The history and future of digital health in the field of behavioral medicine.

Since its earliest days, the field of behavioral medicine has leveraged technology to increase the reach and effectiveness of its interventions. Here, we highlight key areas of opportunity and recommend next steps to further advance intervention development, evaluation, and commercialization with a focus on three technologies: mobile applications (apps), social media, and wearable devices. Ultimately, we argue that future of digital health behavioral science research lies in finding ways to advance more robust academic-industry partnerships. These include academics consciously working towards preparing and training the work force of the twenty first century for digital health, actively working towards advancing methods that can balance the needs for efficiency in industry with the desire for rigor and reproducibility in academia, and the need to advance common practices and procedures that support more ethical practices for promoting healthy behavior

Using the Habit App for Weight Loss Problem Solving: Development and Feasibility Study

BACKGROUND: Reviews of weight loss mobile apps have revealed they include very few evidence-based features, relying mostly on self-monitoring. Unfortunately, adherence to self-monitoring is often low, especially among patients with motivational challenges. One behavioral strategy that is leveraged in virtually every visit of behavioral weight loss interventions and is specifically used to deal with adherence and motivational issues is problem solving. Problem solving has been successfully implemented in depression mobile apps, but not yet in weight loss apps. OBJECTIVE: This study describes the development and feasibility testing of the Habit app, which was designed to automate problem-solving therapy for weight loss. METHODS: Two iterative single-arm pilot studies were conducted to evaluate the feasibility and acceptability of the Habit app. In each pilot study, adults who were overweight or obese were enrolled in an 8-week intervention that included the Habit app plus support via a private Facebook group. Feasibility outcomes included retention, app usage, usability, and acceptability. Changes in problem-solving skills and weight over 8 weeks are described, as well as app usage and weight change at 16 weeks. RESULTS: Results from both pilots show acceptable use of the Habit app over 8 weeks with on average two to three uses per week, the recommended rate of use. Acceptability ratings were mixed such that 54% (13/24) and 73% (11/15) of participants found the diet solutions helpful and 71% (17/24) and 80% (12/15) found setting reminders for habits helpful in pilots 1 and 2, respectively. In both pilots, participants lost significant weight (P=.005 and P=.03, respectively). In neither pilot was an effect on problem-solving skills observed (P=.62 and P=.27, respectively). CONCLUSIONS: Problem-solving therapy for weight loss is feasible to implement in a mobile app environment; however, automated delivery may not impact problem-solving skills as has been observed previously via human delivery. TRIAL REGISTRATION: ClinicalTrials.gov NCT02192905; https://clinicaltrials.gov/ct2/show/NCT02192905 (Archived by WebCite at http://www.webcitation.org/6zPQmvOF2). Danielle E Jake-Schoffman. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 20.06.2018

Clinic Versus Online Social Network-Delivered Lifestyle Interventions: Protocol for the Get Social Noninferiority Randomized Controlled Trial

BACKGROUND: Online social networks may be a promising modality to deliver lifestyle interventions by reducing cost and burden. Although online social networks have been integrated as one component of multimodality lifestyle interventions, no randomized trials to date have compared a lifestyle intervention delivered entirely via online social network with a traditional clinic-delivered intervention. OBJECTIVE: This paper describes the design and methods of a noninferiority randomized controlled trial, testing (1) whether a lifestyle intervention delivered entirely through an online social network would produce weight loss that would not be appreciably worse than that induced by a traditional clinic-based lifestyle intervention among overweight and obese adults and (2) whether the former would do so at a lower cost. METHODS: Adults with body mass index (BMI) between 27 and 45 kg/m(2) (N=328) will be recruited from the communities in central Massachusetts. These overweight or obese adults will be randomized to two conditions: a lifestyle intervention delivered entirely via the online social network Twitter (Get Social condition) and an in-person group-based lifestyle intervention (Traditional condition) among overweight and obese adults. Measures will be obtained at baseline, 6 months, and 12 months after randomization. The primary noninferiority outcome is percentage weight loss at 12 months. Secondary noninferiority outcomes include dietary intake and moderate intensity physical activity at 12 months. Our secondary aim is to compare the conditions on cost. Exploratory outcomes include treatment retention, acceptability, and burden. Finally, we will explore predictors of weight loss in the online social network condition. RESULTS: The final wave of data collection is expected to conclude in June 2019. Data analysis will take place in the months following and is expected to be complete in September 2019. CONCLUSIONS: Findings will extend the literature by revealing whether delivering a lifestyle intervention via an online social network is an effective alternative to the traditional modality of clinic visits, given the former might be more scalable and feasible to implement in settings that cannot support clinic-based models. TRIAL REGISTRATION: ClinicalTrials.gov NCT02646618; https://clinicaltrials.gov/ct2/show/NCT02646618

