Factors influencing the use of an artificial intelligence-based app (selfBACK) for tailored self-management support among adults with neck and/or low back pain

PURPOSE

Tailored self-management support is recommended as first-line treatment for neck and low back pain, for which mHealth applications could be promising. However, there is limited knowledge about factors influencing the engagement with such apps. The aim of this study was to assess barriers and facilitators for engaging with a self-management mHealth app among adults suffering from neck and/or low back pain.

MATERIALS AND METHODS

We carried out a qualitative descriptive study among adults with neck and/or low back pain. The artificial intelligence-based selfBACK app supports tailored self-management of neck and low back pain and was used for 6 weeks. After these 6 weeks, participants were interviewed by phone.

RESULTS

Thirty-two adults (17 males) with neck and/or low back pain participated (mean age = 54.9 (SD = 15.8)). Our results show that the mode of delivery and the novelty of the selfBACK app were perceived most often as a barrier to use the app. The action plans of the app and health-related factors were perceived most often as facilitating factors.

CONCLUSIONS

This study provides insight into possible strategies to improve an mHealth service. Furthermore, it shows that adults with neck and/or low back pain are willing and ready to receive blended treatment.

MyTrack+: Human-centered design of an mHealth app to support long-term weight loss maintenance

A growing body of research has focused on the utility of adaptive intervention models for promoting long-term weight loss maintenance; however, evaluation of these interventions often requires customized smartphone applications. Building such an app from scratch can be resource-intensive. To support a novel clinical trial of an adaptive intervention for weight loss maintenance, we developed a companion app, MyTrack+, to pair with a main commercial app, FatSecret (FS), leveraging a user-centered design process for rapid prototyping and reducing software engineering efforts. MyTrack+ seamlessly integrates data from FS and the BodyTrace smart scale, enabling participants to log and self-monitor their health data, while also incorporating customized questionnaires and timestamps to enhance data collection for the trial. We iteratively refined the app by first developing initial mockups and incorporating feedback from a usability study with 17 university students. We further improved the app based on an in-the-wild pilot study with 33 participants in the target population, emphasizing acceptance, simplicity, customization options, and dual app usage. Our work highlights the potential of using an iterative human-centered design process to build a companion app that complements a commercial app for rapid prototyping, reducing costs, and enabling efficient research progress.

Mining User Reviews From Hypertension Management Mobile Health Apps to Explore Factors Influencing User Satisfaction and Their Asymmetry: Comparative Study

BACKGROUND

Hypertension significantly impacts the well-being and health of individuals globally. Hypertension management apps (HMAs) have been shown to assist patients in controlling blood pressure (BP), with their efficacy validated in clinical trials. However, the utilization of HMAs continues to be suboptimal. Presently, there is a dearth of real-world research based on big data and exploratory mining that compares Chinese and American HMAs.

OBJECTIVE

This study aims to systematically gather HMAs and their user reviews from both China and the United States. Subsequently, using data mining techniques, the study aims to compare the user experience, satisfaction levels, influencing factors, and asymmetry between Chinese and American users of HMAs. In addition, the study seeks to assess the disparities in satisfaction and its determinants while delving into the asymmetry of these factors.

METHODS

The study sourced HMAs and user reviews from 10 prominent Chinese and American app stores globally. Using the latent Dirichlet allocation (LDA) topic model, the research identified various topics within user reviews. Subsequently, the Tobit model was used to investigate the impact and distinctions of each topic on user satisfaction. The Wald test was applied to analyze differences in effects across various factors.

RESULTS

We examined a total of 261 HMAs along with their associated user reviews, amounting to 116,686 reviews in total. In terms of quantity and overall satisfaction levels, Chinese HMAs (n=91) and corresponding reviews (n=16,561) were notably fewer compared with their American counterparts (n=220 HMAs and n=100,125 reviews). The overall satisfaction rate among HMA users was 75.22% (87,773/116,686), with Chinese HMAs demonstrating a higher satisfaction rate (13,866/16,561, 83.73%) compared with that for American HMAs (73,907/100,125, 73.81%). Chinese users primarily focus on reliability (2165/16,561, 13.07%) and measurement accuracy (2091/16,561, 12.63%) when considering HMAs, whereas American users prioritize BP tracking (17,285/100,125, 17.26%) and data synchronization (12,837/100,125, 12.82%). Seven factors (easy to use: P<.001; measurement accuracy: P<.001; compatibility: P<.001; cost: P<.001; heart rate detection function: P=.02; blood pressure tracking function: P<.001; and interface design: P=.01) significantly influenced the positive deviation (PD) of Chinese HMA user satisfaction, while 8 factors (easy to use: P<.001; reliability: P<.001; measurement accuracy: P<.001; compatibility: P<.001; cost: P<.001; interface design: P<.001; real-time: P<.001; and data privacy: P=.001) affected the negative deviation (ND). Notably, BP tracking had the greatest effect on PD (β=.354, P<.001), while cost had the most significant impact on ND (β=3.703, P<.001). All 12 factors (easy to use: P<.001; blood pressure tracking function: P<.001; data synchronization: P<.001; blood pressure management effect: P<.001; heart rate detection function: P<.001; data sharing: P<.001; reliability: P<.001; compatibility: P<.001; interface design: P<.001; advertisement distribution: P<.001; measurement accuracy: P<.001; and cost: P<.001) significantly influenced the PD and ND of American HMA user satisfaction. Notably, BP tracking had the greatest effect on PD (β=0.312, P<.001), while data synchronization had the most significant impact on ND (β=2.662, P<.001). In addition, the influencing factors of PD and ND in user satisfaction of HMA in China and the United States are different.

CONCLUSIONS

User satisfaction factors varied significantly between different countries, showing considerable asymmetry. For Chinese HMA users, ease of use and interface design emerged as motivational factors, while factors such as cost, measurement accuracy, and compatibility primarily contributed to user dissatisfaction. For American HMA users, motivational factors were ease of use, BP tracking, BP management effect, interface design, measurement accuracy, and cost. Moreover, users expect features such as data sharing, synchronization, software reliability, compatibility, heart rate detection, and nonintrusive advertisement distribution. Tailored experience plans should be devised for different user groups in various countries to address these diverse preferences and requirements.

