Hospitalized Older Patients’ Readiness to Use mHealth Mobility Apps

Introduction: Addressing the challenges of an ageing population and increasing chronic conditions necessitates a transformative shift in healthcare. It involves moving away from a service-oriented model and adopting an integrated care approach emphasizing prevention. Research underscores the positive impact of regular physical activity (PA) on older adults' physical, cognitive, and mental well-being. The World Health Organization recommends at least 150-300 minutes of moderate-intensity PA weekly, and muscle-strengthening exercises. Despite increased awareness, PA participation rates among older adults remain concerning. Portable technologies, such as mobile health (mHealth) apps, show promise in promoting PA and can play a vital role in delivering integrated preventive care. Nevertheless, sustaining long-term engagement remains challenging. Involving end-users in the design process using co-creative methodologies is essential for creating effective solutions (7, 8, 9). This study aims to develop a mHealth app promoting PA and a healthy lifestyle through a co-creative process with community-dwelling older adults. Methodology: To better understand the needs of older adults, a co-creative process was employed using design thinking . This process involved interviews with 22 participants, to grasp the target population's needs and motivations while identifying problems related to inadequate PA. Subsequently, two co-creative workshops were conducted with 21 older adults and eight experts to generate innovative solutions for the identified issues. Participants met specific criteria: age (≥65 years), no severe illnesses, Dutch language proficiency, and active participation ability. Results were analyzed, using thematic synthesis. Finally, a prototype concept was developed and tested on a sample of 65 older adults. Results: Twenty-two interviews unveiled four themes: PA-perception, health benefits, influencing factors, and attitude towards technology. Participants acknowledged PA's health benefits, such as improved mobility, and mental health. Barriers included poor health and lack of time. Facilitators were enjoyment and social connections. Co-creative workshops addressed PA coping strategies and app features, resulting in an app with tailored tips, literacy content, workouts, a community calendar, and a helpdesk function. Feedback (n=65) indicated positive user experiences, with an overall System Usability Scale score of 70.38±14.51, and a mean net promoter score of 7.66. Discussion: Design thinking is a powerful tool in technology development, especially for older adults. This study aimed to create a mHealth app for promoting PA using co-creative methods with experts and older adults. It employed interviews and workshops for extensive data collection on technology experiences and PA. The research revealed that motivating older adults to engage in PA requires a holistic approach, considering social, individual, and contextual factors. Addressing the digital divide and offering personalized solutions aligned with older adults' preferences are implementation challenges. Focusing on benefits, reliability, and effectiveness encourages long-term technology use among older adults. Conclusion: In conclusion, this study aimed to identify coping strategies, barriers, and facilitators for engaging in PA while highlighting the challenges of implementing mHealth apps and the importance of personalized solutions. Future research should assess the long-term impact of such interventions and consider the holistic factors that influence behavior change in this population, fostering a comprehensive approach to integrated preventive care.

BackgroundKnowledge of the characteristics of adolescents who use mobile health (mHealth) apps to monitor health and how these characteristics differ from those of app nonusers is limited.ObjectiveWe aimed to determine mHealth app use based on adolescent and parental factors, including sociodemographics, digital skills, and health indicators, in a nationally representative sample of Czech adolescents (N=2500).MethodsAdolescents aged 11 to 16 years and one of their parents participated in an online survey in 2021. A professional research agency recruited the participants. Quotas were used to ensure the sample’s representativeness. The sociodemographic factors were the adolescents’ age, gender, and parental perceived financial security. The adolescents also provided information about their screen time, eHealth literacy, BMI, health anxiety, physical activity, and sleep quality. Parents reported their digital skills, mobile phone attitudes, and the mediation of their children’s online health information–seeking behaviors. We evaluated the differences between the users and nonusers of mHealth apps and identified the significant predictors of mHealth app use. Next, we separately examined how these factors were associated with the use of mHealth apps that track calorie intake or expenditure, number of steps, weight, or sports activity (eg, exercise, running, and working out), as well as other mHealth apps (eg, those that track sleep and heart rate).ResultsMore than half of the adolescents (1429/2455, 58.21%) reported using mHealth apps. App users were relatively older and, more often, girls. Apps that counted the number of steps were used most frequently, and adolescents whose parents reported higher perceived financial security used them more regularly. Overall, being older and physically active and having higher eHealth literacy skills were associated with using mHealth apps. Adolescents with higher BMI, health anxiety, and lower sleep quality more frequently used mHealth apps to track calorie intake or expenditure, weight, and health indicators. mHealth apps to track physical activity were used more regularly by girls. There was a positive association between parental mediation of online health information–seeking behaviors and adolescents’ mHealth app use.ConclusionsThese findings demonstrated that older age, physical activity, and eHealth literacy skills were the common underlying factors of adolescents’ mHealth app use. We initially showed parents as significant role models for their children’s adoption of, and engagement with, mHealth apps when they actively mediate their online health information–seeking behaviors. Improving the eHealth literacy skills of adolescents through parental guidance might enhance health technology use in this population. Tracking eating behaviors, weight, and health were more prevalent for adolescents who reported higher BMI, health anxiety, and lower sleep quality. Future research studies should examine the determinants and health outcomes of adolescents’ mHealth app use longitudinally.

