The App Behavior Change Scale: Creation of a Scale to Assess the Potential of Apps to Promote Behavior Change

Complementary App-Based Yoga Home Exercise Therapy for Patients With Axial Spondyloarthritis: Usability Study

BACKGROUND

Axial spondyloarthritis (AS) is a chronic inflammatory rheumatic disease characterized by potentially disabling inflammation of the spine and adjacent joints. Regular exercise is a cornerstone of treatment. However, patients with AS currently have little support. YogiTherapy (MaD Lab) is an app developed to support patients with AS by providing instructions for yoga-based home exercise therapy.

OBJECTIVE

This study aimed to evaluate the usability and acceptance of the newly designed YogiTherapy app for patients with AS.

METHODS

Patients completed the User Version of the Mobile Application Rating Scale (uMARS) and net promoter score (NPS) questionnaires after the app introduction. Wilcoxon Mann-Whitney rank sum test, chi-square test for count data, and correlation analysis were conducted to examine the usability of the app, acceptance, and patient characteristics.

RESULTS

A total of 65 patients with AS (33, 51% female; age: mean 43.3, SD 13.6 years) were included in the study from May 2022 to June 2023. Subsequently, the data were analyzed. Usability was rated moderate, with a mean uMARS of 3.35 (SD 0.47) points on a scale from 0 to 5. The highest-rated uMARS dimension was information (mean 3.88, SD 0.63), followed by functionality (mean 3.84, SD 0.87). Females reported a significantly higher uMARS total score than males (mean 3.47, SD 0.48 vs mean 3.23, SD 0.45; P=.03, Vargha and Delaney A [VDA] 0.66, 95% CI 0.53-0.77). The mean average of the NPS was 6.23 (SD 2.64) points (on a scale from 0 to 10), based on 43% (26/65 nonpromoters, 42% (25/65) indifferent, and 15% (9/65) promoters. A total of 7% (5/65) of those surveyed did not answer the question. When applying the NPS formula, the result is -26%. The NPS showed a positive correlation with the usage of mobile apps (r=0.39; P=.02). uMARS functionality was significantly higher rated by patients younger than 41 years (mean 4.17, SD 0.55 vs mean 3.54, SD 1; P<.001; VDA 0.69, 95% CI 0.56-0.80). Patients considering mobile apps as useful reported higher uMARS (r=0.38, P=.02). The uMARS app quality mean score was correlated with the frequency of using apps (r=-0.21, P<.001).

CONCLUSIONS

The results revealed moderate acceptance and usability ratings, prompting further app improvement. Significant differences were observed between age and gender. Our results emphasize the need for further improvements in YogiTherapy.

Content, Behaviour Change Techniques, and Quality of Postpartum Depression Apps to Be Recommended by Midwives: Systematic Search and Evaluation

BACKGROUND

Postpartum depression is a public health problem that affects a considerable percentage of women. Despite the proliferation of related apps, there are limited data available on the best apps to prevent postpartum depression. We identified which apps available in Spanish could be recommended by midwives based on their content, quality, and behaviour change techniques, as a complementary tool for preventing postpartum depression in women.

METHODS

A systematic search was performed to identify apps available on iOS App Store and Google Play, which were used to replicate how patients' access "postpartum depression prevention" apps. Apps' quality, behaviour change potential, and contents were assessed.

RESULTS

A total of 1408 apps were identified, of which 7 were retrieved for assessment (0.5%). The mean objective and subject quality were 3.1 (SD = 1.01) and 2.7 (SD = 1.27), respectively. A total of 24 topics were identified. The mean ABACUS score was 6.6 (SD = 3.64), and the mean number of topics addressed by the apps was 9.9 (SD = 5.90).

CONCLUSION

The results of the present study suggest that a specific free app is not available in Spanish for the prevention of postpartum depression, and only a small percentage of free apps should be recommended based on their quality, BCTs, and contents. The systematic review protocol was not registered.

Evaluating the Quality and Comparative Validity of Manual Food Logging and Artificial Intelligence-Enabled Food Image Recognition in Apps for Nutrition Care

For artificial intelligence (AI) to support nutrition care, high quality and accuracy of its features within smartphone applications (apps) are essential. This study evaluated popular apps' features, quality, behaviour change potential, and comparative validity of dietary assessment via manual logging and AI. The top 200 free and paid nutrition-related apps from Australia's Apple App and Google Play stores were screened (n = 800). Apps were assessed using MARS (quality) and ABACUS (behaviour change potential). Nutritional outputs from manual food logging and AI-enabled food-image recognition apps were compared with food records for Western, Asian, and Recommended diets. Among 18 apps, Noom scored highest on MARS (mean = 4.44) and ABACUS (21/21). From 16 manual food-logging apps, energy was overestimated for Western (mean: 1040 kJ) but underestimated for Asian (mean: -1520 kJ) diets. MyFitnessPal and Fastic had the highest accuracy (97% and 92%, respectively) out of seven AI-enabled food image recognition apps. Apps with more AI integration demonstrated better functionality, but automatic energy estimations from AI-enabled food image recognition were inaccurate. To enhance the integration of apps into nutrition care, collaborating with dietitians is essential for improving their credibility and comparative validity by expanding food databases. Moreover, training AI models are needed to improve AI-enabled food recognition, especially for mixed dishes and culturally diverse foods.

The Effect of Mobile Lifestyle Intervention Combined with High-Protein Meal Replacement on Liver Function in Patients with Metabolic Dysfunction-Associated Steatotic Liver Disease: A Pilot Randomized Controlled Trial

While many studies have explored dietary substitutes and mobile apps separately, a combined approach to metabolic dysfunction-associated steatotic liver disease (MASLD) has not been investigated. This study evaluated short-term mobile interventions coupled with partial meal replacement in patients with MASLD. Sixty adults with MASLD and a body mass index ≥25 kg/m2 from a health examination center were randomized into an intervention group using a mobile app with partial meal replacements or a control group receiving standard educational materials. Liver enzyme levels, lipid profiles, and anthropometric measurements were assessed at baseline and after 4 weeks. Twenty-five participants in the intervention group and 24 in the control group completed the trial. Significant reductions were observed in the intervention group for alanine aminotransferase (-28.32 versus [vs.] -10.67, p = 0.006) and gamma-glutamyl transferase (-27.76 vs. 2.79, p = 0.014). No significant changes in aspartate aminotransferase, body weight, or waist circumference were noted in the intervention group. Four weeks of mobile lifestyle intervention incorporating partial meal replacements improved liver enzyme profiles in patients with MASLD. This strategy demonstrated the potential for mitigating elevated liver enzyme levels without altering body weight or waist circumference. Comprehensive and longer-term research is needed to substantiate and elaborate these preliminary outcomes.

Effects of mHealth Practice Patterns on Improving Metabolic Syndrome Using the Information-Motivation-Behavioral Skills Model

Chronic diseases contribute to 68% of global mortality, highlighting the importance of early detection and management of conditions such as metabolic syndrome. Effective lifestyle interventions, particularly through mobile health (mHealth), have shown potential in promoting health and reducing cardiometabolic risk. This study utilized mHealth data from public health centers in South Korea, targeting adults with risk factors for metabolic syndrome. The Intervention-Motivation-Behavioral skills (IMB) theoretical model was applied to categorize participants' practice patterns over time using the Group-Based Trend Model (GBTM). And the Generalized Estimating Equations (GEE) methodology was applied to confirm the effective practice patterns for improving metabolic syndrome. Data were collected over 24 weeks. The dataset encompasses life-log data capable of capturing changes in intervention, self-report surveys, and clinical measurements, all linked to personal identification keys and thereby integrated. Participants demonstrated improved health behaviors, with the healthy eating score increasing from 5.0 to 6.4 and physical activity rates rising from 41.5% to 59%. Health risk factors decreased significantly, with the mean number of risk factors dropping from 2.4 to 1.4. The percentage of subjects with three or more metabolic syndrome components decreased from 42.3% in the initial period to 19.2% in the final period. Practice patterns by IMB components were classified into three categories: continuous type, late decline type, and early decline type. Improvements in health behavior and metabolic syndrome were observed in the continuous type of each IMB component. The mHealth interventions were confirmed to be positively associated with improved health behavior and management of metabolic syndrome in the continuous practice patterns of IMB.

Digital Apps to Improve Mobility in Adults with Neurological Conditions: A Health App-Focused Systematic Review

The provision of mobility exercises through a smartphone application (app) for people undertaking neurological rehabilitation may improve mobility outcomes. However, it is difficult for clinicians and consumers to select high-quality, appropriate apps. This review aimed to identify (1) which mobile health (mHealth) apps are suitable for prescribing mobility exercises for adults with neurological health conditions, (2) how well these apps incorporate telehealth strategies, and (3) how well these apps rate in terms of quality and capacity for behaviour change. The Australian Apple iTunes Store was systematically searched, by using a search code and manually, for apps suitable for training mobility in neurological rehabilitation. Additional searches were conducted in known app repositories and for web-based apps. Trained reviewers extracted data from the included apps, including population-specific characteristics; quality, by using the Mobile App Rating Scale (MARS); and behaviour change potential, by using the App Behaviour Change Scale (ABACUS). The included apps (n = 18) provided <50 to >10,000 exercises, many incurred a subscription fee (n = 13), and half included telehealth features. App quality was moderate (mean MARS score of 3.2/5 and SD of 0.5), and potential for behaviour change was poor (mean ABACUS score of 5.7/21 and SD of 2.1). A limited number of high-quality apps are available for the prescription of mobility exercises in people with neurological conditions.

Implementing a mental health app library in primary care: A feasibility study

Confronted with a wide range of digital health tools (DHT), professionals and patients need guidance to use these tools correctly and optimize health management. In the fall of 2020, a DHT library developed by Quebec-based company TherAppX was implemented in 22 institutions. The library was designed to enable healthcare professionals to use DHT in clinical care. The purpose of the current study was to assess the feasibility of implementing the library, including user experience, changes in DHT recommendation habits, and factors that helped or hindered the implementation process. A multi-methods design focusing on secondary use of quantitative data collected by TherAppX and semi-structured interviews with users was employed. While the quantitative analyses indicated infrequent use of the library, qualitative analyses highlighted several factors that hindered its implementation, including certain library and user characteristics and the unprecedented context of the COVID-19 pandemic. Nevertheless, the quantitative analyses confirmed interest in DHT and their usefulness during follow-ups. The results revealed a marginally significant pre-post changes in the frequency with which DHT were recommended. This study helped identify areas for improvements and indicates that further evaluation is needed. Future implementations would benefit from ensuring optimal conditions for a successful implementation.

Methodological challenges in systematic reviews of mHealth interventions: Survey and consensus-based recommendations

OBJECTIVE

Mobile Health (mHealth) refers to using mobile devices to support health. This study aimed to identify specific methodological challenges in systematic reviews (SRs) of mHealth interventions and to develop guidance for addressing selected challenges.

STUDY DESIGN AND SETTING

Two-phase participatory research project. First, we sent an online survey to corresponding authors of SRs of mHealth interventions. On a five-category scale, survey respondents rated how challenging they found 24 methodological aspects in SRs of mHealth interventions compared to non-mHealth intervention SRs. Second, a subset of survey respondents participated in an online workshop to discuss recommendations to address the most challenging methodological aspects identified in the survey. Finally, consensus-based recommendations were developed based on the workshop discussion and subsequent interaction via email with the workshop participants and two external mHealth SR authors.

