Dietary Self-Monitoring in Weight Management: Current Evidence on Efficacy and Adherence

Evaluating the Validity of the PortionSize Smartphone Application for Estimating Dietary Intake in Free-Living Conditions: A Pilot Study

OBJECTIVE

Evaluate the validity of the PortionSize application.

METHODS

In this pilot study, 14 adults used PortionSize to record their free-living food intake over 3 consecutive days. Digital photography was the criterion measure, and the main outcomes were estimated intake of food (grams), energy (kilocalories), and food groups. Equivalence tests with ±25% equivalence bounds and Bland-Altman analysis were performed.

RESULTS

Estimated gram intake from PortionSize was equivalent (P < 0.001) to digital photography estimates. PortionSize and digital photography estimated energy intake, however, were not equivalent (P = 0.08), with larger estimates from PortionSize. In addition, PortionSize and digital photography were equivalent for vegetable intake (P = 0.01), but PortionSize had larger estimates of fruits, grains, dairy, and protein intake (P >0.07; error range 11% to 23%).

CONCLUSIONS AND IMPLICATIONS

Compared with digital photography, PortionSize accurately estimated food intake and had reasonable error rates for other nutrients; however, it overestimated energy intake, indicating further application improvements are needed for free-living conditions.

Perceptions of self-monitoring dietary intake according to a plate-based approach: A qualitative study

Dietary self-monitoring is a behaviour change technique used to help elicit and sustain dietary changes over time. Current dietary self-monitoring tools focus primarily on itemizing foods and counting calories, which can be complex, time-intensive, and dependent on health literacy. Further, there are no dietary self-monitoring tools that conform to the plate-based approach of the 2019 Canada Food Guide (CFG), wherein the recommended proportions of three food groups are visually represented on a plate without specifying daily servings or portion sizes. This paper explored the perceptions of end-users (i.e., general public) and Registered Dietitians of iCANPlateTM-a dietary self-monitoring mobile application resembling the CFG. Qualitative data were collected through virtual focus groups. Focus group questions were based on the Capability, Opportunity, Motivation-Behaviour (COM-B) theoretical framework to explore perceptions of using the CFG and currently available dietary self-monitoring tools. The prototype iCANPlateTM (version 0.1) was presented to gain feedback on perceived barriers and facilitators of its use. Focus group discussions were audio recorded and verbatim transcribed. Trained researchers used thematic analysis to code and analyze the transcripts independently. Seven focus groups were conducted with Registered Dietitians (n = 44) and nine focus groups with members from the general public (n = 52). During the focus groups, participants mainly discussed the capabilities and opportunities required to use the current iteration of iCANPlateTM. Participants liked the simplicity of the application and its capacity to foster self-awareness of dietary behaviours rather than weight control or calorie counting. However, concerns were raised regarding iCANPlateTM's potential to improve adherence to dietary self-monitoring due to specific characteristics (i.e., insufficient classifications, difficulty in conceptualizing proportions, and lack of inclusivity). Overall, participants liked the simplicity of iCANPlateTM and its ability to promote self-awareness of dietary intakes, primarily through visual representation of foods on a plate as opposed to reliance on numerical values or serving sizes, were benefits of using the app. Findings from this study will be used to further develop the app with the goal of increasing adherence to plate-based dietary approaches.

Implementing multicomponent, eHealth-based behaviour change support within a dietary intervention trial improves adherence to study-related behaviours in healthy young adults

BACKGROUND

Behaviour change science is proposed to improve participant retention and enhance the validity of trials. However, researchers seldom systematically consider and implement behaviour change strategies within trials for this purpose. The objective of this article is to evaluate how an eHealth behaviour change support (BCS) program enhances young adults' adherence to behaviours required within a dietary intervention.

METHODS

The Nine Principles framework was used to develop BCS to implement across both arms of a 10-week randomised parallel-group intervention to enhance adherence to (i) eating healthily and (ii) reporting dietary intake. Key components of the BCS included access to a dietitian-led Facebook group, text reminders, and food delivery. Effectiveness was measured using the following analyses of the 78 participants who completed the study; pre-post change in targeted dietary habits over time using a subscore of the Healthy Diet Habits Index, questionnaire to assess change in perception of barriers to eating healthily over time, Facebook group engagement, and impact evaluation of the BCS. Participants received a dietary reporting score out of 100 to assess adherence across the 10 weeks.

RESULTS

The total Healthy Diet Habits Index subscore out of 16 significantly increased from baseline to week 10 (10.6 ± 2.6 to 11.2 ± 2.6, p value < 0.05), driven primarily by an increase in vegetable consumption. Overall adherence to reporting was high across the 10 weeks, with the total population mean reporting score 90.4 ± 14.6 out of 100. Relatively low Facebook engagement was observed. Adding objects to the environment, prompts/cues and removing reward appeared to be effective components of the BCS for enhancing adherence to the target behaviours.

CONCLUSION

Using a behaviour change framework to support the design of randomised trials is a promising way to enhance participant adherence to study requirements that are typically considered burdensome, such as dietary reporting. It also enables researchers to identify and replicate effective components of BCS, including behaviour change techniques and modes of delivery. Further research into the use of different behaviour change frameworks for this purpose is warranted.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04869163; https://clinicaltrials.gov/ct2/show/NCT04869163 . (03/05/2021).

