A Mixed-Methods Approach to the Development, Refinement, and Pilot Testing of Social Networks for Improving Healthy Behaviors

Potential associations between behavior change techniques and engagement with mobile health apps: a systematic review

Introduction

Lack of engagement is a common challenge for digital health interventions. To achieve their potential, it is necessary to understand how best to support users' engagement with interventions and target health behaviors. The aim of this systematic review was to identify the behavioral theories and behavior change techniques being incorporated into mobile health apps and how they are associated with the different components of engagement.

Methods

The review was structured using the PRISMA and PICOS frameworks and searched six databases in July 2022: PubMed, Embase, CINAHL, APA PsycArticles, ScienceDirect, and Web of Science. Risk of bias was evaluated using the Cochrane Collaboration Risk of Bias 2 and the Mixed Methods Appraisal Tools.

Analysis

A descriptive analysis provided an overview of study and app characteristics and evidence for potential associations between Behavior Change Techniques (BCTs) and engagement was examined.

Results

The final analysis included 28 studies. Six BCTs were repeatedly associated with user engagement: goal setting, self-monitoring of behavior, feedback on behavior, prompts/cues, rewards, and social support. There was insufficient data reported to examine associations with specific components of engagement, but the analysis indicated that the different components were being captured by various measures.

Conclusion

This review provides further evidence supporting the use of common BCTs in mobile health apps. To enable developers to leverage BCTs and other app features to optimize engagement in specific contexts and individual characteristics, we need a better understanding of how BCTs are associated with different components of engagement.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42022312596.

Effects of technology-based interventions on dietary intake or anthropometrics among adolescents and adults in South Asia - A systematic review of intervention studies

INTRODUCTION

Mobile technology has been increasingly used as part of dietary interventions, but the effects of such interventions have not been systematically evaluated in the South Asian context. The systematic review aimed to determine the effects of technology-based interventions on dietary intake or anthropometrics among adolescents and adults in South Asia.

METHODS

Five electronic databases were searched (PubMed, Scopus, Web of Science, Global Health Library and Health Technology Assessment). Studies published in English between 1st January 2011 and 31st December 2021were included. Interventions that evaluated the effects of dietary interventions using technology on dietary outcomes and anthropometrics in adolescents or adults in the age group of 13-44 years (or a broader age group) from South Asia were eligible for inclusion. The risk of bias was assessed using the Cochrane Risk-of-bias 2 tool and ROBINS-I tool. A narrative synthesis was conducted.

RESULTS

Twenty-one studies met the inclusion criteria (20,667 participants). Eleven of the 17 randomised controlled trials (RCTs) had a high overall risk of bias. The four non-randomised intervention studies had a serious or critical overall risk of bias. When including studies with low risk or some concern for bias, the interventions had a beneficial effect on at least one dietary outcome in four of the six RCTs that measured changes in diet, and no effect on the anthropometric outcomes in the six RCTs that measured changes in anthropometric outcomes.

DISCUSSION

Technology-based dietary interventions have had some positive effects on dietary intake, but no effects on anthropometry in South Asia. More evidence is needed as the overall risk of bias was high in a majority of the studies.

User Models for Personalized Physical Activity Interventions: Scoping Review

Background

Fitness devices have spurred the development of apps that aim to motivate users, through interventions, to increase their physical activity (PA). Personalization in the interventions is essential as the target users are diverse with respect to their activity levels, requirements, preferences, and behavior.

Objective

This review aimed to (1) identify different kinds of personalization in interventions for promoting PA among any type of user group, (2) identify user models used for providing personalization, and (3) identify gaps in the current literature and suggest future research directions.

Methods

A scoping review was undertaken by searching the databases PsycINFO, PubMed, Scopus, and Web of Science. The main inclusion criteria were (1) studies that aimed to promote PA; (2) studies that had personalization, with the intention of promoting PA through technology-based interventions; and (3) studies that described user models for personalization.

Results

The literature search resulted in 49 eligible studies. Of these, 67% (33/49) studies focused solely on increasing PA, whereas the remaining studies had other objectives, such as maintaining healthy lifestyle (8 studies), weight loss management (6 studies), and rehabilitation (2 studies). The reviewed studies provide personalization in 6 categories: goal recommendation, activity recommendation, fitness partner recommendation, educational content, motivational content, and intervention timing. With respect to the mode of generation, interventions were found to be semiautomated or automatic. Of these, the automatic interventions were either knowledge-based or data-driven or both. User models in the studies were constructed with parameters from 5 categories: PA profile, demographics, medical data, behavior change technique (BCT) parameters, and contextual information. Only 27 of the eligible studies evaluated the interventions for improvement in PA, and 16 of these concluded that the interventions to increase PA are more effective when they are personalized.

Conclusions

This review investigates personalization in the form of recommendations or feedback for increasing PA. On the basis of the review and gaps identified, research directions for improving the efficacy of personalized interventions are proposed. First, data-driven prediction techniques can facilitate effective personalization. Second, use of BCTs in automated interventions, and in combination with PA guidelines, are yet to be explored, and preliminary studies in this direction are promising. Third, systems with automated interventions also need to be suitably adapted to serve specific needs of patients with clinical conditions. Fourth, previous user models focus on single metric evaluations of PA instead of a potentially more effective, holistic, and multidimensional view. Fifth, with the widespread adoption of activity monitoring devices and mobile phones, personalized and dynamic user models can be created using available user data, including users’ social profile. Finally, the long-term effects of such interventions as well as the technology medium used for the interventions need to be evaluated rigorously.