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.

Exploring the benefits and costs of a growth mindset in a digital app weight management program

We explored the potential benefits and costs of believing one can change their weight (i.e. growth mindset) in the context of a digital weight management program. We investigated mechanisms by which growth mindsets relate to weight loss achievement and body shame. Among participants seeking to lose weight (N = 1626; 74.7% female; 77.9% White; Mage = 45.7), stronger growth mindsets indirectly predicted greater weight loss achievement through positive offset expectations and subsequent increased program engagement. Additionally, stronger growth mindsets predicted less body shame through positive offset expectations but predicted more body shame through increased onset responsibility, replicating the double-edged sword model of growth mindsets. We conclude with applications that leverage growth mindsets for optimal behavior change while mitigating costs such as body shame.

Exploring the role of decision support systems in promoting healthier and more sustainable online food shopping: A card sorting study

This study aims to identify opportunities and barriers in developing and implementing Food Shopping Support Systems (FSSS) for healthier and more sustainable choices, given the growing consumer demand and persistent societal problems related to food. The study examined the social and technical value of FSSS in an early development stage through one-on-one expert interviews (n = 20) and consumer focus groups (4 groups, n = 19). Experts were employed in the fields of behavioral sciences, digital marketing, decision aids, software development, persuasive technologies, and public health and sustainability. Consumer participants were used to shopping online. Through a card sorting task followed by semi-structured interview questions, responses were elicited. Participants were presented with 17 cards in 5 rounds, each addressing a different topic related to decision support. Results show that support is perceived useful, particularly when suggestions are personalized, transparent, and justified (using labelling or informative text). Opportunities for uptake were presenting suggestions early in the shopping trip in a visible but non-disruptive manner, allowing autonomy to choose the type of guidance (e.g., show sustainable but not healthier suggestions) and to (not) provide personal data, and educating consumers. Negative attitudes were associated with support being disruptive or steering, being of low credibility, and unclarity about what is healthy or sustainable. Consumer participants expressed concerns about too generic suggestions in relation to health and lack of knowledge about labelling. They emphasized that excessive support and required effort, such as repeatedly providing data, can be burdensome. Experts also worried about limited consumer interest and not having the required data to provide support. Results from this study reveal the potential for successful digital interventions to encourage healthier and more sustainable choices and what this means for further development.

Improving Predictability and Effectiveness in Preventive Digital Health Interventions: Scoping Review

BACKGROUND

Lifestyle-related diseases caused by inadequate diet and physical activity cause premature death, loss of healthy life years, and increased health care costs. Randomized controlled trial (RCT) studies indicate that preventive digital health interventions (P-DHIs) can be effective in preventing these health problems, but the results of these studies are mixed. Adoption studies have identified multiple factors related to individuals and the context in which they live that complicate the transfer of positive results from RCT studies to practical use. Implementation studies have revealed barriers to the large-scale implementation of mobile health (mHealth) solutions in general. Consequently, there is no clear path to delivering predictable outcomes from P-DHIs and achieving effectiveness when scaling up interventions to reduce health problems in society.

OBJECTIVE

This research aimed to expand our understanding of how to increase the outcome predictability of P-DHIs by focusing on physical activity and diet behaviors and amplify our understanding of how to improve effectiveness in large-scale implementations.

METHODS

The research objective was pursued through a multidisciplinary scoping review. This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) as a guide. A comprehensive search of Web of Science and PubMed limited to English-language journal articles published before January 2022 was conducted. Google Scholar was used for hand searches. Information systems theory was used to identify key constructs influencing outcomes of IT in general. Public health and mHealth literature were used to identify factors influencing the adoption of, outcomes from, and implementation of P-DHIs. Finally, the P-DHI investment model was developed based on information systems constructs and factors from the public health and mHealth literature.

RESULTS

In total, 203 articles met the eligibility criteria. The included studies used a variety of methodologies, including literature reviews, interviews, surveys, and RCT studies. The P-DHI investment model suggests which constructs and related factors should be emphasized to increase the predictability of P-DHI outcomes and improve the effectiveness of large-scale implementations.

CONCLUSIONS

The research suggests that outcome predictability could be improved by including descriptions of the constructs and factors in the P-DHI investment model when reporting from empirical studies. Doing so would increase our understanding of when and why P-DHIs succeed or fail. The effectiveness of large-scale implementations may be improved by using the P-DHI investment model to evaluate potential difficulties and possibilities in implementing P-DHIs to create better environments for their use before investing in them and when designing and implementing them. The cost-effectiveness of large-scale implementations is unknown; implementations are far more complicated than just downloading and using apps, and there is uncertainty accompanying implementations given the lack of coordinated control over the constructs and factors that influence the outcome.

The Efficacy of Mobile Applications for Weight Loss

Purpose of Review

A variety of mobile-based applications aimed at weight loss have become popular in recent years. This review describes the features and effectiveness of mobile weight loss apps.

Recent Findings

Overall, mobile apps can help patients lose weight either as well as or better than traditional paper-and-pencil weight loss interventions and often better than minimal intervention control groups. Mobile apps promote multiple strategies, including self-monitoring of diet, exercise, and weight, as well as social support and educational content. Significant variation exists in app types, which makes it difficult to conclude which features drive program effectiveness. Intervention success varies based on patients’ level of engagement with the app. There is a deficit of apps and app-based studies of older, less tech-savvy adults, ethnic/racial minorities, and low-income individuals, as well as longer-term studies.

Summary

Mobile apps can successfully help patients lose weight and represent a cost-effective, accessible alternative to intensive in-person weight loss programs. More research is needed into their long-term potential, especially for hard-to-reach populations.

