Smartphone Apps Targeting Physical Activity in People With Rheumatoid Arthritis: Systematic Quality Appraisal and Content Analysis

Framework-based qualitative analysis of free responses of Large Language Models: Algorithmic fidelity

Today, with the advent of Large-scale generative Language Models (LLMs) it is now possible to simulate free responses to interview questions such as those traditionally analyzed using qualitative research methods. Qualitative methodology encompasses a broad family of techniques involving manual analysis of open-ended interviews or conversations conducted freely in natural language. Here we consider whether artificial "silicon participants" generated by LLMs may be productively studied using qualitative analysis methods in such a way as to generate insights that could generalize to real human populations. The key concept in our analysis is algorithmic fidelity, a validity concept capturing the degree to which LLM-generated outputs mirror human sub-populations' beliefs and attitudes. By definition, high algorithmic fidelity suggests that latent beliefs elicited from LLMs may generalize to real humans, whereas low algorithmic fidelity renders such research invalid. Here we used an LLM to generate interviews with "silicon participants" matching specific demographic characteristics one-for-one with a set of human participants. Using framework-based qualitative analysis, we showed the key themes obtained from both human and silicon participants were strikingly similar. However, when we analyzed the structure and tone of the interviews we found even more striking differences. We also found evidence of a hyper-accuracy distortion. We conclude that the LLM we tested (GPT-3.5) does not have sufficient algorithmic fidelity to expect in silico research on it to generalize to real human populations. However, rapid advances in artificial intelligence raise the possibility that algorithmic fidelity may improve in the future. Thus we stress the need to establish epistemic norms now around how to assess the validity of LLM-based qualitative research, especially concerning the need to ensure the representation of heterogeneous lived experiences.

Digital Therapeutics for Improving Effectiveness of Pharmaceutical Drugs and Biological Products: Preclinical and Clinical Studies Supporting Development of Drug + Digital Combination Therapies for Chronic Diseases

Limitations of pharmaceutical drugs and biologics for chronic diseases (e.g., medication non-adherence, adverse effects, toxicity, or inadequate efficacy) can be mitigated by mobile medical apps, known as digital therapeutics (DTx). Authorization of adjunct DTx by the US Food and Drug Administration and draft guidelines on "prescription drug use-related software" illustrate opportunities to create drug + digital combination therapies, ultimately leading towards drug-device combination products (DTx has a status of medical devices). Digital interventions (mobile, web-based, virtual reality, and video game applications) demonstrate clinically meaningful benefits for people living with Alzheimer's disease, dementia, rheumatoid arthritis, cancer, chronic pain, epilepsy, depression, and anxiety. In the respective animal disease models, preclinical studies on environmental enrichment and other non-pharmacological modalities (physical activity, social interactions, learning, and music) as surrogates for DTx "active ingredients" also show improved outcomes. In this narrative review, we discuss how drug + digital combination therapies can impact translational research, drug discovery and development, generic drug repurposing, and gene therapies. Market-driven incentives to create drug-device combination products are illustrated by Humira® (adalimumab) facing a "patent-cliff" competition with cheaper and more effective biosimilars seamlessly integrated with DTx. In conclusion, pharma and biotech companies, patients, and healthcare professionals will benefit from accelerating integration of digital interventions with pharmacotherapies.

The Most Popular Commercial Weight Management Apps in the Chinese App Store: Analysis of Quality, Features, and Behavior Change Techniques

BACKGROUND

Many smartphone apps designed to assist individuals in managing their weight are accessible, but the assessment of app quality and features has predominantly taken place in Western countries. Nevertheless, there is a scarcity of research evaluating weight management apps in China, which highlights the need for further investigation in this area.

OBJECTIVE

This study aims to conduct a comprehensive search for the most popular commercial Chinese smartphone apps focused on weight management and assess their quality, behavior change techniques (BCTs), and content-related features using appropriate evaluation scales. Additionally, the study sought to investigate the associations between the quality of various domains within weight management apps and the number of incorporated BCTs and app features.

