Currently accepted at: JMIR Formative Research
Date Submitted: Jun 26, 2026
Date Accepted: Sep 29, 2026
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/105637
The final accepted version (not copyedited yet) is in this tab.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Understanding the Unintended Consequences of Healthcare Data in Public Reporting Systems: A Structural Equation Model of Cognitive, Heuristic, and Emotional Mechanisms
ABSTRACT
Background:
Public reporting (PR) systems aim to improve transparency in healthcare by providing patients with access to performance-based information. However, despite extensive investments in data infrastructure and visualization, the availability of healthcare data does not consistently translate into system adoption. This study addresses this paradox by asking why healthcare data fail to directly shape user behavior in PR systems.
Objective:
Drawing on dual-process theories of information processing, we develop a framework in which healthcare data influence behavior indirectly through cognitive, heuristic, and affective mechanisms. Users form understanding through systematic processing of information, rely on heuristic cues embedded in information presentation, and experience emotional responses during information interpretation. These mechanisms jointly shape perceived credibility and behavioral intentions.
Methods:
We conducted a cross-sectional questionnaire survey among users of healthcare public reporting (PR) systems in China. A total of 215 valid responses were collected using a structured questionnaire with 48 items measured on a seven-point Likert scale. The proposed research model and hypotheses were tested using partial least squares structural equation modeling (PLS-SEM) in R.
Results:
The findings reveal that information accessibility enables comprehension of healthcare data, which subsequently enhances perceived credibility and influences adoption behavior. At the same time, heuristic cues embedded in information design shape trust formation, while emotional responses play a non-trivial role in shaping system engagement. Collectively, the results suggest that user behavior in PR systems emerges from the interplay of cognitive, heuristic, and affective mechanisms rather than from data exposure alone.
Conclusions:
This study extends dual-process theorizing in information systems research by integrating affective responses into models of information processing and reconceptualizing healthcare data as an indirect, interpretation-dependent driver of behavior in public reporting systems.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.