Conducting 24-Hour Dietary Recalls in Group Settings with Adults Having Low-Income: Perspectives of EFNEP Peer Educators

The Expanded Food and Nutrition Education Program (EFNEP) is a federally funded program that teaches nutrition education to adults and youth with low-income. EFNEP is funded throughout the United States including federal territories. The purpose of EFNEP is to provide nutrition education. Evaluation for adult programs includes pre/post surveys and pre/post 24-h diet recalls (24HDR). A validated standard of dietary measures, 24HDR are useful when collected as designed: one-on-one by a trained professional. In EFNEP, 24HDR are collected in group settings by EFNEP peer educators who often have not received a college degree or any formal education in nutrition. The purpose of this study was to explore attitudes and behaviors of EFNEP peer educators regarding how they collect diet recalls in a group setting, their perceptions of how adult participants feel about the recalls, and the benefits and challenges of using recalls. Online interviews were conducted with EFNEP peer educators across the U.S. Peer educators recognized the importance of collecting the recall data but identified several challenges such as time, resources, and participant reluctance to complete the recall. Program evaluation through methods like the 24HDR is important to measure outcomes and inform program improvements but also needs to include how evaluation can benefit participants and minimize data collection burden. Future research needs to examine the validity of collecting recalls in a group setting compared to other measures of diet quality.

A Qualitative Evaluation of a Plate-Method Dietary Self-Monitoring Tool in a Sample of Adults Over 50

Background

Self-monitoring is an important behavioral change technique to help users initiate and maintain dietary changes. Diet self-monitoring tools often involve the itemization of foods and recording of serving sizes. However, this traditional method of tracking does not conform to food guides using plate-based approach to nutrition education, such as the 2019 Canada's Food Guide (CFG).

Objective

To explore the acceptability, facilitators and barriers of using a plate-based dietary self-monitoring tool based on the 2019 CFG (Plate Tool) compared with a traditional Food Journal (Food Journal).

Methods

The 2 dietary self-monitoring tools were compared using a crossover study design over 2 wk. Adults over 50 (n = 47) from Montreal, Canada, were randomly assigned to use one tool over 3 d during 1 wk, then used the other tool the next week. Semistructured interviews (n = 45) were conducted after completing the second tool. A qualitative description of the interviews was conducted through an inductive determination of themes.

Results

Facilitators to using the Plate Tool were its simplicity, quick completion time compared with the Food Journal and easiness to use, increased awareness of dietary habits and accountability, with participants expressing that it could help users make informed dietary changes aligning with the CFG. However, barriers to using the Plate Tool were its lack of precision, the participants' difficulty categorizing foods into the CFG categories and recording intake of foods not present on the CFG.

Conclusions

The Plate Tool is an acceptable dietary self-monitoring tool for healthy adults over 50. Self-monitoring tools based on the plate method should take the barriers described in this study into account. Future studies should compare dietary self-monitoring methods to assess adherence and effectiveness at eliciting dietary behavior change.

Patterns and Predictors of Engagement With Digital Self-Monitoring During the Maintenance Phase of a Behavioral Weight Loss Program: Quantitative Study

BACKGROUND

Long-term self-monitoring (SM) of weight, diet, and exercise is commonly recommended by behavioral weight loss (BWL) treatments. However, sustained SM engagement is notoriously challenging; therefore, more must be learned about patterns of engagement with digital SM tools during weight loss maintenance (WLM). In addition, insight into characteristics that may influence SM engagement could inform tailored approaches for participants at risk for poor adherence.

OBJECTIVE

This study explored patterns of digital SM of weight, diet, and exercise during WLM (aim 1) and examined timing, patterns, and rates of disengagement and reengagement (aim 2). This study also assessed relationships between individual-level factors (weight-related information avoidance and weight bias internalization) and SM engagement (aim 3).

METHODS

Participants were 72 adults enrolled in a BWL program consisting of a 3-month period of weekly treatment designed to induce weight loss (phase I), followed by a 9-month period of less frequent contact to promote WLM (phase II). Participants were prescribed daily digital SM of weight, diet, and exercise. At baseline, self-report measures assessed weight-related information avoidance and weight bias internalization. SM adherence was objectively measured with the days per month that participants tracked weight, diet, and exercise. Repeated-measures ANOVA examined differences in adherence across SM targets. Multilevel modeling examined changes in adherence across phase II. Relationships between individual-level variables and SM adherence were assessed with Pearson correlations, 2-tailed independent samples t tests, and multilevel modeling.