Methods for Evaluating the Content, Usability, and Efficacy of Commercial Mobile Health Apps

Commercial mobile apps for health behavior change are flourishing in the marketplace, but little evidence exists to support their use. This paper summarizes methods for evaluating the content, usability, and efficacy of commercially available health apps. Content analyses can be used to compare app features with clinical guidelines, evidence-based protocols, and behavior change techniques. Usability testing can establish how well an app functions and serves its intended purpose for a target population. Observational studies can explore the association between use and clinical and behavioral outcomes. Finally, efficacy testing can establish whether a commercial app impacts an outcome of interest via a variety of study designs, including randomized trials, multiphase optimization studies, and N-of-1 studies. Evidence in all these forms would increase adoption of commercial apps in clinical practice, inform the development of the next generation of apps, and ultimately increase the impact of commercial apps. Boudreaux, Rajani S Sadasivam, Sean P Mullen, Jennifer L Carey, Rashelle B Hayes, Eric Y Ding, Gary G Bennett, Sherry L Pagoto. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 18.12.2017

LiveWell RERC State of the Science Conference Report on ICT Access to Support Community Living, Health and Function for People with Disabilities

This article summarizes the proceedings of the three session State of the Science (SOS) Conference that was conducted by the Rehabilitation Engineering Research Center for Community Living, Health and Function (LiveWell RERC) in June 2019 in Toronto, Canada. RERCs customarily convene an SOS conference toward the end of their five-year funding cycle in order to assess the current state and identify potential future research, development, and knowledge translation efforts needed to advance their field. The first two sessions focused on the current and future state of information and communication technology (ICT) for mobile health (mHealth) and mobile rehabilitation (mRehab). The third session was a wide-ranging discussion of pressing needs for future research and development in the field. Several “big ideas” resulted from the discussion among participants in the SOS Conference that should inform the structure and operation of future efforts, including: (1) identifying active ingredients of interventions, (2) incorporating effective behavior-change techniques into all interventions, (3) including measures of social determinants of health in evaluation studies, (4) incorporating user-customizable features into technology solutions, and (5) ensuring “discoverability” of research and development outputs by stakeholders via structured and continuous outreach, education and training. Substantive areas of work include gaming and esports, the gamification of interventions for health and fitness, the cultivation of community supports, and continuous outreach and education wherever a person with a disability may live

Use of Fitbit Devices in Physical Activity Intervention Studies Across the Life Course: Narrative Review

BACKGROUND: Commercial off-the-shelf activity trackers (eg, Fitbit) allow users to self-monitor their daily physical activity (PA), including the number of steps, type of PA, amount of sleep, and other features. Fitbits have been used as both measurement and intervention tools. However, it is not clear how they are being incorporated into PA intervention studies, and their use in specific age groups across the life course is not well understood. OBJECTIVE: This narrative review aims to characterize how PA intervention studies across the life course use Fitbit devices by synthesizing and summarizing information on device selection, intended use (intervention vs measurement tool), participant wear instructions, rates of adherence to device wear, strategies used to boost adherence, and the complementary use of other PA measures. This review provides intervention scientists with a synthesis of information that may inform future trials involving Fitbit devices. METHODS: We conducted a search of the Fitabase Fitbit Research Library, a database of studies published between 2012 and 2018. Of the 682 studies available on the Fitabase research library, 60 interventions met the eligibility criteria and were included in this review. A supplemental search in PubMed resulted in the inclusion of 15 additional articles published between 2019 and 2020. A total of 75 articles were reviewed, which represented interventions conducted in childhood; adolescence; and early, middle, and older adulthood. RESULTS: There was considerable heterogeneity in the use of Fitbit within and between developmental stages. Interventions for adults typically required longer wear periods, whereas studies on children and adolescents tended to have more limited device wear periods. Most studies used developmentally appropriate behavior change techniques and device wear instructions. Regardless of the developmental stage and intended Fitbit use (ie, measurement vs intervention tool), the most common strategies used to enhance wear time included sending participants reminders through texts or emails and asking participants to log their steps or synchronize their Fitbit data daily. The rates of adherence to the wear time criteria were reported using varying metrics. Most studies supplemented the use of Fitbit with additional objective or self-reported measures for PA. CONCLUSIONS: Overall, the heterogeneity in Fitbit use across PA intervention studies reflects its relative novelty in the field of research. As the use of monitoring devices continues to expand in PA research, the lack of uniformity in study protocols and metrics of reported measures represents a major issue for comparability purposes. There is a need for increased transparency in the prospective registration of PA intervention studies. Researchers need to provide a clear rationale for the use of several PA measures and specify the source of their main PA outcome and how additional measures will be used in the context of Fitbit-based interventions

