Exploring the Far Side of Mobile Health: Information Security and Privacy of Mobile Health Apps on iOS and Android

Fertility apps, datafication and knowledge production in reproductive health

Despite being the target of much criticism, commercialised digital technologies have proliferated in reproductive health arenas. Fertility applications (apps) are now some of the most popular and ubiquitous digital health tracking technologies, with millions of downloads. Previous scholarship has already underlined the problematic nature of their design and surveillance features. However, less attention has been paid to the wider effects of datafied knowledge availability. This research specifically asks: How does the proliferation of fertility apps shape knowledge (and associated practices) in reproductive health? Drawing on an analysis of key document sources, I here argue that fertility apps act as mediators between stakeholders, data and datafied outputs, thus facilitating: (1) the datafication of fertility awareness knowledge and the production of new datafied knowledge, (2) legitimation discourses and practices and (3) the remaking of private/public expertise and knowledge production networks in reproductive health. To effectively analyse the effects of commercialised reproductive health apps, this work argues for an understanding of data technologies that is informed by critical data studies.

Applications of digital health approaches for cardiometabolic diseases prevention and management in the Western Pacific region

Cardiometabolic diseases (CMDs) are the major types of non-communicable diseases, contributing to huge disease burdens in the Western Pacific region (WPR). The use of digital health (dHealth) technologies, such as wearable gadgets, mobile apps, and artificial intelligence (AI), facilitates interventions for CMDs prevention and treatment. Currently, most studies on dHealth and CMDs in WPR were conducted in a few high- and middle-income countries like Australia, China, Japan, the Republic of Korea, and New Zealand. Evidence indicated that dHealth services promoted early prevention by behavior interventions, and AI-based innovation brought automated diagnosis and clinical decision-support. dHealth brought facilitators for the doctor-patient interplay in the effectiveness, experience, and communication skills during healthcare services, with rapidly development during the pandemic of coronavirus disease 2019. In the future, the improvement of dHealth services in WPR needs to gain more policy support, enhance technology innovation and privacy protection, and perform cost-effectiveness research.

[Apps for tinnitus? A systematic review on quality, intervention components, and behavior change techniques]

BACKGROUND

Various smartphone applications (apps) for people with tinnitus are available and promise tinnitus relief. Yet, it is difficult for people suffering from tinnitus and healthcare professionals to estimate their quality, potential, or risks. The current study aims to generate an overview of available tinnitus apps in the German language and to offer orientation for research and healthcare providers.

METHOD

The most prominent stores were searched systematically (November 2020-April 2021; Google Play Store and Apple App Store). Apps specifically developed for tinnitus were evaluated by two independent raters using multiple approaches: a) a quality screening was performed using the German version of the Mobile App Rating Scale (MARS-G), b) intervention components were assessed using a newly developed list of categories, and c) implemented strategies for active tinnitus management were analyzed using behavior change techniques (BCTs).

RESULTS

The search yielded 1073 apps, of which 21 apps were analyzed. The apps' overall quality as assessed by MARS‑G was average (M = 3.37, SD = 039). A lot of apps offered sounds (n = 18) and information (n = 9) or assessed tinnitus characteristics (n = 13). Out of 93 BCTs, 24 were identified at least once. Only one app was evaluated in non-randomized trials.

CONCLUSION

Although a variety of apps are available, most of them focus on a few intervention components (e.g., sounds or information). Therefore, apps do not exploit their potential to impart important evidence-based content for tinnitus management. The app evaluation using multiple approaches points out potential for improvement.

Assessing the Quality, Privacy, and Security of Breast Cancer Apps for Arabic Speakers: Systematic Search and Review of Smartphone Apps

BACKGROUND

Breast cancer is a widespread disease, and its incidence is rapidly increasing in the Middle East and North Africa region. With the increasing availability of smartphone apps for various health purposes, breast cancer apps have emerged as tools for raising awareness, providing support, and empowering women affected by this disease. These apps offer many features, including information on breast cancer risk factors, self-examination guides, appointment reminders, and community support groups or hotlines. Using apps raises the risk of privacy and security issues, and we hope that examining these features of the apps will contribute to the understanding of how technology can be used to improve these apps and provide insights for future development and improvement of breast cancer apps.

OBJECTIVE

This study aims to critically review the quality, privacy, and security of breast cancer apps available to Arabic speakers.

METHODS

Similar to several recent studies, we used a systematic search for apps available in Google Play and Apple App stores using both the web interface and the built-in native stores installed on smartphones. The search was conducted in mid-December 2022 in Arabic using the following keywords: سرطان الثدي - فحص سرطان الثدي - علاج سرطان الثدي - مرض سرطان الثدي - أعراض سرطان الثدي - فحص الثدي (breast cancer, breast cancer treatment, breast cancer disease, breast cancer symptoms, breast cancer screening, and breast test). These preidentified search terms are based on earlier work concerning the top searched breast cancer topics by Arabic speakers through Google's search engine. We excluded apps that did not have an Arabic interface, were developed for non-Arabic speakers, were paid, needed a subscription, or were directed toward health care workers. The Mobile App Rating Scale was used to evaluate the quality of the apps concerning their engagement, functionality, aesthetics, and information. A risk score was calculated for the apps to determine their security risk factors.

RESULTS

Only 9 apps were included, with most (6/9, 67%) being supported by advertisements and categorized as informational. Overall, the apps had low numbers of downloads (>10 to >1000). The majority of the included apps (8/9, 89%) requested dangerous access permissions, including access to storage, media files, and the camera. The average security score of the included apps was 3.22, while only 2 apps provided information about data security and privacy. The included apps achieved an overall average quality score of 3.27, with individual dimension scores of 4.75 for functionality, 3.04 for information, 3.00 for aesthetics, and 2.32 for engagement.

CONCLUSIONS

The limited availability of breast cancer apps available to Arabic speakers should be a call to action and prompt health care organizations and developers to join forces and collaboratively develop information-rich, usable, functional, engaging, and secure apps.

Human-centred artificial intelligence for mobile health sensing: challenges and opportunities

Advances in wearable sensing and mobile computing have enabled the collection of health and well-being data outside of traditional laboratory and hospital settings, paving the way for a new era of mobile health. Meanwhile, artificial intelligence (AI) has made significant strides in various domains, demonstrating its potential to revolutionize healthcare. Devices can now diagnose diseases, predict heart irregularities and unlock the full potential of human cognition. However, the application of machine learning (ML) to mobile health sensing poses unique challenges due to noisy sensor measurements, high-dimensional data, sparse and irregular time series, heterogeneity in data, privacy concerns and resource constraints. Despite the recognition of the value of mobile sensing, leveraging these datasets has lagged behind other areas of ML. Furthermore, obtaining quality annotations and ground truth for such data is often expensive or impractical. While recent large-scale longitudinal studies have shown promise in leveraging wearable sensor data for health monitoring and prediction, they also introduce new challenges for data modelling. This paper explores the challenges and opportunities of human-centred AI for mobile health, focusing on key sensing modalities such as audio, location and activity tracking. We discuss the limitations of current approaches and propose potential solutions.

Consumers' Preferences for Purchasing mHealth Apps: Discrete Choice Experiment

Background

There is growing interest in mobile health apps; however, not all of them have been successful. The most common issue has been users' nonadoption or abandonment of health apps because the app designs do not meet their preferences. Therefore, to facilitate design-preference fit, understanding consumers' preferences for health apps is necessary, which can be accomplished by using a discrete choice experiment.

Objective

This study aims to examine consumer preferences for health apps and how these preferences differ across individuals with different sociodemographic characteristics and health app usage and purchase experiences.

Methods

A cross-sectional discrete choice experiment questionnaire survey was conducted with 593 adults living in Hong Kong. A total of 7 health app attributes that might affect consumers' preferences for health apps were examined, including usefulness, ease of use, security and privacy, health care professionals' attitudes, smartphone storage consumption, mobile data consumption, and cost. Mixed-effect logit regressions were used to examine how these attributes affected consumer preferences for health apps. Fixed effects (coefficient β) of the attributes and random effects of individual differences were modeled. Subgroup analyses of consumer preferences by sex, age, household income, education level, and health app usage and purchase experiences were conducted.

Results

Cost was the attribute that had the greatest effect on consumers' choice of health apps (compared to HK $10 [US $1.27]-HK $50 [US $6.37]: β=-1.064; P<.001; HK $100 [US $12.75]: β=-2.053; P<.001), followed by security and privacy (compared to no security insurance-some security policies: β=.782; P<.001; complete security system: β=1.164; P<.001) and usefulness (compared to slightly useful-moderately useful: β=.234; P<.001; very useful: β=.979; P=.007), mobile data consumption (compared to data-consuming-a bit data-consuming: β=.647; P<.001; data-saving: β=.815; P<.001), smartphone storage consumption (compared to >100 MB-around 38 MB: β=.334; P<.001; <10 MB: β=.511; P<.001), and attitudes of health care professionals (compared to neutral-moderately supportive: β=.301; P<.001; very supportive: β=.324; P<.001). In terms of ease of use, consumers preferred health apps that were moderately easy to use (compared to not easy to use-moderately easy to use: β=.761; P<.001; very easy to use: β=.690; P<.001). Our results also showed that consumers with different sociodemographic characteristics and different usage and purchase experiences with health apps differed in their preferences for health apps.