Linking Podcasts With Social Media to Promote Community Health and Medical Research: Feasibility Study

Background

Linking podcasts with social media is a strategy to promote and disseminate health and health research information to the community without constraints of time, weather, and geography.

Objective

To describe the process of creating a podcast library and promoting it on social media as a strategy for disseminating health and biomedical research topics to the community.

Methods

We used a community and patient engagement in research approach for developing a process to use podcasts for dissemination of health and health research information. We have reported the aspects of audience reach, impressions, and engagement on social media through the number of downloads, shares, and reactions posted on SoundCloud, Twitter, and Facebook, among others.

Results

In collaboration with our local community partner, we produced 45 podcasts focused on topics selected from a community health needs assessment with input from health researchers. Episodes lasted about 22 minutes and presented health-related projects, community events, and community resources, with most featured guests from Olmsted County (24/45, 53%). Health research was the most frequently discussed topic. Between February 2016 and June 2017, episodes were played 1843 times on SoundCloud and reached 1702 users on our Facebook page.

Conclusions

This study demonstrated the process and feasibility of creating a content library of podcasts for disseminating health- and research-related information. Further examination is needed to determine the best methods to develop a sustainable social media plan that will further enhance dissemination (audience reach), knowledge acquisition, and communication of health topics.

The role of smartphones in encouraging physical activity in adults

Lack of physical activity is a global public health issue. Behavioral change interventions utilizing smartphone applications (apps) are considered a potential solution. The purpose of this literature review was to: 1) determine whether smartphone-based interventions encourage the initiation of, and participation in, physical activity; 2) explore the success of interventions in different populations; and 3) examine the key factors of the interventions that successfully encouraged physical activity. Eight databases (Medline, Scopus, EBM Reviews–Cochrane Central Register of Controlled Trials, EBM Reviews–Cochrane Database of Systematic Reviews, PsycInfo, SportDISCUS, CINAHL, and EMBASE) were searched and studies reporting physical activity outcomes following interventions using smartphone apps in adults were included in the narrative review. Results were mixed with eight studies reporting increased physical activity and ten reporting no change. Interventions did not appear to be successful in specific populations defined by age, sex, country, or clinical diagnosis. There was no conclusive evidence that a specific behavioral theory or behavioral change technique was superior in eliciting behavioral change. The literature remains limited primarily to short-term studies, many of which are underpowered feasibility or pilot studies; therefore, many knowledge gaps regarding the effectiveness of smartphone apps in encouraging physical activity remain. Robust studies that can accommodate the fast pace of the technology industry are needed to examine outcomes in large populations.

Choosing between responsive-design websites versus mobile apps for your mobile behavioral intervention: presenting four case studies

Both mobile apps and responsive-design websites (web apps) can be used to deliver mobile health (mHealth) interventions, but it can be difficult to discern which to use in research. The goal of this paper is to present four case studies from behavioral interventions that developed either a mobile app or a web app for research and present an information table to help researchers determine which mobile option would work best for them. Four behavioral intervention case studies (two developed a mobile app, and two developed a web app) presented include time, cost, and expertise. Considerations for adopting a mobile app or a web app-such as time, cost, access to programmers, data collection, security needs, and intervention components- are presented. Future studies will likely integrate both mobile app and web app modalities. The considerations presented here can help guide researchers on which platforms to choose prior to starting an mHealth intervention.

Trading pounds for points: Engagement and weight loss in a mobile health intervention

Objective

The objective of this study was to describe participant engagement and examine predictors of weight loss and points earned through the point-based incentive system of the Social Pounds Off Digitally (POD) app.

Materials and methods

Overweight and obese adults with Android smartphones/tablets (body mass index 25-49.9 kg/m²; N = 24) were recruited for a 3-month weight loss intervention. Participants completed a survey assessing demographics and personality and had their weight measured. Participants received the content of the intervention via podcasts and used the Social POD app to self-monitor diet, physical activity, and weight. The Social POD app contained: tracking features; in-app notifications to track; pre-set goals for tracking; newsfeed for updates on others' goal attainment; ability to earn and track points for usage (exchanged for study-provided prizes); and a message screen. Analyses examined relationships between percent weight loss, personality characteristics, and total points earned.

Results

A total of 4843 points were earned (mean = 202 ± 105 points/participant). Most participants earned all three prizes (62.5%), followed by two prizes (21%), no prizes (12.5%), and one prize (4%). Total points earned significantly predicted percent weight loss (B = -0.02, p = .01), and higher conscientiousness significantly predicted greater total points earned (B = 10.27, p = .01), but other personality characteristics assessed did not.

Conclusion

A mobile app yielded moderately high participant engagement, as demonstrated by points earned. Earning points was significantly associated with percent weight loss, and conscientiousness was significantly associated with total points earned. Future research should examine whether point systems impact health behavior and weight loss when rewards are discontinued.

Clinical trial registration number

NCT02344836.