Patients' Perspectives on the Data Confidentiality, Privacy, and Security of mHealth Apps: Systematic Review.

BACKGROUND: Mobile health (mHealth) apps have the potential to enhance health care service delivery. However, concerns regarding patients' confidentiality, privacy, and security consistently affect the adoption of mHealth apps. Despite this, no review has comprehensively summarized the findings of studies on this subject matter. OBJECTIVE: This systematic review aims to investigate patients' perspectives and awareness of the confidentiality, privacy, and security of the data collected through mHealth apps. METHODS: Using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a comprehensive literature search was conducted in 3 electronic databases: PubMed, Ovid, and ScienceDirect. All the retrieved articles were screened according to specific inclusion criteria to select relevant articles published between 2014 and 2022. RESULTS: A total of 33 articles exploring mHealth patients' perspectives and awareness of data privacy, security, and confidentiality issues and the associated factors were included in this systematic review. Thematic analyses of the retrieved data led to the synthesis of 4 themes: concerns about data privacy, confidentiality, and security; awareness; facilitators and enablers; and associated factors. Patients showed discordant and concordant perspectives regarding data privacy, security, and confidentiality, as well as suggesting approaches to improve the use of mHealth apps (facilitators), such as protection of personal data, ensuring that health status or medical conditions are not mentioned, brief training or education on data security, and assuring data confidentiality and privacy. Similarly, awareness of the subject matter differed across the studies, suggesting the need to improve patients' awareness of data security and privacy. Older patients, those with a history of experiencing data breaches, and those belonging to the higher-income class were more likely to raise concerns about the data security and privacy of mHealth apps. These concerns were not frequent among patients with higher satisfaction levels and those who perceived the data type to be less sensitive. CONCLUSIONS: Patients expressed diverse views on mHealth apps' privacy, security, and confidentiality, with some of the issues raised affecting technology use. These findings may assist mHealth app developers and other stakeholders in improving patients' awareness and adjusting current privacy and security features in mHealth apps to enhance their adoption and use. TRIAL REGISTRATION: PROSPERO CRD42023456658; https://tinyurl.com/ytnjtmca.

The French General Population's Perception of New Information and Communication Technologies for Medical Consultations: National Survey.

BACKGROUND: The development of telehealth and telemedicine, in the form of increased teleconsultation and medical telemonitoring, accelerated during the COVID-19 health crisis in France to ensure continued access to care for the population. Since these new information and communication technologies (ICTs) are diverse and likely to transform how the health care system is organized, there is a need better to understand public attitudes toward them and their relationship with peoples' current experience of health care. OBJECTIVE: This study aimed to determine the French general population's perception of the usefulness of video recording/broadcasting (VRB) and mobile Health (mHealth) apps for medical consultations in France during the COVID-19 health crisis and the factors associated with this perception. METHODS: Data were collected for 2003 people in 2 waves of an online survey alongside the Health Literacy Survey 2019 (1003 in May 2020 and 1000 in January 2021) based on quota sampling. The survey collected sociodemographic characteristics, health literacy levels, trust in political representatives, and perceived health status. The perceived usefulness of VRB in medical consultations was measured by combining 2 responses concerning this technology for consultations. The perceived usefulness of mHealth apps was measured by combining 2 responses concerning their usefulness for booking doctor appointments and for communicating patient-reported outcomes to doctors. RESULTS: The majority (1239/2003, 62%) of respondents considered the use of mHealth apps useful, while only 27.6% (551/2003) declared VRB useful. The factors associated with the perceived usefulness of both technologies were younger age (≤ 55 years), trust in political representatives (VRB: adjusted odds ratio [aOR] 1.68, 95% CI 1.31-2.17; mHealth apps: aOR 1.88, 95% CI 1.42-2.48), and higher (sufficient and excellent) health literacy. The period of the beginning of the COVID-19 epidemic, living in an urban area, and being limited in daily activities were also associated with perceiving VRB positively. The perceived usefulness of mHealth apps increased with the level of education. It was also higher in people who had 3 or more consultations with a medical specialist. CONCLUSIONS: There are important differences in attitudes toward new ICTs. Perceived usefulness was lower for VRB than for mHealth apps. Moreover, it decreased after the initial months of the COVID-19 pandemic. There is also the possibility of new inequalities. Hence, despite the potential benefits of VRB and mHealth apps, people with low health literacy considered them to be of little use for their health care, possibly increasing their difficulties in accessing health care in the future. As such, health care providers and policy makers need to consider those perceptions to guarantee that new ICTs are accessible and beneficial to all.