BackgroundHealth apps on mobile devices provide an unprecedented opportunity for ordinary people to develop social connections revolving around health issues. With increasing penetration of mobile devices and well-recorded behavioral data on such devices, it is desirable to employ digital traces on mobile devices rather than self-reported measures to capture the behavioral patterns underlying the use of mobile health (mHealth) apps in a more direct and valid way.ObjectiveThe objectives of this study were to (1) assess the demographic predictors of the adoption of mHealth apps; (2) investigate the temporal pattern underlying the use of mHealth apps; and (3) explore the impacts of demographic variables, temporal features, and app genres on the use of mHealth apps.MethodsLogfile data of mobile devices were collected from a representative panel of about 2500 users in Hong Kong. Users’ mHealth app activities were analyzed. We first conducted a binary logistic regression analysis to uncover demographic predictors of users’ adoption status. Then we utilized a multilevel negative binomial regression to examine the impacts of demographic characteristics, temporal features, and app genres on mHealth app use.ResultsIt was found that 27.5% of mobile device users in Hong Kong adopt at least one genre of mHealth app. Adopters of mHealth apps tend to be female and better educated. However, demographic characteristics did not showcase the predictive powers on the use of mHealth apps, except for the gender effect (Bfemale vs Bmale=–0.18; P=.006). The use of mHealth apps demonstrates a significant temporal pattern, which is found to be moderately active during daytime and intensifying at weekends and at night. Such temporal patterns in mHealth apps use are moderated by individuals’ demographic characteristics. Finally, demographic characteristics were also found to condition the use of different genres of mHealth apps.ConclusionsOur findings suggest the importance of dynamic perspective in understanding users’ mHealth app activities. mHealth app developers should consider more the demographic differences in temporal patterns of mHealth apps in the development of mHealth apps. Furthermore, our research also contributes to the promotion of mHealth apps by emphasizing the differences of usage needs for various groups of users.

There are many mobile health (mHealth) apps for older adult patients, but research has found that broadly speaking, mHealth still fails to meet the specific needs of older adult users. Others have highlighted the need to embed users in the mHealth design process in a fulsome and meaningful way. Co-design has been widely used in the development of mHealth apps and involves stakeholders in each phase of the design and development process. The involvement of older adults in the co-design processes is variable. To date, co-design approaches have tended toward embedding the stakeholders in early phases (eg, predesign and generative) but not throughout. The aim of this study was to reflect on the processes and lessons learned from engaging in an extended co-design process to develop an mHealth app for older adults, with older users contributing at each phase. This study aimed to design an mHealth tool to assist older adults in coordinating their care with health care professionals and caregivers. Our work to conceptualize, develop, and test the mHealth app consisted of 4 phases: phase 1, consulting stakeholders; phase 2, app development and co-designing with older adults; phase 3, field-testing with a smaller sample of older adult volunteer testers; and phase 4, reflecting, internally, on lessons learned from this process. In each phase, we drew on qualitative methods, including in-depth interviews and focus groups, all of which were analyzed in NVivo 11, using team-based thematic analysis. In phase 1, we identified key features that older adults and primary care providers wanted in an app, and each user group identified different priority features (older adults principally sought support to use the mHealth app, whereas primary care providers prioritized recoding illnesses, immunizations, and appointments). Phases 2 and 3 revealed significant mismatches between what the older adult users wanted and what our developers were able and willing to deliver. We were unable to craft the app that our consultations recommended, which the older adult field testers asked for. In phase 4, we reflected on our abilities to embed the voices and perspectives of older adults throughout the project when working with a developer not familiar with or committed to the core principles of co-design. We draw on this challenging experience to highlight several recommendations for those embarking on a co-design process that includes developers and IT vendors, researchers, and older adult users. Although our final mHealth app did not reflect all the needs and wishes of our older adult testers, our consultation process identified key features and contextual information essential for those developing apps to support older adults in managing their health and health care.