Is the uptake, engagement, and effectiveness of exclusively mobile interventions for the promotion of weight-related behaviors equal for all? A systematic review

Mobile health interventions are promising behavior change tools. However, there is a concern that they may benefit some populations less than others and thus widen inequalities in health. This systematic review investigated differences in uptake of, engagement with, and effectiveness of mobile interventions for weight-related behaviors (i.e., diet, physical activity, and sedentary behavior) based on a range of inequality indicators including age, gender, race/ethnicity, and socioeconomic status. The protocol was registered on PROSPERO (CRD42020192473). Six databases (CINAHL, EMBASE, ProQuest, PsycINFO, Pubmed, and Web of Science) were searched from inception to July 2021. Publications were eligible for inclusion if they reported the results of an exclusively mobile intervention and examined outcomes by at least one inequality indicator. Sixteen publications reporting on 13 studies were included with most reporting on multiple behaviors and inequality indicators. Uptake was investigated in one study with no differences reported by the inequality indicators studied. Studies investigating engagement (n = 7) reported differences by age (n = 1), gender (n = 3), ethnicity (n = 2), and education (n = 2), while those investigating effectiveness (n = 9) reported differences by age (n = 3), gender (n = 5), education (n = 2), occupation (n = 1), and geographical location (n = 1). Given the limited number of studies and their inconsistent findings, evidence of the presence of a digital divide in mobile interventions targeting weight-related behaviors is inconclusive. Therefore, we recommend that inequality indicators are specifically addressed, analyzed, and reported when evaluating mobile interventions.

Smartphone-supported behavioural weight loss treatment in adults with severe obesity: study protocol for an exploratory randomised controlled trial (SmartBWL)

INTRODUCTION

Behavioural weight loss (BWL) treatment is the standard evidence-based treatment for severe obesity (SO; body mass index ≥40.0 kg/m² or ≥35.0 kg/m² with obesity-related comorbidity), leading to moderate weight loss which often cannot be maintained in the long term. Because weight loss depends on patients' use of weight management skills, it is important to support them in daily life. In an ecological momentary intervention design, this clinical trial aims to adapt, refine and evaluate a personalised cognitive-behavioural smartphone application (app) in BWL treatment to foster patients' weight management skills use in everyday life. It is hypothesised that using the app is feasible and acceptable, improves weight loss and increases skills use and well-being.

METHODS AND ANALYSIS

In the pilot phase, the app will be adapted, piloted and optimised for BWL treatment following a participatory patient-oriented approach. In the subsequent single-centre, assessor-blind, exploratory randomised controlled trial, 90 adults with SO will be randomised to BWL treatment over 6 months with versus without adjunctive app. Primary outcome is the amount of weight loss (kg) at post-treatment (6 months), compared with pretreatment, derived from measured body weight. Secondary outcomes encompass feasibility, acceptance, weight management skills use, well-being and anthropometrics assessed at pretreatment, midtreatment (3 months), post-treatment (6 months) and 6-month follow-up (12 months). An intent-to-treat linear model with randomisation arm, pretreatment weight and stratification variables as covariates will serve to compare arms regarding weight at post-treatment. Secondary analyses will include linear mixed models, generalised linear models and regression and mediation analyses. For safety analysis (serious) adverse events will be analysed descriptively.

ETHICS AND DISSEMINATION

The study was approved by the Ethics Committee of the University of Leipzig (DE-21-00013674) and notified to the Federal Institute for Drugs and Medical Devices. Study results will be disseminated through peer-reviewed publications.

REGISTRATION

This study was registered at the German Clinical Trials Register (DRKS00026018), www.drks.de.

TRIAL REGISTRATION NUMBER

DRKS00026018.

Evaluating a Digital Mental Health Intervention (Wysa) for Workers' Compensation Claimants: Pilot Feasibility Study

OBJECTIVE

This study examines the feasibility and acceptability of an AI-led digital mental health intervention in a Workers' Compensation (WC) program, Wysa for Return to Work.

METHODS

Self-reported demographic data and responses to psychosocial screening questions were analyzed alongside participants' app usage through which four key outcomes were measured: recruitment rate, onboarding rate, retention, and engagement.

RESULTS

The data demonstrated a high need for psychosocial interventions among injured workers, especially women, young adults, and those with high severity injuries. Those with more psychosocial risk factors had a higher rate of onboarding, retention, and engagement, and those with severe injuries had higher retention.

CONCLUSIONS

Our study concluded that Wysa for Return to Work, the AI-led digital mental health intervention that delivers a recovery program using a digital conversational agent, is feasible and acceptable for a return-to-work population.

Essential elements of weight loss apps for a multi-ethnic population with high BMI: a qualitative study with practical recommendations

Smartphone weight loss apps are constantly being developed but the essential elements needed by a multi-ethnic population with overweight and obesity remains unclear. Purpose: To explore the perceptions of an Asian multi-ethnic population with overweight and obesity on the essential elements of weight loss apps. Twenty two participants were purposively sampled from a specialist weight management clinic in Singapore from 13 April to 30 April 2021. Recorded interviews were conducted using face-to-face and videoconferencing modalities. Data saturation was reached at the 18th participant. Data analysis was performed using inductive content analysis with constant comparison between and within transcripts. Findings: Three themes and eight subthemes on the essential app components emerged-(a) comprehensive and flexible calorie counters; (b) holistic, gradual and individualized behavior change recommendations tailored for people with overweight and obesity, and (c) just-in-time reminders of future consequences. There was a need to incorporate flexible options for food logging; break down general recommendations into small steps towards sustainable changes; tailor app contents for people with overweight and obesity; and evoke one's considerations of future consequences. Future weight loss apps should be designed to meet the needs of those with overweight and obesity, the very population that needs assistance with weight loss. Future apps could consider leveraging the capacity of artificial intelligence to provide personalized weight management in terms of sustaining self-regulation behaviors, optimizing goal-setting and providing personalized and timely recommendations for weight loss.

DECENT: A sociotechnical approach for developing mobile health apps in underserved settings

Objective

Despite the fact that user engagement is critical to the efficacy of mobile health (mHealth) interventions in the Global South, many of these interventions lack user engagement features. This is because sociotechnical aspects of such initiatives are frequently ignored during the design, development, and implementation stages. This research highlighted the importance of considering sociotechnical factors when developing mHealth apps. The intended users for the mHealth technologies in this study are care professionals.

Materials and Methods

Five semi-structured interviews and a pilot interview were conducted to identify user engagement facilitators and barriers. The interview data were analysed using NVivo. The Capability, Opportunity, Motivation - Behaviour (COM-B) model is then used to map the facilitators and barriers to mHealth app engagement, allowing researchers to better understand how users engage/disengage with mHealth apps.

