ArticleJMIR mHealth and uHealth2023
Critical Criteria and Countermeasures for Mobile Health Developers to Ensure Mobile Health Privacy and Security: Mixed Methods Study.
Article in JMIR mHealth and uHealth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Perceived Sensitivity of Sensor-Based Digital Health Data: Qualitative Interview Study.JMIR mHealth and uHealth · 2026Article
- A hierarchical framework to evaluate the usability of smartphone health applications.Scientific reports · 2026Article
- Developing the i-MoMCARE application in Cambodia: an iterative co-design approach using rapid prototyping.BMJ digital health & AI · 2026Article
- Interpretable Machine Learning Models for Analyzing Determinants Affecting the Use of mHealth Apps Among Family Caregivers of Patients With Stroke in Chinese Communities: Cross-Sectional Survey Study.JMIR mHealth and uHealth · 2025Article
- mHealth technologies in research studying cardiovascular health in cancer: A systematic review.PLOS digital health · 2025Article
- Exploring the Requirements for an mHealth App to Prevent and Manage Perinatal Anxiety and Depression.Health science reports · 2025Article
- Quality and Privacy Policy Compliance of Mental Health Care Apps in China: Cross-Sectional Evaluation Study.Journal of medical Internet research · 2025Article
- Bridging language barriers in healthcare: a patient-centric mobile app for multilingual health record access and sharing.Frontiers in digital health · 2025Article
- Development of an mHealth App by Experts for Queer Individuals' Sexual-Reproductive Health Care Services and Needs: Nominal Group Technique Study.JMIR formative research · 2024Article
- Mobile Health Interventions: A Frontier for Mitigating the Global Burden of Cardiovascular Disease.Cureus · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDespite 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.
objectiveThis study aims to develop and validate a comprehensive tool to be considered by developers for assessing the security and privacy of mHealth apps.
methodsA 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.
resultsThe 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.
conclusionsThe 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.
Indexed as
Identifiers
What OpenQuestion holds
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.