RESULTS

During WLM, consistently high rates of SM (≥50% of the days in each month) were observed for 61% (44/72) of the participants for exercise, 40% (29/72) of the participants for weight, and 21% (15/72) of the participants for diet. Adherence for SM of exercise was higher than that for weight or diet (P<.001). Adherence decreased over time for all SM targets throughout phase II (P<.001), but SM of exercise dropped off later in WLM (mean 10.07, SD 2.83 months) than SM of weight (mean 7.92, SD 3.23 months) or diet (mean 7.58, SD 2.92 months; P<.001). Among participants with a period of low SM adherence (ie, <50% of the days in a month), only 33% (17/51 for weight, 19/57 for diet) to 46% (13/28 for exercise) subsequently had ≥1 months with high adherence. High weight-related information avoidance predicted a faster rate of decrease in dietary SM (P<.001). Participants with high weight bias internalization had the highest rates of weight SM (P=.03).

CONCLUSIONS

Participants in BWL programs have low adherence to the recommendation to sustain daily SM during WLM, particularly for SM of diet and weight. Weight-related information avoidance and weight bias internalization may be relevant indicators for SM engagement. Interventions may benefit from innovative strategies that target participants at key moments of risk for disengagement.

A nutritional web-based approach in obesity and diabetes before and during the COVID-19 lockdown

INTRODUCTION

Obesity and type 2 diabetes (T2D) are two closely related pandemic conditions. Novel technologies represent promising tools for their management, the use of which has been greatly encouraged during the COVID-19 pandemic. The aim of the present study is to compare a web-based nutritional intervention versus a traditional one, before and during the Italian 'lockdown' period due to the COVID-19 outbreak, in overweight and obese subjects affected by T2D or impaired glucose regulation (IGR).

METHODS

For the study, 36 subjects were randomly allocated into two arms: a traditional arm, providing face-to-face individual and group-based intervention; and a web arm, deploying the in-presence traditional approach with intervention provided through web technologies. The outcomes were the data resulting from the comparison between the subjects' anthropometric and clinical parameters as well as PREDIMED scores at baseline with those at 3 months (T3), 6 months (T6) and at lockdown.

RESULTS

In the web arm we detected a progressive reduction in weight and body mass index (BMI) from baseline to T6 and a minimal increase of both parameters during the lockdown. Improvement of these parameters compared with baseline was observed in controls during the lockdown. The PREDIMED score improved at T6 compared with baseline in both arms. Significant variations were observed considering weight (p < 0.001), BMI (p = 0.001) and PREDIMED scores (p = 0.023) over time.

DISCUSSION

The study showed the effectiveness and feasibility of a short-term nutritional web-based intervention in patients affected by T2D or IGR before and during the COVID 19 pandemic.Clinical Trial registration number: NCT04386200, ClinicalTrials.gov.

The Cost-effectiveness of a Mass Media Campaign to Promote Smartphone Apps for Weight Loss: Updated Modeling Study

BACKGROUND

Evidence suggests that smartphone apps can be effective in the self-management of weight. Given the low cost, broad reach, and apparent effectiveness of weight loss apps, governments may seek to encourage their uptake as a tool to reduce excess weight in the population. Mass media campaigns are 1 mechanism for promoting app use. However, the cost and potential cost-effectiveness are important considerations.

OBJECTIVE

The aim of our study was to use modeling to assess the health impacts, health system costs, cost-effectiveness, and health equity of a mass media campaign to promote high-quality smartphone apps for weight loss in New Zealand.

METHODS

We used an established proportional multistate life table model that simulates the 2011 New Zealand adult population over the lifetime, subgrouped by age, sex, and ethnicity (Māori [Indigenous] or non-Māori). The risk factor was BMI. The model compared business as usual to a one-off mass media campaign intervention, which included the pooled effect size from a recent meta-analysis of smartphone weight loss apps. The resulting impact on BMI and BMI-related diseases was captured through changes in health gain (quality-adjusted life years) and in health system costs. The difference in total health system costs was the net sum of intervention costs and downstream cost offsets because of altered disease rates. An annual discount rate of 3% was applied to health gains and health system costs. Multiple scenarios and sensitivity analyses were conducted, including an equity adjustment.

RESULTS

Across the remaining lifetime of the modeled 2011 New Zealand population, the mass media campaign to promote weight loss app use had an estimated overall health gain of 181 (95% uncertainty interval 113-270) quality-adjusted life years and health care costs of -NZ $606,000 (-US $408,000; 95% uncertainty interval -NZ $2,540,000 [-US $1,709,000] to NZ $907,000 [US $610,000]). The mean health care costs were negative, representing overall savings to the health system. Across the outcomes examined in this study, the modeled mass media campaign to promote weight loss apps among the general population would be expected to provide higher per capita health gain for Māori and hence reduce health inequities arising from high BMI, assuming that the intervention would be as effective for Māori as it is for non-Māori.

CONCLUSIONS

A modeled mass media campaign to encourage the adoption of smartphone apps to promote weight loss among the New Zealand adult population is expected to yield an overall gain in health and to be cost-saving to the health system. Although other interventions in the nutrition and physical activity space are even more beneficial to health and produce larger cost savings (eg, fiscal policies and food reformulation), governments may choose to include strategies to promote health app use as complementary measures.

The Effectiveness of Combining Nonmobile Interventions With the Use of Smartphone Apps With Various Features for Weight Loss: Systematic Review and Meta-analysis

Background

The effectiveness of smartphone apps for weight loss is limited by the diversity of interventions that accompany such apps. This research extends the scope of previous systematic reviews by including 2 subgroup analyses based on nonmobile interventions that accompanied smartphone use and human-based versus passive behavioral interventions.