Results and Discussion

Capability facilitators included features that assist users in learning more about the app (e.g. a user manual and statistical data) as well as features that assist users in developing a routine. The lack of app skills and cognitive overload limit capability. While social connectedness and offline functionality were identified as facilitators of user engagement, non-user-friendly design and cultural dimensions were identified as barriers. Early user engagement and rewards were identified as motivational facilitators that influence user engagement. Furthermore, perceived non-utility and a lack of encouragement were identified as motivational barriers to engagement.

Conclusion

Several factors were discovered across all COM-B model components that could be used to develop more engaging mHealth apps. Adopting a techno-centric approach that ignores sociotechnical factors can reduce user engagement. The design process engagement enhancement system (DECENT) framework was proposed based on the findings.

Long-term weight loss in a 24-month primary care-anchored telehealth lifestyle coaching program: Randomized controlled trial

Long-term weight loss can reduce the risk of type 2 diabetes for people living with obesity and reduce complications for patients diagnosed with type 2 diabetes. We investigated whether a telehealth lifestyle-coaching program (Liva) leads to long-term (24 months) weight loss compared to usual care. In a randomized controlled trial, n = 340 participants living with obesity with or without type 2 diabetes were enrolled and randomized via an automated computer algorithm to an intervention group ( n = 200) or to a control group ( n = 140). The telehealth lifestyle-coaching program comprised of an initial one-hour face-to-face motivational interview followed by asynchronous telehealth coaching. The behavioural change techniques used were enabled by individual live monitoring. The primary outcome was a change in body weight from baseline to 24 months. Data were assessed for n = 136 participants (40%), n = 81 from the intervention group and n = 55 from the control group, who completed the 24-month follow-up. After 24 months mean body weight and body mass index were reduced significantly for completers in both groups, but almost twice as much was registered for those in the intervention group which was not significant between groups −4.4 (CI −6.1; −2.8) kg versus −2.5 (CI −3.9; −1.1) kg, P = 0.101. Haemoglobin A1c was significantly reduced in the intervention group −3.1 (CI −5.0; −1.2) mmol/mol, but not in the control group −0.2 (CI −2.4; −2.0) mmol/mol without a significant between group difference ( P = 0.223). Low completion was partly due to coronavirus disease 2019. Telehealth lifestyle coaching improve long-term weight loss (> 24 months) for obese people with and without type 2 diabetes compared to usual care.

Adherence and Engagement with a Cognitive Behavioral Therapy Based Conversational Agent (Wysa) in Adults with Chronic Pain: Survival Analysis

BACKGROUND

Digital applications are commonly used to support mental health and well-being. However, successfully retaining and engaging users to complete digital interventions is challenging, and comorbidities such as chronic pain further reduce user engagement. Digital conversational agents may improve user engagement by applying engagement principles that have been implemented within in-person care settings.

OBJECTIVE

To evaluate user retention and engagement with an artificial intelligence (AI)-led digital mental health application (app) that is customized for individuals managing mental health symptoms and coexisting chronic pain (Wysa for Chronic Pain).

METHODS

In this ancillary survival analysis of a clinical trial, participants included 51 adults who presented to a tertiary care center for chronic musculoskeletal pain, who endorsed coexisting symptoms of depression and/or anxiety (PROMIS Depression and/or Anxiety score ≥ 55), and initiated onboarding to an 8-week subscription of Wysa for Chronic Pain. The study outcomes were user retention, defined as revisiting the app each week and the last day of engagement, and user engagement, defined by the number of sessions the user completed.

RESULTS

Users engaged in a cumulative mean of 33.3 sessions during the eight-week study period. The survival analysis depicted a median user retention period (i.e., time to complete disengagement) of 51 days, with the usage of a morning check-in feature statistically significant in its relationship with a longer retention period (p = .001).

CONCLUSIONS

Our findings suggest that the user retention and engagement with a CBT-based conversational agent which is built for users with chronic pain is higher than standard industry metrics. These results have clear implications for addressing issues of suboptimal engagement of digital health interventions and improving access to care for chronic pain. Future work should use these findings to inform the design of evidence-based interventions for individuals with chronic pain and to enhance user retention and engagement of digital health interventions more broadly.

CLINICALTRIAL

NCT04640090, Clinicaltrials.gov.

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.

Weight Loss Trajectories in Healthy Weight Coaching: Cohort Study

Background

As global obesity prevalence continues to increase, there is a need for accessible and affordable weight management interventions, such as web-based programs.

Objective

This paper aims to assess the outcomes of healthy weight coaching (HWC), a web-based obesity management program integrated into standard Finnish clinical care.

Methods

HWC is an ongoing, structured digital 12-month program based on acceptance and commitment therapy. It includes weekly training sessions focused on lifestyle, general health, and psychological factors. Participants received remote one-on-one support from a personal coach. In this real-life, single-arm, prospective cohort study, we examined the total weight loss, weight loss profiles, and variables associated with weight loss success and program retention in 1189 adults (963 women) with a BMI >25 kg/m² among participants of the program between October 2016 and March 2019. Absolute (kg) and relative (%) weight loss from the baseline were the primary outcomes. We also examined the weight loss profiles, clustered based on the dynamic time-warping distance, and the possible variables associated with greater weight loss success and program retention. We compared different groups using the Mann-Whitney test or Kruskal-Wallis test for continuous variables and the chi-squared test for categorical variables. We analyzed changes in medication using the McNemar test.

Results

Among those having reached the 12-month time point (n=173), the mean weight loss was 4.6% (SE 0.5%), with 43% (n=75) achieving clinically relevant weight loss (≥5%). Baseline BMI ≥40 kg/m² was associated with a greater weight loss than a lower BMI (mean 6.6%, SE 0.9%, vs mean 3.2%, SE 0.6%; P=.02). In addition, more frequent weight reporting was associated with greater weight loss. No significant differences in weight loss were observed according to sex, age, baseline disease, or medication use. The total dropout rate was 29.1%. Dropouts were slightly younger than continuers (47.2, SE 0.6 years vs 49.2, SE 0.4 years; P=.01) and reported their weight less frequently (3.0, SE 0.1 entries per month vs 3.3, SE 0.1 entries per month; P<.001).