Characterizing Consumer Smartphone Apps for Virtual Reality-Based Exposure Therapy: Content Analysis.

BACKGROUND: In vivo exposure therapy is the most effective treatment for phobias but is often impractical. Virtual reality exposure therapy (VRET) can help overcome critical barriers to in vivo exposure therapy. However, accessible mobile software related to VRET is not well understood. OBJECTIVE: The purpose of our study is to describe the landscape of accessible smartphone apps with potential utility for clinical VRET. METHODS: We conducted a content analysis of publicly available smartphone apps related to virtual reality on the Google Play Store and the Apple App Store as of March 2020. RESULTS: The initial search yielded 525 apps, with 84 apps (52 on the Google Play Store and 32 on the Apple App Store) included for analysis. The most common phobic stimulus depicted was bodies of water or weather events (25/84, 29.8%), followed by heights (24/84, 28.6%), and animals (23/84, 27.4%). More than half of the apps were visually abstract (39/84, 53.5%). Most apps were free to use (48/84, 57.1%), while the rest were free to try (22/84, 26.2%) or required payment for use (14/84, 16.7%), with the highest cost for use being US $6. The average overall app rating was 2.9 stars out of 5, but the number of ratings ranged from 0 to 49,233. None of the 84 apps advertised compliance with the Health Insurance Portability and Accountability Act, offered the ability to monitor data, provided clinician control over variables in the app experiences, or explicitly stated use by or development with clinicians. CONCLUSIONS: None of the smartphone apps reviewed were explicitly developed for phobia therapy. However, 16 of the 84 included apps were considered ideal candidates to investigate further as part of treatment due to their accessibility, depiction of phobia-relevant stimuli, low or no cost, and high user scores. Most of these apps were visually abstract and free to use, making them accessible and potentially flexible as part of clinical exposure hierarchies. However, none of the apps were designed for clinical use, nor did they provide tools for clinician workflows. Formal evaluation of these accessible smartphone apps is needed to understand the clinical potential of accessible VRET solutions.

Machine learning for mHealth apps quality evaluation: An approach based on user feedback analysis.

Mobile apps for healthcare (mHealth apps for short) have been increasingly adapted to help users manage their health or to get healthcare services. User feedback analysis is a pertinent method that can be used to improve the quality of mHealth apps. The objective of this paper is to use supervised machine learning algorithms to evaluate the quality of mHealth apps according to the ISO/IEC 25010 quality model based on user feedback. For this purpose, a total of 1682 user reviews have been collected from 86 mHealth apps provided by Google Play Store. Those reviews have been classified initially into the ISO/IEC 25010 eight quality characteristics, and further into Negative, Positive, and Neutral opinions. This analysis has been performed using machine learning and natural language processing techniques. The best performances were provided by the Stochastic Gradient Descent (SGD) classifier with an accuracy of 82.00% in classifying user reviews according to the ISO/IEC 25010 quality characteristics. Moreover, Support Vector Machine (SVM) classified the collected user reviews into Negative, Positive, and Neutral with an accuracy of 90.50%. Finally, for each quality characteristic, we classified the collected reviews according to the sentiment polarity. The best performance results were obtained for the Usability, Security, and Compatibility quality characteristics using SGD classifier with an accuracy equal to 98.00%, 97.50%, and 96.00%, respectively. The results of this paper will be effective to assist developers in improving the quality of mHealth apps.

Analysis of mHealth research: mapping the relationship between mobile apps technology and healthcare during COVID-19 outbreak.