Objective

The primary objective of this study is to systematically review and perform a meta-analysis of studies that evaluated the effectiveness of smartphone apps on weight loss in the context of other interventions combined with app use. The secondary objective is to measure the impact of different mobile app features on weight loss and mobile app adherence.

Methods

We conducted a systematic review and meta-analysis of relevant studies after an extensive search of the PubMed, MEDLINE, and EBSCO databases from inception to January 31, 2022. Gray literature, such as abstracts and conference proceedings, was included. Working independently, 2 investigators extracted the data from the articles, resolving disagreements by consensus. All randomized controlled trials that used smartphone apps in at least 1 arm for weight loss were included. The weight loss outcome was the change in weight from baseline to the 3- and 6-month periods for each arm. Net change estimates were pooled across the studies using random-effects models to compare the intervention group with the control group. The risk of bias was assessed independently by 2 authors using the Cochrane Collaboration tool for assessing the risk of bias in randomized trials.

Results

Overall, 34 studies were included that evaluated the use of a smartphone app in at least 1 arm. Compared with controls, the use of a smartphone app–based intervention showed a significant weight loss of –1.99 kg (95% CI –2.19 to –1.79 kg; I²=81%) at 3 months and –2.80 kg (95% CI –3.03 to –2.56 kg; I²=91%) at 6 months. In the subgroup analysis, based on the various intervention components that were added to the mobile app, the combination of the mobile app, tracker, and behavioral interventions showed a statistically significant weight loss of –2.09 kg (95% CI –2.32 to –1.86 kg; I²=91%) and –3.77 kg (95% CI –4.05 to –3.49 kg; I²=90%) at 3 and 6 months, respectively. When a behavioral intervention was present, only the combination of the mobile app with intensive behavior coaching or feedback by a human coach showed a statistically significant weight loss of –2.03 kg (95% CI –2.80 to –1.26 kg; I²=83%) and –2.63 kg (95% CI –2.97 to –2.29 kg; I²=91%) at 3 and 6 months, respectively. Neither the type nor the number of mobile app features was associated with weight loss.

Conclusions

Smartphone apps have a role in weight loss management. Nevertheless, the human-based behavioral component remained key to higher weight loss results.

Digital Interventions on Healthy Lifestyle Management: Systematic Review

BACKGROUND

Digital interventions have tremendous potential to improve well-being and health care conveyance by improving adequacy, proficiency, availability, and personalization. They have gained acknowledgment in interventions for the management of a healthy lifestyle. Therefore, we are reviewing existing conceptual frameworks, digital intervention approaches, and associated methods to identify the impact of digital intervention on adopting a healthier lifestyle.

OBJECTIVE

This study aims to evaluate the impact of digital interventions on weight management in maintaining a healthy lifestyle (eg, regular physical activity, healthy habits, and proper dietary patterns).

METHODS

We conducted a systematic literature review to search the scientific databases (Nature, SpringerLink, Elsevier, IEEE Xplore, and PubMed) that included digital interventions on healthy lifestyle, focusing on preventing obesity and being overweight as a prime objective. Peer-reviewed articles published between 2015 and 2020 were included. We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and a framework for an evidence-based systematic review. Furthermore, we improved the review process by adopting the Rayyan tool and the Scale for the Assessment of Narrative Review Articles.

RESULTS

Our initial searches identified 780 potential studies through electronic and manual searches; however, 107 articles in the final stage were cited following the specified inclusion and exclusion criteria. The identified methods for a successful digital intervention to promote a healthy lifestyle are self-monitoring, self-motivation, goal setting, personalized feedback, participant engagement, psychological empowerment, persuasion, digital literacy, efficacy, and credibility. In this study, we identified existing conceptual frameworks for digital interventions, different approaches to provide digital interventions, associated methods, and execution challenges and their impact on the promotion of healthy lifestyle management.

CONCLUSIONS

This systematic literature review selected intervention principles (rules), theories, design features, ways to determine efficient interventions, and weaknesses in healthy lifestyle management from established digital intervention approaches. The results help us understand how digital interventions influence lifestyle management and overcome the existing shortcomings. It serves as a basis for further research with a focus on designing, developing, testing, and evaluating the generation of personalized lifestyle recommendations as a part of digital health interventions.