Conclusions

A comprehensive web-based program such as HWC is a potential addition to the repertoire of obesity management in a clinical setting. Heavier patients lost more weight, but weight loss success was otherwise independent of baseline characteristics.

The development of a core outcomes set for self-management interventions for patients living with obesity

Self-management interventions (SMIs) can improve the life of patients living with obesity. However, there is variability in the outcomes used to assess the effectiveness of SMIs and these are often not relevant for patients. In the context of COMPAR-EU, our aim was to develop a core outcome set (COS) for the evaluation of SMIs for patients with obesity. We followed a four steps multimethod approach: (1) the development of the initial catalogue of outcomes; (2) a scoping review of reviews on patients' values and preferences on outcomes of self-management (SM); (3) a Delphi survey including patients and patient representatives to rate the importance of outcomes; and (4) a 2-day consensus workshop with patients, patient representatives, healthcare professionals and researchers. The initial catalogue included 82 outcomes. Ten patients and patient's representatives participated in the Delphi survey. We identified 16 themes through the thematic synthesis of the scoping review that informed 37.80% of the outcomes on initial catalogue. Five patients, five healthcare professionals, and four researchers participated in the consensus workshop. After the consensus process, 15 outcomes were selected to be part of the final COS, and five supplementary outcomes were also provided. We developed a COS for the evaluation of SMIs in obesity with a significant involvement of patients and other key stakeholders. This COS will help improving data synthesis and increasing the value of SM research data in healthcare decision making.

Perceptions of Factors Influencing Engagement With Health and Well-being Apps in the United Kingdom: Qualitative Interview Study

BACKGROUND

Digital health devices, such as health and well-being smartphone apps, could offer an accessible and cost-effective way to deliver health and well-being interventions. A key component of the effectiveness of health and well-being apps is user engagement. However, engagement with health and well-being apps is typically poor. Previous studies have identified a list of factors that could influence engagement; however, most of these studies were conducted on a particular population or for an app targeting a particular behavior. An understanding of the factors that influence engagement with a wide range of health and well-being apps can inform the design and the development of more engaging apps in general.

OBJECTIVE

The aim of this study is to explore user experiences of and reasons for engaging and not engaging with a wide range of health and well-being apps.

METHODS

A sample of adults in the United Kingdom (N=17) interested in using a health or well-being app participated in a semistructured interview to explore experiences of engaging and not engaging with these apps. Participants were recruited via social media platforms. Data were analyzed with the framework approach, informed by the Capability, Opportunity, Motivation-Behaviour (COM-B) model and the Theoretical Domains Framework, which are 2 widely used frameworks that incorporate a comprehensive set of behavioral influences.

RESULTS

Factors that influence the capability of participants included available user guidance, statistical and health information, reduced cognitive load, well-designed reminders, self-monitoring features, features that help establish a routine, features that offer a safety net, and stepping-stone app characteristics. Tailoring, peer support, and embedded professional support were identified as important factors that enhance user opportunities for engagement with health and well-being apps. Feedback, rewards, encouragement, goal setting, action planning, self-confidence, and commitment were judged to be the motivation factors that affect engagement with health and well-being apps.

CONCLUSIONS

Multiple factors were identified across all components of the COM-B model that may be valuable for the development of more engaging health and well-being apps. Engagement appears to be influenced primarily by features that provide user guidance, promote minimal cognitive load, support self-monitoring (capability), provide embedded social support (opportunity), and provide goal setting with action planning (motivation). This research provides recommendations for policy makers, industry, health care providers, and app developers for increasing effective engagement.

The Perspectives of Patients with Chronic Diseases and Their Caregivers on Self-Management Interventions: A Scoping Review of Reviews

BACKGROUND

Self-management (SM) interventions are supportive interventions systematically provided by healthcare professionals, peers, or laypersons to increase the skills and confidence of patients in their ability to manage chronic diseases. We had two objectives: (1) to summarise the preferences and experiences of patients and their caregivers (informal caregivers and healthcare professionals) with SM in four chronic diseases and (2) to identify and describe the relevant outcomes for SM interventions from these perspectives.

METHODS

We conducted a mixed-methods scoping review of reviews. We searched three databases until December 2020 for quantitative, qualitative, or mixed-methods reviews exploring patients' and caregivers' preferences or experiences with SM in type 2 diabetes mellitus (T2DM), obesity, chronic obstructive pulmonary disease (COPD), and heart failure (HF). Quantitative data were narratively synthesised, and qualitative data followed a three-step descriptive thematic synthesis. Identified themes were categorised into outcomes or modifiable factors of SM interventions.

RESULTS

We included 148 reviews covering T2DM (n = 53 [35.8%]), obesity (n = 20 [13.5%]), COPD (n = 32 [21.6%]), HF (n = 38 [25.7%]), and those with more than one disease (n = 5 [3.4%]). We identified 12 main themes. Eight described the process of SM (disease progression, SM behaviours, social support, interaction with healthcare professionals, access to healthcare, costs for patients, culturally defined roles and perceptions, and health knowledge), and four described their experiences with SM interventions (the perceived benefit of the intervention, individualised care, sense of community with peers, and usability of equipment). Most themes and subthemes were categorised as outcomes of SM interventions.

CONCLUSION

The process of SM shaped the perspectives of patients and their caregivers on SM interventions. Their perspectives were influenced by the perceived benefit of the intervention, the sense of community with peers, the intervention's usability, and the level of individualised care. Our findings can inform the selection of patient-important outcomes, decision-making processes, including the formulation of recommendations, and the design and implementation of SM interventions.

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.

Rural Residents' Perspectives on an mHealth or Personalized Health Coaching Intervention: Qualitative Study With Focus Groups and Key Informant Interviews

Background

Compared with national averages, rural Appalachians experience extremely elevated rates of premature morbidity and mortality. New opportunities, including approaches incorporating personal technology, may help improve lifestyles and overcome health inequities.

Objective

This study aims to gather perspectives on whether a healthy lifestyle intervention, specifically an app originally designed for urban users, may be feasible and acceptable to rural residents. In addition to a smartphone app, this program—Make Better Choices 2—consists of personalized health coaching, accelerometer use, and financial incentives.