RESULTS

We contacted 953 corresponding authors of mHealth intervention SRs, of whom 50 (5 %) completed the survey. All the respondents identified at least one methodological aspect as more or much more challenging in mHealth intervention SRs than in non-mHealth SRs. A median of 11 (IQR 7.25-15) out of 24 aspects (46 %) were rated as more or much more challenging. Those most frequently reported were: defining intervention intensity and components (85 %), extracting mHealth intervention details (71 %), dealing with dynamic research with evolving interventions (70 %), assessing intervention integrity (69 %), defining the intervention (66 %) and maintaining an updated review (65 %). Eleven survey respondents participated in the workshop (five had authored more than three mHealth SRs). Eighteen consensus-based recommendations were developed to address issues related to mHealth intervention integrity and to keep mHealth SRs up to date.

CONCLUSION

mHealth SRs present specific methodological challenges compared to non-mHealth interventions, particularly related to intervention integrity and keeping SRs current. Our recommendations for addressing these challenges can improve mHealth SRs.

Assessing the Quality and Behavior Change Potential of Vaping Cessation Apps: Systematic Search and Assessment

Background

An increasing number of people are using vapes (e-cigarettes), and with growing evidence of associated harms, there is a need for acceptable cessation support and interventions. Smartphone apps for health and well-being have increased in popularity and use. Limited published literature assesses the potential of apps to support vaping cessation.

Objective

A systematic search of vaping cessation apps currently available in Australia for iOS and Android platforms was conducted. Apps were assessed against established health app assessment tools for quality and behavior change potential.

Methods

A systematic search through the Australian Apple iTunes and Google Play stores was conducted using the search terms "vape"; "vaping"; "e-cigarette"; and "cessation," "quit," or "quitting" in May 2023. Only apps that encouraged the cessation of vaping were included. App descriptions were reviewed to determine if they were relevant for inclusion in this study, and relevant apps were downloaded onto the appropriate mobile device for review. The Mobile App Rating Scale (MARS) was used to rate the quality (engagement, functionality, aesthetics, and information) of the apps using an overall score out of 5. The App Behavior Change Scale (ABACUS) was used to assess the behavior change potential of each app using a score out of 21.

Results

An initial search of the app stores yielded 220 Android apps and 124 iOS apps. Screening against the inclusion criteria left 20 iOS apps and 10 Android apps for review. Six apps were available on both operating systems, and these were downloaded, reviewed, and reported separately for each operating system. The average MARS score for all apps assessed in this review was 3.1 (SD 0.41) out of 5. The reviewed apps overall performed well for the MARS elements relating to functionality, such as ease of use and navigation, but had the lowest scores for information-related elements, such as credibility. The number of ABACUS behavior change features per app ranged from 0 to 19 out of 21, with a mean of 8.9 (SD 4.51). The apps commonly included information-related features, such as requesting baseline information. The least common behavior change features were those relating to goal-setting, such as asking about the user's willingness for behavior change and providing feedback on current actions in comparison to future goals.

Conclusions

The identified vaping cessation apps had moderate levels of quality and some behavior change components. Future vaping cessation apps could benefit from including more features that are known to support behavior change, such as goal-setting, to improve the potential benefit of these apps to support people to stop vaping. As guidelines for vaping cessation continue to be established, future apps need to reference these in their development.

Evaluation of Patient-Facing Mobile Apps to Support Physiotherapy Care: Systematic Review

BACKGROUND

Mobile health interventions delivered through mobile apps are increasingly used in physiotherapy care. This may be because of the potential of apps to facilitate changes in behavior, which is central to the aims of care delivered by physiotherapists. A benefit of using apps is their ability to incorporate behavior change techniques (BCTs) that can optimize the effectiveness of physiotherapeutic interventions. Research continues to suggest that despite their importance, behavior change strategies are often missing in patient management. Evaluating mobile apps that physiotherapists can use to drive behavior change may inform clinical practice and potentially improve patient outcomes. Examining the quality of apps and exploring their key features that can support behavior change and physiotherapy care are important aspects of such an evaluation.

OBJECTIVE

The primary aim of this study was to describe the range of mobile apps in app stores that are intended for use by patients to support physiotherapy care. The secondary aims were to assess app quality, BCTs, and their behavior change potential.

METHODS

A systematic review of mobile apps in app stores was undertaken. The Apple App Store and Google Play were searched using a 2-step search strategy, using terms relevant to the physiotherapy discipline. Strict inclusion and exclusion criteria were applied: apps had to be intended for use by patients and be self-contained (or stand-alone) without the requirement to be used in conjunction with a partner wearable device or another plugin. Included apps were coded for BCTs using the Behavior Change Technique Taxonomy version 1. App quality was assessed using the Mobile App Rating Scale, and the App Behavior Change Scale was used to assess the app's potential to change behavior.

RESULTS

In total, 1240 apps were screened, and 35 were included. Of these 35 apps, 22 (63%) were available on both the Apple App Store and Google Play platforms. In total, 24 (69%) were general in their focus (eg, not condition-specific), with the remaining 11 (31%) being more specific (eg, knee rehabilitation and pelvic floor training). The mean app quality score (Mobile App Rating Scale) was 3.7 (SD 0.4) of 5 (range 2.8-4.5). The mean number of BCTs identified per app was 8.5 (SD 3.6). BCTs most frequently included in the apps were instruction on how to perform a behavior (n=32), action planning (n=30), and self-monitoring of behavior (n=28). The mean behavior change potential score (App Behavior Change Scale) was 8.5 (SD 3.1) of 21 (range 3-15).

CONCLUSIONS

Mobile apps available to support patient care received from a physiotherapist are of variable quality. Although they contain some BCTs, the potential for behavior change varied widely across apps.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/29047.

Use Patterns of Smartphone Apps and Wearable Devices Supporting Physical Activity and Exercise: Large-Scale Cross-Sectional Survey

Background

Physical inactivity is a global health issue, and mobile health (mHealth) apps are expected to play an important role in promoting physical activity. Empirical studies have demonstrated the efficacy and efficiency of app-based interventions, and an increasing number of apps with more functions and richer content have been released. Regardless of the success of mHealth apps, there are important evidence gaps in the literature; that is, it is largely unknown who uses what app functions and which functions are associated with physical activity.

Objective

This study aims to investigate the use patterns of apps and wearables supporting physical activity and exercise in a Japanese-speaking community sample.

Methods

We recruited 20,573 web-based panelists who completed questionnaires concerning demographics, regular physical activity levels, and use of apps and wearables supporting physical activity. Participants who indicated that they were using a physical activity app or wearable were presented with a list of app functions (eg, sensor information, goal setting, journaling, and reward), among which they selected any functions they used.

Results

Approximately one-quarter (n=4465) of the sample was identified as app users and showed similar demographic characteristics to samples documented in the literature; that is, compared with app nonusers, app users were younger (odds ratio [OR] 0.57, 95% CI 0.50-0.65), were more likely to be men (OR 0.83, 95% CI 0.77-0.90), had higher BMI scores (OR 1.02, 95% CI 1.01-1.03), had higher levels of education (university or above; OR 1.528, 95% CI 1.19-1.99), were more likely to have a child (OR 1.16, 95% CI 1.05-1.28) and job (OR 1.28, 95% CI 1.17-1.40), and had a higher household income (OR 1.40, 95% CI 1.21-1.62). Our results revealed unique associations between demographic variables and specific app functions. For example, sensor information, journaling, and GPS were more frequently used by men than women (ORs <0.84). Another important finding is that people used a median of 2 (IQR 1-4) different functions within an app, and the most common pattern was to use sensor information (ie, self-monitoring) and one other function such as goal setting or reminders.

Conclusions

Regardless of the current trend in app development toward multifunctionality, our findings highlight the importance of app simplicity. A set of two functions (more precisely, self-monitoring and one other function) might be the minimum that can be accepted by most users. In addition, the identified individual differences will help developers and stakeholders pave the way for the personalization of app functions.

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.

Study protocol for a pilot trial analysing the usability, validity and safety of an interventional health app programme for the structured prehabilitation of patients before major surgical interventions: the PROTEGO MAXIMA trial

INTRODUCTION

Major surgery is associated with a high risk for postoperative complications, leading to an increase in mortality and morbidity, particularly in frail patients with a reduced cardiopulmonary reserve. Prehabilitation, including aerobic exercise training, aims to improve patients' physical fitness before major surgery and reduce postoperative complications, length of hospital stay and costs. The purpose of the study is to assess the usability, validity and safety of an app-based endurance exercise software in accordance with the Medical Device Regulation using wrist-worn wearables to measure heart rate (HR) and distance.

METHODS AND ANALYSIS

The PROTEGO MAXIMA trial is a prospective, interventional study with patients undergoing major elective surgery, comprising three tasks. Tasks I and II aim to assess the usability of the app, using evaluation questionnaires and usability scenarios. In Task IIIa, patients will undergo a structured risk assessment by the Patronus App, which will be correlated with the occurrence of postoperative complications after 90 days (non-interventional). In Task IIIb, healthy students and patients will perform a supervised 6 min walking test and a 37 min interval training on a treadmill based on HR reserve, wearing standard ECG limb leads and two smartwatches, which will be driven by the test software. The aim of this task is to assess the accuracy of HR measurement by the wearables and the safety, using specific alarm settings of the devices and lab testing of the participants (interventional).

ETHICS AND DISSEMINATION

Ethical approval was granted by the Institutional Review Board of the University Hospital of Frankfurt and by the Federal Institute for Pharmaceuticals and Medical Products (BfArM, reference number 94.1.04-5660-13655) on 7 February 2022. The results from this study will be submitted to peer-reviewed journals and reported at suitable national and international meetings.

TRIAL REGISTRATION NUMBERS

European Database on Medical Devices (CIV-21-07-037311) and German Clinical Trial Registry (DRKS00026985).

Design Features Associated With Engagement in Mobile Health Physical Activity Interventions Among Youth: Systematic Review of Qualitative and Quantitative Studies

BACKGROUND

Globally, 81% of youth do not meet the physical activity (PA) guidelines. Youth of families with a low socioeconomic position are less likely to meet the recommended PA guidelines. Mobile health (mHealth) interventions are preferred by youth over traditional in-person approaches and are in line with their media preferences. Despite the promise of mHealth interventions in promoting PA, a common challenge is to engage users in the long term or effectively. Earlier reviews highlighted the association of different design features (eg, notifications and rewards) with engagement among adults. However, little is known about which design features are important for increasing engagement among youth.

OBJECTIVE

To inform the design process of future mHealth tools, it is important to investigate the design features that can yield effective user engagement. This systematic review aimed to identify which design features are associated with engagement in mHealth PA interventions among youth who were aged between 4 and 18 years.

METHODS

A systematic search was conducted in EBSCOhost (MEDLINE, APA PsycINFO, and Psychology & Behavioral Sciences Collection) and Scopus. Qualitative and quantitative studies were included if they documented design features associated with engagement. Design features and related behavior change techniques and engagement measures were extracted. Study quality was assessed according to the Mixed Method Assessment Tool, and one-third of all screening and data extraction were double coded by a second reviewer.

RESULTS

Studies (n=21) showed that various features were associated with engagement, such as a clear interface, rewards, multiplayer game mode, social interaction, variety of challenges with personalized difficulty level, self-monitoring, and variety of customization options among others, including self-set goals, personalized feedback, progress, and a narrative. In contrast, various features need to be carefully considered while designing mHealth PA interventions, such as sounds, competition, instructions, notifications, virtual maps, or self-monitoring, facilitated by manual input. In addition, technical functionality can be considered as a prerequisite for engagement. Research addressing youth from low socioeconomic position families is very limited with regard to engagement in mHealth apps.