BACKGROUND: Mobile health applications (mHealth apps) offer enormous promise for illness monitoring and treatment to improve the provided medical care and promote health and wellbeing. OBJECTIVE: We applied bibliometric quantitative analysis and network visualization to highlight research trends and areas of particular interest. We expect by summarizing the trends in mHealth app research, our work will serve as a roadmap for future investigations. METHODS: Relevant English publications were extracted from the Scopus database. VOSviewer (version 1.6.17) was used to build coauthorship networks of authors, countries, and the co-occurrence networks of author keywords. RESULTS: We analyzed 550 published articles on mHealth apps from 2020 to February 1, 2021. The yearly publications increased from 130 to 390 in 2021. JMIR mHealth and uHealth (33/550, 6.0%), J. Med. Internet Res. (27/550, 4.9%), JMIR Res. Protoc. (22/550, 4.0%) were the widest journals for these publications. The United States has the largest number of publications (143/550, 26.0%), and England ranks second (96/550, 17.5%). The top three productive authors were: Giansanti D., Samuel G., Lucivero F., and Zhang L. Frequent authors' keywords have formed major 4 clusters representing the hot topics in the field: (1) artificial intelligence and telehealthcare; (2) digital contact tracing apps, privacy and security concerns; (3) mHealth apps and mental health; (4) mHealth apps in public health and health promotion. CONCLUSIONS: mHealth apps undergo current developments, and they remain hot topics in COVID-19. These findings might be useful in determining future perspectives to improve infectious disease control and present innovative solutions for healthcare.

Factors affecting physicians using mobile health applications: an empirical study.

BACKGROUND: Mobile health applications (mHealth apps) have created innovative service channels for patients with chronic diseases. These innovative service channels require physicians to actively use mHealth apps. However, few studies investigate physicians' participation in mHealth apps. OBJECTIVE: This study aims to empirically explore factors affecting physicians' usage behaviors of mHealth apps. Based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and mHealth apps features, we propose a research model including altruism, cognitive trust, and online ratings. METHODS: We collected data from physicians who have used mHealth apps and conducted a factor analysis to verify the convergence and discriminative effects. We used a hierarchical regression method to test the path coefficients and statistical significance of our research model. In addition, we adopted bootstrapping approach and further analyzed the mediating effects of behavioral intention between all antecedent variables and physicians' usage behavior. Finally, we conducted three robustness analyses to test the validity of results and tested the constructs to verify the common method bias. RESULTS: Our results support the effects of performance expectancy, effort expectancy, social influence, and altruism on the behavioral intentions of physicians using mHealth apps. Moreover, facilitating conditions and habits positively affect physicians using mHealth apps through the mediating effort of behavioral intention. Physicians' cognitive trust and online rating have significant effects on their usage behaviors through the mediating efforts of behavioral intention. CONCLUSIONS: This study contributes to the existing literature on UTAUT2 extension of physicians' acceptance of mHealth apps by adding altruism, cognitive trust, and online ratings. The results of this study provide a novel perspective in understanding the factors affecting physicians' usage behaviors on mHealth apps in China and provide such apps' managers with an insight into the promotion of physicians' active acceptance and usage behaviors.

Preliminary Investigation of Shift, a Novel Smartphone App to Support Junior Doctors' Mental Health and Well-being: Examination of Symptom Progression, Usability, and Acceptability After 1 Month of Use.

BACKGROUND: Shift is a novel smartphone app for providing a digital-first mental health resource to junior doctors. It contains psychoeducational material, cognitive behavioral modules, guided mediations, information on common work stressors, and a section on help-seeking options for psychological problems through workplace and private avenues. OBJECTIVE: This study aimed to conduct a preliminary investigation of the use and potential effectiveness of Shift on depressive and anxiety symptoms (primary outcomes) and work and social functioning, COVID-19 safety concerns, and help seeking (secondary outcomes). This study also sought feedback on whether Shift was seen as an acceptable tool. METHODS: Junior doctors in New South Wales, Australia, were approached through promotional activities from the Ministry of Health, specialist medical colleges, and social media advertisements between June and August 2020. Consenting participants provided web-based baseline data, used the Shift app for 30 days, and were asked to complete a poststudy web-based questionnaire. Outcomes were analyzed under the intention-to-treat principle. RESULTS: A total of 222 (n=156 female, 70.3%; mean age 29.2, SD 4.61 years) junior doctors provided full baseline data. Of these, 89.2% (198/222) downloaded the app, logged into the app approximately 6 times (mean 5.68, SD 7.51), completed 4 in-app activities (mean 3.77, SD 4.36), and spent a total of 1 hour on in-app activities (mean 52:23, SD 6:00:18) over 30 days. Postintervention and app use data were provided by 24.3% (54/222) of participants. Depressive and anxiety symptoms significantly decreased between the pre- and postassessment points as expected; however, physicians' COVID-19 safety concerns significantly increased. Work and social functioning, COVID-19 concerns for family and friends, and help seeking did not change significantly. There was no significant relationship between symptom changes and app use (number of log-ins, days between first and last log-in, and total activity time). Most poststudy completers (31/54, 57%) rated Shift highly or very highly. CONCLUSIONS: Despite high levels of nonresponse to the poststudy assessment and increases in COVID-19 safety concerns, junior doctors who used the app reported some improvements in depression and anxiety, which warrant further exploration in a robust manner.