Conclusions

It is recommended that future health apps keep their mobile data and phone storage consumption low, include a complete security system to protect personal health information, provide useful content and features, adopt user-friendly interfaces, and involve health care professionals. In addition, health app developers should identify the characteristics of their intended users and design and develop health apps to fit the preferences of the intended users.

Exploring mHealth applications for self-management of chronic low back pain: A survey of features and benefits

The adoption of Mobile Health (mHealth) for self-management is growing. mHealth solutions are commonly used in public healthcare and health services, where they are appreciated for their ease of use, broad reach, and wide acceptance. Chronic Low Back Pain (CLBP) is one of the most common health problems and a leading cause of disability. As such, it imposes a tremendous burden on patients and society. Studies have proposed that mHealth self-management solutions, such as mobile applications, can supplement traditional care methods and benefit patients, particularly in self-managing CLBP easier. To this end, the number of available mobile applications for CLBP has increased. This paper i) provides an overview of scientific studies on mobile applications for CLBP management from three different viewpoints: researchers, health professionals, and patients, ii) uncovers the application features that were seen as beneficial in the studies, and iii) contrasts the currently available applications for CLBP in Google Play Store and Apple App Store against the discovered features. The findings show that "Personalization and customization" is the most significant feature as it is beneficial from stakeholders' viewpoint and is represented by most applications. In contrast, "Gamification" and "Artificial intelligence" are the least significant features, indicating a lack of attention from application creators and researchers in this area.

Critical Criteria and Countermeasures for Mobile Health Developers to Ensure Mobile Health Privacy and Security: Mixed Methods Study

BACKGROUND

Despite the importance of the privacy and confidentiality of patients' information, mobile health (mHealth) apps can raise the risk of violating users' privacy and confidentiality. Research has shown that many apps provide an insecure infrastructure and that security is not a priority for developers.

OBJECTIVE

This study aims to develop and validate a comprehensive tool to be considered by developers for assessing the security and privacy of mHealth apps.

METHODS

A literature search was performed to identify papers on app development, and those papers reporting criteria for the security and privacy of mHealth were assessed. The criteria were extracted using content analysis and presented to experts. An expert panel was held for determining the categories and subcategories of the criteria according to meaning, repetition, and overlap; impact scores were also measured. Quantitative and qualitative methods were used for validating the criteria. The validity and reliability of the instrument were calculated to present an assessment instrument.

RESULTS

The search strategy identified 8190 papers, of which 33 (0.4%) were deemed eligible. A total of 218 criteria were extracted based on the literature search; of these, 119 (54.6%) criteria were removed as duplicates and 10 (4.6%) were deemed irrelevant to the security or privacy of mHealth apps. The remaining 89 (40.8%) criteria were presented to the expert panel. After calculating impact scores, the content validity ratio (CVR), and the content validity index (CVI), 63 (70.8%) criteria were confirmed. The mean CVR and CVI of the instrument were 0.72 and 0.86, respectively. The criteria were grouped into 8 categories: authentication and authorization, access management, security, data storage, integrity, encryption and decryption, privacy, and privacy policy content.

CONCLUSIONS

The proposed comprehensive criteria can be used as a guide for app designers, developers, and even researchers. The criteria and the countermeasures presented in this study can be considered to improve the privacy and security of mHealth apps before releasing the apps into the market. Regulators are recommended to consider an established standard using such criteria for the accreditation process, since the available self-certification of developers is not reliable enough.

Healthcare Monitoring Using Low-Cost Sensors to Supplement and Replace Human Sensation: Does It Have Potential to Increase Independent Living and Prevent Disease?

Continuous monitoring of health status has the potential to enhance the quality of life and life expectancy of people suffering from chronic illness and of the elderly. However, such systems can only come into widespread use if the cost of manufacturing is low. Advancements in material science and engineering technology have led to a significant decrease in the expense of developing healthcare monitoring devices. This review aims to investigate the progress of the use of low-cost sensors in healthcare monitoring and discusses the challenges faced when accomplishing continuous and real-time monitoring tasks. The major findings include (1) only a small number of publications (N = 50) have addressed the issue of healthcare monitoring applications using low-cost sensors over the past two decades; (2) the top three algorithms used to process sensor data include SA (Statistical Analysis, 30%), SVM (Support Vector Machine, 18%), and KNN (K-Nearest Neighbour, 12%); and (3) wireless communication techniques (Zigbee, Bluetooth, Wi-Fi, and RF) serve as the major data transmission tools (77%) followed by cable connection (13%) and SD card data storage (10%). Due to the small fraction (N = 50) of low-cost sensor-based studies among thousands of published articles about healthcare monitoring, this review not only summarises the progress of related research but calls for researchers to devote more effort to the consideration of cost reduction as well as the size of these components.

Patient-facing cancer mobile apps that enable patient reported outcome data to be collected: A systematic review of content, functionality, quality, and ability to integrate with electronic health records

PURPOSE

Enabling cancer patients to self-manage symptoms through mobile applications can result in more informed, autonomous patients who are partners in their care, consequently reducing the burden on health services. Electronic patient reported outcomes completed before a clinical review can increase the frequency and quality of holistic assessments, while integration into electronic health records can maximise clinical utility. The ability of apps to integrate with electronic health records is key to providing a real-time interface between patient reports and healthcare response. This review identifies patient-facing cancer apps which can record patient reported outcomes, and explores their purpose, functionality, quality, and ability to integrate with electronic health records.

METHODS

A systematic app review and content synthesis was conducted on patient-facing cancer apps available in the United Kingdom. Where applicable, the review aligned with the Preferred Reporting Items for Systematic Reviews and meta-Analysis. Two validated scales assessed functionality and quality: The IMS Institute for Healthcare Informatics functionality score and the Mobile App Rating Scale. Flesch-Kincaid metrics explored readability.

RESULTS

Apple App and Google Play stores identified 405 apps, of which 12 met the eligibility criteria. All were free to download, 1 (8%) had in-app purchases/subscriptions. Nine (75%) were affiliated with a professional health body/charity. Six (50%) analysed inputted data and provided medical advice based on answers. The average Flesch Reading Ease score was 42.7 out of 100. The apps had an average of 7.3 functions each and a mean MARS score of 4/5. None integrated with electronic health records.

CONCLUSION

While many cancer apps exist, few enable patient reported outcomes to be recorded and shared with clinicians in real-time. Further research is warranted to explore the feasibility of integrating with electronic health records, as this function can improve patient experience and outcomes, and increase efficiency of hospital resources through more proactive care.

Do the Right Thing: A Privacy Policy Adherence Analysis of over Two Million Apps in Apple iOS App Store

Mobile app developers are often obliged by regulatory frameworks to provide a privacy policy in natural comprehensible language to describe their apps' privacy practices. However, prior research has revealed that: (1) not all app developers offer links to their privacy policies; and (2) even if they do offer such access, it is difficult to determine if it is a valid link to a (valid) policy. While many prior studies looked at this issue in Google Play Store, Apple App Store, and particularly the iOS store, is much less clear. In this paper, we conduct the first and the largest study to investigate the previous issues in the iOS app store ecosystem. First, we introduce an App Privacy Policy Extractor (APPE), a system that embraces and analyses the metadata of over two million apps to give insightful information about the distribution of the supposed privacy policies, and the content of the provided privacy policy links, store-wide. The result shows that only 58.5% of apps provide links to purported privacy policies, while 39.3% do not provide policy links at all. Our investigation of the provided links shows that only 38.4% of those links were directed to actual privacy policies, while 61.6% failed to lead to a privacy policy. Further, for research purposes we introduce the App Privacy Policy Corpus (APPC-451K); the largest app privacy policy corpus consisting of data relating to more than 451K verified privacy policies.

Assessment of Mobile Health Applications for Management of Knee and/or Hip Osteoarthritis Using the Mobile Application Rating Scale

BACKGROUND

Mobile health applications (apps) can help individuals with knee and/or hip osteoarthritis (OA) learn about, monitor, and manage their condition. These apps have not been formally evaluated.

OBJECTIVE

The aim of this study was to evaluate the publicly available mobile health apps for individuals with knee and/or hip OA using a systematic review.

METHODS

We searched the Apple App Store, Android Google Play, and Amazon Appstore using the terms "arthritis," "osteoarthritis," "hip OA," "knee OA," "hip," "knee," "rehabilitation," "rehab," and "physical therapy" in December of 2021. Applications that met the inclusion/exclusion criteria were reviewed using the Mobile Application Rating Scale (MARS; 29 items across 6 sections, each rated at 1-5).

RESULTS

Among 1104 identified apps, 94 met the inclusion/exclusion criteria for MARS appraisal. Fourteen apps met the predetermined score thresholds for final summary. Of the 14 apps appraised, the total overall mean app score on the MARS ranged from 3.12 to 4.20 (mean, 3.51 ± 0.37). Although app features varied, common features were symptom tracking, exercise recommendations, education, goal setting, and improving well-being. Many apps allowed for sharing with health care providers and included some measures to protect privacy. Jointfully Osteoarthritis was the top-rated app in both the Apple App Store and Android Google Play.

CONCLUSIONS

The majority of the apps we identified for knee and/or hip OA did not meet predetermined score thresholds for final summary. Many failed to provide comprehensive education and deliver management plans and lacked scientific testing. Future research should focus on apps that fit the needs of health care providers and patients including quality information, structured exercise programs tailored to individual needs, secure communication methods, and health information protection.

