Greater dietary self‐monitoring adherence is associated with weight loss, however, the dietary self‐monitoring adherence criteria that predict weight loss are unknown. The criteria used to define adherence to dietary self‐monitoring in obesity treatment tend to vary, particularly in studies that include dietary self‐monitoring via mobile applications (apps). The objectives of this study were to (a) determine weight change outcomes related to app‐based dietary self‐monitoring and (b) determine the associations between the frequency, consistency, and completeness of dietary self‐monitoring and weight change.

Methods

In this single‐arm uncontrolled prospective study, employees at a large, urban health system who had overweight or obesity self‐monitored dietary intake for 8 weeks using the Calorie Counter by FatSecret app. A paired sample t‐test examined the association of app‐based dietary self‐monitoring and weight change; linear regression examined the associations of frequent, consistent, and complete dietary self‐monitoring and weight change.

Results

A significant mean difference [t (89) = 6.59, p < 0.001] was found between baseline and 8‐week weight (M = −1.5 ± 2.1 kg) in the sample (N = 90). Linear regression revealed a significant association [F (1, 88) = 7.18, p = 0.009] between total weeks of consistent dietary self‐monitoring (M = 4.4 ± 2.8) and percent weight loss (M = −1.54% ± 2.26%), and a significant association [F (1, 88) = 6.42, p = 0.013] between dietary self‐monitoring frequency (M = 50.1% ± 33.3%) and percent weight loss. The total weeks of complete dietary self‐monitoring (M = 3.42 ± 2.87) was not associated [F (1, 88) = 3.57, p = 0.062] with percent weight loss.

Conclusions

Consistent and frequent app‐based dietary self‐monitoring were associated with short‐term weight loss. Emphasizing these aspects of self‐monitoring may be an avenue for decreasing the burden of self‐monitoring.

Slip Buddy App for Weight Management: Randomized Feasibility Trial of a Dietary Lapse Tracking App

BACKGROUND

Although calorie tracking is one of the strongest predictors of weight loss in behavioral weight loss interventions, low rates of adherence are common.

OBJECTIVE

This study aims to examine the feasibility and acceptability of using the Slip Buddy app during a 12-week web-based weight loss program.

METHODS

We conducted a randomized pilot trial to evaluate the feasibility and acceptability of using the Slip Buddy app compared with a popular commercial calorie tracking app during a counselor-led, web-based behavioral weight loss intervention. Adults who were overweight or obese were recruited on the web and randomized into a 12-week web-based weight loss intervention that included either the Slip Buddy app or a commercial calorie tracking app. Feasibility outcomes included retention, app use, usability, slips reported, and contextual factors reported at slips. Acceptability outcomes included ratings of how helpful, tedious, taxing, time consuming, and burdensome using the assigned app was. We described weight change from baseline to 12 weeks in both groups as an exploratory outcome. Participants using the Slip Buddy app provided feedback on how to improve it during the postintervention focus groups.

RESULTS

A total of 75% (48/64) of the participants were female and, on average, 39.8 (SD 11.0) years old with a mean BMI of 34.2 (SD 4.9) kg/m2. Retention was high in both conditions, with 97% (31/32) retained in the Slip Buddy condition and 94% (30/32) retained in the calorie tracking condition. On average, participants used the Slip Buddy app on 53.8% (SD 31.3%) of days, which was not significantly different from those using the calorie tracking app (mean 57.5%, SD 28.4% of days), and participants who recorded slips (30/32, 94%) logged on average 17.9 (SD 14.4) slips in 12 weeks. The most common slips occurred during snack times (220/538, 40.9%). Slips most often occurred at home (297/538, 55.2%), while working (153/538, 28.4%), while socializing (130/538, 24.2%), or during screen time (123/538, 22.9%). The conditions did not differ in participants' ratings of how their assigned app was tedious, taxing, or time consuming (all values of P>.05), but the calorie tracking condition gave their app higher helpfulness and usability ratings (all values of P<.05). Technical issues were the most common type of negative feedback, whereas simplicity was the most common type of positive feedback. Weight losses of ≥5% of baseline weight were achieved by 31% (10/32) of Slip Buddy participants and 34% (11/32) of calorie tracking participants.

CONCLUSIONS

Self-monitoring of dietary lapses and the contextual factors associated with them may be an alternative for people who do not prefer calorie tracking. Future research should examine patient characteristics associated with adherence to different forms of dietary self-monitoring.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02615171; https://clinicaltrials.gov/ct2/show/NCT02615171.