BackgroundTraditional Chinese medicine (TCM) theories assert that body constitution and meridian energy lay the foundation for disease prevention. TCM-based health concepts have not yet been incorporated into mobile health (mHealth) apps for individuals with prediabetes.ObjectiveThe aim of this study was to examine the effectiveness of a TCM mHealth app for individuals with prediabetes.MethodsThis randomized controlled trial recruited 121 individuals with prediabetes at a teaching hospital in New Taipei City between February 2020 and May 2021. The participants were randomly assigned to the TCM mHealth app group (n=42), ordinary mHealth app group (n=41), or control group (n=38). All participants received the usual care that included 15-20 minutes of health education about the disease, along with healthy diet and exercise encouragement. The ordinary mHealth app included physical activity (PA), diet, and disease education, along with individual records. The TCM mHealth app additionally included qi and body constitution information, along with constitution-based PA and diet advice. The control group received the usual care alone and did not have access to any app. Data were collected at baseline, at the end of the 12-week intervention, and 1 month after the intervention. Body constitution, including yang-deficiency, yin-deficiency, and phlegm-stasis, was measured according to the Body Constitution Questionnaire, with higher scores indicating a greater deficiency. Body energy was examined using the Meridian Energy Analysis Device. The Short-Form 36 questionnaire was used to evaluate health-related quality of life (HRQOL), which yielded physical component scores and mental component scores, with higher scores indicating better physical and mental aspects of HRQOL, respectively.ResultsCompared to the control group, the TCM mHealth app group showed greater improvement in hemoglobin A1c (HbA1c), yang-deficiency and phlegm-stasis body constitution, and BMI; however, no significant differences were found in these outcomes between the TCM mHealth app and ordinary mHealth app groups. The TCM mHealth app group showed better improvement in body energy and mental component scores than the ordinary mHealth app group. There were no significant differences in fasting plasma glucose, yin-deficiency body constitution, Dietary Approaches to Stop Hypertension dietary behavior, and total PA among the three groups after the intervention.ConclusionsUse of either the ordinary or TCM mHealth app improved HRQOL among individuals with prediabetes. Compared to the outcomes of controls not using any app, use of the TCM mHealth app was effective at improving HbA1c, BMI, yang-deficiency and phlegm-stasis body constitution, and HRQOL. Moreover, using the TCM mHealth app seemed to improve the body energy and HRQOL more than when using the ordinary mHealth app. Further studies with a larger sample size and longer follow-up period may be necessary to determine whether the differences favoring the TCM app are clinically meaningful.Trial RegistrationClinicalTrials.gov NCT04096989; https://clinicaltrials.gov/ct2/show/NCT04096989

BackgroundNoncommunicable diseases (NCDs) are the leading global health problem in this century and are the principal causes of death and health care spending worldwide. Mobile health (mHealth) apps can help manage and prevent NCDs if people are willing to use them as supportive tools. Still, many people are reluctant to adopt these technologies. Implementing new apps could result in earlier intervention for many health conditions, preventing more serious complications.ObjectiveThis research project aimed to test the factors that facilitate the adoption of mHealth apps by users with NCDs. We focused on determining, first, what user interface (UI) qualities and complexity levels appeal to users in evaluating mHealth apps. We also wanted to determine whether people prefer that the data collected by an mHealth app be analyzed using a physician or an artificial intelligence (AI) algorithm. The contribution of this work is both theoretical and practical. We examined users’ considerations when adopting mHealth apps that promote healthy lifestyles and helped them manage their NCDs. Our results can also help direct mHealth app UI designers to focus on the most appealing aspects of our findings.MethodsA total of 347 respondents volunteered to rate 3 models of mHealth apps based on 16 items that measured instrumentality, aesthetics, and symbolism. Respondents rated each model after reading 1 of 2 different scenarios. In one scenario, a physician analyzed the data, whereas, in the other, the data were analyzed by an AI algorithm. These scenarios tested the degree of trust people placed in AI algorithms versus the “human touch” of a human physician regarding analyzing data collected by an mHealth app.ResultsAs shown by the responses, the involvement of a human physician in the application had a significant effect (P<.001) on the perceived instrumentality of the simple model. The complex model with more controls was rated significantly more aesthetic when associated with a physician performing data analysis rather than an AI algorithm (P=.03).ConclusionsGenerally, when participants found a human touch in the mHealth app (connection to a human physician who they assumed would analyze their data), they judged the app more favorably. Simple models were evaluated more positively than complex ones, and aesthetics and symbolism were salient predictors of preference. These trends suggest that designers and developers of mHealth apps should keep the designs simple and pay special attention to aesthetics and symbolic value.