The role of commercially available smartphone apps and wearable devices in monitoring patients after total knee arthroplasty: a systematic review

Purpose

Commercially available smartphone apps and wearable devices have proven valuable in a variety of clinical settings, yet their utility in measuring physical activity and monitoring patient status following total knee arthroplasty (TKA) remains unclear.

Methods

A systematic review was performed to assess the evidence supporting the use of smartphone apps and wearable devices to assist rehabilitation interventions following TKA. A search was conducted in the PubMed, Cochrane, Medline, and Web of Science databases in September 2021.

Results

One hundred and seventy-six studies were retrieved, of which 15 met inclusion criteria, including 6 randomized control trials. Four of these studies utilized smartphone apps, seven utilized wearable devices, and four utilized a combination of both. A total of 1607 TKA patients participated in the included studies. For primary outcomes, three reported on device accuracy, three on recovery prediction, two on functional recovery, two on physical activity promotion, two on patient compliance, two on pain control, and one on healthcare utilization.

Conclusion

Commercially available smartphone apps and wearable devices were shown to capably monitor physical activity and improve patient engagement following TKA, making them potentially viable adjuncts or replacements to traditional rehabilitation programs. Components of interventions such as step goals, app-based patient engagement platforms, and patient-specific benchmarks for recovery may improve effectiveness. However, future research should focus on the economics of implementation, long-term outcomes, and optimization of compliance and accuracy when using these devices.

Data Privacy Concerns Using mHealth Apps and Smart Speakers: Comparative Interview Study Among Mature Adults

Background

New technologies such as mobile health (mHealth) apps and smart speakers make intensive use of sensitive personal data. Users are typically aware of this and express concerns about their data privacy. However, many people use these technologies although they think their data are not well protected. This raises specific concerns for sensitive health data.

Objective

This study aimed to contribute to a better understanding of data privacy concerns of mature adults using new technologies and provide insights into their data privacy expectations and associated risks and the corresponding actions of users in 2 different data contexts: mHealth apps and smart speakers.

Methods

This exploratory research adopted a qualitative approach, engaging with 20 mature adults (aged >45 years). In a 6-month test period, 10 (50%) participants used a smart speaker and 10 (50%) participants used an mHealth app. In interviews conducted before and after the test period, we assessed the influence of data privacy concerns on technology acceptance, use behavior, and continued use intention.

Results

Our results show that although participants are generally aware of the need to protect their data privacy, they accept the risk of misuse of their private data when using the technology. Surprisingly, the most frequently stated risk was not the misuse of personal health data but the fear of receiving more personalized advertisements. Similarly, surprisingly, our results indicate that participants value recorded verbal data higher than personal health data.

Conclusions

Older adults are initially concerned about risks to their data privacy associated with using data-intensive technologies, but those concerns diminish fairly quickly, culminating in resignation. We find that participants do not differentiate between risky behaviors, depending on the type of private data used by different technologies.

Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review

Background

Mobile health (mHealth) apps show vast potential in supporting patients and health care systems with the increasing prevalence and economic costs of noncommunicable diseases (NCDs) worldwide. However, despite the availability of evidence-based mHealth apps, a substantial proportion of users do not adhere to them as intended and may consequently not receive treatment. Therefore, understanding the factors that act as barriers to or facilitators of adherence is a fundamental concern in preventing intervention dropouts and increasing the effectiveness of digital health interventions.

Objective

This review aimed to help stakeholders develop more effective digital health interventions by identifying factors influencing the continued use of mHealth apps targeting NCDs. We further derived quantified adherence scores for various health domains to validate the qualitative findings and explore adherence benchmarks.

Methods

A comprehensive systematic literature search (January 2007 to December 2020) was conducted on MEDLINE, Embase, Web of Science, Scopus, and ACM Digital Library. Data on intended use, actual use, and factors influencing adherence were extracted. Intervention-related and patient-related factors with a positive or negative influence on adherence are presented separately for the health domains of NCD self-management, mental health, substance use, nutrition, physical activity, weight loss, multicomponent lifestyle interventions, mindfulness, and other NCDs. Quantified adherence measures, calculated as the ratio between the estimated intended use and actual use, were derived for each study and compared with the qualitative findings.

Results

The literature search yielded 2862 potentially relevant articles, of which 99 (3.46%) were included as part of the inclusion criteria. A total of 4 intervention-related factors indicated positive effects on adherence across all health domains: personalization or tailoring of the content of mHealth apps to the individual needs of the user, reminders in the form of individualized push notifications, user-friendly and technically stable app design, and personal support complementary to the digital intervention. Social and gamification features were also identified as drivers of app adherence across several health domains. A wide variety of patient-related factors such as user characteristics or recruitment channels further affects adherence. The derived adherence scores of the included mHealth apps averaged 56.0% (SD 24.4%).

Conclusions

This study contributes to the scarce scientific evidence on factors that positively or negatively influence adherence to mHealth apps and is the first to quantitatively compare adherence relative to the intended use of various health domains. As underlying studies mostly have a pilot character with short study durations, research on factors influencing adherence to mHealth apps is still limited. To facilitate future research on mHealth app adherence, researchers should clearly outline and justify the app’s intended use; report objective data on actual use relative to the intended use; and, ideally, provide long-term use and retention data.

User Perception of New E-Health Challenges: Implications for the Care Process

Establishing new models of health care and new forms of professional health-patient communication are lines of development in the field of health care. The onset of the COVID-19 pandemic has accelerated the evolution of information systems and communication platforms to guarantee continuity of care and compliance with social distancing measures. Our objective in this article was, firstly, to know the expectations of patients treated in the healthcare processes "cervical cancer" and "pregnancy, childbirth and puerperium" regarding online access to their clinical history and follow-up in the care process. Secondly, we analyzed times involved in the cervical cancer process to find points of improvement in waiting times when digital tools were used for communication with the patient. A descriptive cross-sectional study was carried out on 120 women included in any of the aforementioned processes using a hetero-administered questionnaire. The analysis of times was carried out using the Business Intelligence tool Biwer Analytics^®. Patients showed interest in knowing their results before the appointment with the doctor and would avoid appointments with their doctor if the right conditions were met. Most recognized that this action would relieve their restlessness and anxiety. They were highly interested in receiving recommendations to improve their health status. It was estimated that there was room for improvement in the times involved in the care process, which could be shortened by 34.48 days if communication of results were through digital information access technologies. This would favor the optimization of time, resources and user perception.

Patient-facing genetic and genomic mobile apps in the UK: a systematic review of content, functionality, and quality

Close relative (consanguineous) marriage is widely practised globally, and it increases the risk of genetic disorders. Mobile apps may increase awareness and education regarding the associated risks in a sensitive, engaging, and accessible manner. This systematic review of patient-facing genetic/genomic mobile apps explores content, function, and quality. We searched the NHS Apps Library and the UK Google Play and Apple App stores for patient-facing genomic/genetic smartphone apps. Descriptive information and information on content was extracted and summarized. Readability was examined using the Flesch–Kincaid metrics. Two raters assessed each app, using the Mobile App Rating Scale (MARS) and the IMS Institute for Healthcare Informatics functionality score. A total of 754 apps were identified, of which 22 met the eligibility criteria. All apps intended to inform/educate users, while 32% analyzed genetic data, and 18% helped to diagnose genetic conditions. Most (68%) were clearly about genetics, but only 14% were affiliated with a medical/health body or charity, and only 36% had a privacy strategy. Mean reading scores were 35 (of 100), with the average reading age being equivalent to US grade 12 (UK year 13). On average, apps had 3.3 of the 11 IMS functionality criteria. The mean MARS quality score was 3.2 ± 0.7. Half met the minimum acceptability score (3 of 5). None had been formally evaluated. It was evident that there are few high-quality genomic/genetic patient-facing apps available in the UK. This demonstrates a need for an accessible, culturally sensitive, evidence-based app to improve genetic literacy within patient populations and specific communities.

Value of normative belief in intention to use workplace health promotion apps

BACKGROUND

Mobile applications (apps) have started to be used for workplace health promotion (WHP). However, the factors that lead to the usage of apps in the workplace from the end-user perspective remain unclear.

METHODS

To investigate the research gap, the study evaluates a model for the adoption of WHP apps by combining the theory of planned behavior, the health belief model, and the technology acceptance model. A self-administered questionnaire with validated scales among 354 participants was used to evaluate the proposed model for WHP.

RESULTS

Although the study indicated a limited overall model fit, interesting aspects were derived. In particular, the study demonstrated that normative belief (especially), perceived usefulness, and attitudinal belief play important roles in the intention to use WHP apps.

CONCLUSION

The study is among the first to validate the theoretical models of mHealth adoption for WHP. Moreover, it shows that not only normative belief but also adjustment to several target groups is a necessary factor to be considered in the development and implementation of an app for WHP.

Digital Medication Adherence Support: Could Healthcare Providers Recommend Mobile Health Apps?

