Dataset Information

Assessment of Mobile Health Apps Using Built-In Smartphone Sensors for Diagnosis and Treatment: Systematic Survey of Apps Listed in International Curated Health App Libraries.

ABSTRACT: BACKGROUND:More than a million health and well-being apps are available from the Apple and Google app stores. Some apps use built-in mobile phone sensors to generate health data. Clinicians and patients can find information regarding safe and effective mobile health (mHealth) apps in third party-curated mHealth app libraries. OBJECTIVE:These independent Web-based repositories guide app selection from trusted lists, but do they offer apps using ubiquitous, low-cost smartphone sensors to improve health? This study aimed to identify the types of built-in mobile phone sensors used in apps listed on curated health app libraries, the range of health conditions these apps address, and the cross-platform availability of the apps. METHODS:This systematic survey reviewed three such repositories (National Health Service Apps Library, AppScript, and MyHealthApps), assessing the availability of apps using built-in mobile phone sensors for the diagnosis or treatment of health conditions. RESULTS:A total of 18 such apps were identified and included in this survey, representing 1.1% (8/699) to 3% (2/76) of all apps offered by the respective libraries examined. About one-third (7/18, 39%) of the identified apps offered cross-platform Apple and Android versions, with a further 50% (9/18) only dedicated to Apple and 11% (2/18) to Android. About one-fourth (4/18, 22%) of the identified apps offered dedicated diagnostic functions, with a majority featuring therapeutic (9/18, 50%) or combined functionality (5/18, 28%). Cameras, touch screens, and microphones were the most frequently used built-in sensors. Health concerns addressed by these apps included respiratory, dermatological, neurological, and anxiety conditions. CONCLUSIONS:Diligent mHealth app library curation, medical device regulation constraints, and cross-platform differences in mobile phone sensor architectures may all contribute to the observed limited availability of mHealth apps using built-in phone sensors in curated mHealth app libraries. However, more efforts are needed to increase the number of such apps on curated lists, as they offer easily accessible low-cost options to assist people in managing clinical conditions.

SUBMITTER: Baxter C

PROVIDER: S-EPMC7055743 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Assessment of Mobile Health Apps Using Built-In Smartphone Sensors for Diagnosis and Treatment: Systematic Survey of Apps Listed in International Curated Health App Libraries.

Baxter Clarence C Carroll Julie-Anne JA Keogh Brendan B Vandelanotte Corneel C

JMIR mHealth and uHealth 20200203 2

<h4>Background</h4>More than a million health and well-being apps are available from the Apple and Google app stores. Some apps use built-in mobile phone sensors to generate health data. Clinicians and patients can find information regarding safe and effective mobile health (mHealth) apps in third party-curated mHealth app libraries.<h4>Objective</h4>These independent Web-based repositories guide app selection from trusted lists, but do they offer apps using ubiquitous, low-cost smartphone senso ...[more]

PMID: 32012102

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Project description:BackgroundIn recent years, mobile health (mHealth) has gradually developed in China, and intelligent medicine has become an important research topic. However, there are still significant problems in mHealth applications (apps). Although healthcare professionals and patients are the main users, few studies have focused on their perceptions of the quality of mHealth apps.ObjectiveThis study aimed to (1) understand the respective perceptions of healthcare professionals and patients regarding mHealth apps, (2) assess what barriers exist that influence the user experience, and (3) explore how to improve the quality of mHealth apps and the development of the mHealth market in China. The study aims to promote the standardization of mHealth apps and provide effective information for the improvement and development of mHealth apps in the future.MethodsSemistructured interviews with 9 patients and 14 healthcare professionals were conducted from January 2022 to April 2022 in the Affiliated Hospital of Xuzhou Medical University. The participants used mHealth apps for more than 3 months, including the "Good Mood" and "Peace and Safe Doctors" apps and apps developed by the hospital that were popular in China. Interview transcripts were analysed using thematic analysis.ResultsThe following five themes were extracted: different concerns, hidden medical dangers, distance and insecurity, barriers for older people, and having positive perceptions of mHealth apps. Healthcare professionals prioritized simplicity in regard to mHealth apps, whereas patients rated effectiveness as the most crucial factor. The study also revealed several problems with mHealth apps, including insufficient information about physician qualifications, inaccurate medical content, nonstandard treatment processes, and unclear accountability, which led to a sense of distance and insecurity among participants. Older individuals faced additional obstacles when using mHealth apps. Despite these issues, the participants remained optimistic about the future of mHealth app development.ConclusionThe utilization, advantages, and obstacles of mHealth applications for healthcare professionals and patients were explored through semistructured interviews. Despite the promising prospects for mHealth apps in China, numerous issues still need to be addressed. Enhancing the safety monitoring system and developing user-friendly mHealth apps for older adult patients are essential steps to bridge the gap between healthcare providers and patients.