CONCLUSIONS

Mismatches between different design features in terms of target group, study design, and content translation from behavior change techniques to design features are highlighted and set up in a design guideline and future research agenda.

TRIAL REGISTRATION

PROSPERO CRD42021254989; https://tinyurl.com/5n6ppz24.

Pregnancy Apps for Self-Monitoring: Scoping Review of the Most Popular Global Apps Available in Australia

Digital health tools, such as apps, have the potential to promote healthy behaviours, especially self-monitoring, which can facilitate pregnancy management and reduce the risk of associated pregnancy health conditions. While pregnancy apps are popular amongst pregnant women, there is limited information about the overall quality of their content or self-monitoring tools and the number of behaviour change techniques (BCTs) that they include. The aim of this study was thus to assess the quality of pregnancy apps for self-monitoring, and their usage of BCTs. We identified pregnancy apps by web scraping the most popular global apps for self-monitoring in the Apple App Store and Google Play Store available in Australia. The app quality was evaluated using the scorecard approach and the inclusion of BCTs was evaluated using the ABACUS tool. We identified 31 pregnancy apps that met our eligibility criteria. We found that pregnancy apps tended to score the highest in the domains of 'cost and time', 'usability', and 'technical', and lowest on 'clinical' and 'end-user requirements'. Additionally, the majority of apps contained minimal BCTs. Based on our findings, we propose a digital health scorecard visualisation that would break down app quality criteria and present them in a more accessible way to clinicians and pregnant users. We conclude that these findings highlight the shortcomings of available commercial pregnancy apps and the utility of a digital health scorecard visualisation that would empower users to make more informed decisions about which apps are the most appropriate for their needs.

Mobile app use to support therapeutic exercise for musculoskeletal pain conditions may help improve pain intensity and self-reported physical function: a systematic review

QUESTION

What is the effect of therapeutic exercise or tailored physical activity programs supported by a mobile app (compared with exercise or physical activity programs delivered using other modes) for people with musculoskeletal pain conditions?

DESIGN

Systematic review of published randomised controlled trials with meta-analysis.

PARTICIPANTS

People of all ages with musculoskeletal pain conditions.

INTERVENTION

Therapeutic exercise or tailored physical activity programs supported by a mobile app.

OUTCOME MEASURES

Pain intensity, pain interference, self-reported physical function, physical performance, adherence, psychosocial outcomes, health-related quality of life, work participation, physical activity, goal attainment and satisfaction.

RESULTS

Eleven studies were eligible for inclusion, with a total of 845 participants. There was low certainty evidence that using mobile apps to deliver exercise programs helps to reduce pain intensity to a worthwhile extent (SMD -0.60, 95% CI -0.93 to -0.27). There was low certainty evidence that using mobile apps to deliver exercise programs helps to improve self-reported physical function to a worthwhile extent (SMD -0.92, 95% CI -1.57 to -0.27). Although the effect of using mobile apps to deliver exercise programs on pain interference was also estimated to be a worthwhile benefit (SMD -0.66), this estimate came with marked uncertainty (95% CI -1.52 to 0.19) so the effect remains unclear. The remainder of the outcomes were unclear due to sparse evidence. The most common behaviour change intervention functions in the mobile app interventions were: training, enablement and environmental restructuring.

CONCLUSION

Mobile apps supporting therapeutic exercise or tailored physical activity programs for musculoskeletal pain conditions may help in reducing pain intensity and improving physical function. The mobile apps utilised a limited range of behaviour change intervention functions.

REGISTRATION

CRD42021248046.

Availability, content and quality of commercially available smartphone applications for the self-management of low back pain: a systematic assessment

PURPOSE

Explore smartphone apps that may be recommended by clinicians for the self-management of low back pain.

METHODS

Prospectively registered systematic assessment of self-contained apps for self-management of low back pain on the Google Play and Apple App stores (Oceania), including ≥1 NICE low back pain and sciatica clinical guideline-recommended component and functioning without health professional input. Outcomes were quality (Mobile App Rating Scale; MARS), and self-management (Self-Management Support Checklist; SMS-14) and behaviour change potential (App Behaviour Change Scale; ABACUS).

RESULTS

25 apps were included. The average quality of included apps was acceptable (Mean MARS score of 3.9 out of a maximum possible 5). The self-management support and behaviour change potential of included apps appeared low (mean SMS-14 score was 3.4/14; mean ABACUS score was 5.4/21). The apps showed no significant correlation between app consumer ratings and MARS scores. App quality was significantly correlated with app price (p = 0.049) but not consumer ratings, however, these findings were based on a small number of studies and the overall model was not significant.

CONCLUSIONS

Smartphone apps for the self-management of low back pain are of average to good quality, with questionable potential for self-management and behaviour change. Clinicians should consider that few apps were designed to specifically incorporate self-management support and behaviour change potential when recommending apps to clients. Further development in these areas of app design would be of benefit.Implications for RehabilitationSmartphone apps have the potential to improve LBP self-management outcomes, however, apps are not well regulated and the quality of information and advice provided is often low quality.The findings from this systematic assessment indicate that LBP self-management apps have limited self-management support and behaviour change potential features.Recommendation of current smartphone apps for LBP should take into consideration that although apps are of acceptable quality they are not specifically designed with self-management support and behaviour change principles.App quality does not appear to be associated with consumer ratings, however, there may be a positive association between app price and quality which requires further investigation.

Assessing the Content and Quality of Digital Tools for Managing Gestational Weight Gain: Systematic Search and Evaluation

BACKGROUND

Digital health resources have the potential to assist women in optimizing gestational weight gain (GWG) during pregnancy to improve maternal health outcomes.

OBJECTIVE

In this study, we aimed to evaluate the quality and behavior change potential of publicly available digital tools (websites and apps) that facilitate GWG tracking.

METHODS

Digital tools were identified using key search terms across website search engines and app stores and evaluated using the Mobile App Rating Scale, the App Behavior Change Scale, as well as criteria to evaluate the rigor and safety of GWG information.

RESULTS

Overall, 1085 tools were screened for inclusion (162 websites and 923 apps), and 19 were deemed eligible. The mean Mobile App Rating Scale quality score was 3.31 (SD 0.53) out of 5, ranging from 2.26 to 4.39, and the mean App Behavior Change Scale score was 6 (SD 3.4) out of 21, ranging from 19 to 0. Of the 19 items used to evaluate rigor of GWG advice, most tools (n=11, 57.9%) contained ≤3 items.

CONCLUSIONS

This review emphasizes the substantial limitations in current digital resources promoting the monitoring and optimization of GWG. Most tools were of low quality, had minimal behavior change potential, and were potentially unsafe, with minimal linkage to evidence-based information or partnership with health care.

Exercise adherence Mobile app for Knee Osteoarthritis: protocol for the MappKO randomised controlled trial

Background

In people with knee osteoarthritis (OA), ongoing exercise participation, particularly with strengthening exercises, is central to management. Patient adherence to prescribed exercise typically declines once consultations with a clinician have ceased. Mobile applications (apps) can incorporate behaviour change techniques that may assist adherence, potentially optimising clinical outcomes.

Methods

This is a two-arm, pragmatic, superiority randomised trial. One hundred and eighty two Australians with chronic knee pain (clinical knee OA) and who have at least a mild level of physical dysfunction are being recruited. Participants are randomly allocated i) exercise (physiotherapist-prescribed exercise) or; ii) exercise plus app (physiotherapist-prescribed exercise plus access to the ‘My Exercise Messages’ mobile app). Exercise care comprises two videoconferencing consultations with a physiotherapist over two weeks (30 min each) for a strengthening exercise program, which is then conducted independently at home for 24 weeks without any further physiotherapist consultations. Participants are also provided with exercise resources to facilitate home-based exercise. Those randomised to exercise plus app will download the app after completing the two weeks of physiotherapy consultations and will be instructed by research staff to use the app for the 24 weeks of unsupervised home-based exercises. The app works by tracking completion of weekly exercise sessions, providing regular messages to facilitate weekly exercise and providing personalised messages to help overcome individual barriers to exercise participation. The two primary outcomes are i) self-reported physical function; and ii) number of days strengthening exercises were performed (previous fortnight), with a primary endpoint of 26 weeks and a secondary endpoint of 14 weeks. Secondary outcomes include knee pain severity; knee-related quality of life; global change; exercise program satisfaction; exercise self-efficacy; physical activity; sport and recreation function; another measure of exercise adherence; and willingness to undergo joint replacement. Process measures are also included.

Discussion

Findings will determine if a theory-informed mobile app improves exercise adherence and physical function in people with knee OA who have received a home-based strengthening program.

Trial Registration

Australian New Zealand Clinical Trials Registry, ACTRN12621000724875. Prospectively registered 9/06/2021.

Antifragile Behavior Change Through Digital Health Behavior Change Interventions

Digital health behavior change interventions (DHBCIs) offer users accessible support, yet their promise to improve health behaviors at scale has not been met. One reason for this unmet potential may be a failure to offer users support that is tailored to their personal characteristics and goals. We apply the concept of antifragility to propose how DHBCIs could be better designed to support diverse users’ behavior change journeys. We first define antifragility as a feature of an individual’s relationship to a particular challenge such that if one is antifragile to a challenge, one is well positioned to benefit from facing that challenge. Second, we introduce antifragile behavior change to describe behavior change processes that leverage person-specific antifragilities to maximize benefits and minimize risk in the behavior change process. While most existing behavior change models focus on improving one’s motivation and ability to face challenges, antifragile behavior change complements these models by helping to select challenges that are most likely to produce desired outcomes. Next, we propose three principles by which DHBCIs can help users to develop antifragile behavior change strategies: providing personalized guidance, embracing variance and exploration in choosing behaviors, and prioritizing user agency. Finally, we offer an example of how a DHBCI could be designed to support antifragile behavior change.

Eating for 2: A Systematic Review of Dutch App Stores for Apps Promoting a Healthy Diet during Pregnancy

A healthy diet during pregnancy has been associated with beneficial child and maternal health outcomes but is challenging to achieve. Recent technological advances offer new opportunities to support pregnant women in their food choices-for instance, via apps. This is already reflected by a wide availability of pregnancy-related apps, but health care professionals feel unsure about their potential. Therefore, the Dutch Google Play Store and Apple App Store were reviewed to identify existing apps on diet and pregnancy. App quality was assessed using the 1) Mobile App Rating Scale (MARS; i.e., assessing functionality, aesthetics, engagement, information quality), 2) Dutch dietary guidelines for pregnant women, and 3) App Behavior Change Scale (ABACUS). Fifty-seven unique apps were identified with an average star rating of 4.2 ±  0.6 and MARS quality score of 3.2 ±  0.3, indicating a moderate quality. Most apps scored best in terms of functionality and aesthetics (4.0 ±  0.4 and 3.3 ±  0.6), but lowest in terms of engagement (2.5 ±  0.6). Regarding nutrition information provision, most apps were incomplete or deviated from the Dutch guidelines. Folic acid supplementation (91%), hygiene (81%), caffeine (79%), and alcohol (77%) were the most commonly addressed nutrition aspects, whereas licorice (11%), iodine (19%), and soy (18%) were only addressed in a few apps. Moreover, a median of 2 out of 21 ABACUS behavior change items were identified per app, which were predominantly related to the category "knowledge and information." Thus, despite the abundance of apps supporting a healthy diet during pregnancy in the Dutch app stores, there is an urgent need for apps with complete and scientifically sound dietary information that is supported by effective behavior change techniques.