Adherence to prescribed medication is suboptimal in 50% of the chronic population, resulting in negative medical and economic outcomes. With the widespread use of mobile phones worldwide, medication adherence apps for mobile phones become promising medication adherence aids thanks to simplicity, user-friendliness, and accessibility for the public. Yet, until today, there is insufficient evidence in favor of using mobile health (mHealth) apps to increase medication adherence. This study aims to develop a methodology for scientific and end-user (patient) mHealth evaluation (a) to identify medication adherence apps search terms, (b) to evaluate identified apps based on scientific criteria, and (c) to report best smartphone apps evaluated by patients. Search terms were identified via literature review and expertise. Firstly, an online questionnaire was developed to identify frequently used search terms by recruited patients. Related medication adherence apps were identified and selected using predefined inclusion criteria. Secondly, identified apps were evaluated thanks to a scientific evaluation method and a created online questionnaire for patient feedback. Recruited patients were invited to test and evaluate the selected apps. Out of 1,833 free-of-charge and 307 paid apps identified, only four free-of-charge and three paid apps remained included in the study after eligibility criteria. None of the selected app reached a high score. Looking at the overall scores, Medisafe (59%), MyTherapy (56%), and Meds on time (44%) received the highest scores in the scientific app evaluation. In the patient evaluation, Dosecast (3.83 out of five points), Medisafe (3.62), and SwissMeds (3.50) received the highest scores. None of the apps in this research has undergone a process for certification, for example, CE marking, through a notified body. Security and data protection aspects of existing apps highly contribute to these low evaluation scores through little information on patient's data processing and storage. This might be corrected through the introduction of General Data Protection Regulation (GDPR) in the European Economic Area (EEA) and more scrutiny through regulatory bodies in the EU/EEA and the USA. None of the applications should be recommended by healthcare providers. In addition, clinical studies with chronic patients are necessary to measure long-term app impacts.

A Smart-Phone App for Fluid Balance Monitoring in Patients with Heart Failure: A Usability Study

BACKGROUND

For a long time, fluid balance monitoring has been one of the most difficult problems in the management of patients with heart failure (HF). There is considerable interest in technology-facilitated fluid balance monitoring. However, little is known about patient acceptance and the use of mobile technology for fluid balance monitoring.

OBJECTIVE

The aim of this study was to develop a mobile app for technology-facilitated fluid balance monitoring and to determine its usability.

METHODS

A mixed-methods study was conducted in a tertiary hospital in Shanghai, China. A mobile app named I-Self-Care was developed through a best practice implementation project. Patients and nurses both completed the System Usability Scale (SUS, 0-100) and participated in semistructured interviews.

RESULTS

I-Self-Care includes patients' daily fluid intake and output (I&O), symptoms, hospitalization, and diuretic records. It can automatically calculate food water content and perform real-time analysis of I&O. The average SUS scores were 81.74 (SD 5.44) among 36 patients and 80.80 (SD 13.26) among 28 nurses (scale 0-100, with 100 being the best usability), which means that I-Self-Care has high usability for both patients and nurses. Semistructured interviews about the usability of the app were conducted with 17 participants. During the interviews, the patients expressed the high ease of use of I-Self-Care, their expectations for a continuously updated database, and improved self-management behaviour. The nurses thought that family support and repeated operation demonstrations were needed for patients to use the app. The nurses also expressed the convenience of this app for nursing work and the information security of patients.

CONCLUSION

With participant feedback, we confirmed the usability of I-Self-Care for fluid balance monitoring in patients with HF. Continuously updated databases, family support, repeated operation demonstrations, and information security are important for HF patients to use I-Self-Care.

ACCU3RATE: A mobile health application rating scale based on user reviews

Background

Over the last decade, mobile health applications (mHealth App) have evolved exponentially to assess and support our health and well-being.

Objective

This paper presents an Artificial Intelligence (AI)-enabled mHealth app rating tool, called ACCU³RATE, which takes multidimensional measures such as user star rating, user review and features declared by the developer to generate the rating of an app. However, currently, there is very little conceptual understanding on how user reviews affect app rating from a multi-dimensional perspective. This study applies AI-based text mining technique to develop more comprehensive understanding of user feedback based on several important factors, determining the mHealth app ratings.

Method

Based on the literature, six variables were identified that influence the mHealth app rating scale. These factors are user star rating, user text review, user interface (UI) design, functionality, security and privacy, and clinical approval. Natural Language Toolkit package is used for interpreting text and to identify the App users’ sentiment. Additional considerations were accessibility, protection and privacy, UI design for people living with physical disability. Moreover, the details of clinical approval, if exists, were taken from the developer’s statement. Finally, we fused all the inputs using fuzzy logic to calculate the new app rating score.

Results and conclusions

ACCU³RATE concentrates on heart related Apps found in the play store and App gallery. The findings indicate the efficacy of the proposed method as opposed to the current device scale. This study has implications for both App developers and consumers who are using mHealth Apps to monitor and track their health. The performance evaluation shows that the proposed mHealth scale has shown excellent reliability as well as internal consistency of the scale, and high inter-rater reliability index. It has also been noticed that the fuzzy based rating scale, as in ACCU³RATE, matches more closely to the rating performed by experts.

A Review of the Quality and Impact of Mobile Health Apps

Mobile health applications (apps) have transformed the possibilities for health promotion and disease self-management; however, their promise is not fully realized owing to their reliance on commercial ecosystems for development and distribution. This review provides an overview of the types of mobile health apps and describes key stakeholders in terms of how apps are used, developed, and regulated. I outline key challenges facing consumers, public health professionals, and policy makers in evaluating the quality of health apps and summarize what is known about the impact of apps on health outcomes and health equity. I suggest that factors within the wider mobile ecosystem largely define the impact of health apps and, most notably, practices around the collection and commercialization of user data. Finally, I suggest that upstream public health strategies, grounded in an understanding of corporate influences on health, are necessary to promote healthy digital environments in which mobile health app innovation can flourish. Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Governing health data across changing contexts: A focus group study of citizen's views in England, Iceland, and Sweden

BACKGROUND

The governance structures associated with health data are evolving in response to advances in digital technologies that enable new ways of capturing, using, and sharing different types of data. Increasingly, health data moves between different contexts such as from healthcare to research, or to commerce and marketing. Crossing these contextual boundaries has the potential to violate societal expectations about the appropriate use of health data and diminish public trust. Understanding citizens' views on the acceptability of and preferences for data use in different contexts is essential for developing information governance policies in these new contexts.

METHODS

Focus group design presenting data sharing scenarios in England, Iceland, and Sweden.

RESULTS

Seventy-one participants were recruited. Participants supported the need for data to help understand the observable world, improve medical research, the quality of public services, and to benefit society. However, participants consistently identified the lack of information, transparency and control as barriers to trusting organisations to use data in a way that they considered appropriate. There was considerable support for fair and transparent data sharing practices where all parties benefitted.

CONCLUSION

Data governance policy should involve all stakeholders' perspectives on an ongoing basis, to inform and implement changes to health data sharing practices that accord with stakeholder views. The Findings showed that (1) data should be used for ethical purposes even when there was commercial interest; (2) data subjects and/or public institutions that provide and share data should also receive benefits from the sharing of data; (3) third parties use of data requires greater transparency and accountability than currently exists, (4) there should be greater information provided to empower data subjects.

Evaluating the utility of digital phenotyping to predict health outcomes in schizophrenia: protocol for the HOPE-S observational study

INTRODUCTION

The course of schizophrenia illness is characterised by recurrent relapses which are associated with adverse clinical outcomes such as treatment-resistance, functional and cognitive decline. Early identification is essential and relapse prevention remains a primary treatment goal for long-term management of schizophrenia. With the ubiquity of devices such as smartphones, objective digital biomarkers can be harnessed and may offer alternative means for symptom monitoring and relapse prediction. The acceptability of digital sensors (smartphone and wrist-wearable device) and the association between the captured digital data with clinical and health outcomes in individuals with schizophrenia will be examined.

METHODS AND ANALYSIS

In this study, we aim to recruit 100 individuals with schizophrenia spectrum disorders who are recently discharged from the Institute of Mental Health (IMH), Singapore. Participants are followed up for 6 months, where digital, clinical, cognitive and functioning data are collected while health utilisation data are obtained at the 6 month and 1 year timepoint from study enrolment. Associations between digital, clinical and health outcomes data will be examined. A data-driven machine learning approach will be used to develop prediction algorithms to detect clinically significant outcomes. Study findings will inform the design, data collection procedures and protocol of future interventional randomised controlled trial, testing the effectiveness of digital phenotyping in clinical management of individuals with schizophrenia spectrum disorders.

ETHICS AND DISSEMINATION

Ethics approval has been granted by the National Healthcare Group (NHG) Domain Specific Review Board (DSRB Reference no.: 2019/00720). The results will be published in peer-reviewed journals and presented at conferences.

TRIAL REGISTRATION NUMBER

NCT04230590.

Health technology assessment of telemedicine applications in Northern borders of India

BACKGROUND

Economic evaluations of health technology help to decide which interventions are to be continued and which are to be terminated. In the Armed Forces, the provision of efficient medical services requires meticulous planning for optimal utilization of scarce resources. We report a cost analysis of telemedicine and air transportation of casualties, and attempt to identify the strengths, weaknesses, opportunities and threats of telemedicine services.

METHODS

The costs incurred in telemedicine were compared with the cost of air evacuation. A qualitative assessment of telemedicine was undertaken through in-depth interviews with the hospital authorities and focused group discussions with medical officers and paramedical staff.

