Cited by 2Privacy, Security, and Data ProtectionHealth, Technology, Consumer BehaviorTechnology Adoption and User Behaviour

The DOI matches its Crossref record.

Determinants of Personal Health Information Disclosure: A Case of Mobile Application

Abstract

This study explored the factors that affect personal health information (PHI) disclosure via a mobile application (app) in Thailand. Since mobile apps are increasingly popular, as is the Thai people's concern on their health condition, many mobile app service providers want to know which factors would persuade customers to reveal their PHI via mobile apps. This research model was, therefore, developed and included the six factors of: personalized service, self-presentation, mobile app reputation, familiarity, perceived benefits and privacy concerns. The hypotheses were tested by structural equation modeling using the questionnaire responses from 294 valid subjects. Surprisingly, privacy concern was not significantly negatively related to the intention to disclose PHI. However, the significance effect of the perceived benefit, personalized service and self-presentation were consistent with previous studies. In addition, the respondents were willing to reveal different personal information in different situations. The implication of the result will shed light on the development of a healthcare mobile app service provider.

Overview

Integrity signals

Registry

Crossref · 10.4018/ijsi.2018010103

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 16

  1. J. C.Anderson, 1988, Structural equation modeling in practice: A review and recommended two-step approach, Psychological Bulletin, 3, 3411
  2. 10.1016/j.dss.2010.01.010 · DOI · Paper page
  3. 10.1037/0033-2909.88.3.588 · DOI
  4. M. B.Byrne, 2001, Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming
  5. 10.1080/10705519909540118 · DOI · Paper page
  6. 10.1016/j.ijhcs.2013.08.016 · DOI · Paper page
  7. S.Kim, 2016, Analysis of the factors influencing healthcare professionals’ adoption of mobile electronic medical record (EMR) using the unified theory of acceptance and use of technology (UTAUT) in a tertiary hospital, BMC Medical Informatics and Decision Making, 16, 1
  8. 10.1016/j.im.2003.08.004 · DOI · Paper page
  9. 10.1016/j.dss.2013.09.018 · DOI
  10. 10.1504/IJMC.2011.040608 · DOI
  11. 10.1016/j.cose.2017.03.001 · DOI
  12. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate Data Analysis (6th ed.). Prentice-Hall.
  13. J. C.Nunnally, 1978, Psychometric Theory
  14. J. H.Steiger, 2007, Understanding the limitations of global fit assessment in structural equation modeling, Personality and Individual Differences, 5, 93
  15. 10.1016/j.ijinfomgt.2016.10.006 · DOI
  16. 10.1016/j.ijinfomgt.2016.03.003 · DOI

Cited by

Sorted by citations

See all 2

Metadata

Authors
Atchariyachanvanich, K., Mitinunwong, N., Tamthong, B., & Sonehara, N.
Affiliations
  • King Mongkut's Institute of Technology Ladkrabang (TH)
  • Tsuda University (JP)
Venue
International Journal of Software Innovation
Published
2018-01
Volume
6
Issue
1
Pages
31-43
ISSN
  • 2166-7160 (ISSN-L)
  • 2166-7179
OpenAlex
W2765572442
Cited by
2
References
0
Citations by year
2023: 1 · 2020: 1
FWCI
0.70
Type
journal article
Language
en
Open access
closed
Locations
International Journal of Software Innovation (publishedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
  • Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Keywords
mobile health apps, privacy concerns, perceived benefits, personalized services, self-presentation, familiarity, disclosure intention, Thailand

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Determinants of Personal Health Information Disclosure: A Case of Mobile Application. https://app.cochat.ai/papers/10.4018/ijsi.2018010103
The paper
Atchariyachanvanich, K., Mitinunwong, N., Tamthong, B., & Sonehara, N. (2018). Determinants of Personal Health Information Disclosure: A Case of Mobile Application. International Journal of Software Innovation. https://doi.org/10.4018/ijsi.2018010103