A developmental cascade perspective of paediatric obesity: a conceptual model and scoping review

Considering the immense challenge of preventing obesity, the time has come to reconceptualise the way we study the obesity development in childhood. The developmental cascade model offers a longitudinal framework to elucidate the way cumulative consequences and spreading effects of risk and protective factors, across and within biopsychosocial spheres and phases of development, can propel individuals towards obesity. In this article, we use a theory-driven model-building approach and a scoping review that included 310 published studies to propose a developmental cascade model of paediatric obesity. The proposed model provides a basis for testing hypothesised cascades with multiple intervening variables and complex longitudinal processes. Moreover, the model informs future research by resolving seemingly contradictory findings on pathways to obesity previously thought to be distinct (low self-esteem, consuming sugary foods, and poor sleep cause obesity) that are actually processes working together over time (low self-esteem causes consumption of sugary foods which disrupts sleep quality and contributes to obesity). The findings of such inquiries can aid in identifying the timing and specific targets of preventive interventions across and within developmental phases. The implications of such a cascade model of paediatric obesity for health psychology and developmental and prevention sciences are discussed

Harnessing technology and gamification to increase adult physical activity: a cluster randomized controlled trial of the Columbia Moves pilot

Abstract Background The use of health technologies and gamification to promote physical activity has increasingly been examined, representing an opportunistic method for harnessing social support inherent within existing social ties. However, these prior studies have yielded mixed findings and lacked long-term follow-up periods. Thus, a pilot cluster randomized controlled trial was conducted to gauge the feasibility and preliminary efficacy of a digital gamification-based physical activity promotion approach among teams of insufficiently active adults with existing social ties. Methods Teams (N = 24; 116 total participants) were randomized to either a 12-week intervention (Fitbit, step goals, app, feedback; TECH) or the same program plus gamification (TECH + Gamification). Mixed effects models were used to compare group differences in treatment adherence, and changes in social support, steps, and moderate-to-vigorous physical activity at 12 weeks and 52 weeks from baseline, adjusted for sociodemographic characteristics and team size. Results TECH had a lower mean number of days of Fitbit self-monitoring versus TECH + Gamification during the intervention (adjusted difference: -.30; 95% CI, -.54 to -.07; P = .01). Post-intervention, TECH had 47% lower odds of self-monitoring 7 days per week versus TECH + Gamification (.53; 95% CI, .31 to .89; P = .02). No differences were observed between TECH + Gamification and TECH in increases in social support (0.04; 95% CI, -.21 to .29; P = .76), ActiGraph-measured daily steps (-425; 95% CI, -1065 to 215; P = .19), or moderate-to-vigorous physical activity minutes (-3.36; 95% CI, -8.62 to 1.91; P = .21) from baseline to 12 weeks or in the regression of these improvements by 1 year (Ps > .05). Although not significant in the adjusted models (Ps > .05), clinically meaningful differences in Fitbit-measured daily steps (TECH, 7041 ± 2520; TECH + Gamification, 7988 ± 2707) and active minutes (TECH, 29.90 ± 29.76; TECH + Gamification, 36.38 ± 29.83) were found during the intervention. Conclusions A gamified physical activity intervention targeting teams of adults with existing social ties was feasible and facilitated favorable, clinically meaningful additive physical activity effects while in place but did not drive enhanced, long-term physical activity participation. Future investigations should explore optimal team dynamics and more direct ways of leveraging social support (training teams; gamifying social support). Trial registration Clinicaltrials.gov ( NCT03509129 , April 26, 2018)