BackgroundAs the global aging population accelerates, mobile health (mHealth) apps have emerged as critical tools in the health management of older people. However, the promotion of mHealth apps has faced multiple obstacles, including insufficient technological adaptation to aging, digital resistance, and ageism. The impact of ageism on technology usage experiences among older adults is influenced by mechanisms such as stereotypes and biases. Notably, extant research has not adequately explored the subjective experiences of older adults in the context of mHealth app usage scenarios.ObjectivesThe present study was predicated on the extended unified theory of acceptance and use of technology model and the risks of ageism model to systematically explore and understand older adults’ ageism experiences in mHealth app usage. Our objectives were to provide a reference for optimizing age-friendly design and enhancing digital health management capabilities for older adults.MethodsThis qualitative study utilized an interpretive phenomenological design and was conducted between February and April 2025. Purposive sampling was employed to select older adults with experience using mHealth apps in a Shanghai community for semistructured interviews. This study used Colaizzi’s phenomenological method to analyze and summarize older adults’ experiences and perceptions of ageism and to extract themes.ResultsThe study identified 3 core themes: (1) internalized age stereotypes, which manifest as technological uselessness and learning barriers; (2) anxiety and avoidance behaviors caused by stereotype threat; and (3) external unfair treatment (such as age-friendly design flaws and inadequate support systems), which inhibits usage. These experiences significantly impact older adults’ intention to use mHealth apps.ConclusionsAgeism profoundly affects the engagement of older adults with mHealth apps. It is advisable to execute systematic interventions to improve digital inclusion and health self-management capabilities, including strategies to challenge age stereotypes, optimize intergenerational support, refine age-friendly design, and establish strong social support networks.

BackgroundThe global population is aging rapidly, with projections indicating a doubling of older adults by 2050. Among the chronic conditions affecting this demographic, diabetes stands out due to its prevalence and impact on health. Mobile health (mHealth) app interventions show promise in improving health outcomes, leveraging the widespread adoption of smartphones among older adults.ObjectiveThis meta-analysis aimed to evaluate the effectiveness of mHealth apps specifically tested for older adults with type 1 or type 2 diabetes. It addresses the gap in existing literature by focusing on this age group, aiming to provide insights into the benefits and challenges of these technologies.MethodsA meta-analysis of randomized controlled trials (RCTs) was conducted across major databases using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines to examine the effectiveness of mHealth apps for improving older adults’ diabetes outcomes. Primary outcomes included changes in glycated hemoglobin (HbA1c), fasting blood glucose, and medication adherence levels. We retrieved 4247 papers, of which 257 were moved to full review, and 7 were identified following our criteria. Papers were excluded if the study was not an RCT, did not examine the effect of mHealth apps, or was not conducted with older adults. We provide a mixed methods perspective, pairing the effect sizes in the literature with a review of features included in these apps, allowing for a more comprehensive comparison and reference for future RCT interventions with similar technologies designed for older adults.ResultsOverall, our results indicated that mHealth app interventions can be effective for managing blood glucose in older adult populations. The 7 RCTs that met the inclusion criteria involved a total of 490 participants. The meta-analysis revealed a significant reduction in HbA1c levels (Hedges g –0.40, 95% CI –0.75 to –0.06) among older adults using mHealth apps. Limited data on fasting blood glucose and medication adherence showed positive trends, echoing the main HbA1c findings.ConclusionsmHealth apps demonstrated effectiveness in improving glycemic control among older adults with diabetes, highlighting their potential as tools for health management in this demographic. Our effect sizes were comparable with other meta-analyses conducted across different aging groups, suggesting that diabetes mHealth apps can be as effective for older adults compared to younger cohorts. Some data suggests that the effectiveness of mHealth apps might decrease over trial time. These findings underscore the need for further research to refine these interventions and optimize their impact on older adults’ health outcomes. We evaluated each RCT intervention and identified app components that could relate to the app’s effectiveness to guide the design of future diabetes management RCTs and mHealth tools for older adults.Trial RegistrationOpen Science Framework 10.17605/OSF.IO/AWVCX; https://osf.io/awvcx