Methods

We convened 4 focus groups and 16 key informant interviews with diverse community stakeholders to assess perspectives on this novel, evidence-based diet and physical activity intervention. Participants were shown a slide presentation and asked open-ended follow-up questions. The focus group and key informant interview sessions were audiotaped, transcribed, and subjected to thematic analysis.

Results

We identified 3 main themes regarding Appalachian residents’ perspectives on this mobile health (mHealth) intervention: personal technology is feasible and desirable; challenges persist in implementing mHealth lifestyle interventions in Appalachian communities; and successful mHealth interventions should include personal connections, local coaches, and educational opportunities. Although viewed as feasible and acceptable overall, lack of healthy lifestyle awareness, habitual behavior, and financial constraints may challenge the success of mHealth lifestyle interventions in Appalachia. Finally, participants described several minor elements that require modification, including expanding the upper age inclusion, providing extra coaching on technology use, emphasizing personal and supportive connections, employing local coaches, and ensuring adequate educational content for the program.

Conclusions

Blending new technologies, health coaching, and other features is not only acceptable but may be essential to reach vulnerable rural residents.

The role of self-efficacy and information processing in weight loss during an mHealth behavioral intervention

Self-efficacy (SE) and information processing (IP) may be important constructs to target when designing mHealth interventions for weight loss. The goal of this study was to examine the relationship between SE and IP with weight loss at six-months as part of the Dietary Interventions Examining Tracking with mobile study, a six-month randomized trial with content delivered remotely via twice-weekly podcasts. Participants were randomized to self-monitor their diet with either a mobile app (n = 42) or wearable Bite Counter device (n = 39). SE was assessed using the Weight Efficacy Life-Style Questionnaire and the IP variables assessed included user control, cognitive load, novelty, elaboration. Regression analysis examined the relationship between weight loss, SE change & IP at six months. Results indicate that elaboration was the strongest predictor of weight loss (ß =−0.423, P = 0.011) among all SE & IP variables and that for every point increase in elaboration, participants lost 0.34 kg body weight.

A Mobile Social Networking App for Weight Management and Physical Activity Promotion: Results From an Experimental Mixed Methods Study

BACKGROUND

Smartphone apps, fitness trackers, and online social networks have shown promise in weight management and physical activity interventions. However, there are knowledge gaps in identifying the most effective and engaging interventions and intervention features preferred by their users.

OBJECTIVE

This 6-month pilot study on a social networking mobile app connected to wireless weight and activity tracking devices has 2 main aims: to evaluate changes in BMI, weight, and physical activity levels in users from different BMI categories and to assess user perspectives on the intervention, particularly on social comparison and automated self-monitoring and feedback features.

METHODS

This was a mixed methods study involving a one-arm, pre-post quasi-experimental pilot with postintervention interviews and focus groups. Healthy young adults used a social networking mobile app intervention integrated with wireless tracking devices (a weight scale and a physical activity tracker) for 6 months. Quantitative results were analyzed separately for 2 groups-underweight-normal and overweight-obese BMI-using t tests and Wilcoxon sum rank, Wilcoxon signed rank, and chi-square tests. Weekly BMI change in participants was explored using linear mixed effects analysis. Interviews and focus groups were analyzed inductively using thematic analysis.

RESULTS

In total, 55 participants were recruited (mean age of 23.6, SD 4.6 years; 28 women) and 45 returned for the final session (n=45, 82% retention rate). There were no differences in BMI from baseline to postintervention (6 months) and between the 2 BMI groups. However, at 4 weeks, participants' BMI decreased by 0.34 kg/m² (P<.001), with a loss of 0.86 kg/m² in the overweight-obese group (P=.01). Participants in the overweight-obese group used the app significantly less compared with individuals in the underweight-normal BMI group, as they mentioned negative feelings and demotivation from social comparison, particularly from upward comparison with fitter people. Participants in the underweight-normal BMI group were avid users of the app's self-monitoring and feedback (P=.02) and social (P=.04) features compared with those in the overweight-obese group, and they significantly increased their daily step count over the 6-month study duration by an average of 2292 steps (95% CI 898-3370; P<.001). Most participants mentioned a desire for a more personalized intervention.

CONCLUSIONS

This study shows the effects of different interventions on participants from higher and lower BMI groups and different perspectives regarding the intervention, particularly with respect to its social features. Participants in the overweight-obese group did not sustain a short-term decrease in their BMI and mentioned negative emotions from app use, while participants in the underweight-normal BMI group used the app more frequently and significantly increased their daily step count. These differences highlight the importance of intervention personalization. Future research should explore the role of personalized features to help overcome personal barriers and better match individual preferences and needs.

Important Factors Affecting User Experience Design and Satisfaction of a Mobile Health App-A Case Study of Daily Yoga App

In recent years, mobile health (mHealth) has gained popularity. Yoga apps help users to exercise at home and improve their health. It is worth discussing how to give yogis a better experience and higher satisfaction to improve their willingness to keep using yoga apps. In this study, the Daily Yoga app was selected as the research object to explore important factors related to its user experience design and user satisfaction. Through a literature review and Delphi method composed of eight experts, this study put forward the important criteria framework of user experience design for the Daily Yoga app and then, used the DEMATEL (Decision Making and Trial Evaluation Laboratory)-based ANP (Analytic Network Process) method to determine the factors’ importance order and the causal relationships among them. Finally, combined with the results of an importance–performance analysis of 16 real users, we discuss the improvement measures. The research results show that the yoga class is the most critical factor in the user experience design of the Daily Yoga app, the target plan is a factor that is in great need of improvement, and having an attractive interface can improve user experience. The evaluation model of the study can act as a reference for improving user experience with the Daily Yoga app, and can also be widely used in the process of user experience design, questionnaire production, and evaluation optimization of mHealth app and related applications.