METHODS

In April 2023, data on weight management apps from the iOS and Android app stores were downloaded from the Qimai Data platform. Subsequently, a total of 35 weight management apps were subjected to screening and analysis by 2 researchers. The features and quality of the apps were independently assessed by 6 professionals specializing in nutrition management and health behavioral change using the Mobile Application Rating Scale (MARS). Two registered dietitians, who had experience in app development and coding BCTs, applied the established 26-item BCT taxonomy to verify the presence of BCTs. Mean (SD) scores and their distributions were calculated for each section and item. Spearman correlations were used to assess the relationship between an app's quality and its technical features, as well as the number of incorporated BCTs.

RESULTS

The data set included a total of 35 apps, with 8 available in the Android Store, 10 in the Apple Store, and 17 in both. The overall quality, with a mean MARS score of 3.44 (SD 0.44), showed that functionality was the highest scoring domain (mean 4.18, SD 0.37), followed by aesthetics (mean 3.43, SD 0.42), engagement (mean 3.26, SD 0.64), and information (mean 2.91, SD 0.52), which had the lowest score. The mean number of BCTs in the analyzed apps was 9.17 (range 2-18 BCTs/app). The most common BCTs were "prompt review of behavioral goals" and "provide instruction," present in 31 apps (89%). This was followed by "prompt self-monitoring of behavior" in 30 apps (86%), "prompt specific goal setting" in 29 apps (83%), and "provide feedback on performance" in 27 apps (77%). The most prevalent features in the analyzed apps were the need for web access (35/35, 100%), monitoring/tracking (30/35, 86%), goal setting (29/35, 83%), and sending alerts (28/35, 80%). The study also revealed strong positive correlations among the number of BCTs incorporated, app quality, and app features. This suggests that apps with a higher number of BCTs tend to have better overall quality and more features.

CONCLUSIONS

The study found that the overall quality of weight management apps in China is moderate, with a particular weakness in the quality of information provided. The most prevalent BCTs in these apps were reviewing behavioral goals, providing guidance, self-monitoring of behavior, goal setting, and offering performance feedback. The most common features were the need for web access, monitoring and tracking, goal setting, and sending alerts. Notably, higher-quality weight management apps in China tended to incorporate more BCTs and features. These findings can be valuable for developers looking to improve weight management apps and enhance their potential to drive behavioral change in weight management.

Content and Quality of Mobile Apps for the Monitoring of Musculoskeletal or Neuropathic Pain in Australia: Systematic Evaluation

Background

Mobile apps offer a potential mechanism for people with persistent pain to monitor pain levels conveniently within their own environment and for clinicians to remotely monitor their patients' pain. However, the quality of currently available apps and the usefulness of included features from a clinical perspective are not known.

Objective

The aim of this study was to examine the content and quality of currently available smartphone apps designed for monitoring the intensity or presence of musculoskeletal or neuropathic pain.

Methods

A systematic search was performed in the Australian Apple and Google Play stores. Apps were included if they were designed to monitor the intensity or presence of musculoskeletal or neuropathic pain and were available in the English language within the Australian app stores. Data pertaining to the intended use of the app and clinical population were extracted by using a custom-designed data extraction form, and app quality was assessed by using the 23-item Mobile App Rating Scale.

Results

Of the 2190 apps screened, 49 met the inclusion criteria. Apps were primarily designed for adult users (36/49, 73%) with nonspecific musculoskeletal or neuropathic pain conditions, arthritis, and joint pain. All apps monitored pain intensity, with almost half (23/49, 47%) also specifying pain location. Overall, the mean quality scores from the Mobile App Rating Scale ranged from 1.5 to 4.4 (out of 5.0). Between 20% (10/49) and 22% (11/49) of apps involved clinicians, consumers, or both in their development, and 20% (10/49) had published literature related to the development or use of the app in clinical scenarios. Although 71% (35/49) had data sharing features, only 5 apps enabled client-clinician communication through the app.