Integrating Behavioral Science and Design Thinking to Develop Mobile Health Interventions: Systematic Scoping Review

Background

Mobile health (mHealth) interventions are increasingly being designed to facilitate health-related behavior change. Integrating insights from behavioral science and design science can help support the development of more effective mHealth interventions. Behavioral Design (BD) and Design Thinking (DT) have emerged as best practice approaches in their respective fields. Until now, little work has been done to examine how BD and DT can be integrated throughout the mHealth design process.

Objective

The aim of this scoping review was to map the evidence on how insights from BD and DT can be integrated to guide the design of mHealth interventions. The following questions were addressed: (1) what are the main characteristics of studies that integrate BD and DT during the mHealth design process? (2) what theories, models, and frameworks do design teams use during the mHealth design process? (3) what methods do design teams use to integrate BD and DT during the mHealth design process? and (4) what are key design challenges, implementation considerations, and future directions for integrating BD and DT during mHealth design?

Methods

This review followed the Joanna Briggs Institute reviewer manual and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. Studies were identified from MEDLINE, PsycINFO, Embase, CINAHL, and JMIR by using search terms related to mHealth, BD, and DT. Included studies had to clearly describe their mHealth design process and how behavior change theories, models, frameworks, or techniques were incorporated. Two independent reviewers screened the studies for inclusion and completed the data extraction. A descriptive analysis was conducted.

Results

A total of 75 papers met the inclusion criteria. All studies were published between 2012 and 2021. Studies integrated BD and DT in notable ways, which can be referred to as “Behavioral Design Thinking.” Five steps were followed in Behavioral Design Thinking: (1) empathize with users and their behavior change needs, (2) define user and behavior change requirements, (3) ideate user-centered features and behavior change content, (4) prototype a user-centered solution that supports behavior change, and (5) test the solution against users’ needs and for its behavior change potential. The key challenges experienced during mHealth design included meaningfully engaging patient and public partners in the design process, translating evidence-based behavior change techniques into actual mHealth features, and planning for how to integrate the mHealth intervention into existing clinical systems.

Conclusions

Best practices from BD and DT can be integrated throughout the mHealth design process to ensure that mHealth interventions are purposefully developed to effectively engage users. Although this scoping review clarified how insights from BD and DT can be integrated during mHealth design, future research is needed to identify the most effective design approaches.

Evidence of User-Expert Gaps in Health App Ratings and Implications for Practice

Searching the commercial Google Play Store and App Store is one of the most common strategies for discovering mobile applications for digital health, both among consumers and healthcare professionals. However, several studies have suggested a possible mismatch between this strategy and the objective of finding apps in physical and mental health that are both clinically relevant and reliable from a privacy standpoint. This study provides direct evidence of a gap between the five-star user rating system and expert ratings from a curated library of over 1,200 apps that cover both physical and mental health. An objective metric is derived to assess the strength of the user-expert gap for each app, which in turn allows identifying missed opportunities—low user ratings and high expert ratings—and overrated apps—high user ratings and low expert ratings. Implications for practice and care delivery are discussed.

The Quality of Health Apps and Their Potential to Promote Behavior Change in Patients With a Chronic Condition or Multimorbidity: Systematic Search in App Store and Google Play

Background

Mobile apps offer an opportunity to improve the lifestyle of patients with chronic conditions or multimorbidity. However, for apps to be recommended in clinical practice, their quality and potential for promoting behavior change must be considered.

Objective

We aimed to investigate the quality of health apps for patients with a chronic condition or multimorbidity (defined as 2 or more chronic conditions) and their potential for promoting behavior change.

Methods

We followed the Cochrane Handbook guidelines to conduct and report this study. A systematic search of apps available in English or Danish on App Store (Apple Inc) and Google Play (Google LLC) for patients with 1 or more of the following common and disabling conditions was conducted: osteoarthritis, heart conditions (heart failure and ischemic heart disease), hypertension, type 2 diabetes mellitus, depression, and chronic obstructive pulmonary disease. For the search strategy, keywords related to these conditions were combined. One author screened the titles and content of the identified apps. Subsequently, 3 authors independently downloaded the apps onto a smartphone and assessed the quality of the apps and their potential for promoting behavior change by using the Mobile App Rating Scale (MARS; number of items: 23; score: range 0-5 [higher is better]) and the App Behavior Change Scale (ABACUS; number of items: 21; score: range 0-21 [higher is better]), respectively. We included the five highest-rated apps and the five most downloaded apps but only assessed free content for their quality and potential for promoting behavior change.

Results

We screened 453 apps and ultimately included 60. Of the 60 apps, 35 (58%) were available in both App Store and Google Play. The overall average quality score of the apps was 3.48 (SD 0.28) on the MARS, and their overall average score for their potential to promote behavior change was 8.07 (SD 2.30) on the ABACUS. Apps for depression and apps for patients with multimorbidity tended to have higher overall MARS and ABACUS scores, respectively. The most common app features for supporting behavior change were the self-monitoring of physiological parameters (eg, blood pressure monitoring; apps: 38/60, 63%), weight and diet (apps: 25/60, 42%), or physical activity (apps: 22/60, 37%) and stress management (apps: 22/60, 37%). Only 8 out of the 60 apps (13%) were completely free.

Conclusions

Apps for patients with a chronic condition or multimorbidity appear to be of acceptable quality but have low to moderate potential for promoting behavior change. Our results provide a useful overview for patients and clinicians who would like to use apps for managing chronic conditions and indicate the need to improve health apps in terms of their quality and potential for promoting behavior change.

Russian-Language Mobile Apps for Reducing Alcohol Use: Systematic Search and Evaluation

BACKGROUND

Personalized prevention tools such as mobile apps designed to reduce alcohol consumption are widespread in mobile app stores accessible in Russia. However, the quality and content of these mobile apps have not been systematically evaluated.

OBJECTIVE

This study aimed to identify Russian-language mobile apps for reducing alcohol use and to evaluate their quality and potential to change alcohol-related health behavior. It further aimed to identify apps that could facilitate screening and brief interventions in primary health care in Russia.

METHODS

A systematic search for mobile apps available in Russia was carried out between April 1 and 15, 2020, December 1 and 15, 2020, and in March 2021 in the iPhone App Store, Google Play Store, and the 4PDA forum. App quality was assessed using the Mobile App Rating Scale (MARS), and structured searches in electronic libraries and bibliographic databases were used to evaluate the apps' evidence base. The number of features facilitating changes in lifestyle behavior was assessed using the App Behavior Change Scale (ABACUS).

RESULTS

We identified 63 mobile apps for reducing alcohol use. The mean MARS quality ratings were high for the subscales of functionality (3.92 out of 5, SD 0.58) and aesthetics (2.96, SD 0.76) and low for engagement (2.42, SD 0.76) and information (1.65, SD 0.60). Additional searches in electronic libraries and bibliographic databases (eLibrary, CyberLeninka, Google Scholar) yielded no studies involving the identified apps. ABACUS scores ranged from 1 to 15 out of 25, with a mean of 5 (SD 3.24). Two of the identified apps might be useful for screening and brief interventions in Russian primary health care after improvements in content and scientific testing.

CONCLUSIONS

Russian-language mobile apps for reducing alcohol use are accessible in the app stores. Many of them are aesthetically pleasing, functional, and easy to use. However, information about their scientific trialing or testing is lacking. Most apps contain a low number of features that facilitate changes in lifestyle behavior. Further research should examine the context of Russian-language mobile apps for reducing alcohol use. Our findings underline the need to develop evidence-based apps to mitigate alcohol consumption in Russia and elsewhere.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42020167458; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=167458.

Patient-Facing Mobile Apps to Support Physiotherapy Care: Protocol for a Systematic Review of Apps Within App Stores

Background

Care delivered by physiotherapists aims to facilitate engagement in positive health behaviors by patients (eg, adherence to exercise). However, research suggests that behavioral interventions are frequently omitted from care. Hence, better understanding of strategies that can be used by physiotherapists to support patients to engage in positive behaviors is important and likely to optimize outcomes. Digital health interventions delivered via mobile apps are garnering attention for their ability to support behavior change. They have potential to incorporate numerous behavior change techniques (BCTs) to support goals of physiotherapy care, including but not limited to self-monitoring, goal setting, and prompts/alerts. Despite their potential to support physiotherapy care, much is still unknown about what apps are available to consumers, the BCTs they use, their quality, and their potential to change behaviors.

Objective

The primary aim of this study is to systematically review the mobile apps available in app stores that are intended for use by patients to support physiotherapy care, including the BCTs within these apps. The secondary aims are to evaluate the quality and behavior change potential of these apps.

Methods

A systematic review of mobile apps in app stores will be undertaken. This will be guided by recommendations for systematic reviews in line with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement but adapted to suit our app store search, consistent with similar systematic reviews of apps published in the Journal of Medical Internet Research. Apple Store and Google Play will be searched with a two-step search strategy, using terms relevant to physiotherapy, physiotherapists, and common physiotherapy care. Key eligibility criteria will include apps that are intended for use by patients and are self-contained or stand-alone without the need of additional wearable devices or other add-ons. Included apps will be coded for BCTs and rated for quality using the Mobile Application Rating Scale (MARS) and for potential to change behavior using the App Behavior Change Scale (ABACUS).

Results

App store search and screening are expected to be completed in 2021. Data extraction and quality appraisal are expected to commence by November 2021. The study results are expected to be published in a subsequent paper in 2022.

Conclusions

Knowledge gained from this review will support clinical practice and inform research by providing a greater understanding of the quality of currently available mobile apps and their potential to support patient behavior change goals of physiotherapy care.

International Registered Report Identifier (IRRID)

PRR1-10.2196/29047

Why Do We Harm the Environment or Our Personal Health despite Better Knowledge? The Knowledge Action Gap in Healthy and Climate-Friendly Behavior

Non-communicable diseases, such as hypertension, diabetes, or depression, result from an interplay of physiological, genetic, behavioral, and environmental aspects. Together with climate change, they are arguably among the most significant challenges mankind faces in the 21st century. Additionally, the bidirectional influences of climate change and health on each other are undisputed. Behavioral changes could curb both climate change and the spread of non-communicable diseases. Much effort has been put into information campaigns in both fields, but success has been limited. In the following, the knowledge action gap is compared and analyzed in healthy and climate-friendly behavior from a practical point of view and the supporting theoretical models are highlighted. The analysis shows that self-efficacy plays an essential role in both areas of research for effecting behavioral changes. The models of ‘Planned Behavior’ and ‘Stages of Change’ seems helpful and can be applied and adapted to explain behavioral changes in health and climate changes settings. We compared two previously unrelated research fields to uncover new avenues for further study and stimulate fruitful transdisciplinary discussion. Future directions on how behavioral medicine and climate change research can learn from each other are discussed.

Selecting and Evaluating Mobile Health Apps for the Healthy Life Trajectories Initiative: Development of the eHealth Resource Checklist

Background

The ubiquity of smartphones and mobile devices in the general population presents an unprecedented opportunity for preventative health. Not surprisingly, the use of electronic health (eHealth) resources accessed through mobile devices in clinical trials is becoming more prevalent; the selection, screening, and collation of quality eHealth resources is necessary to clinical trials using these technologies. However, the constant creation and turnover of new eHealth resources can make this task difficult. Although syntheses of eHealth resources are becoming more common, their methodological and reporting quality require improvement so as to be more accessible to nonexperts. Further, there continues to be significant variation in quality criteria employed for assessment, with no clear method for developing the included criteria. There is currently no single existing framework that addresses all six dimensions of mobile health app quality identified in Agarwal et al’s recent scoping review (ie, basic descriptions of the design and usage of the resource; technical features and accessibility; health information quality; usability; evidence of impact; and user engagement and behavior change). In instances where highly systematic tactics are not possible (due to time constraints, cost, or lack of expertise), there may be value in adopting practical and pragmatic approaches to helping researchers and clinicians identify and disseminate e-resources.

