Development of the Top Tips Habit-Based Weight Loss App and Preliminary Indications of Its Usage, Effectiveness, and Acceptability: Mixed-Methods Pilot Study

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.

The Effectiveness of Strategies to Improve User Engagement With Digital Health Interventions Targeting Nutrition, Physical Activity, and Overweight and Obesity: Systematic Review and Meta-Analysis

BACKGROUND

Digital health interventions (DHIs) are effective in improving poor nutrition, physical inactivity, overweight and obesity. There is evidence suggesting that the impact of DHIs may be enhanced by improving user engagement. However, little is known about the overall effectiveness of strategies on engagement with DHIs.

OBJECTIVE

This study aims to assess the overall effectiveness of strategies to improve engagement with DHIs targeting nutrition, physical activity, and overweight or obesity and explore associations between strategies and engagement outcomes. The secondary aim was to explore the impact of these strategies on health risk outcomes.

METHODS

The MEDLINE, Embase, PsycINFO, CINAHL, CENTRAL, Scopus, and Academic Source Complete databases were searched up to July 24, 2023. Eligible studies were randomized controlled trials that evaluated strategies to improve engagement with DHIs and reported on outcomes related to DHI engagement (use or user experience). Strategies were classified according to behavior change techniques (BCTs) and design features (eg, supplementary emails). Multiple-variable meta-analyses of the primary outcomes (usage and user experience) were undertaken to assess the overall effectiveness of strategies. Meta-regressions were conducted to assess associations between strategies and use and user experience outcomes. Synthesis of secondary outcomes followed the "Synthesis Without Meta-Analysis" guidelines. The methodological quality and evidence was assessed using the Cochrane risk-of-bias tool, and the Grading of Recommendations Assessment, Development, and Evaluation tool respectively.

RESULTS

Overall, 54 studies (across 62 publications) were included. Pooled analysis found very low-certainty evidence of a small-to-moderate positive effect of the use of strategies to improve DHI use (standardized mean difference=0.33, 95% CI 0.20-0.46; P<.001) and very low-certainty evidence of a small-to-moderate positive effect on user experience (standardized mean difference=0.29, 95% CI 0.07-0.52; P=.01). A significant positive association was found between the BCTs social support (effect size [ES]=0.40, 95% CI 0.14-0.66; P<.001) and shaping knowledge (ES=0.39, 95% CI 0.03-0.74; P=.03) and DHI use. A significant positive association was found among the BCTs social support (ES=0.70, 95% CI 0.18-1.22; P=.01), repetition and substitution (ES=0.29, 95% CI 0.05-0.53; P=.03), and natural consequences (ES=0.29, 95% CI 0.05-0.53; P=.02); the design features email (ES=0.29, 95% CI 0.05-0.53; P=.02) and SMS text messages (ES=0.34, 95% CI 0.11-0.57; P=.01); and DHI user experience. For secondary outcomes, 47% (7/15) of nutrition-related, 73% (24/33) of physical activity-related, and 41% (14/34) of overweight- and obesity-related outcomes reported an improvement in health outcomes.

CONCLUSIONS

Although findings suggest that the use of strategies may improve engagement with DHIs targeting such health outcomes, the true effect is unknown because of the low quality of evidence. Future research exploring whether specific forms of social support, repetition and substitution, natural consequences, emails, and SMS text messages have a greater impact on DHI engagement is warranted.

TRIAL REGISTRATION

PROSPERO CRD42018077333; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=77333.

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.

A Contactless App-Based Intervention to Improve Health Behaviors in Airline Pilots: A Randomized Trial

INTRODUCTION

There is a need for enhanced preventive health care among airline pilots to mitigate the prevalence of cardiometabolic health risk factors.

DESIGN

A randomized, waitlist-controlled trial was utilized to evaluate the effectiveness of a smartphone-based app intervention for improving health behaviors and cardiometabolic health parameters.

SETTING/PARTICIPANTS

A total of 186 airline pilots (aged 43.2±9.1 years; male, 64%) were recruited and participated in the trial during 2022.

INTERVENTION

This intervention was a personalized, 16-week smartphone-based app multicomponent physical activity, healthy eating, and sleep hygiene intervention.

MAIN OUTCOME MEASURES

Outcome measures of objective health (Cooper's 12-minute exercise test, resting heart rate, push ups, plank isometric hold, body mass), subjective health (self-rated health, perceived psychological stress and fatigue), and health behaviors (weekly physical activity, sleep quality and duration, fruit and vegetable intake) were collected at baseline and after intervention. The waitlist control completed the same measures.

RESULTS

Significant interactions for time Χ group from baseline to 16 weeks were found for all outcome measures (p<0.001). Significant between-group differences for positive health changes in favor of the intervention group were found after intervention for all outcome measures (p<0.05, d=0.4-1.0) except for self-rated health, body mass, and Pittsburgh Sleep Quality Index score.

CONCLUSIONS

Study findings show that an app-based health behavior intervention can elicit positive cardiometabolic health changes among airline pilots over 16 weeks, associated with trivial to large effect sizes.