Conclusions

The overall quality of mobile apps that are currently available for monitoring pain intensity is acceptable. Presently, mobile apps for remote pain monitoring lack functionality for clinicians to view data between consults. Both users and clinicians should be aware of the limitations of these apps and make informed choices in using or recommending apps that best suit the clinical need.

Designing an acceptance model and using public health apps by Iranian users

BACKGROUND

Nowadays, there are hundreds of mobile applications related to sports, health and fitness. The benefits of using mobile phones in physical activity can be seen in the increasing use of mobile health applications. The purpose of this study was to design a behavioral model of acceptance and use of public health apps by Iranian users.

MATERIALS AND METHODS

The present study was a qualitative and exploratory approach that was conducted based on the theme analysis method (team). The statistical population included programmers and designers of sports programs and academic specialists in the field of sports and computers. Data collection was performed through review of documents, backgrounds and semi-structured interviews. The interviews were conducted in person or by telephone and each interview lasted about 20 to 40 minutes.

RESULTS

In total, 249 key points with marker codes were extracted from 14 interviews which were classified into 21 sub-themes and 6 main themes (app quality, digital literacy, social influences, facilitating conditions, intention to use, trust and accept the app. Finally, the pattern of acceptance and use of health apps by Iranian users were presented in accordance with UTAUT theory.

CONCLUSION

The results of this study can help the officials of the federation, public sports boards and clubs to use information and communication technology as a media in their strategies and programs to develop sports and health at the community level. It also contributes to social vitality and improves the quality of life of individuals.

Mobile Health Apps for Patient-Centered Care: Review of United States Rheumatoid Arthritis Apps for Engagement and Activation

BACKGROUND

Rheumatoid arthritis (RA) is a highly dynamic and individualized disease in terms of its patterns of symptomatic flare-ups and periods of remission. Patient-centered care (PCC) aligns patients' lifestyle goals with their preferences for managing symptoms and side effects through the selection of therapies appropriate for disease management. Mobile health (mHealth) apps have the potential to engage and activate patients in PCC. mHealth apps can provide features that increase disease knowledge, collect patient-generated health indicators and behavioral metrics, and highlight goals for disease management. However, little evidence-based guidance exists as to which apps contain functionality essential for supporting the delivery of PCC.

OBJECTIVE

The objective of this study was to evaluate the patient-centeredness of United States-based rheumatoid arthritis mobile apps in terms of patient engagement and activation.

METHODS

A search of mobile apps on 2 major United States app stores (Apple App Store and Google Play) was conducted from June 2020 to July 2021 to identify apps designed for use by patients with RA by adapting the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines for mobile health app screening based on the literature. Reviewers conducted a content analysis of mobile app features to evaluate their functionality for patient engagement and activation. Engagement and activation were assessed using the Mobile Application Rating Scale (MARS) and social cognitive theory, respectively. Apps were ranked by their ability to facilitate PCC care along 2 dimensions: engagement and activation.

RESULTS

A total of 202 mobile apps were initially identified, and 20 remained after screening. Two apps emerged with the greatest ability to facilitate PCC. Both apps were scored as having acceptable or good patient engagement according to the MARS. These 2 apps also had high patient activation according to social cognitive theory, with many features within those apps representing theoretical constructs such as knowledge, perceived self-efficacy, and expectations about outcomes that support behavioral management of RA.

CONCLUSIONS

We found very few mobile apps available within the United States that have functionality that both engages and activates the patient to facilitate PCC. As the prevalence of mobile apps expands, the design of mobile apps needs to integrate patients to ensure that their functionality promotes engagement and activation. More research is needed to understand how mobile app use impacts patient engagement and activation, and ultimately, treatment decisions and disease trajectory.