Project description:BACKGROUND:Modern smartphones contain sophisticated high-end hardware features, offering high computational capabilities at extremely manageable costs and have undoubtedly become an integral part in users' daily life. Additionally, smartphones offer a well-established ecosystem that is easily discoverable and accessible via the marketplaces of differing mobile platforms, thus encouraging the development of many smartphone apps. Such apps are not exclusively used for entertainment purposes but are also commonplace in health care and medical use. A variety of those health and medical apps exist within the context of tinnitus, a phantom sound perception in the absence of any physical external source. OBJECTIVE:In this paper, we shed light on existing smartphone apps addressing tinnitus by providing an up-to-date overview. METHODS:Based on PRISMA guidelines, we systematically searched and identified existing smartphone apps on the most prominent app markets, namely Google Play Store and Apple App Store. In addition, we applied the Mobile App Rating Scale (MARS) to evaluate and assess the apps in terms of their general quality and in-depth user experience. RESULTS:Our systematic search and screening of smartphone apps yielded a total of 34 apps (34 Android apps, 26 iOS apps). The mean MARS scores (out of 5) ranged between 2.65-4.60. The Tinnitus Peace smartphone app had the lowest score (mean 2.65, SD 0.20), and Sanvello-Stress and Anxiety Help had the highest MARS score (mean 4.60, SD 0.10). The interrater agreement was substantial (Fleiss ?=0.74), the internal consistency was excellent (Cronbach ?=.95), and the interrater reliability was found to be both high and excellent-Guttman ?6=0.94 and intraclass correlation, ICC(2,k) 0.94 (95% CI 0.91-0.97), respectively. CONCLUSIONS:This work demonstrated that there exists a plethora of smartphone apps for tinnitus. All of the apps received MARS scores higher than 2, suggesting that they all have some technical functional value. However, nearly all identified apps were lacking in terms of scientific evidence, suggesting the need for stringent clinical validation of smartphone apps in future. To the best of our knowledge, this work is the first to systematically identify and evaluate smartphone apps within the context of tinnitus.

Project description:Aim: This brief report provides an overview of the development and structure of the Health App Review Tool. Methods: The Health App Review Tool has been designed to assess smart phone health apps according to their compatibility to individuals within the Alzheimer's disease community. Specifically, app features and functions are characterized according to their appropriateness to the needs, abilities, and preferences of potential users. The Health App Review Tool is comprised of two components, the App and User Assessment; each component includes four complementary domains. Items in these domains can be compared between App and User assessments using a scoring key that will produce a match score. The score indicates the level of appropriateness in reference to the app's ability to meet the user's needs. Discussion: The Health App Review Tool was designed using available evidence and stakeholder preference data to ensure a user-centered design. The result was the development of a tool built on evidence and informed by the perceptions and preferences of those within and working with the Alzheimer's disease population. App and User domains include usefulness, complexity, accessibility, and external variables. This unique matching approach is anticipated to significantly impact individualized, client-centered care. We anticipate that this study will serve as a model for future development of technology matching tools for other diagnostic populations. Discussion: The Health App Review Tool was designed using available evidence and stakeholder preference data to ensure a user-centered design. The result was the development of a tool built on evidence and informed by the perceptions and preferences of those within and working with the Alzheimer's disease population. App and User domains include usefulness, complexity, accessibility, and external variables. This unique matching approach is anticipated to significantly impact individualized, client-centered care. We anticipate that this study will serve as a model for future development of technology matching tools for other diagnostic populations.