TRIAL REGISTRATION

The trial protocol was prospectively registered at The Australian New Zealand Clinical Trials Registry (ACTRN12622000288729).

Effectiveness and Components of Web-Based Interventions on Weight Changes in Adults Who Were Overweight and Obese: A Systematic Review with Meta-Analyses

Overweight and obesity have reached epidemic proportions worldwide. The COVID-19 pandemic resulted in an increased need for remote implementation of weight-loss interventions; therefore, the effectiveness of web-based interventions needed to be assessed. This study aimed to examine the effectiveness of web-based interventions and their potency in facilitating weight changes in adults who were overweight or obese. We searched PubMed and Ichu-shi Web from the first year of inclusion in each database until the search date (30 September 2020). Among 1466 articles retrieved from the two databases and manual search, 97 were selected to undergo qualitative analysis and 51 articles were subjected to quantitative analysis. Qualitative analysis of 97 articles demonstrated that articles showing significant effectiveness mostly used the following components: social support, self-monitoring for behavior, self-monitoring for the outcome (weight), behavioral goal setting, information about health consequences, and outcome goal setting. Quantitative analysis of 51 articles showed a significant effectiveness of web-based intervention (standardized mean difference, -0.57; 95% confidence interval, -0.75 to -0.40). This study demonstrated the effectiveness of web-based interventions on weight change in adults with overweight and obesity. Subgroup meta-analyses identified personalized information provision and expert advice to be remarkably effective components.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Users' Perspective on the AI-Based Smartphone PROTEIN App for Personalized Nutrition and Healthy Living: A Modified Technology Acceptance Model (mTAM) Approach

The ubiquitous nature of smartphone ownership, its broad application and usage, along with its interactive delivery of timely feedback are appealing for health-related behavior change interventions via mobile apps. However, users' perspectives about such apps are vital in better bridging the gap between their design intention and effective practical usage. In this vein, a modified technology acceptance model (mTAM) is proposed here, to explain the relationship between users' perspectives when using an AI-based smartphone app for personalized nutrition and healthy living, namely, PROTEIN, and the mTAM constructs toward behavior change in their nutrition and physical activity habits. In particular, online survey data from 85 users of the PROTEIN app within a period of 2 months were subjected to confirmatory factor analysis (CFA) and regression analysis (RA) to reveal the relationship of the mTAM constructs, i.e., perceived usefulness (PU), perceived ease of use (PEoU), perceived novelty (PN), perceived personalization (PP), usage attitude (UA), and usage intention (UI) with the users' behavior change (BC), as expressed via the acceptance/rejection of six related hypotheses (H1-H6), respectively. The resulted CFA-related parameters, i.e., factor loading (FL) with the related p-value, average variance extracted (AVE), and composite reliability (CR), along with the RA results, have shown that all hypotheses H1-H6 can be accepted (p < 0.001). In particular, it was found that, in all cases, FL > 0.5, CR > 0.7, AVE > 0.5, indicating that the items/constructs within the mTAM framework have good convergent validity. Moreover, the adjusted coefficient of determination (R 2) was found within the range of 0.224-0.732, justifying the positive effect of PU, PEoU, PN, and PP on the UA, that in turn positively affects the UI, leading to the BC. Additionally, using a hierarchical RA, a significant change in the prediction of BC from UA when the UI is used as a mediating variable was identified. The explored mTAM framework provides the means for explaining the role of each construct in the functionality of the PROTEIN app as a supportive tool for the users to improve their healthy living by adopting behavior change in their dietary and physical activity habits. The findings herein offer insights and references for formulating new strategies and policies to improve the collaboration among app designers, developers, behavior scientists, nutritionists, physical activity/exercise physiology experts, and marketing experts for app design/development toward behavior change.

Obesity as a Risk Factor for Severe COVID-19: Summary of the Best Evidence and Implications for Health Care

PURPOSE OF REVIEW

To collate the best evidence from several strands-epidemiological, genetic, comparison with historical data and mechanistic information-and ask whether obesity is an important causal and potentially modifiable risk factor for severe COVID-19 outcomes.

RECENT FINDINGS

Several hundred studies provide powerful evidence that body mass index (BMI) is a strong linear risk factor for severe COVID-19 outcomes, with recent studies suggesting ~5-10% higher risk for COVID-19 hospitalisation per every kg/m² higher BMI. Genetic data concur with hazard ratios increasing by 14% per every kg/m² higher BMI. BMI to COVID-19 links differ markedly from prior BMI-infection associations and are further supported as likely causal by multiple biologically plausible pathways. Excess adiposity appears to be an important, modifiable risk factor for adverse COVID-19 outcomes across all ethnicities. The pandemic is also worsening obesity levels. It is imperative that medical systems worldwide meet this challenge by upscaling investments in obesity prevention and treatments.

ImpulsePal: The systematic development of a smartphone app to manage food temptations using intervention mapping

BACKGROUND

Impulsive processes driving eating behaviour can often undermine peoples' attempts to change their behaviour, lose weight and maintain weight loss.