Objective

The study aimed to create a set of guidelines (ie, a checklist) to aid the members of the Healthy Life Trajectories Initiative (HeLTI) Canada trial—a preconception randomized controlled clinical trial to prevent child obesity—to assist their efforts in searching, identifying, screening, and including selected eHealth resources for participant use in the study intervention.

Methods

A framework for searching, screening, and selecting eHealth resources was adapted from the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) checklist for systematic and scoping reviews to optimize the rigor, clarity, and transparency of the process. Details regarding searching, selecting, extracting, and assessing quality of eHealth resources are described.

Results

This study resulted in the systematic development of a checklist consisting of 12 guiding principles, organized in a chronological versus priority sequence to aid researchers in searching, screening, and assessing the quality of various eHealth resources.

Conclusions

The eHealth Resource Checklist will assist researchers in navigating the eHealth resource space by providing a mechanism to detail their process of developing inclusion criteria, identifying search location, selecting and reviewing evidence, extracting information, evaluating the quality of the evidence, and synthesizing the extracted evidence. The overarching goal of this checklist is to provide researchers or generalists new to the eHealth field with a tool that balances pragmatism with rigor and that helps standardize the process of searching and critiquing digital material—a particularly important aspect given the recent explosion of and reliance on eHealth resources. Moreover, this checklist may be useful to other researchers and practitioners developing similar health interventions.

Evaluation of Android and Apple Store Depression Applications Based on Mobile Application Rating Scale

There are a large number of mobile applications that allow the monitoring of health status. The quality of the applications is only evaluated by users and not by standard criteria. This study aimed to examine depression-related applications in major mobile application stores and to analyze them using the rating scale tool Mobile Application Rating Scale (MARS). A search of digital applications for the control of symptoms and behavioral changes in depression was carried out in the two reference mobile operating systems, Apple (App Store) and Android (Play Store), by means of two reviewers with a blind methodology between September and October 2019 in stores from Spain and the United Kingdom. Eighteen applications from the Android Play Store and twelve from the App Store were included in this study. The quality of the applications was evaluated using the MARS scale from 1 (inadequate) to 5 (excellent). The average score of the applications based on the MARS was 3.67 ± 0.53. The sections with the highest scores were “Functionality” (4.51) and “Esthetics” (3.98) and the lowest “Application Subjective quality” (2.86) and “Information” (3.08). Mobile Health applications for the treatment of depression have great potential to influence the health status of users; however, applications come to the digital market without health control.

Content, Behavior Change Techniques, and Quality of Pregnancy Apps in Spain: Systematic Search on App Stores

Background

Women consult information in mobile apps (apps) during pregnancy, and even obstetrics specialists highlight that pregnancy is the ideal moment for the use of apps as consultation sources. However, the high number of apps designed for pregnancy requires a careful assessment to determine their suitability before recommendation.

Objective

The aim of this study is to identify the apps available in Spanish that can be recommended based on their content, behavior change techniques (BCTs), and quality as a complementary tool during pregnancy.

Methods

A systematic search on app stores to identify apps was performed in the Apple App Store and Google Play with the subject term “pregnancy.” The apps meeting the following criteria were chosen: pregnancy-related content, free, and available in Spanish. An app was excluded if it was classified as a game or entertainment and thus lacking an educational or health aim and if it did not target the population under study. The selected apps were downloaded, and their quality was assessed using the Mobile Application Rating Scale (MARS), with the BCTs included evaluated using the BCT taxonomy version 1 and its content.

Results

A total of 457 apps were identified, 25 of which were downloaded for assessment (5.6%). The median for objective and subjective quality was 2.94 (IQR 2.71-3.46) and 1.75 (IQR 1.25-2.25), respectively. Regarding content, the median of topics included in the apps was 23 (IQR 16-23), with weight gain, nutrition, fetal development, and physical activity being the most common. The median number of BCTs was 12 (IQR 0.5-3.5). The most frequently identified BCTs in the apps were “Self-Monitoring of Outcomes,” followed by “Goal Behavior” and “Instructions.” Statistically significant correlations were observed between objective quality and content (ρ=0.624; P=.001), subjective quality and content (ρ=0.638; P=.001), objective quality and BCTs (ρ=0.672; P<.001), subjective quality and BCTs (ρ=0.623; P<.001), and BCTs and content (ρ=0.580; P=.002).

Conclusions

The results of this study suggest that only a small percentage of free pregnancy apps available in Spanish should be recommended. The apps with the best MARS scores were those that addressed a higher number of topics and included a higher number of BCTs. Those with the best content and quality, and a higher number of BCTs included could be recommended by health professionals.

Identification and Evaluation of Methodologies to Assess the Quality of Mobile Health Apps in High-, Low-, and Middle-Income Countries: Rapid Review

BACKGROUND

In recent years, there has been rapid growth in the availability and use of mobile health (mHealth) apps around the world. A consensus regarding an accepted standard to assess the quality of such apps has yet to be reached. A factor that exacerbates the challenge of mHealth app quality assessment is variations in the interpretation of quality and its subdimensions. Consequently, it has become increasingly difficult for health care professionals worldwide to distinguish apps of high quality from those of lower quality. This exposes both patients and health care professionals to unnecessary risks. Despite progress, limited understanding of the contributions of researchers in low- and middle-income countries (LMICs) exists on this topic. Furthermore, the applicability of quality assessment methodologies in LMIC settings remains relatively unexplored.

OBJECTIVE

This rapid review aims to identify current methodologies in the literature to assess the quality of mHealth apps, understand what aspects of quality these methodologies address, determine what input has been made by authors from LMICs, and examine the applicability of such methodologies in LMICs.

METHODS

This review was registered with PROSPERO (International Prospective Register of Systematic Reviews). A search of PubMed, EMBASE, Web of Science, and Scopus was performed for papers related to mHealth app quality assessment methodologies, which were published in English between 2005 and 2020. By taking a rapid review approach, a thematic and descriptive analysis of the papers was performed.

RESULTS

Electronic database searches identified 841 papers. After the screening process, 52 papers remained for inclusion. Of the 52 papers, 5 (10%) proposed novel methodologies that could be used to evaluate mHealth apps of diverse medical areas of interest, 8 (15%) proposed methodologies that could be used to assess apps concerned with a specific medical focus, and 39 (75%) used methodologies developed by other published authors to evaluate the quality of various groups of mHealth apps. The authors in 6% (3/52) of papers were solely affiliated to institutes in LMICs. A further 15% (8/52) of papers had at least one coauthor affiliated to an institute in an LMIC.

CONCLUSIONS

Quality assessment of mHealth apps is complex in nature and at times subjective. Despite growing research on this topic, to date, an all-encompassing appropriate means for evaluating the quality of mHealth apps does not exist. There has been engagement with authors affiliated to institutes across LMICs; however, limited consideration of current generic methodologies for application in LMIC settings has been identified.

TRIAL REGISTRATION

PROSPERO CRD42020205149; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=205149.

Assessing Apps for Health Care Workers Using the ISYScore-Pro Scale: Development and Validation Study

Background

The presence of mobile phone and smart devices has allowed for the use of mobile apps to support patient care. However, there is a paucity in our knowledge regarding recommendations for mobile apps specific to health care professionals.

Objective

The aim of this study is to establish a validated instrument to assess mobile apps for health care providers and health systems. Our objective is to create and validate a tool that evaluates mobile health apps aimed at health care professionals based on a trust, utility, and interest scale.

Methods

A five-step methodology framework guided our approach. The first step consisted of building a scale to evaluate apps for health care professionals based on a literature review. This was followed with expert panel validation through a Delphi method of (rated) web-based questionnaires to empirically evaluate the inclusion and weight of the indicators identified through the literature review. Repeated iterations were followed until a consensus greater than 75% was reached. The scale was then tested using a pilot to assess reliability. Interrater agreement of the pilot was measured using a weighted Cohen kappa.

Results

Using a literature review, a first draft of the scale was developed. This was followed with two Delphi rounds between the local research group and an external panel of experts. After consensus was reached, the resulting ISYScore-Pro 17-item scale was tested. A total of 280 apps were originally identified for potential testing (140 iOS apps and 140 Android apps). These were categorized using International Statistical Classification of Diseases, Tenth Revision. Once duplicates were removed and they were downloaded to confirm their specificity to the target audience (ie, health care professionals), 66 remained. Of these, only 18 met the final criteria for inclusion in validating the ISYScore-Pro scale (interrator reliabilty 92.2%; kappa 0.840, 95% CI 0.834-0.847; P<.001).

Conclusions

We have developed a reproducible methodology to objectively evaluate mobile health apps targeted to health care professionals and providers, the ISYScore-Pro scale. Future research will be needed to adapt the scale to other languages and across other domains (eg, legal compliance or security).

Efficacy of a Just-in-Time Adaptive Intervention to Promote HIV Risk Reduction Behaviors Among Young Adults Experiencing Homelessness: Pilot Randomized Controlled Trial

BACKGROUND

People experiencing homelessness have higher rates of HIV than those who are stably housed. Mental health needs, substance use problems, and issues unique to homelessness such as lack of shelter and transiency need to be considered with regard to HIV prevention. To date, HIV prevention interventions for young adults experiencing homelessness have not specifically addressed modifiable real-time factors such as stress, sexual or drug use urge, or substance use, or been delivered at the time of heightened risk. Real-time, personalized HIV prevention messages may reduce HIV risk behaviors.

OBJECTIVE

This pilot study tested the initial efficacy of an innovative, smartphone-based, just-in-time adaptive intervention that assessed predictors of HIV risk behaviors in real time and automatically provided behavioral feedback and goal attainment information.

METHODS

A randomized attention control design was used among young adults experiencing homelessness, aged 18-25 years, recruited from shelters and drop-in centers in May 2019. Participants were randomized to either a control or an intervention group. The intervention (called MY-RID [Motivating Youth to Reduce Infection and Disconnection]) consisted of brief messages delivered via smartphone over 6 weeks in response to preidentified predictors that were assessed using ecological momentary assessments. Bayesian hierarchical regression models were used to assess intervention effects on sexual activity, drug use, alcohol use, and their corresponding urges.

RESULTS

Participants (N=97) were predominantly youth (mean age 21.2, SD 2.1 years) who identified as heterosexual (n=51, 52%), male (n=56, 57%), and African American (n=56, 57%). Reports of sexual activity, drug use, alcohol use, stress, and all urges (ie, sexual, drug, alcohol) reduced over time in both groups. Daily drug use reduced by a factor of 13.8 times over 6 weeks in the intervention group relative to the control group (Multimedia Appendix 4). Lower urges for sex were found in the intervention group relative to the control group over the duration of the study. Finally, there was a statistically significant reduction in reports of feeling stressed the day before between the intervention and control conditions (P=.03).

CONCLUSIONS

Findings indicate promising intervention effects on drug use, stress, and urges for sex in a hard-to-reach, high-risk population. The MY-RID intervention should be further tested in a larger randomized controlled trial to further investigate its efficacy and impact on sexual risk behaviors.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03911024; https://clinicaltrials.gov/ct2/show/NCT03911024.

Perceptions and Acceptability of a Smartphone App Intervention (ChildSafe) in Malaysia: Qualitative Exploratory Study

BACKGROUND

Home is a vulnerable place for accidental child injuries. Unintentional injuries are a leading cause of death, hospitalization, and disabilities. These injuries are considered preventable and if not tackled, they will continue to be a persisting problem. Smartphones have become increasingly important in our everyday life and is an important tool not only for communication but also for other purposes-they have apps that can be used for various purposes. Therefore, an app-based intervention (ChildSafe) was developed to assess and reduce child injury at home.