RESULTS

34.2% of casualties could successfully be stabilized on-site using available healthcare resources with the peripheral hospitals. 18 casualties were managed at the periphery on-site by teleconsultations each year, averting air-transportation efforts. Estimated cost savings achieved in the initial management of casualty by teleconsultation was Rs. 146,111 per case. The strengths of telemedicine are knowledge updation, faster decision making, improved pre-hospital care and improved confidence in case management.

CONCLUSION

The reduction in air efforts and remote management of casualties make a substantive case for scaling up telemedicine interventions.

Applying Mobile Technology to Sustain Physical Activity After Completion of Cardiac Rehabilitation: Acceptability Study

BACKGROUND

Many patients do not meet the recommended levels of physical activity after completing a cardiac rehabilitation (CR) program. Wearable activity trackers and mobile phone apps are promising potential self-management tools for maintaining physical activity after CR completion.

OBJECTIVE

This study aims to evaluate the acceptability of a wearable device, mobile app, and push messages to facilitate physical activity following CR completion.

METHODS

We used semistructured interviews to assess the acceptability of various mobile technologies after participation in a pilot randomized controlled trial. Intervention patients in the randomized controlled trial wore the Fitbit Charge 2, used the Movn mobile app, and received push messages on cardiovascular disease prevention and physical activity for over 2 months. We asked 26 intervention group participants for feedback about their experience with the technology and conducted semistructured individual interviews with 7 representative participants. We used thematic analysis to create the main themes from individual interviews.

RESULTS

Our sample included participants with a mean age of 66.7 (SD 8.6) years; 23% (6/26) were female. Overall, there were varying levels of satisfaction with different technology components. There were 7 participants who completed the satisfaction questionnaires and participated in the interviews. The Fitbit and Movn mobile app received high satisfaction scores of 4.86 and 4.5, respectively, whereas push messages had a score of 3.14 out of 5. We identified four main themes through the interviews: technology use increased motivation to be physically active, technology use served as a reminder to be physically active, recommendations for technology to improve user experience, and desire for personal feedback.

CONCLUSIONS

By applying a wearable activity tracker, mobile phone app, and push messages, our study showed strong potential for the adoption of new technologies by older adults to maintain physical activity after CR completion. Future research should include a larger sample over a longer period using a mixed methods approach to assess the efficacy of technology use for promoting long-term physical activity behavior in older adults.

Analyzing security issues of android mobile health and medical applications

OBJECTIVE

We conduct a first large-scale analysis of mobile health (mHealth) apps available on Google Play with the goal of providing a comprehensive view of mHealth apps' security features and gauging the associated risks for mHealth users and their data.

MATERIALS AND METHODS

We designed an app collection platform that discovered and downloaded more than 20 000 mHealth apps from the Medical and Health & Fitness categories on Google Play. We performed a suite of app code and traffic measurements to highlight a range of app security flaws: certificate security, sensitive or unnecessary permission requests, malware presence, communication security, and security-related concerns raised in user reviews.

RESULTS

Compared to baseline non-mHealth apps, mHealth apps generally adopt more reliable signing mechanisms and request fewer dangerous permissions. However, significant fractions of mHealth apps expose users to serious security risks. Specifically, 1.8% of mHealth apps package suspicious codes (eg, trojans), 45.0% rely on unencrypted communication, and as much as 23.0% of personal data (eg, location information and passwords) is sent on unsecured traffic. An analysis of the app reviews reveals that mHealth app users are largely unaware of the surfaced security issues.

CONCLUSION

Despite being better aligned with security best practices than non-mHealth apps, mHealth apps are still far from ensuring robust security guarantees. App users, clinicians, technology developers, and policy makers alike should be cognizant of the uncovered security issues and weigh them carefully against the benefits of mHealth apps.

Pregnant Women's Attitudes Toward and Experiences With a Tablet Intervention to Promote Safety Behaviors in a Randomized Controlled Trial: Qualitative Study

BACKGROUND

Intimate partner violence (IPV) is recognized as a global health problem. Women with low education and limited resources are more vulnerable, as are immigrant women. There is a lack of evidence on how health care professionals should communicate about and intervene against IPV during pregnancy. Earlier research has shown that when women manage digital questionnaires, they are more likely to disclose IPV. However, little is known about how women experience eHealth interventions with safety behaviors to prevent IPV.

OBJECTIVE

The aim of this study was to explore pregnant women's attitudes toward and experiences with a tablet intervention to promote safety behaviors in a randomized controlled trial (RCT) in antenatal care.

METHODS

Individual semistructured interviews were conducted with 10 women who participated in the Safe Pregnancy Study. The Safe Pregnancy Study was a randomized controlled trial (RCT) using a tablet intervention containing IPV questions and a film to promote safety behaviors. Six women from the intervention group and four women from the control group were recruited. The content was available in Norwegian, Somali, and Urdu. Five of the women participating in the interviews spoke Norwegian at home and five spoke another language. The majority of the women who did not speak Norwegian at home perceived themselves as relatively well integrated. The interviews were conducted at different maternal and child health centers (MCHCs) in Norway between March 2020 and June 2020. The analysis was guided by thematic analysis.

RESULTS

Women who participated in the tablet intervention appreciated being asked questions about IPV on a tablet. However, it was important to supplement the tablet intervention with face-to-face communication with a midwife. The MCHC was regarded as a suitable place to answer questions and watch a film about safety behaviors. Women suggested making the tablet intervention available in other settings where women meet health care professionals. Some women expressed uncertainty about their anonymity regarding their answers in the questionnaire. We found no real differences between ethnic Norwegian and immigrant women's attitudes toward and experiences with the tablet intervention.

CONCLUSIONS

Questions about IPV and a film about safety behaviors on a tablet, as a supplement to face-to-face communication, might initiate and facilitate communication about IPV in antenatal care. Uncertainty regarding anonymity has to be addressed when questions about IPV are being asked on a tablet.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03397277; https://clinicaltrials.gov/ct2/show/NCT03397277.

Challenges With Developing Secure Mobile Health Applications: Systematic Review

Background

Mobile health (mHealth) apps have gained significant popularity over the last few years due to their tremendous benefits, such as lowering health care costs and increasing patient awareness. However, the sensitivity of health care data makes the security of mHealth apps a serious concern. Poor security practices and lack of security knowledge on the developers’ side can cause several vulnerabilities in mHealth apps.

Objective

In this review paper, we aimed to identify and analyze the reported challenges concerning security that developers of mHealth apps face. Additionally, our study aimed to develop a conceptual framework with the challenges for developing secure apps faced by mHealth app development organizations. The knowledge of such challenges can help to reduce the risk of developing insecure mHealth apps.

Methods

We followed the systematic literature review method for this review. We selected studies that were published between January 2008 and October 2020 since the major app stores launched in 2008. We selected 32 primary studies using predefined criteria and used a thematic analysis method for analyzing the extracted data.

Results

Of the 1867 articles obtained, 32 were included in this review based on the predefined criteria. We identified 9 challenges that can affect the development of secure mHealth apps. These challenges include lack of security guidelines and regulations for developing secure mHealth apps (20/32, 63%), developers’ lack of knowledge and expertise for secure mHealth app development (18/32, 56%), lack of stakeholders’ involvement during mHealth app development (6/32, 19%), no/little developer attention towards the security of mHealth apps (5/32, 16%), lack of resources for developing a secure mHealth app (4/32, 13%), project constraints during the mHealth app development process (4/32, 13%), lack of security testing during mHealth app development (4/32, 13%), developers’ lack of motivation and ethical considerations (3/32, 9%), and lack of security experts’ engagement during mHealth app development (2/32, 6%). Based on our analysis, we have presented a conceptual framework that highlights the correlation between the identified challenges.

Conclusions

While mHealth app development organizations might overlook security, we conclude that our findings can help them to identify the weaknesses and improve their security practices. Similarly, mHealth app developers can identify the challenges they face to develop mHealth apps that do not pose security risks for users. Our review is a step towards providing insights into the development of secure mHealth apps. Our proposed conceptual framework can act as a practice guideline for practitioners to enhance secure mHealth app development.

A new privacy framework for the management of chronic diseases via mHealth in a post-Covid-19 world

Aim

New challenges are being faced by global healthcare systems such as an increase in the elderly population, budget cuts as well as the ongoing Covid-19 pandemic. As pressures mount on healthcare systems to provide treatment to patients, mHealth is seen as one of the possible solutions to addressing these challenges. Given the sensitivity of health data, the rapid development of the mHealth sector raises privacy concerns. The aims of this research were to investigate privacy threats/concerns in the context of mHealth and the management of chronic diseases and to propose a novel privacy framework to address these concerns.

Subject and method

The study adopted a modified version of the engineering design process. After defining the problem, information was gathered through literature reviews, and analyses of existing regulatory (privacy) frameworks and past research on privacy threats/concerns. Requirements for a new framework were then specified leading to its development and comparison with existing frameworks.

Results

A novel future-proof privacy framework was developed and illustrated. Using existing regulatory frameworks for privacy and privacy threats/concerns from research studies, privacy principles and their resulting requirements were identified. Furthermore, mechanisms and associated technologies needed to implement the privacy principles/requirements into a functional prototype were also identified. A comparison of the proposed framework with existing frameworks, showed that it addressed privacy threats/concerns in a more comprehensive manner.