Digital Rehabilitation Programs Improve Therapeutic Exercise Adherence for Patients With Musculoskeletal Conditions: A Systematic Review With Meta-Analysis

OBJECTIVE: To investigate the effects of digital rehabilitation for improving adherence to therapeutic exercise in people with musculoskeletal conditions. DESIGN: Intervention systematic review with meta-analysis. LITERATURE SEARCH: Five databases were searched from their inception to March 2022. STUDY SELECTION CRITERIA: We included randomized controlled trials evaluating digital rehabilitation programs to improve adherence to therapeutic exercise for people with musculoskeletal conditions. DATA SYNTHESIS: We calculated standardized mean differences (SMDs) or mean differences (MDs) and 95% confidence intervals (CIs). Certainty of evidence was rated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Bias was assessed using the Cochrane risk of bias tool. RESULTS: Eleven trials were included in the meta-analysis (n = 1144 participants). At short-term follow-up, digital rehabilitation was no better than nondigital rehabilitation (3 trials, adherence rate of prescribed exercise test SMD 0.50, 95% CI: -0.13, 1.13; 2 trials, self-reported exercise adherence test MD 1.07, 95% CI: 0.58, 1.56; 2 trials, assessor-reported exercise adherence test SMD -0.10, 95% CI: -0.56, 0.36). At intermediate-term follow-up, digital rehabilitation improved exercise adherence compared with nondigital rehabilitation (6 trials, adherence rate of prescribed exercise test SMD 0.53, 95% CI: 0.35, 0.70; 2 trials, self-reported exercise adherence test MD 1.50, 95% CI: 0.76, 2.25; 2 trials, Exercise Adherence Rating Scale test MD 5.86, 95% CI: 0.08, 11.65). At long-term follow-up, there was no clinically important difference between digital and nondigital rehabilitation (2 trials, adherence rate of prescribed exercise test SMD 0.28, 95% CI: -0.14, 0.70; 1 trial, self-reported exercise adherence test MD 0.20, 95% CI: -0.91, 1.31). CONCLUSION: Digital rehabilitation was effective at improving therapeutic exercise adherence in musculoskeletal conditions at mid-term follow-up, but not at short- and long-term follow-up. J Orthop Sports Phys Ther 2022;52(11):726-739. Epub: 12 August 2022. doi:10.2519/jospt.2022.11384.

Mobile health applications for pregnancy in Iran: Current state investigation

BACKGROUND

The expansion of pregnancy-related mobile applications has led to an increase in the usage of these applications by Iranian women, which has the potential to have a long-term impact on women's pregnancy health and, as a result, community health. The goal of this research was to investigate the state of pregnancy-related mobile applications in Iran.

MATERIALS AND METHODS

This was a descriptive-applied research approach which was conducted in 2020. One hundred and fifty-seven pregnancy apps from different Iranian mobile app markets were installed and were examined in terms of the resources used and their validity, subject distribution, participation of obstetricians in the app development, apps volume, rank acquired by users and distribution of apps according to the developers. The relationship between the number of resources used and user rankings was also tested.

RESULTS

A total of 157 apps were categorized into 12 subject categories based on their content. Only 1.3% of the apps were developed with the participation of obstetricians. Only 5% of the apps had used reliable information resources. Furthermore, the number of resources referenced in the studied apps did not have a significant relationship with star ratings (r = 0.03, P = 0.64), according to the Pearson correlation test.

CONCLUSION

Iranian mobile applications in the field of pregnancy have grown significantly in terms of quantity, subject diversity, and user acceptance; however, the credibility of the information in these apps cannot be validated. This serves as a reminder to users to exercise caution while using such apps.

Development and real-life use assessment of a self-management smartphone application for patients with inflammatory arthritis. A user-centred step-by-step approach

Background

Mobile health applications (apps) are increasing in interest to enhance patient self-management. Few apps are actually used by patients and have been developed for patients with inflammatory arthritis (IA) treated with disease-modifying anti-rheumatic drugs which use entails risk of adverse effects such as infections.

Objective

To develop Hiboot, a self-management mobile app for patients with IA, by using a user-centred step-by-step approach and assess its real-life use.