Background:Mobile health (mHealth) apps have the potential to facilitate convenient health care delivery and self-management of health. However, many users have concerns about their privacy when they use mHealth apps. Different apps provide different solutions for protecting users' privacy.Objective:The purpose of this study was to determine user preferences among the several privacy protection methods used in current mHealth apps and the reasons behind their preferences.Methods:Five privacy protection methods currently used in mHealth apps were presented to a group of study participants who had mild or moderate depression and expressed concerns about privacy of information when they used mental health apps. After a demonstration of the methods, study participants were asked to fill out a questionnaire and indicate their perceived privacy protection level (PPPL) of each method, their preference rating for each method, and the privacy protection methods they had used in the past. A brief interview was then conducted to collect study participants' comments on these methods and elicit the reasons for their preference ratings. Statistical analysis was performed to determine the statistical significance of differences in participants' preference ratings and in the PPPLs obtained for the five methods. Study participants' comments on the privacy protection methods and suggestions were noted and summarized.Results:Forty (40) study participants were selected from a large candidate pool using the IRB approved selection criteria. All study participants viewed the app demonstration and understood the five privacy protection methods properly, which was indicated by their correct sorting of the PPPL of the five methods in their answers to the questionnaire. All study participants specified their preferences with respect to these methods and provided the rationale behind their selections on the questionnaire and during the brief interview. The results indicate that the users preferred privacy protection methods with customizable modules in multi-purpose apps because of their convenience and strong privacy protection, where the customization can be done either in the app or via a Web portal.Conclusions:This study identified user preferred privacy protection methods. These identified privacy protection methods may be used in many types of apps that perform sensitive health information management to better protect users' privacy and encourage more users to adopt these mHealth apps.

BackgroundIntervention with a mobile Health (mHealth) app can improve the efficacy of early detection of oral cancer and the outcomes for patients taking oral anticancer medications. The quality of life of oral cancer patients is significantly reduced within three months after surgery; also, their needs for nursing care and health information increase, mainly due to side effects and associated psychological problems.ObjectiveThis study aimed to evaluate changes in the care needs and quality of life of patients with oral cancer after receiving the intervention of a newly developed mHealth app.MethodsAfter surgery, oral cancer patients were divided into an experimental group (n=50) who received the mHealth app intervention and a control group (n=50) who received routine health care and instruction. After 3 months of intervention, survey questionnaires were used to assess the patients’ quality of life, nursing care needs, and acceptance of the mHealth app.ResultsThe physiological care needs were significantly decreased in the experimental group compared with the control group (P<.05). Although the differences were not statistically significant, the psychological needs, communication needs, and care support needs all improved after the mHealth app intervention. The overall improvement in quality of life was higher in the experimental group than in the control group (–7.24 vs –4.36). In terms of intention to use, perceived usefulness, and perceived ease of use, the acceptability scores of the mHealth app were significantly increased after 3 months of intervention (P<.05).ConclusionsCompared with routine health care and instruction, for patients after surgery, the education/information intervention using the mHealth app significantly reduced their nursing care needs, improved their quality of life, and increased their acceptance of using an mHealth app on a mobile device. These findings can provide a theoretical basis for future health care app design and improvement. This study suggests that an mHealth app should be incorporated into the routine care of oral cancer patients to provide medical information quickly and improve their self-management abilities, thereby reducing the patients’ need for physiological care and improving their quality of life.Trial RegistrationClinicalTrials.gov NCT04049968; https://www.clinicaltrials.gov/ct2/show/NCT04049968

Perception of middle-aged and older adults towards mHealth apps: A comparative factor analysis between Australia and Germany

