# Research on the influencing factors and pathways of user health information disclosure behavior on medical and health platforms: based on PLS-SEM, NCA, and fsQCA analysis

## TL;DR

This study explores what drives users to share health information on online platforms and identifies key factors and pathways influencing this behavior.

## Contribution

The study integrates TAM, TPB, and KAP frameworks and identifies five distinct pathways to high-level health information disclosure behavior.

## Key findings

- Perceived ease of use and usefulness significantly influence users' willingness to disclose health information.
- Perceived trustworthiness and behavioral control enhance the effects of attitudes on disclosure behavior.
- Five distinct pathways to high-level information disclosure behavior were identified through configuration analysis.

## Abstract

With the rapid development of medical and health platforms, user health information disclosure behavior has become increasingly critical to the sustainable operation and effective dissemination of health information online. Given this context, understanding the underlying influencing factors and behavioral pathways is of great significance for promoting health information exchange and enhancing platform engagement. To this end, this study integrates the Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), and Knowledge-Attitude-Practice (KAP) framework to construct a comprehensive model of health information disclosure behavior. Data were collected from 824 users through online questionnaires and analyzed using partial least squares structural equation modeling (PLS-SEM), complemented by fuzzy set qualitative comparative analysis (fsQCA) and necessity analysis (NCA). The results reveal that perceived ease of use and perceived usefulness significantly and positively influence users' attitudes and willingness to disclose, while perceived trustworthiness and perceived behavioral control further enhance these effects. Moreover, both disclosure willingness and perceived behavioral control directly drive actual disclosure behavior. Through systematic configuration analysis, five distinct pathways to high-level information disclosure behavior are identified. These findings provide new theoretical insights into the mechanisms of user disclosure intention and offer practical implications for the sustainable development of digital health platforms.