A large scale analysis of mHealth app user reviews.

The global mHealth app market is rapidly expanding, especially since the COVID-19 pandemic. However, many of these mHealth apps have serious issues, as reported in their user reviews. Better understanding their key user concerns would help app developers improve their apps' quality and uptake. While app reviews have been used to study user feedback in many prior studies, many are limited in scope, size and/or analysis. In this paper, we introduce a very large-scale study and analysis of mHealth app reviews. We extracted and translated over 5 million user reviews for 278 mHealth apps. These reviews were then classified into 14 different aspects/categories of issues reported. Several mHealth app subcategories were examined to reveal differences in significant areas of user concerns, and to investigate the impact of different aspects of mhealth apps on their ratings. Based on our findings, women's health apps had the highest satisfaction ratings. Fitness activity tracking apps received the lowest and most unfavourable ratings from users. Over half of users who reported troubles leading them to uninstall mHealth apps gave a 1-star rating. Half of users gave the account and logging aspect only one star due to faults and issues encountered while registering or logging in. Over a third of users who expressed privacy concerns gave the app a 1-star rating. However, only 6% of users gave apps a one-star rating due to UI/UX concerns. 20% of users reported issues with handling of user requests and internationalisation concerns. We validated our findings by manually analysing a sample of 1,000 user reviews from each investigated aspect/category. We developed a list of recommendations for mHealth apps developers based on our user review analysis.

Effectivness of specific mobile health applications (mHealth-apps) in gestational diabtetes mellitus: a systematic review.

BACKGROUND: Gestational diabetes mellitus (GDM) emerges worldwide and is closely associated with short- and long-term health issues in women and their offspring, such as pregnancy and birth complications respectively comorbidities, Type 2 Diabetes (T2D), metabolic syndrome as well as cardiovascular diseases. Against this background, mobile health applications (mHealth-Apps) do open up new possibilities to improve the management of GDM. Therefore, we analyzed the clinical effectiveness of specific mHealth-Apps on clinical health-related short and long-term outcomes in mother and child. METHODS: A systematic literature search in Medline (PubMed), Cochrane Library, Embase, CINAHL and Web of Science Core Collection databases as well as Google Scholar was performed. We selected studies published 2008 to 2020 analyzing women diagnosed with GDM using specific mHealth-Apps. Controlled clinical trials (CCT) and randomized controlled trials (RCT) were included. Study quality was assessed using the Effective Public Health Practice Project (EPHPP) tool. RESULTS: In total, n = 6 publications (n = 5 RCTs, n = 1 CCT; and n = 4 moderate, n = 2 weak quality), analyzing n = 408 GDM patients in the intervention and n = 405 in the control groups, were included. Compared to control groups, fasting blood glucose, 2-h postprandial blood glucose, off target blood glucose measurements, delivery mode (more vaginal deliveries and fewer (emergency) caesarean sections) and patient compliance showed improving trends. CONCLUSION: mHealth-Apps might improve health-related outcomes, particularly glycemic control, in the management of GDM. Further studies need to be done in more detail.

Mapping evidence of mobile health technologies for disease diagnosis and treatment support by health workers in sub-Saharan Africa: a scoping review.