Conclusion

This research makes a valuable contribution to protecting privacy in mHealth. The novel framework developed is an improvement on existing frameworks. It is also future-proof since its foundations are built on regulatory frameworks and privacy threats/concerns existing at the time of its deployment/revision.

Mobile health and privacy: cross sectional study

OBJECTIVES

To investigate whether and what user data are collected by health related mobile applications (mHealth apps), to characterise the privacy conduct of all the available mHealth apps on Google Play, and to gauge the associated risks to privacy.

DESIGN

Cross sectional study SETTING: Health related apps developed for the Android mobile platform, available in the Google Play store in Australia and belonging to the medical and health and fitness categories.

PARTICIPANTS

Users of 20 991 mHealth apps (8074 medical and 12 917 health and fitness found in the Google Play store: in-depth analysis was done on 15 838 apps that did not require a download or subscription fee compared with 8468 baseline non-mHealth apps.

MAIN OUTCOME MEASURES

Primary outcomes were characterisation of the data collection operations in the apps code and of the data transmissions in the apps traffic; analysis of the primary recipients for each type of user data; presence of adverts and trackers in the app traffic; audit of the app privacy policy and compliance of the privacy conduct with the policy; and analysis of complaints in negative app reviews.

RESULTS

88.0% (n=18 472) of mHealth apps included code that could potentially collect user data. 3.9% (n=616) of apps transmitted user information in their traffic. Most data collection operations in apps code and data transmissions in apps traffic involved external service providers (third parties). The top 50 third parties were responsible for most of the data collection operations in app code and data transmissions in app traffic (68.0% (2140), collectively). 23.0% (724) of user data transmissions occurred on insecure communication protocols. 28.1% (5903) of apps provided no privacy policies, whereas 47.0% (1479) of user data transmissions complied with the privacy policy. 1.3% (3609) of user reviews raised concerns about privacy.

CONCLUSIONS

This analysis found serious problems with privacy and inconsistent privacy practices in mHealth apps. Clinicians should be aware of these and articulate them to patients when determining the benefits and risks of mHealth apps.

Privacy versus Convenience: A Historical Perspective, Analysis of Risks, and an Informatics Call to Action

BACKGROUND

The pace of technological change dwarfs the pace of social and policy change. This mismatch allows for individual harm from lack of recognition of changes in societal context. The value of privacy has not kept pace with changes in technology over time; individuals seem to discount how loss of privacy can lead to directed personal harm.

OBJECTIVE

The authors examined individuals sharing personal data with mobile health applications (mHealth apps) and compared the current digital context to the historical context of harm. The authors make recommendations to informatics professionals to support consumers who wish to use mHealth apps in a manner that balances convenience with personal privacy to reduce the risk of harm.

METHODS

A literature search focused by a historical perspective of risk of harm was performed throughout the development of this paper. Two case studies highlight questions a consumer might ask to assess the risk of harm posed by mobile health applications.

RESULTS

A historical review provides the context for the collective human experience of harm. We then encapsulate current perceptions and views of privacy and list potential risks created by insufficient attention to privacy management.

DISCUSSION

The results provide a historical context for individuals to view the risk of harm and shed light on potential emotional, reputational, economic, and physical harms that can result from naïve use of mHealth apps. We formulate implications for clinical informaticists.

CONCLUSION

Concepts of both harm and privacy have changed substantially over the past 20 years. Technology provides methods to invade privacy and cause harm unimaginable a few decades ago. Only recently have the consequences become clearer. The current regulatory framework is extremely limited. Given the risks of harm and limited awareness, we call upon informatics professionals to support more privacy education and protections and increase mHealth transparency about data usage.

Smartphone Users' Persuasion Knowledge in the Context of Consumer mHealth Apps: Qualitative Study

Background

Persuasion knowledge, commonly referred to as advertising literacy, is a cognitive dimension that embraces recognition of advertising, its source and audience, and understanding of advertisers’ persuasive and selling intents as well as tactics. There is little understanding of users’ awareness of organizations that develop or sponsor mobile health (mHealth) apps, especially in light of personal data privacy. Persuasion knowledge or recognition of a supporting organization’s presence, characteristics, competencies, intents, and persuasion tactics are crucial to investigate because app users have the right to know about entities that support apps and make informed decisions about app usage. The abundance of free consumer mHealth apps, especially those in the area of fitness, often makes it difficult for users to identify apps’ dual purposes, which may be related to not only helping the public manage health but also promoting the supporting organization itself and collecting users’ information for further consumer targeting by third parties.

Objective

This study aims to investigate smartphone users’ awareness of mHealth apps’ affiliations with 3 different types of supporting organizations (commercial, government, and nonprofit); differences in users’ persuasion knowledge and mHealth app quality and credibility evaluations related to each of the 3 organization types; and users’ coping mechanisms for dealing with personal information management within consumer mHealth apps.

Methods

In-depth semistructured interviews were conducted with 25 smartphone users from a local community in midwestern United States. Interviews were thematically analyzed using inductive and deductive approaches.

Results

Participants indicated that their awareness of and interest in mHealth app–supporting organizations were secondary to the app’s health management functions. After being probed, participants showed a high level of persuasion knowledge regarding the types of app-supporting organizations and their promotional intents. They thought that commercial companies sponsored mHealth apps mostly as entertainment tools, whereas noncommercial entities sponsored mHealth apps for users’ education. They assigned self-promotional motives to commercial organizations; however, they associated commercial mHealth apps with good quality and functioning. Noncommercial entities were perceived as more credible. Participants were concerned about losing control over personal information within mHealth apps supported by different organizations. They used alternative digital identities to protect themselves from privacy invasion and advertising spam. They were willing to trade some personal information for high-quality commercial mHealth apps. There was a sense of fatalism in discussing privacy risks linked to mHealth app usage, and some participants did not perceive the risks to be serious.

Conclusions

The discussion of and recommendations for the safe and ethical use of mHealth apps associated with organizations’ promotional strategies and personal data protection are provided to ensure users’ awareness of and enhanced control over digitalized personal information flows. The theoretical implications are discussed in the context of the Persuasion Knowledge Model and dual-processing theories.

Smartphone applications managing antithrombotic therapy: a scoping literature review (Preprint)

Background

Antithrombotic therapy is complex and requires informed decisions and high therapy adherence. Several mobile phone apps exist to either support physicians in the management of antithrombotic therapies or to educate and support patients. For the majority of these apps, both their medical evidence and their development background are unknown.

Objective

This review aims to investigate the available literature describing high-quality apps for managing antithrombotic therapy based on professional scientific information.

Methods

Keywords and Medical Subject Heading terms were used to search MEDLINE via PubMed and Ovid between December 2019 and January 2022. Inclusion criteria were the availability of full text and publications in the English language. Apps that solely focused on atrial fibrillation were excluded. Qualitative findings were thematically synthesized and reported narratively.

Results

Out of 149 identified records, 32 were classified as eligible. We identified four groups: (1) apps for patients supporting self-management of vitamin K antagonists, (2) apps for patients increasing therapy adherence, (3) educational apps for patients, and (4) apps for physicians in supporting guideline adherence.

Conclusions

Throughout the evaluated data, patients from all age groups receiving antithrombotic drugs expressed the desire for a digital tool that could support their therapy management. In addition, physicians using mobile guideline-based apps may have contributed to decreased adverse event rates among their patients. In general, digital apps encompassing both user-friendly designs and scientific backgrounds may enhance the safety of antithrombotic therapies. However, our evaluation did not identify any apps that addressed all antithrombotic drugs in combination with perioperative stratification strategies. Currently, strict regulations for smartphone apps seem to negatively affect the development of new apps. Therefore, new legal policies for medical digital apps are urgently needed.

Digital social entrepreneurship: the N-Helix response to stakeholders' COVID-19 needs

This study explores the emergence of a new entrepreneurship phenomenon (digital social entrepreneurship) as a result of the collaboration among many agents (N-Helix), given the government’s limited capacity to respond to the stakeholders’ needs satisfaction related to an exogenous event (e.g., the COVID-19 pandemic). Our theory development is based on three ongoing academic debates related to (a) the unrepresentativeness of the stakeholder theory in entrepreneurship research; (b) the emergence of digital social entrepreneurship (DSE) as a bridge between stakeholders’ needs, socio-economic actors, and digital-social initiatives; and (c) the role of N-Helix collaborations to facilitate the emergence of global knowledge-intensive initiatives and the rapid adoptions of open innovations. Our results support our assumptions about the positive mediation effect of DSE in the relationship between N-Helix collaborations and stakeholders’ satisfaction. Notably, results show how pandemic has intensified these relationships and how DSE in N-Helix collaborations can generate social impacts globally. Some implications for policy-makers have emerged from our results that should be considered during/post-COVID-19 pandemic.

Learning From Others Without Sacrificing Privacy: Simulation Comparing Centralized and Federated Machine Learning on Mobile Health Data

Background

The use of wearables facilitates data collection at a previously unobtainable scale, enabling the construction of complex predictive models with the potential to improve health. However, the highly personal nature of these data requires strong privacy protection against data breaches and the use of data in a way that users do not intend. One method to protect user privacy while taking advantage of sharing data across users is federated learning, a technique that allows a machine learning model to be trained using data from all users while only storing a user’s data on that user’s device. By keeping data on users’ devices, federated learning protects users’ private data from data leaks and breaches on the researcher’s central server and provides users with more control over how and when their data are used. However, there are few rigorous studies on the effectiveness of federated learning in the mobile health (mHealth) domain.