Personalised eHealth interventions in adults with overweight and obesity: A systematic review and meta-analysis of randomised controlled trials

Given that many existing electronic health (eHealth) interventions with a general approach have limited effects, a personalised approach is necessary. We aimed to evaluate the effectiveness of personalised eHealth interventions in reducing body weight and identify the effective key features of such interventions. We searched seven databases for randomised controlled trials (RCTs) from inception until September 6, 2018. Of the 26,733 records identified, 15 RCTs were included. Meta-analysis revealed a significant reduction (-2.77 kg, 95% confidence interval - 3.54 to -2.00 kg) in the personalised eHealth intervention group compared with that in the control group (Z = -7.04, p < .001). The duration of the interventions ranged from 14 weeks and three trials had follow-up assessments at 6 and 12 months. Our subgroup analyses highlighted several crucial design elements of future personalised eHealth interventions by utilising a combination of tailored content and customised feedback with human feedback, usage of theoretical basis, short message service, device, reminder, self-monitoring, goal setting and synchronous communication for 12 to 14 weeks. Egger's regression asymmetry test suggested no evidence of publication bias (p = .458). Using meta-regression we found evidence that a statistically significant impact of age and year of publication on the effectiveness of intervention. The overall evidence grade of outcomes ranged from very low to low, hence future trials should use well-designed RCTs.

Effect of mHealth With Offline Antiobesity Treatment in a Community-Based Weight Management Program: Cross-Sectional Study

BACKGROUND

Weight loss interventions using mobile phone apps have recently shown promising results.

OBJECTIVE

This study aimed to analyze the short-term weight loss effect of a mobile coaching intervention when it is integrated with a local public health care center and a regional hospital's antiobesity clinic as a multidisciplinary model.

METHODS

A total of 150 overweight or obese adults signed up to complete an 8-week antiobesity intervention program with human coaching through a mobile platform. Paired t tests and multiple linear regression analysis were used to identify the intervention factors related to weight change.

RESULTS

Among the 150 participants enrolled in this study, 112 completed the 8-week weight loss intervention. Weight (baseline: mean 77.5 kg, SD 12.9; after intervention: mean 74.8 kg, SD 12.6; mean difference -2.73 kg), body mass index, waist circumference, fat mass (baseline: mean 28.3 kg, SD 6.6; after intervention: mean 25.7 kg, SD 6.3; mean difference -2.65 kg), and fat percentage all showed a statistically significant decrease, and metabolic equivalent of task (MET) showed a statistically significant increase after intervention. In multiple linear regression analysis, age (beta=.07; P=.06), △MET (beta=-.0009; P=.10), number of articles read (beta=-.01; P=.04), and frequency of weight records (beta=-.05; P=.10; R2=0.4843) were identified as significant factors of weight change. Moreover, age (beta=.06; P=.03), sex (female; beta=1.16; P=.08), △MET (beta=-.0009; P<.001), and number of articles read (beta=-.02; P<.001; R2=0.3728) were identified as significant variables of fat mass change.

CONCLUSIONS

The multidisciplinary approach, combining a mobile health (mHealth) care app by health care providers, was effective for short-term weight loss. Additional studies are needed to evaluate the efficacy of mHealth care apps in obesity treatment.

Mindful Eating Mobile Health Apps: Review and Appraisal

BACKGROUND

Mindful eating is an emerging area of research for managing unhealthy eating and weight-related behaviors such as binge eating and emotional eating. Although there are numerous commercial mindful eating apps available, their quality, effectiveness, and whether they are accurately based on mindfulness-based eating awareness are unknown.

OBJECTIVE

This review aimed to appraise the quality of the mindful eating apps and to appraise the quality of content on mindful eating apps.

METHODS

A review of mindful eating apps available on Apple iTunes was undertaken from March to April 2018. Relevant apps meeting the inclusion criteria were subjectively appraised for general app quality using the Mobile App Rating Scale (MARS) guidelines and for the quality of content on mindful eating. A total of 22 apps met the inclusion criteria and were appraised.

RESULTS

Many of the reviewed apps were assessed as functional and had moderate scores in aesthetics based on the criteria in the MARS assessment. However, some received lower scores in the domains of information and engagement. The majority of the apps did not teach users how to eat mindfully using all five senses. Hence, they were scored as incomplete in accurately providing mindfulness-based eating awareness. Instead, most apps were either eating timers, hunger rating apps, or diaries. Areas of potential improvement were in comprehensiveness and diversity of media, in the quantity and quality of information, and in the inclusion of privacy and security policies. To truly teach mindful eating, the apps need to provide guided examples involving the five senses beyond simply timing eating or writing in a diary. They also need to include eating meditations to assist people with their disordered eating such as binge eating, fullness, satiety, and craving meditations that may help them with coping when experiencing difficulties. They should also have engaging and entertaining features delivered through diverse media to ensure sustained use and interest by consumers.

CONCLUSIONS

Future mindful eating apps could be improved by accurate adherence to mindful eating. Further improvement could be achieved by ameliorating the domains of information, engagement, and aesthetics and having adequate privacy policies.

Perceptions and Acceptability of Text Messaging for Diabetes Care in Primary Care in Argentina: Exploratory Study

Background

Engagement in self-care behaviors that are essential to optimize diabetes care is challenging for many patients with diabetes. mHealth interventions have been shown to be effective in improving health care outcomes in diabetes. However, more research is needed on patient perceptions to support these interventions, especially in resource settings in low- and middle-income countries.

Objective

The goal of the research was to explore perceptions and acceptability of a short message service (SMS) text messaging intervention for diabetes care in underserved people with diabetes in Argentina.

Methods

A qualitative exploratory methodology was adopted as part of the evaluation of a program to strengthen diabetes services in primary care clinics located in low-resource settings. The diabetes program included a text messaging intervention for people with diabetes. A total of 24 semistructured telephone interviews were conducted with people with diabetes.

Results

Twenty-four middle-aged persons with diabetes were interviewed. Acceptability was considered adequate in terms of its actual use, frequency, and the role of texts as a reminder. We found that text messages could be a mediating device in the patient’s learning processes. Also, being exposed to the texts seemed to help bring about changes in risk perception and care practices and to function as psychosocial support. Another relevant finding was the role of text messaging as a potential facilitator in diabetes care. In this sense, we observed a strong association between receiving text messages and having a better patient-physician relationship. Additionally, social barriers that affect diabetes care such as socioeconomic and psychosocial vulnerability were identified.