BackgroundIn Latin American countries, the prevalence of noncommunicable diseases has increased rapidly in recent decades. Mobile health (mHealth) apps are now widely available at low cost and are easy to implement, offering an opportunity to encourage healthy lifestyles in older adults. However, at present, there are no mHealth apps that integrate multidomain healthy lifestyle interventions specifically adapted for older adults in Chile.ObjectiveThis study aims to describe the development and validation of NeoMayor, an mHealth app designed to promote healthy lifestyles as well as cardiovascular and brain health in older adults in Chile.MethodsNeoMayor was developed iteratively with feedback from users and input from a multidisciplinary team of clinicians, researchers, and software developers. Using lean user experience methodology, we ensured user involvement throughout the design and validation process. The research was conducted in 2 phases. In the design and development phase, we created and adapted evidence-based recommendations. In the validation phase, we conducted a pilot study to assess usability, adherence, and cardiovascular health (CVH). A total of 60 functionally independent and cognitively healthy participants used the NeoMayor app for 2 months. Clinical and cognitive assessments were conducted before and after app use. We held 26 cocreation sessions with users, consulted experts, performed a literature review, and collaborated with a team of app developers to create a functional prototype.ResultsThe mean age of the participants was 71 (SD 15) years, and 85% (51/60) were female. Participants had an average of 9.8 (SD 3.6) years of education. At the end of the 2-month intervention, usability testing indicated high engagement and adherence, with participants using the app for an average of 6.6 (SD 11.85) minutes per day twice a week. Improvements were observed in global CVH, with the mean Life’s Essential 8 CVH index score increasing from 64 (SD 10) to 68 (SD 11; P<.001). Reductions were noted in systolic blood pressure (10 mm Hg) and waist circumference (7 cm), along with increased high-density lipoprotein cholesterol levels. Participants also showed improvements in self-reported physical activity and diet, higher scores on the Short Physical Performance Battery, and faster performance times on the sit-to-stand and gait speed tests. The app was optimized for broad compatibility with Android devices, safe data collection and storage, and compliance with data privacy regulations following good clinical practices. The final product is ready for testing in a randomized controlled trial.ConclusionsThis study represents the first initiative in Chile to develop and validate an mHealth app to promote healthy lifestyles as well as cardiovascular and brain health in older adults, offering an effective, accessible, and affordable solution for promoting healthy aging in Latin American countries.

Objectives: Mobile Health (mHealth) apps have emerged as transformative tools with the potential to revolutionize health-care delivery, particularly in resource-constrained settings like Bangladesh. This cross-sectional study aimed to explore the trends of use of mHealth apps among Bangladeshi physicians and assess their attitudes toward integrating these apps into the health-care system. Material and Methods: Data were collected from 120 physicians using structured questionnaires, addressing awareness, usage patterns, barriers, and future considerations related to mHealth apps. Descriptive statistical analyses were conducted to identify factors influencing mHealth app adoption and attitudes among Bangladeshi physicians. Results: The results indicated a relatively high level of engagement with mHealth apps among Bangladeshi physicians, with 63.3% reporting personal usage for health monitoring. However, variability in recommendation practices and integration into clinical workflows highlighted challenges in adoption. Barriers to adoption included lack of awareness, security concerns, and technological barriers. Despite these challenges, a significant proportion of physicians expressed willingness to consider adopting mHealth apps in the future. Conclusion: The findings of this study underscore the need for targeted interventions to address barriers to mHealth app adoption and promote their effective integration into Bangladesh’s health-care system. Recommendations include targeted educational initiatives, addressing infrastructure barriers, and fostering collaboration among stakeholders. By leveraging mHealth technology, Bangladesh can advance toward a more accessible, efficient, and patient-centered health-care delivery model.

