CoChat
Sign Up
Cited by 246Mobile Health and mHealth ApplicationsPrivacy, Security, and Data ProtectionHealth, Technology, Consumer Behavior

Barriers to and Facilitators of the Use of Mobile Health Apps From a Security Perspective: Mixed-Methods Study

Open access
Zhou, Leming, Bao, Jie, Watzlaf, Valerie, Parmanto, Bambang·2019·JMIR mHealth and uHealth
DOI 10.2196/11223PMC PMC6488955

Published version of a preprint

Open this paper in CoChat — free account

Abstract

BACKGROUND: A large number of mobile health (mHealth) apps have been created to help users to manage their health or receive health care services. Many of these mHealth apps have proven to be helpful for maintaining or improving their users' health. However, many people still choose not to use mHealth apps or only use them for a short period. One of the reasons behind this lack of use is the concern for their health information security and privacy. OBJECTIVE: The goal of this study was to determine the relationship between users' characteristics and their security and privacy concerns and to identify desired security features in mHealth apps, which could reduce these concerns. METHODS: A questionnaire was designed and validated by the research team. This questionnaire was then used to determine mobile app users' security and privacy concerns regarding personal health data in mHealth apps as well as the security features most users' desire. A semistructured interview was used to identify barriers to and facilitators of adopting mHealth apps. RESULTS: In total, 117 randomly selected study participants from a large pool took part in this study and provided responses to the validated questionnaire and the semistructured interview questions. The results indicate that most study participants did have concerns about their privacy when using mHealth apps. They also expressed their preferences regarding several security features in mHealth apps, such as regular password updates, remote wipe, user consent, and access control. An association between their demographic characteristics and their concerns and preferences in security and privacy was identified; however, in most cases, the differences among the different demographic groups were not statistically significant, except for a few very specific aspects. These study participants also indicated that the cost of apps and lack of security features in mHealth apps were barriers for adoption, whereas having free apps, strong but easy-to-use security features, and clear user protection privacy policies might encourage them to use mHealth apps in their health management. CONCLUSIONS: This questionnaire and interview study verified the security and privacy concerns of mHealth app users, identified the desired security and privacy features, and determined specific barriers to and facilitators of users adopting mHealth apps. The results can be used to guide mHealth app developers to create apps that would be welcomed by users.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2196/11223

Cites

42 of 42 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • User-focused evaluation includes evaluation of apps targeting specific user groups, such as adolescents or people with mental health problems, or based on user input such as user reviews.

    “This includes evaluation of apps targeting speci c user groups, for instance, adolescents [86] or people with mental health problems [84], or based on user input such as user reviews [64].”

    From Security and Privacy of mHealth Applications: A Scoping Review (2020) · cites this paper as [86]

    The Introduction (Background) discusses heightened user privacy concerns about apps for stigmatized conditions, including mental disease. But the Methods (Study Design) describe recruiting general adult smart-device users, not evaluating apps targeting people with mental health problems. The citations for adolescents and user reviews attach to other sources in the citing sentence. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. [28]Prasad A Sorber J Stablein T Anthony D Kotz D Exposing privacy concerns in mHealth Proceedings of the 2nd USENIX conference on Health security and privacy 2011 the 2nd USENIX conference on Health security and privacy August 9 San Francisco, CA 2 2

Cited by

Sorted by citations

Related

Authors
Zhou, L., Bao, J., Watzlaf, V., & Parmanto, B.
Affiliations
University of Pittsburgh (US)
Corresponding author
Zhou, Leming
ORCID
Venue
JMIR mHealth and uHealth
Publisher
JMIR Publications Inc.
Published
2019-04-16
Volume
7
Issue
4
Pages
e11223
ISSN
2291-5222 (ISSN-L)
DOI
10.2196/11223
PMC
PMC6488955
OpenAlex
W2920187112
Cited by
246
References
42
Citations by year
2026: 20 · 2025: 41 · 2024: 46 · 2023: 30 · 2022: 41 · 2021: 39 · 2020: 27 · 2019: 2
FWCI
37.15
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR mhealth and uhealth (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
  • Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
Keywords
mobile health apps, health information security, privacy concerns, barriers to adoption, adoption facilitators, security features, personal health data, user preferences, password update, user consent, access control, privacy policies, app cost, health self-management
MeSH terms
Adolescent, Adult, Aged, Confidentiality, Female, Humans, Male, Middle Aged, Surveys and Questionnaires, Computer Security, Mobile Applications

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review