Barriers to and Facilitators for Using Nutrition Apps: Systematic Review and Conceptual Framework

BACKGROUND

Nutrition apps are effective in changing eating behavior and diet-related health risk factors. However, while they may curb growing overweight and obesity rates, widespread adoption is yet to be achieved. Hence, profound knowledge regarding factors motivating and hindering (long-term) nutrition app use is crucial for developing design guidelines aimed at supporting uptake and prolonged use of nutrition apps.

OBJECTIVE

In this systematic review, we synthesized the literature on barriers to and facilitators for nutrition app use across disciplines including empirical qualitative and quantitative studies with current users, ex-users, and nonusers of nutrition apps.

METHODS

A systematic literature search including 6 databases (PubMed, Web of Science, PsychINFO, PSYNDEX, PsycArticles, and SPORTDiscus) as well as backward and forward citation search was conducted. Search strategy, inclusion and exclusion criteria, and the planned data extraction process were preregistered. All empirical qualitative and quantitative studies published in German or English were eligible for inclusion if they examined adolescents (aged 13-18) or adults who were either current users, ex-users, and nonusers of nutrition apps. Based on qualitative content analysis, extracted individual barriers and facilitators were grouped into categories.

RESULTS

A total of 28 publications were identified as eligible. A framework with a 3-level hierarchy was designed which grouped 328 individual barriers and facilitators into 23 subcategories, 12 categories, and 4 clusters that focus on either the individual user (goal setting and goal striving, motivation, routines, lack of awareness of knowledge), different aspects of the app and the smartphone (features, usability of the app or food database, technical issues, data security, accuracy/trustworthiness, costs), positive and negative outcomes of nutrition app use, or interactions between the user and their social environment.

CONCLUSIONS

The resulting conceptual framework underlines a pronounced diversity of reasons for (not) using nutrition apps, indicating that there is no "one-size-fits-all" approach for uptake and prolonged use of nutrition apps. Hence, tailoring nutrition apps to needs of specific user groups seems promising for increasing engagement.

Self-Monitoring via Digital Health in Weight Loss Interventions: A Systematic Review Among Adults with Overweight or Obesity

OBJECTIVE

Self-monitoring is a core component of behavioral obesity treatment, but it is unknown how digital health has been used for self-monitoring, what engagement rates are achieved in these interventions, and how self-monitoring and weight loss are related.

METHODS

This systematic review examined digital self-monitoring in behavioral weight loss interventions among adults with overweight or obesity. Six databases (PubMed, Embase, Scopus, PsycInfo, CINAHL, and ProQuest Dissertations & Theses) were searched for randomized controlled trials with interventions ≥ 12 weeks, weight outcomes ≥ 6 months, and outcomes on self-monitoring engagement and their relationship to weight loss.

RESULTS

Thirty-nine studies from 2009 to 2019 met inclusion criteria. Among the 67 interventions with digital self-monitoring, weight was tracked in 72% of them, diet in 81%, and physical activity in 82%. Websites were the most common self-monitoring modality, followed by mobile applications, wearables, electronic scales, and, finally, text messaging. Few interventions had digital self-monitoring engagement rates ≥ 75% of days. Rates were higher in digital- than in paper-based arms in 21 out of 34 comparisons and lower in just 2. Interventions with counseling had similar rates to standalone interventions. Greater digital self-monitoring was linked to weight loss in 74% of occurrences.

CONCLUSIONS

Self-monitoring via digital health is consistently associated with weight loss in behavioral obesity treatment.

Mobile Apps for Health Behavior Change in Physical Activity, Diet, Drug and Alcohol Use, and Mental Health: Systematic Review

Background

With a growing focus on patient interaction with health management, mobile apps are increasingly used to deliver behavioral health interventions. The large variation in these mobile health apps—their target patient group, health behavior, and behavioral change strategies—has resulted in a large but incohesive body of literature.

Objective

This systematic review aimed to assess the effectiveness of mobile apps in improving health behaviors and outcomes and to examine the inclusion and effectiveness of behavior change techniques (BCTs) in mobile health apps.

Methods

PubMed, EMBASE, CINAHL, and Web of Science were systematically searched for articles published between 2014 and 2019 that evaluated mobile apps for health behavior change. Two authors independently screened and selected studies according to the eligibility criteria. Data were extracted and the risk of bias was assessed by one reviewer and validated by a second reviewer.

