ArticleJMIR mHealth and uHealth2020
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.
Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed, 139 citations in OpenAlex.
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- Mapping the Apps: Ethical and Legal Issues with Crowdsourced Smartphone Data using mHealth Applications.Asian bioethics review · 2024Article
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- Beyond the clinic: the rise of wearables and smartphones in decentralising healthcare.NPJ digital medicine · 2023Article
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- What incentives encourage local communities to collect and upload mosquito sound data by using smartphones? A mixed methods study in Tanzania.Global health research and policy · 2023Article
- Orthopaedic and trauma surgeons' prioritisation of app quality principles based on their demographic background.BMC musculoskeletal disorders · 2023Article
- Non-Invasive Data Acquisition and IoT Solution for Human Vital Signs Monitoring: Applications, Limitations and Future Prospects.Sensors (Basel, Switzerland) · 2022Review
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Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMore 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.
objectiveThese 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.
methodsThis 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.
resultsA 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.
conclusionsDiligent 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.