Methods

The app development included first a qualitative study with semi-guided audiotaped interviews of 21 patients to identify the impact of IA on daily life and patient treatments practices and an online cross-sectional survey of 344 patients to assess their health apps use in general and potential user needs. A multidisciplinary team developed the first version of the app via five face-to-face meetings. After app launch, a second qualitative study of 21 patients and a users’ test of 13 patients and 3 rheumatologists led to the app’s current version. The number of app installations, current users and comments were collected from the Google Play store and the Apple store.

Results

The qualitative study revealed needs for counselling, patient–health professional partnership, and skills to cope with risk situations; 86.8% participants would be ready to use an app primarily on their rheumatologist’s recommendation. Six functionalities were implemented: a safety checklist before treatment administration, aids in daily life situations based on the French academic recommendations, treatment reminders, global well-being self-assessment, periodic counselling messages, and a diary. The Hiboot app was installed 20,500 times from September 2017 to October 2020, with 4300 regular current users. Scores were 4.4/5 stars at Android and iOS stores.

Conclusion

Hiboot is a free self-management app for patients with IA developed by a step-by-step process including patients and health professionals. Further evaluation of the Hiboot benefit is needed.

mHealth Apps Using Behavior Change Techniques to Self-report Data: Systematic Review

Background

The popularization of mobile health (mHealth) apps for public health or medical care purposes has transformed human life substantially, improving lifestyle behaviors and chronic condition management.

Objective

This review aimed to identify behavior change techniques (BCTs) commonly used in mHealth, assess their effectiveness based on the evidence reported in interventions and reviews to highlight the most appropriate techniques to design an optimal strategy to improve adherence to data reporting, and provide recommendations for future interventions and research.

Methods

We performed a systematic review of studies published between 2010 and 2021 in relevant scientific databases to identify and analyze mHealth interventions using BCTs that evaluated their effectiveness in terms of user adherence. Search terms included a mix of general (eg, data, information, and adherence), computer science (eg, mHealth and BCTs), and medicine (eg, personalized medicine) terms.

Results

This systematic review included 24 studies and revealed that the most frequently used BCTs in the studies were feedback and monitoring (n=20), goals and planning (n=14), associations (n=14), shaping knowledge (n=12), and personalization (n=7). However, we found mixed effectiveness of the techniques in mHealth outcomes, having more effective than ineffective outcomes in the evaluation of apps implementing techniques from the feedback and monitoring, goals and planning, associations, and personalization categories, but we could not infer causality with the results and suggest that there is still a need to improve the use of these and many common BCTs for better outcomes.

Conclusions

Personalization, associations, and goals and planning techniques were the most used BCTs in effective trials regarding adherence to mHealth apps. However, they are not necessarily the most effective since there are studies that use these techniques and do not report significant results in the proposed objectives; there is a notable overlap of BCTs within implemented app components, suggesting a need to better understand best practices for applying (a combination of) such techniques and to obtain details on the specific BCTs used in mHealth interventions. Future research should focus on studies with longer follow-up periods to determine the effectiveness of mHealth interventions on behavior change to overcome the limited evidence in the current literature, which has mostly small-sized and single-arm experiments with a short follow-up period.

Do pain management apps use evidence-based psychological components? A systematic review of app content and quality

Background

With hundreds of pain management apps on the Canadian marketplace, it can be challenging for patients and clinicians to select effective and evidence-based mobile health (mHealth) apps that address pain from a biopsychosocial perspective.

Aims

The aim of this study is to identify pain management apps within the Canadian app marketplaces to aid clinicians in recommending apps.

Methods

The iOS and Android marketplaces were systematically searched to identify pain management apps that included at least one core component of cognitive behavioral therapy (CBT) or mindfulness- and acceptance-based therapies. Selected apps were assessed using a researcher developed psychological components checklist, and the Mobile App Rating Scale (MARS). These two measures provided a robust assessment of the apps' technical abilities and psychological principles being implemented.