Results

A total of 52 randomized controlled trials met the inclusion criteria and were included in the analysis—37 studies focused on physical activity, diet, or a combination of both, 11 on drug and alcohol use, and 4 on mental health. Participant perceptions were generally positive—only one app was rated as less helpful and satisfactory than the control—and the studies that measured engagement and usability found relatively high study completion rates (mean 83%; n=18, N=39) and ease-of-use ratings (3 significantly better than control, 9/15 rated >70%). However, there was little evidence of changed behavior or health outcomes.

Conclusions

There was no strong evidence in support of the effectiveness of mobile apps in improving health behaviors or outcomes because few studies found significant differences between the app and control groups. Further research is needed to identify the BCTs that are most effective at promoting behavior change. Improved reporting is necessary to accurately evaluate the mobile health app effectiveness and risk of bias.

Consistent self-monitoring in a commercial app-based intervention for weight loss: results from a randomized trial

Self-monitoring is the strongest predictor of success in lifestyle interventions for obesity. In this secondary analysis of the GoalTracker trial, we describe outcomes of consistently self-monitoring in a standalone weight loss intervention. The 12-week intervention focused on daily self-monitoring of diet and/or body weight in a commercial app (MyFitnessPal). Participants (N = 100; 21-65 years; BMI 25-45 kg/m²) were categorized as Consistent Trackers if they tracked ≥ 6 out of 7 days for at least 75% of the targeted weeks. One-fourth of participants were Consistent Trackers. This subset was more likely to be married or living with a partner, be non-Hispanic White, and have higher health literacy than Inconsistent Trackers (ps < .05). Consistent tracking was associated with greater weight change than inconsistent tracking at 1 month (mean difference [95% CI] - 1.11 kg [- 2.12, - 0.10]), 3 months (- 2.42 kg [- 3.80, - 1.04]), and 6 months (- 2.13 kg [- 3.99, - 0.27]). Over 3 times as many Consistent Trackers as Inconsistent Trackers achieved ≥ 5% weight loss at 3 months (48 vs. 13%) and at 6 months (54 vs. 15%; ps < .001). Though causality cannot be determined by the present study, tracking weight and/or diet nearly every day per week for 12 weeks in a commercial app may serve as an effective strategy for weight loss. Strategies are needed to promote greater consistency in tracking.

Defining Adherence to Mobile Dietary Self-Monitoring and Assessing Tracking Over Time: Tracking at Least Two Eating Occasions per Day Is Best Marker of Adherence within Two Different Mobile Health Randomized Weight Loss Interventions

BACKGROUND

Mobile dietary self-monitoring methods allow for objective assessment of adherence to self-monitoring; however, the best way to define self-monitoring adherence is not known.

OBJECTIVE

The objective was to identify the best criteria for defining adherence to dietary self-monitoring with mobile devices when predicting weight loss.

DESIGN

This was a secondary data analysis from two 6-month randomized trials: Dietary Intervention to Enhance Tracking with Mobile Devices (n=42 calorie tracking app or n=39 wearable Bite Counter device) and Self-Monitoring Assessment in Real Time (n=20 kcal tracking app or n=23 photo meal app).

PARTICIPANTS/SETTING

Adults (n=124; mean body mass index=34.7±5.6) participated in one of two remotely delivered weight-loss interventions at a southeastern university between 2015 and 2017.

INTERVENTION

All participants received the same behavioral weight loss information via twice-weekly podcasts. Participants were randomly assigned to a specific diet tracking method.

MAIN OUTCOME MEASURES

Seven methods of tracking adherence to self-monitoring (eg, number of days tracked, and number of eating occasions tracked) were examined, as was weight loss at 6 months.

STATISTICAL ANALYSES PERFORMED

Linear regression models estimated the strength of association (R²) between each method of tracking adherence and weight loss, adjusting for age and sex.

RESULTS

Among all study completers combined (N=91), adherence defined as the overall number of days participants tracked at least two eating occasions explained the most variance in weight loss at 6 months (R²=0.27; P<0.001). Self-monitoring declined over time; all examined adherence methods had fewer than half the sample still tracking after Week 10.

CONCLUSIONS

Using the total number of days at least two eating occasions are tracked using a mobile self-monitoring method may be the best way to assess self-monitoring adherence during weight loss interventions. This study shows that self-monitoring rates decline quickly and elucidates potential times for early interventions to stop the reductions in self-monitoring.