OBJECTIVE

This study aimed to evaluate the acceptance of the ChildSafe smartphone app intervention by parents/guardians.

METHODS

This study was conducted using a qualitative exploratory approach on selected participants of the ChildSafe intervention app study. A total of 27 semistructured in-depth interviews were carried out among parents or guardians who have at least one child between the age of 0 and 59 months in the area of Sungai Buloh, Selangor, between November 2017 and March 2018. Interview questions were developed from the consolidated framework for implementation research (CFIR). Interviews were recorded, transcribed verbatim, and data were thematically analyzed guided by CFIR.

RESULTS

The study revealed users' perception on usability, feasibility, and acceptability toward the ChildSafe app. Three CFIR domains were identified: intervention characteristics, inner setting, and characteristics of individuals. A total of 5 constructs were revealed under intervention characteristics: evidence strength and quality, relative advantage, adaptability, trialability, and design quality and packaging; 2 under inner setting: implementation climate and readiness for implementation; and 4 under characteristics of individuals: knowledge and beliefs about the intervention, self-efficacy, individual stage of change, and other personal attributes. In general, participants felt the app is extremely useful and effective, easy to use, and purposeful in achieving home safety assessment via reminders. The app replaces the need for participants to search for information on home safety and dangers, as the app itself was designed as a tool to assess for this specific purpose. Even at the nascent stage and despite its limitations, the app has prompted users to consider and make changes around their own home. However, future versions of the app should be expanded to make it more attractive to users as it lacks interactive feedback and additional features.

CONCLUSIONS

Parents/guardians are accepting the use of the ChildSafe app to prevent child injury at home. However, further expansion and improvements are needed to increase the acceptability of this app by parents/guardians.

Atrial fibrillation self-management: a mobile telephone app scoping review and content analysis

Atrial fibrillation (AF) affects over 1.4 million people in the UK, resulting in a five-fold increased stroke risk and a three to four times greater risk of severe, disabling stroke. Atrial fibrillation, a chronic disease, requires monitoring, medication, and lifestyle measures. A self-management approach supported by mobile health (mHealth) may empower AF self-care. To assess the need to develop new mHealth self-management interventions for those with AF this review aimed to identify commercially available AF self-management apps, analyse, and synthesize (i) characteristics, (ii) functions, (iii) privacy/security, (iv) incorporated behaviour change techniques (BCTs), and (v) quality and usability. We searched app stores for 'atrial fibrillation' and 'anticoagulation', and included apps focused on AF self-management in the review. We examined app functions, privacy statements against best practice recommendations, the inclusion of BCTs using the App Behaviour Change Scale, and app quality/usability using the Mobile App Rating Scale. From an initial search of 555 apps, five apps were included in the review. Common functions were educational content, medication trackers, and communication with healthcare professionals. Apps contained limited BCTs, lacked intuitive functions and were difficult to use. Privacy policies were difficult to read. App quality rated from poor to acceptable and no app had been evaluated in a clinical trial. The review reports a lack of commercially available AF self-management apps of sufficient standard for use in healthcare settings. This highlights the need for clinically validated mHealth interventions incorporating evidence-based BCTs to support AF self-management.

An App-Based Parenting Program to Promote Healthy Energy Balance-Related Parenting Practices to Prevent Childhood Obesity: Protocol Using the Intervention Mapping Framework

BACKGROUND

The family environment plays an important role in the development of children's energy balance-related behaviors. As a result, parents' energy balance-related parenting practices are important targets of preventive childhood obesity programs. Families with a lower socioeconomic position (SEP) may benefit from participating in such programs but are generally less well reached than families with a higher SEP.

OBJECTIVE

This paper describes the application of the Intervention Mapping Protocol (IMP) for the development of an app-based preventive intervention program to promote healthy energy balance-related parenting practices among parents of children (aged 0-4 years) with a lower SEP.

METHODS

The 6 steps of the IMP were used as a theory- and evidence-based framework to guide the development of an app-based preventive intervention program.

RESULTS

In step 1, behavioral outcomes for the app-based program (ie, children have a healthy dietary intake, sufficient sleep, and restricted screen time and sufficient physical activity) and sociocognitive (ie, knowledge, attitudes, and self-efficacy) and automatic (ie, habitual behaviors) determinants of energy balance-related parenting were identified through a needs assessment. In step 2, the behavioral outcomes were translated into performance objectives. To influence these objectives, in step 3, theory-based intervention methods were selected for each of the determinants. In step 4, the knowledge derived from the previous steps allowed for the development of the app-based program Samen Happie! through a process of continuous cocreation with parents and health professionals. In step 5, community health services were identified as potential adopters for the app. Finally, in step 6, 2 randomized controlled trials were designed to evaluate the process and effects of the app among Dutch parents of infants (trial 1) and preschoolers (trial 2). These trials were completed in November 2019 (trial 1) and February 2020 (trial 2).

CONCLUSIONS

The IMP allowed for the effective development of the app-based parenting program Samen Happie! to promote healthy energy balance-related parenting practices among parents of infants and preschoolers. Through the integration of theory, empirical evidence, and data from the target population, as well as the process of continued cocreation, the program specifically addresses parents with a lower SEP. This increases the potential of the program to prevent the development of obesity in early childhood among families with a lower SEP.

TRIAL REGISTRATION

Netherlands Trial Register NL6727, https://www.trialregister.nl/trial/6727; Netherlands Trial Register NL7371, https://www.trialregister.nl/trial/7371.

Digital interventions for the management of chronic obstructive pulmonary disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is associated with dyspnoea, cough or sputum production (or both) and affects quality of life and functional status. More efficient approaches to alternative management that may include patients themselves managing their condition need further exploration in order to reduce the impact on both patients and healthcare services. Digital interventions may potentially impact on health behaviours and encourage patient engagement.

OBJECTIVES

To assess benefits and harms of digital interventions for managing COPD and apply Behaviour Change Technique (BCT) taxonomy to describe and explore intervention content.

SEARCH METHODS

We identified randomised controlled trials (RCTs) from the Cochrane Airways Trials Register (date of last search 28 April 2020). We found other trials at web-based clinical trials registers.

SELECTION CRITERIA

We included RCTs comparing digital technology interventions with or without routine supported self-management to usual care, or control treatment for self-management. Multi-component interventions (of which one component was digital self-management) compared with usual care, standard care or control treatment were included.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods. Two review authors independently selected trials for inclusion, extracted data, and assessed risk of bias. Discrepancies were resolved with a third review author. We assessed certainty of the evidence using the GRADE approach. Primary outcomes were impact on health behaviours, self-efficacy, exacerbations and quality of life, including the St George's Respiratory Questionnaire (SGRQ). The minimally important difference (MID) for the SGRQ is 4 points. Two review authors independently applied BCT taxonomy to identify mechanisms in the digital interventions that influence behaviours.

MAIN RESULTS

Fourteen studies were included in the meta-analyses (1518 participants) ranging from 13 to 52 weeks duration. Participants had mild to very severe COPD. Risk of bias was high due to lack of blinding. GRADE ratings were low to very low certainty due to lack of blinding and imprecision. Common BCT clusters identified as behaviour change mechanisms in interventions were goals and planning, feedback and monitoring, social support, shaping knowledge and antecedents. Digital technology intervention with or without routine supported self-management Interventions included mobile phone (three studies), smartphone applications (one study), and web or Internet-based (five studies). Evidence is very uncertain about effects on impact on health behaviours as measured by six-minute walk distance (6MWD) at 13 weeks (mean difference (MD) 26.20, 95% confidence interval (CI) -21.70 to 74.10; participants = 122; studies = 2) or 23 to 26 weeks (MD 14.31, 95% CI -19.41 to 48.03; participants = 164; studies = 3). There may be improvement in 6MWD at 52 weeks (MD 54.33 95% CI -35.47 to 144.12; participants = 204; studies = 2) but studies were varied (very low certainty). There may be no difference in self-efficacy on managing Chronic Disease Scale (SEMCD) or pulmonary rehabilitation adapted index of self-efficacy tool (PRAISE). Evidence is very uncertain. Quality of life may be slightly improved on the chronic respiratory disease questionnaire (CRQ) at 13 weeks (MD 0.45, 95% CI 0.01 to 0.90; participants = 123; studies = 2; low certainty), but is not clinically important (MID 0.5). There may be little or no difference at 23 or 52 weeks (low to very low certainty). There may be a clinical improvement on SGRQ total at 52 weeks (MD -26.57, 95% CI -34.09 to -19.05; participants = 120; studies = 1; low certainty). Evidence for COPD assessment test (CAT) and Clinical COPD Questionnaire (CCQ) is very uncertain. There may be little or no difference in dyspnoea symptoms (CRQ dyspnoea) at 13, 23 weeks or 52 weeks (low to very low certainty evidence) or mean number of exacerbations at 26 weeks (low-certainty evidence). There was no evidence for the number of people experiencing adverse events. Multi-component interventions Digital components included mobile phone (one study), and web or internet-based (four studies). Evidence is very uncertain about effects on impact on health behaviour (6MWD) at 13 weeks (MD 99.60, 95% CI -15.23 to 214.43; participants = 20; studies = 1). No evidence was found for self-efficacy. Four studies reported effects on quality of life (SGRQ and CCQ scales). The evidence is very uncertain. There may be no difference in the number of people experiencing exacerbations or mean days to first exacerbation at 52 weeks with a multi-component intervention compared to standard care. Evidence is very uncertain about effects on the number of people experiencing adverse events at 52 weeks.

AUTHORS' CONCLUSIONS

There is insufficient evidence to demonstrate a clear benefit or harm of digital technology interventions with or without supported self-management, or multi-component interventions compared to usual care in improving the 6MWD or self-efficacy. We found there may be some short-term improvement in quality of life with digital interventions, but there is no evidence about whether the effect is sustained long term. Dyspnoea symptoms may improve over a longer duration of digital intervention use. The evidence for multi-component interventions is very uncertain and as there is little or no evidence for adverse events, we cannot determine the benefit or harm of these interventions. The evidence base is predominantly of very low certainty with concerns around high risk of bias due to lack of blinding. Given that variation of interventions and blinding is likely to be a concern, future, larger studies are needed taking these limitations in consideration. Future studies are needed to determine whether the small improvements observed in this review can be applied to the general COPD population. A clear understanding of behaviour change through the BCT classification is important to gauge uptake of digital interventions and health outcomes in people with varying severity of COPD. Currently there is no guidance for interpreting BCT components of a digital intervention for changes to health outcomes. We could not interpret the BCT findings to the health outcomes we were investigating due to limited evidence that was of very low certainty. In future research, standardised approaches need to be considered when designing protocols to investigate effectiveness of digital interventions by including a standardised approach to BCT classification in addition to validated behavioural outcome measures that may reflect changes in behaviour.

Assessing the Quality of Mobile Health-Related Apps: Interrater Reliability Study of Two Guides

Background

There is a huge number of health-related apps available, and the numbers are growing fast. However, many of them have been developed without any kind of quality control. In an attempt to contribute to the development of high-quality apps and enable existing apps to be assessed, several guides have been developed.

Objective

The main aim of this study was to study the interrater reliability of a new guide — the Mobile App Development and Assessment Guide (MAG) — and compare it with one of the most used guides in the field, the Mobile App Rating Scale (MARS). Moreover, we also focused on whether the interrater reliability of the measures is consistent across multiple types of apps and stakeholders.