Results

Five hundred eight pain management apps were identified, yet only 12 included a psychological component and were available for evaluation. On average, apps contained 8.10 out of 18 psychological components (SD = 2.77) with a MARS quality rating of 4.02 out of 5 (SD = 0.32). The most common psychological components were grounded in CBT, including psychoeducation, sleep hygiene, behavioral activation, coping skills training, and social support. Among the least commonly included components were goal setting, values, and culture/diversity. Two-thirds of the apps involved health care practitioners in their development, but independent scientific review of apps was scarce.

Conclusion

The highest scoring apps (Curable, Pathways, Vivify) are highlighted for health care practitioners who may wish to recommend mHealth technologies to their patients for pain management. Future directions for research and app development are discussed.

Smartphones for musculoskeletal research - hype or hope? Lessons from a decennium of mHealth studies

BACKGROUND

Smartphones provide opportunities for musculoskeletal research: they are integrated in participants' daily lives and can be used to collect patient-reported outcomes as well as sensor data from large groups of people. As the field of research with smartphones and smartwatches matures, it has transpired that some of the advantages of this modern technology are in fact double-edged swords. BODY: In this narrative review, we illustrate the advantages of using smartphones for data collection with 18 studies from various musculoskeletal domains. We critically appraised existing literature, debunking some myths around the advantages of smartphones: the myth that smartphone studies automatically enable high engagement, that they reach more representative samples, that they cost little, and that sensor data is objective. We provide a nuanced view of evidence in these areas and discuss strategies to increase engagement, to reach representative samples, to reduce costs and to avoid potential sources of subjectivity in analysing sensor data.

CONCLUSION

If smartphone studies are designed without awareness of the challenges inherent to smartphone use, they may fail or may provide biased results. Keeping participants of smartphone studies engaged longitudinally is a major challenge. Based on prior research, we provide 6 actions by researchers to increase engagement. Smartphone studies often have participants that are younger, have higher incomes and high digital literacy. We provide advice for reaching more representative participant groups, and for ensuring that study conclusions are not plagued by bias resulting from unrepresentative sampling. Costs associated with app development and testing, data storage and analysis, and tech support are substantial, even if studies use a 'bring your own device'-policy. Exchange of information on costs, collective app development and usage of open-source tools would help the musculoskeletal community reduce costs of smartphone studies. In general, transparency and wider adoption of best practices would help bringing smartphone studies to the next level. Then, the community can focus on specific challenges of smartphones in musculoskeletal contexts, such as symptom-related barriers to using smartphones for research, validating algorithms in patient populations with reduced functional ability, digitising validated questionnaires, and methods to reliably quantify pain, quality of life and fatigue.

Smartphone applications for physical activity promotion from physical education

Smartphone applications (apps) are thought to be an adequate instructional strategy not only to improve the quality of the teaching in physical education (PE), but also to effectively promote leisure-time physical activity (PA) of adolescent students in this context. Although the use of smartphone apps has been generalized in PE, little is known about the curricular approach of smartphone apps to be implemented by teacher to teach specific curricular contents in PE lessons. Therefore, the aim of this research was threefold: a) to conduct a systematic search for smartphone apps focused on PA and sport; b) to assess the features, content and quality of every included smartphone app; and c) to analyze the relationships between every selected app and the secondary PE curriculum. Systematic searches were completed on Google Play Store from January 2021 to March 2021. Apps were included when they met: main goal focused on PA and sport; permitted use by underage; they are free; user scores of at least 4. The app selection process was carried out by several reviewers and concordance measures were estimated. Additionally, an app quality assessment was independently conducted by three reviewers. A total of 18 apps focused on PA were included. Particularly, eight apps were suitable for fitness, health and quality of life curricular content; two for sports content; four for body expression content; and four apps for outdoor PA content. The mean quality score was 4.00. Apps could be helpful for teachers to implement the secondary PE curriculum and effectively promote PA among adolescent students.