Preference, Expected Burden, and Willingness to Use Digital and Traditional Methods to Assess Food and Alcohol Intake

We conducted an online survey to examine the preference, expected burden, and willingness of people to use four different methods of assessing food and alcohol intake such as food/drink record, 24-h recall, Remote Food Photography Method© (RFPM, via SmartIntake^® app), and a novel app (PortionSize^®) that allows the in-app portion size estimation of foods/drinks by the user. For food (N = 1959) and alcohol (N = 466) intake assessment, 67.3% and 63.3%, respectively, preferred the RFPM/SmartIntake^®, 51.9% and 53.4% preferred PortionSize^®, 48.0% and 49.3% the food records, and 32.9% and 33.9% the 24-h recalls (difference in preference across all methods was p < 0.001 for food and alcohol intake). Ratings of burden and preference of methods were virtually superimposable, and we found strong correlations between high preference and low expected burden for all methods (all ρ ≥ 0.82; all p < 0.001). Willingness (mean (SD)) to use the RFPM/SmartIntake^® (food: 6.6 (2.0); alcohol: 6.4 (2.4)) was greater than PortionSize^® (food: 6.0 (2.2); alcohol: 6.0 (2.4); all p < 0.001) and 24-h recalls (food: 6.1 (2.2); alcohol: 5.7 (2.7); p < 0.001), but not different from food records (food: 6.6 (2.0); alcohol: 6.5 (2.3); all p ≥ 0.33). Our results can be used in conjunction with existing data on the reliability and validity of these methods in order to inform the selection of methods for the assessment of food and alcohol intake.

A systematic review of the use of dietary self-monitoring in behavioural weight loss interventions: delivery, intensity and effectiveness

OBJECTIVE

To identify dietary self-monitoring implementation strategies in behavioural weight loss interventions.

DESIGN

We conducted a systematic review of eight databases and examined fifty-nine weight loss intervention studies targeting adults with overweight/obesity that used dietary self-monitoring.

SETTING

NA.

PARTICIPANTS

NA.

RESULTS

We identified self-monitoring implementation characteristics, effectiveness of interventions in supporting weight loss and examined weight loss outcomes among higher and lower intensity dietary self-monitoring protocols. Included studies utilised diverse self-monitoring formats (paper, website, mobile app, phone) and intensity levels (recording all intake or only certain aspects of diet). We found the majority of studies using high- and low-intensity self-monitoring strategies demonstrated statistically significant weight loss in intervention groups compared with control groups.

CONCLUSIONS

Based on our findings, lower and higher intensity dietary self-monitoring may support weight loss, but variability in adherence measures and limited analysis of weight loss relative to self-monitoring usage limits our understanding of how these methods compare with each other.

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.

A Smartphone-Based Technique to Detect Dynamic User Preferences for Tailoring Behavioral Interventions: Observational Utility Study of Ecological Daily Needs Assessment

BACKGROUND

Mobile health apps are promising vehicles for delivering scalable health behavior change interventions to populations that are otherwise difficult to reach and engage, such as young adults with psychiatric conditions. To improve uptake and sustain consumer engagement, mobile health interventions need to be responsive to individuals' needs and preferences, which may change over time. We previously created an ecological daily needs assessment to capture microprocesses influencing user needs and preferences for mobile health treatment adaptation.

OBJECTIVE

The objective of our study was to test the utility of a needs assessment anchored within a mobile app to capture individualized, contextually relevant user needs and preferences within the framework of a weight management mobile health app.

METHODS

Participants with an iOS device could download the study app via the study website or links from social media. In this fully remote study, we screened, obtained informed consent from, and enrolled participants through the mobile app. The mobile health framework included daily health goal setting and self-monitoring, with up to 6 daily prompts to determine in-the-moment needs and preferences for mobile health-assisted health behavior change.

RESULTS

A total of 24 participants downloaded the app and provided e-consent (22 female; 2 male), with 23 participants responding to at least one prompt over 2 weeks. The mean length of engagement was 5.6 (SD 4.7) days, with a mean of 2.8 (1.1) responses per day. We observed individually dynamic needs and preferences, illustrating daily variability within and between individuals. Qualitative feedback indicated preferences for self-adapting features, simplified self-monitoring, and the ability to personalize app-generated message timing and content.

CONCLUSIONS

The technique provided an individually dynamic and contextually relevant alternative and complement to traditional needs assessment for assessing individually dynamic user needs and preferences during treatment development or adaptation. The results of this utility study suggest the importance of personalization and learning algorithms for sustaining app engagement in young adults with psychiatric conditions. Further study in broader user populations is needed.

Technology-Assisted Self-Monitoring of Lifestyle Behaviors and Health Indicators in Diabetes: Qualitative Study

BACKGROUND

Self-monitoring is key to successful behavior change in diabetes and obesity, and the use of traditional paper-based methods of self-monitoring may be time-consuming and burdensome.

OBJECTIVE

This study aimed to explore participant experiences while using technology-assisted self-monitoring of lifestyle behaviors and health indicators among overweight or obese adults with type 2 diabetes.

METHODS

Qualitative data collected from the intervention group of a 6-month, three-arm (control, paper diary, and technology-assisted self-monitoring groups) randomized clinical trial were analyzed. Study participants in the intervention group monitored their diet, exercise, and weight using the LoseIt! app, and their blood glucose levels using a glucometer and the Diabetes Connect app. Semistructured group discussions were conducted at 6 weeks (n=10) from the initiation of the behavioral lifestyle intervention and again at 6 months (n=9). All group interviews were audiotaped and transcribed verbatim. Using a combination of thematic and comparative analysis approaches, two trained professionals coded the transcriptions independently and then discussed and concluded common themes for the 6-week and 6-month discussions separately.