BACKGROUND: The rapid growth of mobile technology has given rise to the development of mobile health (mHealth) applications aimed at treating and preventing a wide range of health conditions. However, evidence on the use of mHealth in high disease burdened settings such as sub-Sharan Africa is not clear. Given this, we systematically mapped evidence on mHealth for disease diagnosis and treatment support by health workers in sub-Saharan Africa. METHODS: We conducted a scoping review study guided by the Arksey and O'Malley's framework, Levac et al. recommendations, and Joanna Briggs Institute guidelines. We thoroughly searched the following databases: MEDLINE and CINAHL with full text via EBSCOhost; PubMed; Science Direct and Google Scholar for relevant articles from the inception of mHealth technology to April 2020. Two reviewers independently screened abstracts and full-text articles using the eligibility criteria as reference. This study employed the mixed methods appraisal tool version 2018 to assess the methodological quality of the included studies. RESULTS: Out of the 798 articles identified, only 12 published articles presented evidence on the availability and use of mHealth for disease diagnosis and treatment support by health workers in SSA since 2010. Of the 12 studies, four studies were conducted in Kenya; two in Malawi; two in Nigeria; one in South Africa; one in Zimbabwe; one in Mozambique, and one in Lesotho. Out of the 12 studies, one reported the use of mHealth for diseases diagnosis; three reported the use of mHealth to manage HIV; two on the management of HIV/TB; two on the treatment of malaria; one each on the management of hypertension; cervical cancer; and three were not specific on any disease condition. All the 12 included studies underwent methodological quality appraisal with a scored between 70 and 100%. CONCLUSIONS: The study shows that there is limited research on the availability and use of mHealth by health workers for disease diagnosis and treatment support in sub-Saharan Africa. We, therefore, recommend primary studies focusing on the use of mHealth by health workers for disease diagnosis and treatment support in sub-Saharan Africa.

Driving towards Precision Medicine for angioedema without wheals.

Evidence accumulated over the last two decades indicates that recurrent angioedema without wheals constitutes a diverse family of disorders with a much higher complexity than was previously regarded. Indicatively, during the last two years, novel variants of three genes other than SERPING1 and F12 have been identified in association with hereditary angioedema. Most interestingly, functional studies of at least one of these variants (the variant c.807G > T of ANGPT1 gene) imply the existence of a new disease endotype in which the altered bradykinin metabolism and function does not play a central role. Therefore, using conventional approaches, it seems that the complexity of this disease cannot be sufficiently elucidated and any attempt to interrelate its many diverse aspects seems unrealistic. Similar to other rare and chronic diseases, a Precision Medicine approach, discovering the right target and giving "the right drug, for the right patient, at the right time, every time" seems the optimal future practice. Herein, we review recent data challenging and dictating the need for a switch of angioedema research into high-throughput approaches and we present the expected advantages for better understanding of the disease and patients management.

Old age or cognitive decline? Examining the usability of a mobile health app for older Australians.

There is a growing literature on the role of mobile health applications (mHealth apps) in supporting older adults and the self-management of personal health. The purpose of this pilot study is to assess the usability of a government-funded mobile health app amongst older Australians and to evaluate whether cognitive function and demographic characteristics (i.e. age, gender, education) are associated with usability. A total of 28 older adults living in a regional city in Australia took part in the study. The participants were recruited using purposive sampling. Data collection instruments consisted of validated cognitive tests, task-based usability tests, and a questionnaire. The data was analyzed using non-parametric strategies. The findings of this study demonstrated that a government-funded, mHealth app was usable by older adults. Users were able to perform basic tasks in an effective and efficient manner. The hypothesis that elderly age would be significantly associated with performance on cognitive tests, as well as usability, was not supported. Performance on some cognitive tests was significantly and positively related to usability. Education and gender were not related to usability. The results suggest that traditional stereotypes surrounding aging and cognitive decline need to be reexamined.

mHealth Apps Use and Their Associations With Healthcare Decision-Making and Health Communication Among Informal Caregivers: Evidence From the National Cancer Institute's Health Information National Trends Survey.

PURPOSE: The current study investigates associations between mHealth apps and healthcare decision-making and health communication among informal caregivers in the US. DESIGN: Cross-sectional study employing secondary data. SETTING: The Health Information National Trends Survey (HINTS5, Cycles 2 through 4, 2018 - 2020). SAMPLE: Self-identified informal caregivers (n = 1386; had mHealth apps = 61.3%, female = 63.2%, some college or more in education = 80.3%) who reported owning at least a smartphone or a tablet computer (i.e., ownership of a "smart device"). MEASURES: Sociodemographic characteristics, reports of having mHealth apps, smart device utilization in healthcare decision-making and health communication. ANALYSIS: Accounting for the complex design features of the HINTS data, we constructed multiple hierarchical logistic regressions to compute adjusted odds ratios (aOR) and their 95% confidence intervals (CI). RESULTS: Compared to caregivers without mHealth apps, those with the apps had higher odds of utilizing their smart devices to make a health-related decision, such as how to treat a disease or a medical condition (aOR = 1.65; 95% CI: 1.13-2.39, P < .01), or engage in health-related discussions with a healthcare provider (aOR = 2.36; 95% CI: 1.54-3.61, P < .001). CONCLUSION: Having mHealth apps was associated with a higher likelihood of using smart devices in healthcare decision-making and health communication by informal caregivers. Empowering caregivers to make informed health-related decisions and communicate effectively with healthcare providers are both crucial to health promotion and well-being. Future studies should investigate facilitators as well as barriers to using mHealth apps and smart devices in health-promoting strategies involving informal caregivers.