Methods

In order to study the interrater reliability of the MAG and MARS, we evaluated the 4 most downloaded health apps for chronic health conditions in the medical category of IOS and Android devices (ie, App Store and Google Play). A group of 8 reviewers, representative of individuals that would be most knowledgeable and interested in the use and development of health-related apps and including different types of stakeholders such as clinical researchers, engineers, health care professionals, and end users as potential patients, independently evaluated the quality of the apps using the MAG and MARS. We calculated the Krippendorff alpha for every category in the 2 guides, for each type of reviewer and every app, separately and combined, to study the interrater reliability.

Results

Only a few categories of the MAG and MARS demonstrated a high interrater reliability. Although the MAG was found to be superior, there was considerable variation in the scores between the different types of reviewers. The categories with the highest interrater reliability in MAG were “Security” (α=0.78) and “Privacy” (α=0.73). In addition, 2 other categories, “Usability” and “Safety,” were very close to compliance (health care professionals: α=0.62 and 0.61, respectively). The total interrater reliability of the MAG (ie, for all categories) was 0.45, whereas the total interrater reliability of the MARS was 0.29.

Conclusions

This study shows that some categories of MAG have significant interrater reliability. Importantly, the data show that the MAG scores are better than the ones provided by the MARS, which is the most commonly used guide in the area. However, there is great variability in the responses, which seems to be associated with subjective interpretation by the reviewers.

Assessing the quality of mobile applications in chronic disease management: a scoping review

While there has been a rapid growth of digital health apps to support chronic diseases, clear standards on how to best evaluate the quality of these evolving tools are absent. This scoping review aims to synthesize the emerging field of mobile health app quality assessment by reviewing criteria used by previous studies to assess the quality of mobile apps for chronic disease management. A literature review was conducted in September 2017 for published studies that use a set of quality criteria to directly evaluate two or more patient-facing apps supporting promote chronic disease management. This resulted in 8182 citations which were reviewed by research team members, resulting in 65 articles for inclusion. An inductive coding schema to synthesize the quality criteria utilized by included articles was developed, with 40 unique quality criteria identified. Of the 43 (66%) articles that reported resources used to support criteria selection, 19 (29%) used clinical guidelines, and 10 (15%) used behavior change theory. The most commonly used criteria included the presence of user engagement or behavior change functions (97%, n = 63) and technical features of the app such as customizability (20%, n = 13, while Usability was assessed by 24 studies (36.9%). This study highlights the significant variation in quality criteria employed for the assessment of mobile health apps. Future methods for app evaluation will benefit from approaches that leverage the best evidence regarding the clinical impact and behavior change mechanisms while more directly reflecting patient needs when evaluating the quality of apps.

Tablet-Based Apps for Phonics and Phonological Awareness: Protocol for Evidence-Based Appraisal of Content, Quality, and Usability

Background

The use of mobile apps to manage and promote health is becoming increasingly popular. Mobile apps are gaining popularity particularly in educational and interventional settings owing to their perceived advantages including support for and engagement of individuals with reading difficulties. In the context of COVID-19, the need for technology-based tools has increased. For practitioners and educators who wish to use apps in their practice or recommend apps to individuals with reading difficulties, it is challenging to identify high-quality apps in app stores.

Objective

This protocol describes a systematic search, selection, and appraisal process for tablet apps targeting phonics knowledge and phonological awareness skills. This protocol aimed to (1) provide a systematic method for identifying tablet apps targeting phonics knowledge and phonological awareness skills in the Google Play Store and Apple’s App Store and (2) describe an evidence-based approach for quality appraisal of these apps by using structured tools.

Methods

This protocol describes an evidence-based method guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework to systematically search, select, and appraise apps targeting phonics knowledge and phonological awareness skills, present in Google Play and the App Store. We intend to perform a systematic and comprehensive search and a 2-step process for screening: (1) broad screening (app titles) and (2) narrow screening (marketing descriptions). Quality appraisal of the included apps will involve two structured appraisal tools: (1) the Mobile Application Rating Scale and (2) the Appraising Apps for Reading Checklist.

Results

This method will help determine the number of apps targeting phonics knowledge and phonological awareness, present on the Android and iOS platforms. The content, quality, and usability of these apps will be determined using structured appraisal tools. We have planned to conduct searches on Google Play and the App Store in January-March 2021; broad and focused screening, from April 2021; and data extraction and quality appraisal in October 2021.

Conclusions

This protocol provides a basis for locating and evaluating apps targeting phonics knowledge and phonological awareness skills. This protocol will support practitioners, educators, and families to make informed decisions when purchasing apps for instructional use.

International Registered Report Identifier (IRRID)

PRR1-10.2196/23921

Effectiveness of Mobile Apps to Promote Health and Manage Disease: Systematic Review and Meta-analysis of Randomized Controlled Trials

BACKGROUND

Interventions aimed at modifying behavior for promoting health and disease management are traditionally resource intensive and difficult to scale. Mobile health apps are being used for these purposes; however, their effects on health outcomes have been mixed.

OBJECTIVE

This study aims to summarize the evidence of rigorously evaluated health-related apps on health outcomes and explore the effects of features present in studies that reported a statistically significant difference in health outcomes.

METHODS

A literature search was conducted in 7 databases (MEDLINE, Scopus, PsycINFO, CINAHL, Global Index Medicus, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews). A total of 5 reviewers independently screened and extracted the study characteristics. We used a random-effects model to calculate the pooled effect size estimates for meta-analysis. Sensitivity analysis was conducted based on follow-up time, stand-alone app interventions, level of personalization, and pilot studies. Logistic regression was used to examine the structure of app features.

RESULTS

From the database searches, 8230 records were initially identified. Of these, 172 met the inclusion criteria. Studies were predominantly conducted in high-income countries (164/172, 94.3%). The majority had follow-up periods of 6 months or less (143/172, 83.1%). Over half of the interventions were delivered by a stand-alone app (106/172, 61.6%). Static/one-size-fits-all (97/172, 56.4%) was the most common level of personalization. Intervention frequency was daily or more frequent for the majority of the studies (123/172, 71.5%). A total of 156 studies involving 21,422 participants reported continuous health outcome data. The use of an app to modify behavior (either as a stand-alone or as part of a larger intervention) confers a slight/weak advantage over standard care in health interventions (standardized mean difference=0.38 [95% CI 0.31-0.45]; I2=80%), although heterogeneity was high.

CONCLUSIONS

The evidence in the literature demonstrates a steady increase in the rigorous evaluation of apps aimed at modifying behavior to promote health and manage disease. Although the literature is growing, the evidence that apps can improve health outcomes is weak. This finding may reflect the need for improved methodological and evaluative approaches to the development and assessment of health care improvement apps.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42018106868; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=106868.

Adding team-based financial incentives to the Carrot Rewards physical activity app increases daily step count on a population scale: a 24-week matched case control study

Background

Mobile health applications (mHealth apps) targeting physical inactivity have increased in popularity yet are usually limited by low engagement. This study examined the impact of adding team-based incentives (Step Together Challenges, STCs) to an existing mHealth app (Carrot Rewards) that rewarded individual physical activity achievements.

Methods

A 24-week quasi-experimental study (retrospective matched pairs design) was conducted in three Canadian provinces (pre-intervention: weeks 1–12; intervention: weeks 13–24). Participants who used Carrot Rewards and STCs (experimental group) were matched with those who used Carrot Rewards only (controls) on age, gender, province and baseline mean daily step count (±500 steps/d). Carrot Rewards users earned individual-level incentives (worth $0.04 CAD) each day they reached a personalized daily step goal. With a single partner, STC users could earn team incentives ($0.40 CAD) for collaboratively reaching individual daily step goals 10 times in seven days (e.g., Partner A completes four goals and Partner B completes six goals in a week).

Results

The main analysis included 61,170 users (mean age = 32 yrs.; % female = 64). Controlling for pre-intervention mean daily step count, a significant difference in intervention mean daily step count favoured the experimental group (p < 0.0001; η_p² = 0.024). The estimated marginal mean group difference was 537 steps per day, or 3759 steps per week (about 40 walking min/wk). Linear regression suggested a dose-response relationship between the number of STCs completed (app engagement) and intervention mean daily step count (adjusted R² = 0.699) with each new STC corresponding to approximately 200 more steps per day.

Conclusion

Despite an explosion of physical activity app interest, low engagement leading to small or no effects remains an industry hallmark. In this paper, we found that adding modest team-based incentives to the Carrot Rewards app increased mean daily step count, and importantly, app engagement moderated this effect. Others should consider novel small-teams based approaches to boost engagement and effects.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-020-01043-1.

The use of the behaviour change wheel in the development of ParticipACTION's physical activity app

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Mobile apps rooted in theory have been successful at changing health behaviours.

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ParticipACTION created a mobile app to increase Canadians’ physical activity levels.

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The mobile app development was guided by the Behaviour Change Wheel framework.

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Users’ capability, opportunity and motivation were targeted within the app.

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Five clusters of behaviour change techniques were used to target behaviour change.

The purpose of this study was to provide a detailed and systematic outline of how a theoretical behaviour change framework was applied in the development of ParticipACTION’s app to support a more active Canada. The app development process was guided by the Behaviour Change Wheel (BCW) framework, a theoretically-based approach for intervention development, in collaboration with the commercial app industry. Specifically, a behavioural diagnosis was used to understand what needs to change for the targeted behaviour to occur. Current literature, along with a series of surveys, and market research informed app development. Additionally, a validated app behaviour change scale, was consulted throughout development to help ensure app features maximized behaviour change potential. The behavioural diagnosis revealed that the app needed to target individuals’ physical and psychological capabilities, physical and social opportunities, and reflective and automatic motivations in order to increase physical activity levels. To accomplish this, 6 of a possible 9 intervention functions and 2 of 7 policy categories were selected from the BCW to be included in the app. Goals and planning, feedback and monitoring, behaviour identification, action planning and knowledge shaping were selected as the main behaviour change techniques for the app. Collaboration with a mobile app development firm helped to embed the selected behaviour change techniques, policy categories, intervention functions, and sources of behaviour within the app. Using a systematic approach, this study used the BCW to ensure the health promotion app was theoretically informed. Future research will evaluate its effectiveness in increasing the physical activity of Canadians.

A Personalized Physical Activity Coaching App for Breast Cancer Survivors: Design Process and Early Prototype Testing

Background

Existing evidence supports the many benefits of physical activity (PA) in breast cancer survival. However, few breast cancer survivors adhere to the recommended levels of activity. A PA coaching app that provides personalized feedback, guidance, and motivation to the user might have the potential to engage these individuals in a more active lifestyle, in line with the general recommendations. To develop a successful tool, it is important to involve the end users in the design process and to make theoretically grounded design decisions.

Objective

This study aimed to execute the design process and early prototype evaluation of a personalized PA coaching app for posttreatment breast cancer survivors. In particular, the study explored a design combining behavioral theory and tailored coaching strategies.

Methods

The design process was led by a multidisciplinary team, including technical and health professionals, and involved input from a total of 22 survivors. The process comprised 3 stages. In stage 1, the literature was reviewed and 14 patients were interviewed to understand the needs and considerations of the target population toward PA apps. In stage 2, the global use case for the tool was defined, the features were ideated and refined based on theory, and a digital interactive prototype was created. In stage 3, the prototype went through usability testing with 8 patients and was subjected to quality and behavior change potential evaluations by 2 human-computer interaction experts.