AIM

To develop an impulse management intervention to support weight loss in adults.

METHODS

Intervention Mapping (IM) was used to systematically develop the "ImpulsePal" intervention. The development involved: (1) a needs assessment including a qualitative study, Patient and Public advisory group and expert group consultations, and a systematic review of impulse management techniques; (2) specification of performance objectives, determinants, and change objectives; (3) selection of intervention strategies (mapping of change techniques to the determinants of change); (4) creation of programme materials; (5) specification of adoption and implementation plans; (6) devising an evaluation plan.

RESULTS

Application of the IM Protocol resulted in a smartphone app that could support reductions in unhealthy (energy dense) food consumption, overeating, and alcoholic and sugary drink consumption. ImpulsePal includes inhibition training, mindfulness techniques, implementation intentions (if-then planning), visuospatial loading, use of physical activity for craving management, and context-specific reminders. An "Emergency Button" was also included to provide access to in-the-moment support when temptation is strong.

CONCLUSIONS

ImpulsePal is a novel, theory- and evidence-informed, person-centred app that aims to support impulse management for healthier eating. Intervention Mapping facilitated the incorporation of app components that are practical operationalisations of change techniques targeting our specific change objectives and their associated theoretical determinants. Using IM enabled transparency and provided a clear framework for evaluation, and enhances replicability and the potential of the intervention to accomplish the desired outcome of facilitating weight loss through dietary change.

The Hospital-Community-Family-Based Telemedicine (HCFT-AF) Program for Integrative Management of Patients With Atrial Fibrillation: Pilot Feasibility Study

Background

The potential effectiveness of integrated management in further improving the prognosis of patients with atrial fibrillation has been demonstrated; however, the best strategy for implementation remains to be discovered.

Objective

The aim of this study was to ascertain the feasibility of implementing integrated atrial fibrillation care via the Hospital-Community-Family–Based Telemedicine (HCFT-AF) program.

Methods

In this single-arm, pre-post design pilot study, a multidisciplinary teamwork, supported by efficient infrastructures, provided patients with integrated atrial fibrillation care following the Atrial fibrillation Better Care (ABC) pathway. Eligible patients were continuously recruited and followed up for at least 4 months. The patients’ drug adherence, and atrial fibrillation–relevant lifestyles and behaviors were assessed at baseline and at 4 months. The acceptability, feasibility, and usability of the HCFT-AF technology devices and engagement with the HCFT-AF program were assessed at 4 months.

Results

A total of 73 patients (mean age, 68.42 years; 52% male) were enrolled in November 2019 with a median follow up of 132 days (IQR 125–138 days). The patients’ drug adherence significantly improved after the 4-month intervention (P<.001). The vast majority (94%, 64/68) of indicated patients received anticoagulant therapy at 4 months, and none of them received antiplatelet therapy unless there was an additional indication. The atrial fibrillation–relevant lifestyles and behaviors ameliorated to varying degrees at the end of the study. In general, the majority of patients provided good feedback on the HCFT-AF intervention. More than three-quarters (76%, 54/71) of patients used the software or website more than once a week and accomplished clinic visits as scheduled.

Conclusions

The atrial fibrillation–integrated care model described in this study is associated with improved drug adherence, standardized therapy rate, and lifestyles of patients, which highlights the possibility to better deliver integrated atrial fibrillation management.

Trial Registration

Clinicaltrials.gov NCT04127799; https://clinicaltrials.gov/ct2/show/NCT04127799

Construal beliefs moderate the usability and effectiveness of a novel healthy eating mobile app

Reduced self-control is a strong predictor of overeating and obesity. Priming a high construal level mind-set has been shown to enhance self-control and reduce snack consumption in the lab but the long-term and real-world effects are not known. The use of digital technology is an efficient way to deliver priming cues in real-world settings. Many mobile apps claim to support healthy eating but few are grounded in psychological theories of self-control. The aim of this study was to test the feasibility and effectiveness of a novel, construal-theory-based mobile app to promote self-control and healthy eating. In an exploratory analysis, the moderating influence of user characteristics was also examined. Using an iterative process involving users at every stage of the process, a prototype mobile app was developed. The final version included a high construal, self-control priming task, sent personalised reminder cues before each eating occasion, provided a just-in time 'crave-buster' for unanticipated eating opportunities and an optional food log. In a longitudinal trial the app was used over an eight-week period (N=71; 51 females; M (SD) Age = 33.34 (11.68) years; M (SD) BMI = 26.22 (4.94)) with pre-post measures of weight, percent body fat and dietary intake. The app received high usability ratings on the System Usability Scale (M=76.55; SD=11.35), however food intake, per cent body fat and weight pre- and post- app use showed no significant change (p>.05). Exploratory analyses showed that baseline construal belief moderated the extent to which engagement with the app predicted dietary changes (p<.05). These findings indicate that this novel app was user-friendly and effective but that this was dependent on the user's characteristics. Future development in this area should consider tailoring apps to the specific characteristics of the user for improved support and effectiveness.

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

Background

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

Objective

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

Methods

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

Results

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

Conclusions

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