BackgroundPatients with ankylosing spondylitis (AS), a chronic systematic inflammatory disease, require long-term treatment and management. Mobile health (mHealth) apps can deliver health services through mobile devices, facilitate long-term disease management, support patient–health care provider communication, and enable patients to engage in disease management. There are some apps targeted at patients with AS, but the feature and quality of these apps have not been systematically examined.ObjectiveThe aim of this study was to identify existing, publicly available Chinese mHealth apps for AS management and to evaluate their features and quality.MethodsWe systematically searched potential apps for AS management on the Apple and Huawei App Stores, using 4 search terms: ankylosing spondylitis, spondyloarthritis, rheumatic disease, and arthritis. Apps were included if they were in the Chinese language, targeted at patients with AS, could be downloaded and run on Android and/or iOS operating systems, and incorporated elements of disease management and/or patient education. We excluded apps that were not for patient use, not relevant to AS, or had not been updated since 2018. Apps that met the inclusion criteria were downloaded for final analysis. We formulated a list of app quality measures from and consistent with international guidelines for mHealth apps and AS management to evaluate the features and quality of the included app. The user version of the Mobile App Rating Scale (uMARS) was also used to rate the apps’ quality.ResultsOf the 354 apps screened, 5 met the inclusion criteria and were included in our analysis. All apps were free, and most apps (4/5, 80%) had a privacy policy. Of the 5 apps, 1 (20%) involved medical professionals in the development process, 2 (40%) were developed by companies, and 2 (40%) were developed by medical institutions. All apps provided educational information about AS. Around half of the apps had functions like a basic information record (ie, users can input gender, age, disease history, etc) (n=3, 60%), patient–health care provider (and patient-patient) communication (n=2, 40%), symptom tracking (n=2, 40%), and information sharing (n=3, 60%). Only 1 (20%) app provided comprehensive functions that adhered to international guidelines for AS management and mHealth apps. The overall uMARS scores ranged from 2.7 to 4.2; only 1 app, with an overall uMARS score of 4.2, was considered as a high-quality app.ConclusionsMost apps lacked comprehensive functions for AS management. One high-quality app provided comprehensive functions to help patients manage their conditions. This study assessed and summarized the features and quality of the apps but did not evaluate their efficacy. Future studies should evaluate the feasibility and efficacy of these apps. International guidelines and regulations for the design, development, validation, and implementation of mHealth apps are needed in the future. Meanwhile, health care providers, patients with AS, and app developers should collaborate to develop high-quality, evidence-based apps that take into account patients’ needs and health care professionals’ perspectives.

Mobile health (mHealth) apps are increasingly being used by community members to track symptoms and manage endometriosis. In addition, clinicians use mHealth apps for continued medical education and clinical decision-making and recommend good-quality apps to patients. However, poor-quality apps can spread misinformation or provide recommendations that are not evidence-based. Therefore, a critical evaluation is needed to assess and recommend good-quality endometriosis mHealth apps. This study aimed to evaluate the quality and provide recommendations for good quality endometriosis mHealth apps for the community and clinicians. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines informed the search of mHealth apps on the Google Play Store and Apple App Store. The search terms included "endometriosis," "adenomyosis," and "pelvic pain." mHealth apps were eligible if they were (1) related to the search terms, (2) were in the English language, and (3) were available free of cost. Only the free content of the eligible mHealth apps was assessed. ENLIGHT, a validated evaluation tool for mobile and web-based interventions, was used to assess the quality across 7 domains such as usability, visual design, user engagement, content, therapeutic persuasiveness, therapeutic alliance, and general subjective evaluation. mHealth apps with a total score of ≥3.5 were classified as "good" according to the ENLIGHT scoring system and are recommended as good-quality mHealth apps for endometriosis care. In total, 42 mHealth apps were screened, and 19 were included in the quality assessment. A total of 6 good-quality mHealth apps were identified (QENDO, Bearable, Luna for Health, Matilda Health, Branch Health: Pain Management, and CHARLI Health). These apps provided symptom-tracking functions and self-management support. A total of 17 apps were designed for community use, while 2 apps provided a digital endometriosis classification tool to clinicians. Most mHealth apps scored well (≥3.5) in the domains of usability (16/19, 84.2%), visual design (14/19, 73.7%), user engagement (11/19, 57.9%), and content (15/19, 78.9%). Few eHealth websites scored well on therapeutic persuasiveness (6/19, 31.6%), therapeutic alliance (9/19, 47.4%), and general subjective evaluation (6/19, 31.6%). Although time and geographical location can influence the search results, we identified 6 "good-quality" endometriosis mHealth apps that can be recommended to the endometriosis community. mHealth apps designed for community use should evaluate their effectiveness on user's endometriosis knowledge, self-recommended management strategies, pain self-efficacy, user satisfaction, and user quality of life. Digital technology should be leveraged to develop mHealth apps for clinicians that contribute to continued medical education and assist clinical decision-making in endometriosis management. Factors that enhance usability, visual design, therapeutic persuasiveness, and therapeutic alliance should be incorporated to ensure successful and long-term uptake of mHealth apps. PROSPERO CRD42020185475; https://tinyurl.com/384dkkmj.