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

OBJECTIVE: Although evidence of the global effectiveness and usability of mobile health (mHealth) apps as non-drug interventions is growing, older adults often demonstrate low adoption rates of these apps. This study aims to identify the perspectives of older adults on introducing and adopting mHealth apps in Australia and Germany. MATERIALS AND METHODS: We conducted two online cross-sectional surveys to examine factors from contextual, technological and personal perspectives that influence older adults in mHealth app adoption. Using descriptive statistics, chi-square tests and exploratory factor analysis, we identified the differences and similarities between respondents' perspectives across two countries. RESULTS: A total of 290 respondents (149, Australia; 141, Germany) completed the survey. Older adults' ability to use a mHealth app, the user-friendliness of the app, their positive self-efficacy regarding their health and resource availability for using mHealth apps were related to intended adoption. Differences between Germany and Australia were found in issues concerned with data sharing and empowerment by the doctor, while similarities were related to trust in the doctor and their treatment approaches. DISCUSSION AND CONCLUSION: This study highlights participants' perspectives and attitudes towards mHealth app use, unmet needs and barriers, and the facilitating influences in the two countries. These insights can be used to inform the development and implementation of mHealth apps and to construct tailored strategies to increase the adoption rates of mHealth apps among older adults and to maximise their potential benefits.

CRUSE® -An innovative mobile application for patient monitoring and management in chronic spontaneous urticaria.

BACKGROUND: Chronic spontaneous urticaria (CSU) is unpredictable and can severely impair patients' quality of life. Patients with CSU need a convenient, user-friendly platform to complete patient-reported outcome measures (PROMs) on their mobile devices. CRUSE® , the Chronic Urticaria Self Evaluation app, aims to address this unmet need. METHODS: CRUSE® was developed by an international steering committee of urticaria specialists. Priorities for the app based on recent findings in CSU were defined to allow patients to track and record their symptoms and medication use over time and send photographs. The CRUSE® app collects patient data such as age, sex, disease onset, triggers, medication, and CSU characteristics that can be sent securely to physicians, providing real-time insights. Additionally, CRUSE® contains PROMs to assess disease activity and control, which are individualised to patient profiles and clinical manifestations. RESULTS: CRUSE® was launched in Germany in March 2022 and is now available for free in 17 countries. It is adapted to the local language and displays a country-specific list of available urticaria medications. English and Ukrainian versions are available worldwide. From July 2022 to June 2023, 25,710 observations were documented by 2540 users; 72.7% were females, with a mean age of 39.6 years. At baseline, 93.7% and 51.3% of users had wheals and angioedema, respectively. Second-generation antihistamines were used in 74.0% of days. CONCLUSIONS: The initial data from CRUSE® show the wide use and utility of effectively tracking patients' disease activity and control, paving the way for personalised CSU management.

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

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

Effectiveness of mHealth App-Based Interventions for Increasing Physical Activity and Improving Physical Fitness in Children and Adolescents: Systematic Review and Meta-Analysis.