Project description:BackgroundMobile health (mHealth) apps are becoming increasingly common in surgical practices for training, education, and communication. Factors leading to increased delays, morbidity, and mortality in surgery include inadequate preoperative patient preparation due to a failure to identify patients and procedure details, and missing instruments and equipment required for the procedure. Many apps are available for supporting preoperative, intraoperative, and postoperative care. However, there is a lack of studies that assess the quality of apps that act as surgical preparatory guides.ObjectiveThe aim of this study is to evaluate the quality of apps that act as surgical preparatory guides for operating room personnel through an in-house quality assessment tool.MethodsThe quality assessment tool comprises 35 questions categorized into 5 sections: (1) engagement (customization, interactivity, target audience; 19 points), (2) functionality (performance, ease of use, navigation; 12 points), (3) aesthetics (layout, visual appeal; 6 points), (4) information (quality and quantity of information, visual information, credibility; 29 points), and (5) privacy and security (4 points). An app search was conducted in the Australian Apple and Google Play stores using the following keywords: "surgical apps", "surgical preferences", "surgeon preferences", "operating room", and "perioperative procedures". The overall total scores and scores for each section were reported as medians and IQRs, expressed as raw scores and percentages.ResultsA total of 5 unique apps were evaluated on both iOS and Android platforms. The median overall score across all apps was 35/70 (50%; IQR 38.6%-64.3%). ScrubUp (48/70, 69%) and MySurgeon (42/70, 60%) had the highest overall scores, followed by PrefCard (35/70, 50%) and Scrubnote (28/70, 40%). The lowest scoring app was BrainPadd (26/70, 37%). The sections with the highest median scores, in decreasing order, were privacy and security (4/4, 100%; IQR 75%-100%), aesthetics (5/6, 83%; IQR 75%-91.7%), engagement (15/19, 79%; IQR 57.9%-86.8%), functionality (7/12, 58%; IQR 29.2%-75%), and information (5/29, 17%; IQR 15.5%-34.5%). Most apps scored well (4/4, 100%) on privacy and security, except for Scrubnote (2/4, 50%). ScrubUp received a perfect score for aesthetics (6/6, 100%). MySurgeon (17/19, 90%) had the highest engagement score, while ScrubUp and MySurgeon had the highest functionality scores (9/12, 75% each). All apps scored below 50% for the information section, with ScrubUp having the highest score of 13/29 (45%).ConclusionsScrubUp and MySurgeon had the highest quality scores and can be used as adjuncts to hospital protocols by operating room personnel for their surgical preparation. Developers are encouraged to develop appropriate apps for surgical preparation based on relevant guidelines and standards, as well as the quality evaluation criteria in our tool. Operating room personnel can also use this tool as a guide to select and assess their preferred apps in their practices.