RESULTS

The sample (n=10), which primarily involved African American participants (n=7) and female participants (n=8), had a mean age of 59.4 years. The following eight themes emerged: (1) perceived benefits of technology-assisted self-monitoring; (2) perceived ease of use (eg, barriers: technical difficulties and lack of self-discipline; facilitators: help from family, friends, and the program); (3) use of technology-assisted self-monitoring; (4) facilitators of engaging in healthy lifestyle behaviors (eg, visualization and awareness of calorie input/expenditure); (5) positive lifestyle change; (6) barriers of engaging in healthy lifestyle behaviors (eg, event influence); (7) learning curve; and (8) monitored data sharing. The first six of these themes were shared between the 6-week and 6-month timepoints, but the codes within these themes were not all the same and differed slightly between the two timepoints. These differences provide insights into the evolution of participant thoughts and perceptions on using technology for self-monitoring and subsequent behavioral lifestyle changes while participating in lifestyle interventions. The findings from the 6-week and 6-month data helped to paint a picture of participant comfort and the integration of technology and knowledge overtime, and clarified participant attitudes, difficulties, behavioral processes, and modifications, as well as health indicators that were experienced throughout the study.

CONCLUSIONS

Although there were some barriers, participants were able to identify various individual and external facilitators to adjust to and engage in technology-assisted self-monitoring, and it was concluded that the technology-assisted self-monitoring approach was beneficial, safe, and feasible to use for positive lifestyle change. These patient perspectives need to be considered in future research studies when investigating the effectiveness of using technology-assisted self-monitoring, as well as in clinical practice when recommending technology-assisted self-monitoring of lifestyle behaviors and health indicators to improve health outcomes.

Effect of Behavioral Weight Management Interventions Using Lifestyle mHealth Self-Monitoring on Weight Loss: A Systematic Review and Meta-Analysis

Alongside an increase in obesity, society is experiencing the development of substantial technological advances. Interventions that are easily scalable, such as lifestyle (including diet and physical activity) mobile health (mHealth) self-monitoring, may be highly valuable in the prevention and treatment of excess weight. Thus, the aims of this systematic review and meta-analysis were to estimate the following: (i) the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss and (ii) the adherence to behavioral weight management interventions using lifestyle mHealth self-monitoring. MEDLINE via PubMed, EMBASE, the Cochrane Central Register of Controlled Trials and the Web of Science databases were systematically searched. The DerSimonian and Laird method was used to estimate the effect of and adherence to behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss. Twenty studies were included in the systematic review and meta-analysis, yielding a moderate decrease in weight and higher adherence to intervention of behavioral weight management interventions using lifestyle mHealth self-monitoring, which was greater than other interventions. Subgroup analyses showed that smartphones were the most effective mHealth approach to achieve weight management and the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring was more pronounced when compared to usual care and in the short-term (less than six months). Furthermore, behavioral weight management interventions using lifestyle mHealth self-monitoring showed a higher adherence than: (i) recording on paper at any time and (ii) any other intervention at six and twelve months.

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.

Sustaining eHealth engagement in a multi-year weight gain prevention intervention

INTRODUCTION

Digital tools are widely used and effective in weight management interventions; however, usage declines over time. Strategies to promote continued engagement should be explored. We examined the effects of offering additional modes of weight reporting as well as periodic online campaigns to promote engagement, assessed by frequency of weight reporting, in a weight gain prevention study for young adults.

METHODS

Using an observational design, self-reported weights obtained through digital tools were pooled across participants assigned to two interventions (n = 312). Analysis examined the effects before during and after introduction of an additional reporting modality (email) and for three time-limited refresher campaigns over 2 years.

RESULTS

Adding a new modality to the three existing modes (SMS, web, and mobile web) increased weight reporting as well as the number of modalities participants used to report weights. The use of several modes of reporting was associated with more weights submitted (p < 0.01). Refresher campaigns did not increase the proportion of participants reporting; however, the number of weights submitted during the 4-week campaigns increased compared with the 4 weeks before the campaign (p's ≥ 0.45, <0.001, respectively).

CONCLUSION

Using multiple digital modalities and periodic campaigns shows promise for sustaining engagement with weight reporting in a young adult population, and incorporating such strategies may mitigate typical declines in eHealth and mHealth interventions.

Comparing Self-Monitoring Strategies for Weight Loss in a Smartphone App: Randomized Controlled Trial

BACKGROUND

Self-monitoring of dietary intake is a valuable component of behavioral weight loss treatment; however, it declines quickly, thereby resulting in suboptimal treatment outcomes.

OBJECTIVE

This study aimed to examine a novel behavioral weight loss intervention that aims to attenuate the decline in dietary self-monitoring engagement.