BACKGROUND: The COVID-19 pandemic has significantly reduced physical activity (PA) levels and increased sedentary behavior (SB), which can lead to worsening physical fitness (PF). Children and adolescents may benefit from mobile health (mHealth) apps to increase PA and improve PF. However, the effectiveness of mHealth app-based interventions and potential moderators in this population are not yet fully understood. OBJECTIVE: This study aims to review and analyze the effectiveness of mHealth app-based interventions in promoting PA and improving PF and identify potential moderators of the efficacy of mHealth app-based interventions in children and adolescents. METHODS: We searched for randomized controlled trials (RCTs) published in the PubMed, Web of Science, EBSCO, and Cochrane Library databases until December 25, 2023, to conduct this meta-analysis. We included articles with intervention groups that investigated the effects of mHealth-based apps on PA and PF among children and adolescents. Due to high heterogeneity, a meta-analysis was conducted using a random effects model. The Cochrane Risk of Bias Assessment Tool was used to evaluate the risk of bias. Subgroup analysis and meta-regression analyses were performed to identify potential influences impacting effect sizes. RESULTS: We included 28 RCTs with a total of 5643 participants. In general, the risk of bias of included studies was low. Our findings showed that mHealth app-based interventions significantly increased total PA (TPA; standardized mean difference [SMD] 0.29, 95% CI 0.13-0.45; P<.001), reduced SB (SMD -0.97, 95% CI -1.67 to -0.28; P=.006) and BMI (weighted mean difference -0.31 kg/m2, 95% CI -0.60 to -0.01 kg/m2; P=.12), and improved muscle strength (SMD 1.97, 95% CI 0.09-3.86; P=.04) and agility (SMD -0.35, 95% CI -0.61 to -0.10; P=.006). However, mHealth app-based interventions insignificantly affected moderate to vigorous PA (MVPA; SMD 0.11, 95% CI -0.04 to 0.25; P<.001), waist circumference (weighted mean difference 0.38 cm, 95% CI -1.28 to 2.04 cm; P=.65), muscular power (SMD 0.01, 95% CI -0.08 to 0.10; P=.81), cardiorespiratory fitness (SMD -0.20, 95% CI -0.45 to 0.05; P=.11), muscular endurance (SMD 0.47, 95% CI -0.08 to 1.02; P=.10), and flexibility (SMD 0.09, 95% CI -0.23 to 0.41; P=.58). Subgroup analyses and meta-regression showed that intervention duration was associated with TPA and MVPA, and age and types of intervention was associated with BMI. CONCLUSIONS: Our meta-analysis suggests that mHealth app-based interventions may yield small-to-large beneficial effects on TPA, SB, BMI, agility, and muscle strength in children and adolescents. Furthermore, age and intervention duration may correlate with the higher effectiveness of mHealth app-based interventions. However, due to the limited number and quality of included studies, the aforementioned conclusions require validation through additional high-quality research. TRIAL REGISTRATION: PROSPERO CRD42023426532; https://tinyurl.com/25jm4kmf.

Nurses' Use of mHealth Apps for Chronic Conditions: Cross-Sectional Survey.

BACKGROUND: Mobile health (mHealth) is increasingly used to support public health practice, as it has positive benefits such as enhancing self-efficacy and facilitating chronic disease management. Yet, relatively few studies have explored the use of mHealth apps among nurses, despite their important role in caring for patients with and at risk of chronic conditions. OBJECTIVE: The aim of the study is to explore nurses' use of mHealth apps to support adults with or at risk of chronic conditions and understand the factors that influence technology adoption. METHODS: A web-based cross-sectional survey was conducted between September 2022 and January 2023. The survey was shared via social media and professional nursing organizations to Australian nurses caring for adults with or at risk of chronic conditions. RESULTS: A total of 158 responses were included in the analysis. More than two-thirds (n=108, 68.4%) of respondents reported that they personally used at least 1 mHealth app. Over half (n=83, 52.5% to n=108, 68.4%) reported they use mHealth apps at least a few times a month for clinical purposes. Logistic regression demonstrated that performance expectancy (P=.04), facilitating condition (P=.05), and personal use of mHealth apps (P=.05) were significantly associated with mHealth app recommendation. In contrast, effort expectancy (P=.09) and social influence (P=.46) did not have a significant influence on whether respondents recommended mHealth apps to patients. The inability to identify the quality of mHealth apps and the lack of access to mobile devices or internet were the most common barriers to mHealth app recommendation. CONCLUSIONS: While nurses use mHealth apps personally, there is potential to increase their clinical application. Given the challenges reported in appraising and assessing mHealth apps, app regulation and upskilling nurses will help to integrate mHealth apps into usual patient care.

Translating Suicide Safety Planning Components Into the Design of mHealth App Features: Systematic Review.