Project description:BackgroundApproximately 800 million people, representing 11% of the world's population, are affected by mental health problems. The COVID-19 pandemic exacerbated problems and triggered a decline in well-being, with drastic increase in the incidence of conditions such as anxiety, depression, and stress. Approximately 20,000 mental health apps are listed in mobile app stores. However, no significant evaluation of mental health apps in French, spoken by approximately 300 million people, has been identified in the literature yet.ObjectiveThis study aims to review the mental health mobile apps currently available on the French Apple App Store and Google Play Store and to evaluate their quality using Mobile App Rating Scale-French (MARS-F).MethodsScreening of mental health apps was conducted from June 10, 2022, to June 17, 2022, on the French Apple App Store and Google Play Store. A shortlist of 12 apps was identified using the criteria of selection and assessed using MARS-F by 9 mental health professionals. Intraclass correlation was used to evaluate interrater agreement. Mean (SD) scores and their distributions for each section and item were calculated.ResultsThe highest scores for MARS-F quality were obtained by Soutien psy avec Mon Sherpa (mean 3.85, SD 0.48), Evoluno (mean 3.54, SD 0.72), and Teale (mean 3.53, SD 0.87). Mean engagement scores (section A) ranged from 2.33 (SD 0.69) for Reflexe reussite to 3.80 (SD 0.61) for Soutien psy avec Mon Sherpa. Mean aesthetics scores (section C) ranged from 2.52 (SD 0.62) for Mental Booster to 3.89 (SD 0.69) for Soutien psy avec Mon Sherpa. Mean information scores (section D) ranged from 2.00 (SD 0.75) for Mental Booster to 3.46 (SD 0.77) for Soutien psy avec Mon Sherpa. Mean Mobile App Rating Scale subjective quality (section E) score varied from 1.22 (SD 0.26) for VOS - journal de l'humeur to 2.69 (SD 0.84) for Soutien psy avec Mon Sherpa. Mean app specificity (section F) score varied from 1.56 (SD 0.97) for Mental Booster to 3.31 (SD 1.22) for Evoluno. For all the mental health apps studied, except Soutien psy avec Mon Sherpa (11/12, 92%), the subjective quality score was always lower than the app specificity score, which was always lower than the MARS-F quality score, and that was lower than the rating score from the iPhone Operating System or Android app stores.ConclusionsMental health professionals assessed that, despite the lack of scientific evidence, the mental health mobile apps available on the French Apple App Store and Google Play Store were of good quality. However, they are reluctant to use them in their professional practice. Additional investigations are needed to assess their compliance with recommendations and their long-term impact on users.

Project description:BackgroundHealth and well-being smartphone apps can provide a cost-effective solution to addressing unhealthy behaviors. The selection of these apps tends to occur in commercial app stores, where thousands of health apps are available. Their uptake is often influenced by popularity indicators. However, these indicators are not necessarily associated with app effectiveness or evidence-based content. Alternative routes to app selection are increasingly available, such as via curated app portals, but little is known about people's experiences of them.ObjectiveThe aim of this study is to explore how people select health apps on the internet and their views on curated app portals.MethodsA total of 18 UK-based adults were recruited through social media and asked during an in-person meeting to verbalize their thoughts while searching for a health or well-being app on the internet on a platform of their choice. The search was then repeated on 2 curated health app portals: the National Health Service Apps Library and the Public Health England One You App portal. This was followed by semistructured interviews. Data were analyzed using framework analysis, informed by the Capability, Opportunity, Motivation-Behavior model and the Theoretical Domains Framework.ResultsSearching for health and well-being apps on the internet was described as a minefield. App uptake appeared to be influenced by participants' capabilities such as app literacy skills and health and app awareness, and opportunities including the availability of apps, app esthetics, the price of an app, and social influences. Motivation factors that seemed to affect the uptake were perceived competence, time efficiency, perceived utility and accuracy of an app, transparency about data protection, commitment and social identity, and a wide range of emotions. Social influences and the perceived utility of an app were highlighted as particularly important. Participants were not previously aware of curated portals but found the concept appealing. Curated health app portals appeared to engender trust and alleviate data protection concerns. Although apps listed on these were perceived as more trustworthy, their presentation was considered disappointing. This disappointment seemed to stem from the functionality of the portals, lack of user guidance, and lack of tailored content to an individual's needs.ConclusionsThe uptake of health and well-being apps appears to be primarily affected by social influences and the perceived utility of an app. App uptake via curated health app portals perceived as credible may mitigate concerns related to data protection and accuracy, but their implementation must better meet user needs and expectations.