METHODS

GoalTracker was an automated randomized controlled trial. Participants were adults with overweight or obesity (n=105; aged 21-65 years; body mass index, BMI, 25-45 kg/m²) and were randomized to a 12-week stand-alone weight loss intervention using the MyFitnessPal smartphone app for daily self-monitoring of either (1) both weight and diet, with weekly lessons, action plans, and feedback (Simultaneous); (2) weight through week 4, then added diet, with the same behavioral components (Sequential); or (3) only diet (App-Only). All groups received a goal to lose 5% of initial weight by 12 weeks, a tailored calorie goal, and automated in-app reminders. Participants were recruited via online and offline methods. Weight was collected in-person at baseline, 1 month, and 3 months using calibrated scales and via self-report at 6 months. We retrieved objective self-monitoring engagement data from MyFitnessPal using an application programming interface. Engagement was defined as the number of days per week in which tracking occurred, with diet entries counted if ≥800 kcal per day. Other assessment data were collected in-person via online self-report questionnaires.

RESULTS

At baseline, participants (84/100 female) had a mean age (SD) of 42.7 (11.7) years and a BMI of 31.9 (SD 4.5) kg/m². One-third (33/100) were from racial or ethnic minority groups. During the trial, 5 participants became ineligible. Of the remaining 100 participants, 84% (84/100) and 76% (76/100) completed the 1-month and 3-month visits, respectively. In intent-to-treat analyses, there was no difference in weight change at 3 months between the Sequential arm (mean -2.7 kg, 95% CI -3.9 to -1.5) and either the App-Only arm (-2.4 kg, -3.7 to -1.2; P=.78) or the Simultaneous arm (-2.8 kg, -4.0 to -1.5; P=.72). The median number of days of self-monitoring diet per week was 1.9 (interquartile range [IQR] 0.3-5.5) in Sequential (once began), 5.3 (IQR 1.8-6.7) in Simultaneous, and 2.9 (IQR 1.2-5.2) in App-Only. Weight was tracked 4.8 (IQR 1.9-6.3) days per week in Sequential and 5.1 (IQR 1.8-6.3) days per week in Simultaneous. Engagement in neither diet nor weight tracking differed between arms.

CONCLUSIONS

Regardless of the order in which diet is tracked, using tailored goals and a commercial mobile app can produce clinically significant weight loss. Stand-alone digital health treatments may be a viable option for those looking for a lower intensity approach.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03254953; https://clinicaltrials.gov/ct2/show/NCT03254953 (Archived by WebCite at http://www.webcitation.org/72PyQrFjn).

Internet-based self-monitoring interventions for overweight and obese adolescents: A systematic review and meta-analysis

BACKGROUND

Internet-based self-monitoring intervention offers accessibleand convenient weight management. This review aimed to systematically review the evidence on the effectiveness of internet-based self-monitoring intervention for overweight and obese adolescents.

METHOD

PubMed, CINAHL, Cochrane Library, EMBASE, ProQuest, PsycINFO and SCOPUS were systematically searched for randomised controlled trials (RCTs) from inception until December 13, 2017. The risk of bias and strength of evidence was assessed using the Cochrane Collaboration Risk of Bias Tool and the Grading of Recommendations, Assessment, Development and Evaluations criteria. Meta-analysis was performed on the RevMan software using a random effects model. The overall effect was assessed using effect size (Cohen'sd)and heterogeneity was evaluated using Cochrane Q and I2 values. PROSPERO database #CRD42016050089.

RESULTS

A total of 6841 records were identified. Six RCTs in 10 articles were selected amongst 505 adolescents across three countries who were overweight and obese. The meta-analysis revealed a small effect on the reduction of body mass index (BMI) and BMI z-scores (d = 0.30, 95% CI: -0.48 to -0.12). Subgroup analyses suggest the use of daily multicomponent self-monitoring, specified goal setting, face-to-face counselling and parental involvement. The overall quality of evidence was low due to the risk of bias and imprecision.

CONCLUSION

Internet-based self-monitoring intervention is a possible approach for overweight and obese adolescents to reduce their BMI. Further well-designed RCTs with follow-up data and large sample sizes are needed to ensure the robustness of the evidence.

Systematic review and meta-analysis of remotely delivered interventions using self-monitoring or tailored feedback to change dietary behavior

Background

Self-monitoring (SM) of diet and tailored feedback (TF) have been suggested as tools for changing dietary behavior. New technologies allow users to monitor behavior remotely, potentially improving reach, adherence, and outcomes.

Objective

We conducted a systematic literature review and meta-analysis to address the following question: are remotely delivered standalone (i.e., no human contact) interventions that use SM or TF effective in changing eating behaviors?

Design

Five databases were searched in October 2016 (updated in September 2017). Only randomized controlled trials published after 1990 were included. Trials could include any adult population with no history of disordered eating which delivered an SM or TF intervention without direct contact and recorded actual dietary consumption as an outcome. Three assessors independently screened the search results. Two reviewers extracted the study characteristics, intervention details, and outcomes, and assessed risk of bias using the Cochrane tool. Results were converted to standardized mean differences and incorporated into a 3-level (individuals and outcomes nested in studies) random effects meta-analysis.

Results

Twenty-six studies containing 21,262 participants were identified. The majority of the studies were judged to be unclear or at high risk of bias. The meta-analysis showed dietary improvement in the intervention group compared to the control group with a standardized mean difference of 0.17 (95% CI: 0.10, 0.24; P < 0.0001). The I2 statistic for the meta-analysis was 0.77, indicating substantial heterogeneity in results. A "one study removed" sensitivity analysis showed that no single study excessively influenced the results.