BACKGROUND: Suicide safety planning is an evidence-based approach used to help individuals identify strategies to keep themselves safe during a mental health crisis. This study systematically reviewed the literature focused on mobile health (mHealth) suicide safety planning apps. OBJECTIVE: This study aims to evaluate the extent to which apps integrated components of the safety planning intervention (SPI), and if so, how these safety planning components were integrated into the design-based features of the apps. METHODS: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we systematically analyzed 14 peer-reviewed studies specific to mHealth apps for suicide safety planning. We conducted an analysis of the literature to evaluate how the apps incorporated SPI components and examined similarities and differences among the apps by conducting a comparative analysis of app features. An independent review of SPI components and app features was conducted by downloading the available apps. RESULTS: Most of the mHealth apps (5/7, 71%) integrated SPI components and provided customizable features that expanded upon traditional paper-based safety planning processes. App design features were categorized into 5 themes, including interactive features, individualized user experiences, interface design, guidance and training, and privacy and sharing. All apps included access to community supports and revisable safety plans. Fewer mHealth apps (3/7, 43%) included interactive features, such as associating coping strategies with specific stressors. Most studies (10/14, 71%) examined the usability, feasibility, and acceptability of the safety planning mHealth apps. Usability findings were generally positive, as users often found these apps easy to use and visually appealing. In terms of feasibility, users preferred using mHealth apps during times of crisis, but the continuous use of the apps outside of crisis situations received less support. Few studies (4/14, 29%) examined the effectiveness of mHealth apps for suicide-related outcomes. Positive shifts in attitudes and desire to live, improved coping strategies, enhanced emotional stability, and a decrease in suicidal thoughts or self-harm behaviors were examined in these studies. CONCLUSIONS: Our study highlights the need for researchers, clinicians, and app designers to continue to work together to align evidence-based research on mHealth suicide safety planning apps with lessons learned for how to best deliver these technologies to end users. Our review brings to light mHealth suicide safety planning strategies needing further development and testing, such as lethal means guidance, collaborative safety planning, and the opportunity to embed more interactive features that leverage the advanced capabilities of technology to improve client outcomes as well as foster sustained user engagement beyond a crisis. Although preliminary evidence shows that these apps may help to mitigate suicide risk, clinical trials with larger sample sizes and more robust research designs are needed to validate their efficacy before the widespread adoption and use.

Dissemination Strategies for mHealth Apps: Systematic Review.

BACKGROUND: Among the millions of mobile apps in existence, thousands fall under the category of mobile health (mHealth). Although the utility of mHealth apps has been demonstrated for disease diagnosis, treatment data management, and health promotion strategies, to be effective they must reach and be used by their target audience. An appropriate marketing strategy can ensure that apps reach potential users and potentially convert them to actual users. Such a strategy requires definitions of target end users, communication channels, and advertising content, as well as a timeline for effectively reaching and motivating end users to adopt and maintain engagement with the mHealth app. OBJECTIVE: The aim of this study was to identify strategies and elements that ensure that end users adopt and remain engaged with mHealth apps. METHODS: A systematic search of the PubMed, PsycINFO, Scopus, and CINAHL databases was conducted for suitable studies published between January 1, 2018, and September 30, 2022. Two researchers independently screened studies for inclusion, extracted data, and assessed the risk of bias. The main outcome was dissemination strategies for mHealth apps. RESULTS: Of the 648 papers retrieved from the selected databases, only 10 (1.5%) met the inclusion criteria. The marketing strategies used in these studies to inform potential users of the existence of mHealth apps and motivate download included both paid and unpaid strategies and used various channels, including social media, emails, printed posters, and face-to-face communication. Most of the studies reported a combination of marketing concepts used to advertise their mHealth apps. Advertising messages included instructions on where and how to download and install the apps. In most of the studies (6/10, 60%), instructions were oriented toward how to use the apps and maintain engagement with a health intervention. The most frequently used paid marketing platform was Facebook Ads Manager (2/10, 20%). Advertising performance was influenced by many factors, including but not limited to advertising content. In 1 (10%) of the 10 studies, animated graphics generated the greatest number of clicks compared with other image types. The metrics used to assess marketing strategy effectiveness were number of downloads; nonuse rate; dropout rate; adherence rate; duration of app use; and app usability over days, weeks, or months. Additional indicators such as cost per click, cost per install, and clickthrough rate were mainly used to assess the cost-effectiveness of paid marketing campaigns. CONCLUSIONS: mHealth apps can be disseminated via paid and unpaid marketing strategies using various communication channels. The effects of these strategies are reflected in download numbers and user engagement with mHealth apps. Further research could provide guidance on a framework for disseminating mHealth apps and encouraging their routine use.