Results

The design process has led to the conceptualization of a personalized coaching app for walking activities that addresses the needs of breast cancer survivors. The main features of the tool include a training plan and schedule, adaptive goal setting, real-time feedback and motivation during walking sessions, activity status through the day, activity history, weekly summary reports, and activity challenges. The system was designed to measure users’ cadence during walking, use this measure to infer their training zone, and provide real-time coaching to control the intensity of the walking sessions. The outcomes from user testing and expert evaluation of the digital prototype were very positive, with scores from the system usability scale, mobile app rating scale, and app behavior change scale of 95 out of 100, 4.6 out of 5, and 15 out of 21, respectively.

Conclusions

Implementing a user-centered design approach for the development and early evaluation of an app brings essential considerations to tailor the solution to the user’s needs and context. In addition, informing the design on behavioral and tailored coaching theories supports the conceptualization of the PA coaching system. This is critical for optimizing the usability, acceptability, and long-term effectiveness of the tool. After successful early in-laboratory testing, the app will be developed and evaluated in a pilot study in a real-world setting.

Obesity Applications in Smartphones: Development and Use of an Evaluation Tool

INTRODUCTION

Rates of obesity amongst children and teens in the United States have tripled since the 1970s, and 18.5% are now considered obese. With smartphone use among children and teens becoming the norm, smartphone applications may be a cost-effective solution to support patients and families motivated to change lifestyle behaviors and reduce obesity. The purpose of this quality-improvement project was (1) to develop an app evaluation tool and star rating system based on scientific evidence and current clinical practice guidelines in managing childhood obesity, and (2) to determine whether an in-service training can increase provider knowledge and efficacy in the use of smartphone apps in managing childhood obesity.

METHODS

An app evaluation tool (Ped-WHAT) was developed that includes evidence-based behavior modification strategies (BMS) and the American Academy of Pediatrics (AAP) guidelines for healthy weight management in pediatrics. Apps were given a rating based on the number of these criteria included in the app. An educational in-service training was developed to assist health care providers in using the app evaluation tool with patients. This training was tested with providers working in a pediatric weight management clinic. Pre- and post-training surveys were administered. Results were analyzed using t tests to assess differences.

RESULTS

Sixteen commercially available apps were evaluated using the Ped-WHAT tool. Those that included the greatest number of BMS and AAP criteria received the highest rating on a 0-5 scale. Statistically significant improvements in provider knowledge and confidence were found after the in-service training.

DISCUSSION

In this current digital environment, commercially available weight management apps should undergo evaluation by health care providers to ensure that they follow the standard of care and current practice guidelines/recommendations.

Design and testing of a mobile health application rating tool

Mobile health applications ("apps") have rapidly proliferated, yet their ability to improve outcomes for patients remains unclear. A validated tool that addresses apps' potentially important dimensions has not been available to patients and clinicians. The objective of this study was to develop and preliminarily assess a usable, valid, and open-source rating tool to objectively measure the risks and benefits of health apps. We accomplished this by using a Delphi process, where we constructed an app rating tool called THESIS that could promote informed app selection. We used a systematic process to select chronic disease apps with ≥4 stars and <4-stars and then rated them with THESIS to examine the tool's interrater reliability and internal consistency. We rated 211 apps, finding they performed fair overall (3.02 out of 5 [95% CI, 2.96-3.09]), but especially poorly for privacy/security (2.21 out of 5 [95% CI, 2.11-2.32]), interoperability (1.75 [95% CI, 1.59-1.91]), and availability in multiple languages (1.43 out of 5 [95% CI, 1.30-1.56]). Ratings using THESIS had fair interrater reliability (κ = 0.3-0.6) and excellent scale reliability (ɑ = 0.85). Correlation with traditional star ratings was low (r = 0.24), suggesting THESIS captures issues beyond general user acceptance. Preliminary testing of THESIS suggests apps that serve patients with chronic disease could perform much better, particularly in privacy/security and interoperability. THESIS warrants further testing and may guide software and policymakers to further improve app performance, so apps can more consistently improve patient outcomes.

Analysis of Secure Apps for Daily Clinical Use by German Orthopedic Surgeons: Searching for the "Needle in a Haystack"

Background

It is undeniable that appropriate smartphone apps offer enormous opportunities for dealing with future challenges in orthopedic surgery and public health, in general. However, it is still unclear how the apps currently available in the two major app stores can be used in daily clinical routine by German orthopedic surgeons.

Objective

This study aimed to gain evidence regarding the quantity and quality of apps available in the two major app stores and their suitability for use by orthopedic surgeons in Germany.

Methods

We conducted a systematic, keyword-based app store screening to obtain evidence concerning the quantity and quality of commercially available apps. Apps that met the inclusion criteria were evaluated using the app synopsis–checklist for users and the German Mobile App Rating Scale for secure use, trustworthiness, and quality.

Results

The investigation revealed serious shortcomings regarding legal and medical aspects. Furthermore, most apps turned out to be useless and unsuitable for the clinical field of application (4242/4249, 99.84%). Finally, 7 trustworthy and high-quality apps (7/4249, 0.16%) offering secure usage in the daily clinical routine of orthopedists were identified. These apps mainly focused on education (5/7). None of them were CE (Conformité Européenne) certified. Moreover, there are no studies providing evidence that these apps have any positive use whatsoever.

Conclusions

The data obtained in our study suggest that the number of trustworthy and high-quality apps on offer is extremely low. Nowadays, finding appropriate apps in the fast-moving, complex, dynamic, and rudimentarily controlled app stores is most challenging. Promising approaches, for example, systematic app store screenings, app-rating developments, reviews or app libraries, and the creation of consistent standards have been established. However, further efforts are necessary to ensure that these innovative mobile health apps not only provide the correct information but are also safe to use in daily clinical practice.

Commercial app use linked with sustained physical activity in two Canadian provinces: a 12-month quasi-experimental study

Background

Top tier commercial physical activity apps rarely undergo peer-reviewed evaluation. Even fewer are assessed beyond six months, the theoretical threshold for behaviour maintenance. The purpose of this study was to examine whether a multi-component commercial app rewarding users with digital incentives for walking was associated with an increase in physical activity over one year.

Methods

This 12-month quasi-experimental study was conducted in two Canadian provinces (n = 39,113 participants). Following a two-week baseline period, participants earned digital incentives ($0.04 CAD/day) every day they reached a personalized daily step goal. Mixed-effects models estimated changes in weekly mean daily step count between the baseline period and the last two recorded weeks. Models were fit for several engagement groups and separately by baseline physical activity status within engagement groups.

Results

Nearly half of participants (43%) were categorized as physically inactive at baseline (fewer than 5000 daily steps), and 60% engaged with the app for at least six months [‘Regular’ (24–51 weeks of step data) or ‘Committed’ sub-groups (52 weeks)]. Weekly mean daily step count increased for physically inactive users regardless of engagement status (P < .0001). The increase was largest for ‘Regular’ and ‘Committed’ participants—1215 and 1821 steps/day, respectively. For physically active participants, step count increases were only observed in the ‘Committed’ sub-group (P < .0001). Effect sizes were modest-to-medium depending on the sub-group analyzed.

Conclusions

A commercial app providing small but immediate digital incentives for individualized goals was associated with an increased weekly mean daily step count on a population-scale over one year. This effect was more evident for physically inactive and more engaged participants.

Mobile Health Projects in a High-Complexity Reference Hospital: Case Study

BACKGROUND

The widespread adoption of mobile and wearable devices and apps makes it essential to assess their possible impact on the management of health and diseases. Health care providers (HCPs) find themselves faced with a new situation in their setting with the proliferation of mobile health (mHealth) intervention tests. Few studies have addressed the development of mHealth and the methodologies to manage these apps in a tertiary hospital.

OBJECTIVE

The aim of this study was to evaluate the mHealth projects implemented in the Hospital Clínic of Barcelona to increase awareness of the context in which they are used and to develop policies for the development of good practice in mHealth innovation.

METHODS

A prospective, descriptive cross-sectional study was conducted in a highly specialized university hospital with 850 beds for adults and a reference population of 520,000 inhabitants. A specific questionnaire was developed based on the Mobile Health 5 Dimensions European (MOHE 5D-EU) theoretical model to find mHealth projects. Apps, telemedicine, and wearable devices were included in the systematic search. For that purpose, a vertical (top-down) email-based snowball process was conducted. Data were collected from February to December 2018 by conducting personal interviews with HCPs using a structured questionnaire.

RESULTS

During the study period, 45 interviews were conducted; 35 mHealth initiatives were found, with 25 targeted to patients and 10 to health professionals. Most mHealth initiatives (34/35, 97%) were related to the software field (apps and telemedicine initiatives), and one was related to wearable devices. Among the projects, 68% (24/35) were classified as medical devices or developments at the edge (developments susceptible to limitations depending on the intended use). In relation to data protection, 27 initiatives managing personal data (27/35, 77%) considered data protection legislation. Only 9% (3/35) of the initiatives had foreseen the use of interconnectivity standards. Most of the initiatives were funded by grants (14/35, 40%), sponsorships (5/35, 14%), or the hospital itself (5/35, 14%). In terms of clinical management, most projects were developed in the field of research, followed by professional tools, clinical information, and therapeutic education. Only 6 projects were involved with health care; all were led by either the industry or small and medium enterprises.

CONCLUSIONS

This study helped create the design of a map of the mHealth projects conducted in our hospital that showed the stages of development of the different ongoing projects. This will allow monitoring of mHealth projects and construction of tools to reinforce areas with detected deficiencies. Our theoretical approach using a modified MOHE 5D-EU model was found to be useful for analyzing the characteristics of mHealth projects.

Using Health and Well-Being Apps for Behavior Change: A Systematic Search and Rating of Apps

Background

Smartphones have allowed for the development and use of apps. There is now a proliferation of mobile health interventions for physical activity, healthy eating, smoking and alcohol cessation or reduction, and improved mental well-being. However, the strength or potential of these apps to lead to behavior change remains uncertain.

Objective

The aim of this study was to review a large sample of healthy lifestyle apps at a single point in time (June to July 2018) to determine their potential for promoting health-related behavior change with a view to sharing this information with the public. In addition, the study sought to test a wide range of apps using a new scale, the App Behavior Change Scale (ABACUS).

Methods

Apps focusing on 5 major modifiable lifestyle behaviors were identified using a priori key search terms across the Australian Apple iTunes and Google Play stores. Lifestyle behavior categories were selected for their impact on health and included smoking, alcohol use, physical activity, nutrition, and mental well-being. Apps were included if they had an average user rating between 3 and 5, if they were updated in the last 18 months, if the description of the app included 2 of 4 behavior change features, and if they were in English. The selected behavior change apps were rated in 2 ways using previously developed rating scales: the Mobile App Rating Scale (MARS) for functionality and the ABACUS for potential to encourage behavior change.

Results

The initial search identified 212,352 apps. After applying the filtering criteria, 5018 apps remained. Of these, 344 were classified as behavior change apps and were reviewed and rated. Apps were given an average MARS score of 2.93 out of 5 (SD 0.58, range 1.42-4.16), indicating low-to-moderate functionality. Scores for the ABACUS ranged from 1 to 17, out of 21, with an average score of 7.8 (SD 2.8), indicating a low-to-moderate number of behavior change techniques included in apps. The ability of an app to encourage practice or rehearsal, in addition to daily activities, was the most commonly identified feature across all apps (310/344, 90.1%), whereas the second most common feature was the ability of the user to easily self-monitor behavior (289/344, 84.0%).

Conclusions

The wide variety of apps included in this 2018 study and the limited number of behavior change techniques found in many apps suggest an opportunity for improvement in app design that will promote sustained and significant lifestyle behavior change and, therefore, better health. The use of the 2 scales for the review and rating of the apps was successful and provided a method that could be replicated and tested in other behavior change areas.