Objective

We review federated learning and assess whether it can be useful in the mHealth field, especially for addressing common mHealth challenges such as privacy concerns and user heterogeneity. The aims of this study are to describe federated learning in an mHealth context, apply a simulation of federated learning to an mHealth data set, and compare the performance of federated learning with the performance of other predictive models.

Methods

We applied a simulation of federated learning to predict the affective state of 15 subjects using physiological and motion data collected from a chest-worn device for approximately 36 minutes. We compared the results from this federated model with those from a centralized or server model and with the results from training individual models for each subject.

Results

In a 3-class classification problem using physiological and motion data to predict whether the subject was undertaking a neutral, amusing, or stressful task, the federated model achieved 92.8% accuracy on average, the server model achieved 93.2% accuracy on average, and the individual model achieved 90.2% accuracy on average.

Conclusions

Our findings support the potential for using federated learning in mHealth. The results showed that the federated model performed better than a model trained separately on each individual and nearly as well as the server model. As federated learning offers more privacy than a server model, it may be a valuable option for designing sensitive data collection methods.

Depression screening using mobile phone usage metadata: a machine learning approach

OBJECTIVE

Depression is currently the second most significant contributor to non-fatal disease burdens globally. While it is treatable, depression remains undiagnosed in many cases. As mobile phones have now become an integral part of daily life, this study examines the possibility of screening for depressive symptoms continuously based on patients' mobile usage patterns.

MATERIALS AND METHODS

412 research participants reported a range of their mobile usage statistics. Beck Depression Inventory-2nd ed (BDI-II) was used to measure the severity of depression among participants. A wide array of machine learning classification algorithms was trained to detect participants with depression symptoms (ie, BDI-II score ≥ 14). The relative importance of individual variables was additionally quantified.

RESULTS

Participants with depression were found to have fewer saved contacts on their devices, spend more time on their mobile devices to make and receive fewer and shorter calls, and send more text messages than participants without depression. The best model was a random forest classifier, which had an out-of-sample balanced accuracy of 0.768. The balanced accuracy increased to 0.811 when participants' age and gender were included.

DISCUSSIONS/CONCLUSION

The significant predictive power of mobile usage attributes implies that, by collecting mobile usage statistics, mental health mobile applications can continuously screen for depressive symptoms for initial diagnosis or for monitoring the progress of ongoing treatments. Moreover, the input variables used in this study were aggregated mobile usage metadata attributes, which has low privacy sensitivity making it more likely for patients to grant required application permissions.

A Mobile App to Facilitate Socially Distanced Hospital Communication During COVID-19: Implementation Experience

BACKGROUND

COVID-19 has significantly altered health care delivery, requiring clinicians and hospitals to adapt to rapidly changing hospital policies and social distancing guidelines. At our large academic medical center, clinicians reported that existing information on distribution channels, including emails and hospital intranet posts, was inadequate to keep everyone abreast with these changes. To address these challenges, we adapted a mobile app developed in-house to communicate critical changes in hospital policies and enable direct telephonic communication between clinical team members and hospitalized patients, to support social distancing guidelines and remote rounding.

OBJECTIVE

This study aimed to describe the unique benefits and challenges of adapting an app developed in-house to facilitate communication and remote rounding during COVID-19.

METHODS

We adapted moblMD, a mobile app available on the iOS and Android platforms. In conjunction with our Hospital Incident Command System, resident advisory council, and health system innovation center, we identified critical, time-sensitive policies for app usage. A shared collaborative document was used to align app-based communication with more traditional communication channels. To minimize synchronization efforts, we particularly focused on high-yield policies, and the time of last review and the corresponding reviewer were noted for each protocol. To facilitate social distancing and remote patient rounding, the app was also populated with a searchable directory of numbers to patient bedside phones and hospital locations. We monitored anonymized user activity from February 1 to July 31, 2020.

RESULTS

On its first release, 1104 clinicians downloaded moblMD during the observation period, of which 46% (n=508) of downloads occurred within 72 hours of initial release. COVID-19 policies in the app were reviewed most commonly during the first week (801 views). Users made sustained use of hospital phone dialing features, including weekly peaks of 2242 phone number dials, 1874 directory searches, and 277 patient room phone number searches through the last 2 weeks of the observation period. Furthermore, clinicians submitted 56 content- and phone number-related suggestions through moblMD.

CONCLUSIONS

We rapidly developed and deployed a communication-focused mobile app early during COVID-19, which has demonstrated initial and sustained value among clinicians in communicating with in-patients and each other during social distancing. Our internal innovation benefited from our team's familiarity with institutional structures, short feedback loops, limited security and privacy implications, and a path toward sustainability provided by our innovation center. Challenges in content management were overcome through synchronization efforts and timestamping review. As COVID-19 continues to alter health care delivery, user activity metrics suggest that our solution will remain important in our efforts to continue providing safe and up-to-date clinical care.

Towards the Use of Blockchain in Mobile Health Services and Applications

With the advent of cryptocurrencies and blockchain, the growth and adaptation of cryptographic features and capabilities were quickly extended to new and underexplored areas, such as healthcare. Currently, blockchain is being implemented mainly as a mechanism to secure Electronic Health Records (EHRs). However, new studies have shown that this technology can be a powerful tool in empowering patients to control their own health data, as well for enabling a fool-proof health data history and establishing medical responsibility. Additionally, with the proliferation of mobile health (m-Health) sustained on service-oriented architectures, the adaptation of blockchain mechanisms into m-Health applications creates the possibility for a more decentralized and available healthcare service. Hence, this paper presents a review of the current security best practices for m-Health and the most used and widely known implementations of the blockchain protocol, including blockchain technologies in m-Health. The main goal of this comprehensive review is to further discuss and elaborate on identified open-issues and potential use cases regarding the uses of blockchain in this area. Finally, the paper presents the major findings, challenges and advantages on future blockchain implementations for m-Health services and applications.

Smartphone-Based Applications to Detect Hearing Loss: A Review of Current Technology

BACKGROUND/OBJECTIVES

Age-related hearing loss (ARHL) is a widely prevalent yet manageable condition that has been linked to neurocognitive and psychiatric comorbidities. Multiple barriers hinder older individuals from being diagnosed with ARHL through pure-tone audiometry. This is especially true during the COVID-19 pandemic, which has resulted in the closure of many outpatient audiology and otolaryngology offices. Smartphone-based hearing assessment apps may overcome these challenges by enabling patients to remotely self-administer their own hearing examination. The objective of this review is to provide an up-to-date overview of current mobile health applications (apps) that claim to assess hearing.

DESIGN

Narrative review.

MEASUREMENTS

The Apple App Store and Google Play Store were queried for apps that claim to assess hearing. Relevant apps were downloaded and used to conduct a mock hearing assessment. Names of included apps were searched on four literature databases (PubMed/MEDLINE, EMBASE, Cochrane Library, and CINAHL) to determine which apps had been validated against gold standard methods.

RESULTS

App store searches identified 44 unique apps. Apps differed with respect to the type of test offered (e.g., hearing threshold test), cost, strategies to reduce ambient noise, test output (quantitative vs qualitative results), and options to export results. Validation studies were identified for seven apps.

CONCLUSION

Given their low cost and relative accessibility, smartphone-based hearing apps may facilitate screening for ARHL, particularly in the setting of limitations on in-person medical care due to COVID-19. However, app features vary widely, few apps have been validated, and user-centered designs for older adults are largely lacking. Further research and validation efforts are necessary to determine whether smartphone-based hearing assessments are a feasible and accurate screening tool for ARHL. Key Points Age-related hearing loss is a prevalent yet undertreated condition among older adults. Why Does this Paper Matter?     Smartphone-based hearing test apps may facilitate remote screening for hearing loss, but limitations surrounding app validation, usability, equipment calibration, and data security should be addressed.

Assessment of the Quality of Mobile Applications (Apps) for Management of Low Back Pain Using the Mobile App Rating Scale (MARS)

Digital health interventions may improve different behaviours. However, the rapid proliferation of technological solutions often does not allow for a correct assessment of the quality of the tools. This study aims to review and assess the quality of the available mobile applications (apps) related to interventions for low back pain. Two reviewers search the official stores of Android (Play Store) and iOS (App Store) for localisation in Spain and the United Kingdom, in September 2019, searching for apps related to interventions for low back pain. Seventeen apps finally are included. The quality of the apps is measured using the Mobile App Rating Scale (MARS). The scores of each section and the final score of the apps are retrieved and the mean and standard deviation obtained. The average quality ranges between 2.83 and 4.57 (mean 3.82) on a scale from 1 (inadequate) to 5 (excellent). The best scores are found in functionality (4.7), followed by aesthetic content (mean 4.1). Information (2.93) and engagement (3.58) are the worst rated items. Apps generally have good overall quality, especially in terms of functionality and aesthetics. Engagement and information should be improved in most of the apps. Moreover, scientific evidence is necessary to support the use of applied health tools.

Digital health developments and drawbacks: a review and analysis of top-returned apps for bipolar disorder

BACKGROUND

Although a growing body of literature highlights the potential benefit of smartphone-based mobile apps to aid in self-management and treatment of bipolar disorder, it is unclear whether such evidence-based apps are readily available and accessible to a user of the app store.

