Exploring User Satisfaction in Online Mental Health Platform: An Integrated Framework Analysis of Trust, Quality, and Value Perceptions

Abstract

Background: The rapid digital transformation of mental health service has led to the emergence of online psychological platforms, presenting new challenges in understanding user satisfaction and service quality. Despite the growing importance of these platforms, there is limited research on the factors that influence user satisfaction in this unique context.

Objective: This study aims to develop and validate an integrated framework for understanding user satisfaction in online mental health platforms by (1) identifying perceived quality as the primary driver of satisfaction, (2) revealing the crucial role of trust and cost considerations in online psychological services, and (3) demonstrating how brand image and user expectations function as important antecedents in this emerging field.

Methods:A mixed-method approach was employed, combining expert interviews (N=10) and a user survey (N=629) of China's largest online mental health platform. Structural equation modeling (SEM) and analytic hierarchy process (AHP) were utilized to test the theoretical framework and evaluate the relative importance of factors.

Results:The findings reveal that perceived quality is the strongest predictor of user satisfaction (β=0.525, p<0.001), with trust (β=0.285) and cost structure (β=0.203) emerging as the most critical sub-dimensions. While brand image and user expectations showed no direct significant effect on satisfaction, they demonstrated important indirect effects through perceived quality. Notably, brand awareness (weight=0.866) and effect expectations (weight=0.771) carried substantial weights in the overall evaluation framework.

Conclusion: The findings suggest that while brand image and user expectations may not directly influence satisfaction, they serve as important foundational elements in shaping users' quality perceptions.