Project description:BackgroundThe success of mobile apps in improving the lifestyle of patients with noncommunicable diseases through self-management interventions is contingent upon the emerging growth in this field. While users of mobile health (mHealth) apps continue to grow in number, little is known about the quality of available apps that provide self-management for common noncommunicable diseases such as diabetes, hypertension, and obesity.ObjectiveWe aimed to investigate the availability, characteristics, and quality of mHealth apps for common noncommunicable disease health management that included dietary aspects (based on the developer's description), as well as their features for promoting health outcomes and self-monitoring.MethodsA systematic search of English-language apps on the Google Play Store (Google LLC) and Apple App Store (Apple Inc) was conducted between August 7, 2022, and September 13, 2022. The search terms used included weight management, obesity, diabetes, hypertension, cardiovascular diseases, stroke, and diet. The selected mHealth apps' titles and content were screened based on the description that was provided. Apps that were not designed with self-management features were excluded. We analyzed the mHealth apps by category and whether they involved health care professionals, were based on scientific testing, and had self-monitoring features. A validated and multidimensional tool, the Mobile App Rating Scale (MARS), was used to evaluate each mHealth app's quality based on a 5-point Likert scale from 1 (inadequate) to 5 (excellent).ResultsOverall, 42 apps were identified. Diabetes-specific mHealth apps accounted for 7% (n=3) of the market, hypertension apps for 12% (n=5), and general noncommunicable disease management apps for 21% (n=9). About 38% (n=16) of the apps were for managing chronic diseases, while 74% (n=31) were for weight management. Self-management features such as weight tracking, BMI calculators, diet tracking, and fluid intake tracking were seen in 86% (n=36) of the apps. Most mHealth apps (n=37, 88%) did not indicate whether there was involvement of health professionals in app development. Additionally, none of the apps reported scientific evidence demonstrating their efficacy in managing health. The overall mean MARS score was 3.2 of 5, with a range of 2.0 to 4.1. Functionality was the best-rated category (mean score 3.9, SD 0.5), followed by aesthetics (mean score 3.2, SD 0.9), information (mean score 3.1, SD 0.7), and engagement (mean score 2.9, SD 0.6).ConclusionsThe quality of mHealth apps for managing chronic diseases was heterogeneous, with roughly half of them falling short of acceptable standards for both quality and content. The majority of apps contained scant information about scientific evidence and the developer's history. To increase user confidence and accomplish desired health outcomes, mHealth apps should be optimized with the help of health care professionals. Future studies on mHealth content analysis should focus on other diseases as well.

Project description:BACKGROUND:Each year, millions of older adults fall, with more than 1 out of 4 older people experiencing a fall annually, thereby causing a major social and economic impact. Falling once doubles one’s chances of falling again, making fall prediction an important aspect of preventative strategies. In this study, 22 older adults aged between 65 and 85 years were trained in the use of a smartphone-based fall prediction system. The system is designed to continuously assess fall risk by measuring various gait and balance parameters using a smart insole and smartphone, and is also designed to detect falls. The use case of the fall prediction system in question required the users to interact with the smartphone via an app for device syncing, data uploads, and checking system status. OBJECTIVE:The objective of this study was to observe the effect that basic smartphone training could have on the user experience of a group that is not technically proficient with smartphones when using a new connected health system. It was expected that even short rudimentary training could have a large effect on user experience and therefore increase the chances of the group accepting the new technology. METHODS:All participants received training on how to use the system smartphone app; half of the participants (training group) also received extra training on how to use basic functions of the smartphone, such as making calls and sending text messages, whereas the other half did not receive this extra training (no extra training group). Comparison of training group and no extra training group was carried out using metrics such as satisfaction rating, time taken to complete tasks, cues required to complete tasks, and errors made during tasks. RESULTS:The training group fared better in the first 3 days of using the system. There were significant recorded differences in number of cues required and errors committed between the two groups. By the fourth and fifth day of use, both groups were performing at the same level when using the system. CONCLUSIONS:Supplementary basic smartphone training may be critical in trials where a smartphone app–based system for health intervention purposes is being introduced to a population that is not proficient with technology. This training could prevent early technology rejection and increase the engagement of older participants and their overall user experience with the system.

Dataset Information

Assessment of Mobile Health Apps Using Built-In Smartphone Sensors for Diagnosis and Treatment: Systematic Survey of Apps Listed in International Curated Health App Libraries.

Publications

Assessment of Mobile Health Apps Using Built-In Smartphone Sensors for Diagnosis and Treatment: Systematic Survey of Apps Listed in International Curated Health App Libraries.

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