Conclusions

Standalone interventions containing self-regulatory methods have a small but significant effect on dietary behavior, and integrating these elements could be important in future interventions. However, there was substantial variation in study results that could not be explained by the characteristics we explored, and there were risk-of-bias concerns with the majority of studies.

Vegan diets: practical advice for athletes and exercisers

With the growth of social media as a platform to share information, veganism is becoming more visible, and could be becoming more accepted in sports and in the health and fitness industry. However, to date, there appears to be a lack of literature that discusses how to manage vegan diets for athletic purposes. This article attempted to review literature in order to provide recommendations for how to construct a vegan diet for athletes and exercisers. While little data could be found in the sports nutrition literature specifically, it was revealed elsewhere that veganism creates challenges that need to be accounted for when designing a nutritious diet. This included the sufficiency of energy and protein; the adequacy of vitamin B12, iron, zinc, calcium, iodine and vitamin D; and the lack of the long-chain n-3 fatty acids EPA and DHA in most plant-based sources. However, via the strategic management of food and appropriate supplementation, it is the contention of this article that a nutritive vegan diet can be designed to achieve the dietary needs of most athletes satisfactorily. Further, it was suggested here that creatine and β-alanine supplementation might be of particular use to vegan athletes, owing to vegetarian diets promoting lower muscle creatine and lower muscle carnosine levels in consumers. Empirical research is needed to examine the effects of vegan diets in athletic populations however, especially if this movement grows in popularity, to ensure that the health and performance of athletic vegans is optimised in accordance with developments in sports nutrition knowledge.

The Effect of Different Types of Monitoring Strategies on Weight Loss: A Randomized Controlled Trial

OBJECTIVE

To determine the effectiveness of various monitoring strategies on weight loss, body composition, blood markers, exercise, and psychosocial indices in adults with overweight and obesity following a 12-month weight loss program.

METHODS

Two hundred fifty adults with BMI ≥ 27 were randomized to brief, monthly, individual consults, daily self-monitoring of weight, self-monitoring of diet using MyFitnessPal, self-monitoring of hunger, or control over 12 months. All groups received diet and exercise advice, and 171 participants (68.4%) remained at 12 months.

RESULTS

No significant differences in weight, body composition, blood markers, exercise, or eating behavior were apparent between those in the four monitoring groups and the control condition at 12 months (all P ≥ 0.053). Weight differences between groups ranged from -1.1 kg (-3.8 to 1.6) to 2.2 kg (-1.0 to 5.3). However, brief support and hunger training groups reported significantly lower scores for depression (difference [95% CI]: -3.16 [-5.70 to -0.62] and -3.05 [-5.61 to -0.50], respectively) and anxiety (-1.84, [-3.67 to -0.02]) scores than control participants.

CONCLUSIONS

Although adding a monitoring strategy to diet and exercise advice did not further increase weight loss, no adverse effects on eating behavior were observed, and some monitoring strategies may even benefit mental health.

Providing Nutritional Care in the Office Practice: Teams, Tools, and Techniques

Provision of dietary counseling in the office setting is enhanced by using team-based care and electronic tools. Effective provider-patient communication is essential for fostering behavior change: the key component of lifestyle medicine. The principles of communication and behavior change are skill-based and grounded in scientific theories and models. Motivational interviewing and shared decision making, a collaboration process between patients and their providers to reach agreement about a health decision, is an important process in counseling. The stages of change, self-determination, health belief model, social cognitive model, theory of planned behavior, and cognitive behavioral therapy are used in the counseling process.

Practice Paper of the Academy of Nutrition and Dietetics: Social Media and the Dietetics Practitioner: Opportunities, Challenges, and Best Practices

Social media tools, including blogs, social networks, and media-sharing sites, help nutrition and dietetics practitioners reach broader audiences and connect directly with the public. In many ways, social media has transformed the practice of dietetics and has opened up new avenues for communicating food and nutrition information. Social media has been an effective tool for virtual nutrition counseling, patient education, peer-to-peer support, and public health campaigns. Increasingly, nutrition and dietetics practitioners are using social media to network and collaborate with colleagues, conduct a job search, stay current with new research, champion a cause, promote products or services, and build a business. The potential role of social media in the profession is far reaching, yet there are important guidelines to follow related to ethics and professionalism. When using social media, nutrition and dietetics practitioners must remember that they are governed by the same Code of Ethics that guides all other aspects of practice. In addition, it is critical to have a thorough understanding of all the factors related to social media professionalism, including disclosure rules from the Federal Trade Commission, patient/client privacy and confidentiality as covered by the Health Insurance Portability and Accountability Act, and copyright laws that protect intellectual property. In today's digital age, it is essential for nutrition and dietetics practitioners to recognize the professional opportunities and challenges of social media. Failing to effectively and ethically use social media can reflect poorly on the individual practitioner and the profession. Certain violations may have legal implications. The purpose of this Academy of Nutrition and Dietetics practice paper is to provide guidance on social media's relevance, potential applications, best practices, benefits, and risks.