The Characteristics and Functionalities of Mobile Apps Aimed at Patients Diagnosed With Immune-Mediated Inflammatory Diseases: Systematic App Search

Background

Immune-mediated inflammatory diseases (IMIDs) are systemic conditions associated with a high social and health impact. New treatments have changed the prognosis of IMIDs and have increased patient autonomy in disease management. Mobile apps have enormous potential to improve health outcomes in patients with IMIDs. Although a large number of IMID apps are available, the app market is not regulated, and functionality and reliability remain uncertain.

Objective

Our aims are to review available apps for patients with IMIDs or caregivers and to describe the main characteristics and functionalities of these apps.

Methods

We performed an observational, cross-sectional, descriptive study of all apps for patients with IMIDs. Between April 5 and 14, 2021, we conducted a search of the App Store (iOS) and Play Store (Android) platforms. We used the names of the different IMIDs as search terms. The inclusion criteria were as follows: content related to IMIDs, English or Spanish language, and user population consisting of patients and health care consumers, including family and caregivers. The variables analyzed were as follows: app name, type of IMID, platform (Android or iOS), country of origin, language, category of the app, cost, date of the last update, size, downloads, author affiliation, and functionalities.

Results

We identified 713 apps in the initial search, and 243 apps met the criteria and were analyzed. Of these, 37% (n=90) were on Android, 27.2% (n=66) on iOS, and 35.8% (n=87) on both platforms. The most frequent categories were health and well-being/fitness apps (n=188, 48.5%) and medicine (n=82, 37.9%). A total of 211 (82.3%) apps were free. The mean time between the date of the analysis and the date of the most recent update was 18.5 (SD 19.3) months. Health care professionals were involved in the development of 100 (41.1%) apps. We found differences between Android and iOS in the mean time since the last update (16.2, SD 14.7 months vs 30.3, SD 25.7 months) and free apps (85.6% vs 75.8%; respectively). The functionalities were as follows: general information about lifestyles, nutrition, or exercises (n=135, 55.6%); specific information about the disease or treatment (n=102, 42%); recording of symptoms or adverse events (n=51, 21%); agenda/calendar (n=44, 18.1%); reminder medication (n=41, 16.9%); and recording of patient-reported outcomes (n=41, 16.9%). A total of 147 (60.5%) apps had more than one functionality.

Conclusions

IMID-related apps are heterogeneous in terms of functionality and reliability. Apps may be a useful complement to IMID care, especially inpatient education (their most frequent functionality). However, more than half of the IMID apps had not been developed by health care professionals or updated in the last year.

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.

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.

Effectiveness of web-based and mobile health interventions designed to enhance adherence to physical activity for people with inflammatory arthritis: a systematic review

Objective

The aim of this systematic review was to assess the evidence from randomized controlled trials (RCTs) and cohort studies for the effectiveness of digital interventions designed to enhance adherence to physical activity (PA) for people with inflammatory arthritis and describe the intervention content using established coding criteria.

Methods

Six electronic databases were searched for published and unpublished studies. Independent data extraction and quality assessment (Cochrane risk of bias II or ROBINS-I) were conducted by two reviewers. The primary outcome was self-reported adherence to PA post-intervention. Secondary outcomes included self-reported adherence to PA at other time points, level of PA or engagement with intervention at any follow-up time point. Intervention content was assessed using the Consensus on Exercise Reporting Template and the Behaviour Change Techniques Taxonomy version 1.

Results

From 11 136 citations, four moderate risk of bias studies (three RCTs and one cohort study) including 1160 participants with RA or JIA were identified. Owing to heterogeneity of outcomes, a narrative synthesis was conducted. Only one RCT reported a small between-group difference in adherence to PA [mean difference (95% CI) −0.46 (−0.82, −0.09)] in favour of the intervention. There were no between-group differences in any secondary outcomes. Interventions included between 3 and 11 behaviour change techniques but provided minimal information on exercise prescription.

Conclusion

There is currently limited moderate-quality evidence available to provide confident evaluation of the effect of web-based and mobile health interventions on adherence to PA or level of PA post-intervention in people with inflammatory arthritis.