Conclusions

Our findings show positive contributions of a text messaging intervention for the care of people with diabetes. We consider that an SMS strategy has potential to be replicated in other contexts. However, further studies are needed to explore its sustainability and long-term impact from the perspective of patients.

Perceptions on using interactive voice response surveys for non-communicable disease risk factors in Uganda: a qualitative exploration

BACKGROUND

Decision-makers need up to date information on risk factors for effective prevention and control of non-communicable diseases (NCDs). Currently available surveys are infrequent and costly to implement. The objective of the study was to explore perceptions on using an interactive voice response (IVR) survey for data collection on NCD risk factors.

METHODS

Five focus group discussions (FGDs), including rural and urban, elderly and young adults, male and female groups; and eleven key informant interviews (KIIs) of researchers and NCD policy makers were conducted. Respondents were audio recorded and data were transcribed into text. Data were entered into QDA miner software for analysis. Meaningful units were generated and then merged into codes and categories. Quotes are presented highlighting findings.

RESULTS

At the individual level, age, gender, disability, past experience and being technology literate were perceived as key determinants on whether respondents would accept an IVR survey. Receiving the IVR at a time at which people are usually available to take calls increases participation. However, technological accessibility like presence of a mobile network signal and possession of mobile phones were critical for use of IVR. Participants recommended that community sensitization activities be provided, IVR be conducted at appropriate times and frequency, and that incentives may improve survey participation.

CONCLUSIONS

IVR has the potential to quickly collect data from a wide geographic scope. However, caution needs to be taken to ensure that certain categories of people are not excluded because of their location, ability, age or gender. Sensitization prior to the survey, proper timing and structured incentives could increase participation.

Digital Weight Loss Intervention for Parents of Children Being Treated for Obesity: A Prospective Cohort Feasibility Trial

BACKGROUND

The prevalence of childhood obesity continues to increase, and clinic-based treatment options have failed to demonstrate effectiveness. One of the strongest predictors of child weight is parent weight. Parental treatment for weight loss may indirectly reduce obesity in the child. We have previously demonstrated the effectiveness among adults of a fully automated, evidence-based digital weight loss intervention (Track). However, it is unknown if it is feasible to deliver such a treatment directly to parents with obesity who bring their child with obesity to a weight management clinic for treatment.

OBJECTIVE

The objective of our study was to evaluate the feasibility of and engagement with a digital weight loss intervention among parents of children receiving treatment for obesity.

METHODS

We conducted a 6-month pre-post feasibility trial among parents or guardians and their children aged 4-16 years presenting for tertiary care obesity treatment. Along with the standard family-based treatment protocol, parents received a 6-month digital weight loss intervention, which included weekly monitoring of personalized behavior change goals via mobile technologies. We examined levels of engagement by tracking completed weeks of self-monitoring and feasibility by assessing change in weight.

RESULTS

Participants (N=48) were on average 39 years old, mostly female (35/42, 82% ), non-Hispanic Black individuals (21/41, 51%) with obesity (36/48, 75%). Over a quarter had a yearly household income of <US $25,000, and about a third had the equivalent of a high school education. Children were on average 10 years old and had a body mass index of 29.8 kg/m². The median percentage of weeks participants tracked their behaviors was 77% (18.5/24 total weeks; interquartile range [IQR] 6.3 to 100). The median number of attempts via phone or text message (short message service) required to complete one tracking week was 3.3 (IQR 2.6 to 4.9). Nearly half (23/48, 48%) had high levels of engagement, completing 80% (19/24) or more weeks of tracking. Of the 26 participants with weight measurements reported at 6 months, of which 81% (21/26) were self-reported, there was a median 2.44 kg (IQR -6.5 to 1.0) decrease in weight.

CONCLUSIONS

It is feasible to deliver an evidence-based digital weight loss intervention to parents or guardians whose children are enrolled in a weight management program. Given the feasibility of this approach, future studies should investigate the effectiveness of digital weight loss interventions for parents on child weight and health outcomes.

A Church-Based Weight Loss Intervention in African American Adults using Text Messages (LEAN Study): Cluster Randomized Controlled Trial

Background

African American adults experience a high prevalence of obesity and its associated comorbidities, including diabetes. Church-based interventions have been shown to be effective in decreasing weight in this population. mHealth interventions can address two needs for obesity treatment in this community, including enhancing weight loss and providing wide dissemination.

Objective

This study aimed to assess the feasibility and efficacy of a church-based weight loss intervention that incorporates mHealth technology.

Methods

In this study, 8 churches (n=97) were randomly assigned to the intervention or delayed intervention condition (control group). We recruited participants through their respective church. Volunteer church members were trained by study staff to deliver the 10-session, 6-month intervention. Participants in the intervention group attended group sessions and received automated short message service (SMS) text messages designed to reinforce behavioral strategies. Conversely, participants in the delayed intervention condition received SMS text messages related to health conditions relevant for African American adults. We obtained measures of body composition, blood pressure, blood glucose, and cholesterol.

Results

We successfully recruited 97 African American adults, with a mean age of 56.0 (SE 10.3) years and a mean body mass index of 38.6 (SE 6.4) kg/m2 (89/97, 91.8% females), who attended the churches that were randomized to the intervention (n=68) or control (n=29) condition. Of these, 74.2% (72/97) of the participants (47/68, 69.1% intervention; 25/29, 86.2% delayed intervention) completed the 6-month assessment. The average intervention group attendance was 55%. There was a significant difference in weight loss (P=.04) between participants in the intervention (–1.5 (SE 0.5) kg) and control (0.11 (SE 0.6) kg) groups. Among participants in the intervention group, the correlation between the number of SMS text messages sent and the percent body fat loss was r=.3 with P=.04. The participants reported high satisfaction with the automated SMS text messages.

Conclusions

Automated SMS text messages were well-received by participants, suggesting that more enhanced mHealth technologies are a viable option for interventions targeting African American adults.

Trial Registration

ClinicalTrials.gov NCT02863887; https://clinicaltrials.gov/ct2/show/NCT02863887 (Archived by WebCite at http://www.webcitation.org/71JiYzizO)