RESULTS

Using our systematic framework for the evaluation of mental health apps, we analyzed the accessibility, privacy, clinical foundation, features, and interoperability of the top-returned 100 apps for bipolar disorder. Only 56% of the apps mentioned bipolar disorder specifically in their title, description, or content. Only one app's efficacy was supported in a peer-reviewed study, and 32 apps lacked privacy policies. The most common features provided were mood tracking, journaling, and psychoeducation.

CONCLUSIONS

Our analysis reveals substantial limitations in the current digital environment for individuals seeking an evidence-based, clinically usable app for bipolar disorder. Although there have been academic advances in development of digital interventions for bipolar disorder, this work has yet to be translated to the publicly available app marketplace. This unmet need of digital mood management underscores the need for a comprehensive evaluation system of mental health apps, which we have endeavored to provide through our framework and accompanying database (apps.digitalpsych.org).

Monitoring Patient Recovery After THA or TKA Using Mobile Technology

BACKGROUND

Smartphones offer the possibility of assessing recovery of mobility after total hip or knee arthroplasty (THA or TKA) passively and reliably, as well as facilitating the collection of patient-reported outcome measures (PROMs) with greater frequency.

QUESTIONS/PURPOSES

We investigated the feasibility of using mobile technology to collect daily step data and biweekly PROMs to track recovery after total joint arthroplasty.

METHODS

Pre- and post-operative daily steps were recorded in prospectively enrolled patients (128 THA and 139 TKA) via an app, which uses the phone's accelerometer. During 6-month follow-up, patients also completed PROMs (the pain numeric rating scale, the Hip Disability and Osteoarthritis Outcome Score Joint Replacement [HOOS JR] and the Knee Injury and Osteoarthritis Outcome Score Joint Replacement [KOOS JR]), and HOOS or KOOS JR quality of life domain via a mobile-enabled web link.

RESULTS

At least 6 months of follow-up was completed by 65% for THA and 68% for TKA patients. Reasons for non-completion included time commitment, phone battery, app issues, and health complications. Responses from 78% of requested PROMs were returned with 96% of patients returning at least one post-operative PROM. Step data were available from 92% of days from male patients and 86% of days from female patients. The most robust recovery occurred early, within the first 2 months. The groups with higher pre-operative steps were more likely to recover their maximum daily steps at an earlier time point. Correlations between step counts and PROMs scores were modest.

CONCLUSION

Assessing large amounts of post-TKA and post-THA step data using mobile technology is feasible. Completion rates were good, making the technology very useful for collecting frequent PROMs. Being unable to ensure that patients always carried their phones limited our analysis of the step counts.

Changes in public preferences for technologically enhanced surveillance following the COVID-19 pandemic: a discrete choice experiment

OBJECTIVES

As governments attempt to navigate a path out of COVID-19 restrictions, robust evidence is essential to inform requirements for public acceptance of technologically enhanced communicable disease surveillance systems. We examined the value of core surveillance system attributes to the Australian public, before and during the early stages of the current pandemic.

DESIGN

A discrete choice experiment was conducted in Australia with a representative group of respondents, before and after the WHO declared COVID-19 a Public Health Emergency of International Concern. We identified and investigated the relative importance of seven attributes associated with technologically enhanced disease surveillance: respect for personal autonomy; privacy/confidentiality; data certainty/confidence; data security; infectious disease mortality prevention; infectious disease morbidity prevention; and attribution of (causal) responsibility. Specifically, we explored how the onset of the COVID-19 outbreak influenced participant responses.

SETTING AND PARTICIPANTS

2008 Australians (general public) completed the experiment: 793 before COVID-19 outbreak onset (mean age 45.9 years, 50.2% male) and 1215 after onset (mean age 47.2 years, 49% male).

RESULTS

All seven attributes significantly influenced respondents' preferences for communicable disease surveillance systems. After onset, participants demonstrated greater preference for a surveillance system that could prevent a higher number of illnesses and deaths, and were less concerned about their personal autonomy. However, they also increased their preference for a system with high data security.

CONCLUSIONS

Public acceptance of technology-based communicable disease surveillance is situation dependent. During an epidemic, there is likely to be greater tolerance of technologically enhanced disease surveillance systems that result in restrictions on personal activity if such systems can prevent high morbidity and mortality. However, this acceptance of lower personal autonomy comes with an increased requirement to ensure data security. These findings merit further research as the pandemic unfolds and strategies are put in place that enable individuals and societies to live with SARS-CoV-2 endemicity.

Children and young people's concerns and needs relating to their use of health technology to self-manage long-term conditions: a scoping review

BACKGROUND

The use of patient-facing health technologies to manage long-term conditions is increasing; however, children and young people may have particular concerns or needs before deciding to use different health technologies.

AIMS

To identify children and young people's reported concerns or needs in relation to using health technologies to self-manage long-term conditions.

METHODS

A scoping review was conducted. We searched MEDLINE, PsycINFO and CINAHL in February 2019. Searches were limited to papers published between January 2008 and February 2019. We included any health technology used to manage long-term conditions. A thematic synthesis of the data from the included studies was undertaken. We engaged children with long-term conditions (and parents) to support review design, interpretation of findings and development of recommendations.

RESULTS

Thirty-eight journal articles were included, describing concerns or needs expressed by n=970 children and/or young people aged 5-18 years. Most included studies were undertaken in high-income countries with children aged 11 years and older. Studies examined concerns with mobile applications (n=14), internet (n=9), social media (n=3), interactive online treatment programmes (n=3), telehealth (n=1), devices (n=3) or a combination (n=5). Children and young people's main concerns were labelling and identity; accessibility; privacy and reliability; and trustworthiness of information.

DISCUSSION

This review highlights important concerns that children and young people may have before using technology to self-manage their long-term condition. In future, research should involve children and young people throughout the development of technology, from identifying their unmet needs through to design and evaluation of interventions.

Evaluation of Mobile Health Applications to Track Patient-Reported Outcomes for Oncology Patients: A Systematic Review

Purpose

In response to the COVID-19 pandemic, there has been a rapid growth in the use of telehealth/telemedicine that will likely be sustained in the postpandemic setting. Mobile health applications (apps) can be used as part of the telehealth encounter to monitor patient-reported outcomes (PROs) and enhance patient-provider communication.

Methods and Materials

A systematic review was performed of mobile health apps with symptom trackers. We searched the iOS App Store and Android Google Play using the words cancer, oncology, and symptom tracker. Apps were included if they incorporated a symptom tracking function that could allow patients with cancer to record symptoms and PROs. Apps were evaluated using the mobile apps rating scale, which includes engagement, functionality, aesthetics, information, and app subjective quality.

Results

The initial search yielded 1189 apps, with 101 apps eligible after title and description screening. A total of 41 apps met eligibility criteria and were included in this study. The majority of apps (73%, n = 30) were general health/pain symptom trackers, and 27% (n = 11) were cancer-specific. The app quality mean scores assessed using the mobile apps rating scale ranged from 2.43 to 4.23 (out of 5.00). Only 1 app has been trialed for usability among patients with cancer.

Conclusions

Although various symptom tracking apps are available, cancer-specific apps remain limited. Future collaboration between oncologists, app developers, and patients to optimize PRO assessment and integration with telehealth/telemedicine encounters to increase symptom recognition and enhance patient-provider communication is urgently needed.

Developments in Mobile Health Just-in-Time Adaptive Interventions for Addiction Science

PURPOSE OF REVIEW

Addiction is a serious and prevalent problem across the globe. An important challenge facing intervention science is how to support addiction treatment and recovery while mitigating the associated cost and stigma. A promising solution is the use of mobile health (mHealth) just-in-time adaptive interventions (JITAIs), in which intervention options are delivered in situ via a mobile device when individuals are most in need.

RECENT FINDINGS

The present review describes the use of mHealth JITAIs to support addiction treatment and recovery, and provides guidance on when and how the micro-randomized trial (MRT) can be used to optimize a JITAI. We describe the design of five mHealth JITAIs in addiction and three MRT studies, and discuss challenges and future directions.

SUMMARY

This review aims to provide guidance for constructing effective JITAIs to support addiction treatment and recovery.

Ethical and Safety Concerns Regarding the Use of Mental Health-Related Apps in Counseling: Considerations for Counselors

Mental health-related smartphone apps (MHapps) have the potential to greatly enhance and enrich the counseling relationship, and dramatically improve the lives of clients. However, a large portion of MHapps have not been empirically researched and found to be effective. An average of 2 million apps are available in the Apple and Android stores, and users average more than 80 apps on their phones. Many of the apps lack disclaimers about the collection of user information, and there is no governing body to oversee and regulate app development and availability. This is particularly problematic with mental health-related smartphone apps, because many developers are not affiliated with mental health professionals, and many apps do not provide emergency information should a mental health emergency occur while using the app. Moreover, users are left to haphazardly make decisions about health-related apps usage without assistance. Counselors who supplement counseling with mental health-related smartphone apps could unknowingly violate their Code of Ethics by integrating apps that may jeopardize their clients' safety. The authors review literature related to mental health-related app efficacy, safety, and ethics and provide a compilation of items to consider that can be used before supplementing counseling with mental health-related apps.