ArticleJMIR mHealth and uHealth2018
A Mobile App for Assisting Users to Make Informed Selections in Security Settings for Protecting Personal Health Data: Development and Feasibility Study.
Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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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
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Patients' Perspectives on the Data Confidentiality, Privacy, and Security of mHealth Apps: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Patients' mHealth Apps Usage and Data Privacy, Security, and Confidentiality Concerns: Exploratory Study.JMIR formative research · 2026Article
- Perspectives Regarding the Privacy, Security, and Confidentiality of Data Collected via mHealth Apps in Saudi Arabia: Qualitative Analysis.Journal of medical Internet research · 2026Article
- Development of a personal health management system integrating digital twin technology and smart wearables in China.Frontiers in public health · 2025Article
- Patients and Stakeholders' Perspectives Regarding the Privacy, Security, and Confidentiality of Data Collected via Mobile Health Apps in Saudi Arabia: Protocol for a Mixed Method Study.JMIR research protocols · 2024Article
- Privacy versus Convenience: A Historical Perspective, Analysis of Risks, and an Informatics Call to Action.Applied clinical informatics · 2021Article
- Analysis of Diabetes Apps to Assess Privacy-Related Permissions: Systematic Search of Apps.JMIR diabetes · 2021Article
- User Preferences for Privacy Protection Methods in Mobile Health Apps: A Mixed-Methods Study.International journal of telerehabilitation · 2020Article
- Human-Computer Interaction, Ethics, and Biomedical Informatics.Yearbook of medical informatics · 2020Review
- Development and Validation of a Comprehensive Well-Being Scale for People in the University Environment (Pitt Wellness Scale) Using a Crowdsourcing Approach: Cross-Sectional Study.Journal of medical Internet research · 2020Article
- Development and Testing of a Mobile Phone App for Risk Estimation of Gas Volume Expansion and Intraocular Pressure Elevation in Patients With Intravitreous Gas or Air Tamponade: Interobserver Assessment Study.JMIR mHealth and uHealth · 2019Article
- Barriers to and Facilitators of the Use of Mobile Health Apps From a Security Perspective: Mixed-Methods Study.JMIR mHealth and uHealth · 2019Article
- Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundOn many websites and mobile apps for personal health data collection and management, there are security features and privacy policies available for users. Users sometimes are given an opportunity to make selections in a security setting page; however, it is challenging to make informed selections in these settings for users who do not have much education in information security as they may not precisely know the meaning of certain terms mentioned in the privacy policy or understand the consequences of their selections in the security and privacy settings.
objectiveThe aim of this study was to demonstrate several commonly used security features such as encryption, user authentication, and access control in a mobile app and to determine whether this brief security education is effective in encouraging users to choose stronger security measures to protect their personal health data.
methodsA mobile app named SecSim (Security Simulator) was created to demonstrate the consequences of choosing different options in security settings. A group of study participants was recruited to conduct the study. These participants were asked to make selections in the security settings before and after they viewed the consequences of security features. At the end of the study, a brief interview was conducted to determine the reason for their selections in the security settings. Their selections before and after the security education were compared in order to determine the effectiveness of the security education. The usability of the app was also evaluated.
resultsIn total, 66 participants finished the study and provided their answers in the app and during a brief interview. The comparison between the pre- and postsecurity education selection in security settings indicated that 21% (14/66) to 32% (21/66) participants chose a stronger security measure in text encryption, access control, and image encryption; 0% (0/66) to 2% (1/66) participants chose a weaker measure in these 3 security features; and the remainder kept their original selections. Several demographic characteristics such as marital status, years of experience using mobile devices, income, employment, and health status showed an impact on the setting changes. The usability of the app was good.
conclusionsThe study results indicate that a significant percentage of users (21%-32%) need guidance to make informed selection in security settings. If websites and mobile apps can provide embedded security education for users to understand the consequences of their security feature selection and the meaning of commonly used security features, it may help users to make the best choices in terms of security settings. Our mobile app, SecSim, offers a unique approach for mobile app users to understand commonly used security features. This app may be incorporated into other apps or be used before users make selections in their security settings.
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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.