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Exploring the relationship between textual reviews and ratings of patients in online healthcare communities: The psychological attribute perspective

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  • Chen, Qin
  • Jin, Jiahua
  • Yan, Xiangbin

Abstract

Textual reviews and ratings in online healthcare communities (OHCs) are vital for reducing information asymmetry between physicians and patients, as well as informing patients' decision-making. However, the consistency between these two review formats remains insufficiently theorized and empirically examined. Drawing on cognitive-affective model (CAM) and attribute-based model, this study investigates how psychological attributes—manifested through patients' writing styles and vocabulary—are associated with their rating behaviors. Focusing on six psychological constructs (positive emotion, negative emotion, negation, discrepancy, certainty, and uncertainty), we explore: (1) their associations with patients' ratings; (2) differences in their relationships with outcome quality and process quality ratings; and (3) the moderating role of disease severity. Utilizing ordered logit regression models and path comparison analysis, our findings reveal that discrepancy and certainty are significantly and linearly associated with ratings, with these relationships negatively moderated by disease severity. In contrast, positive emotion exhibits a non-linear association with ratings. Moreover, psychological attributes show stronger associations with process quality ratings than with outcome quality ratings. These findings advance the understanding of feedback mechanisms in OHCs by uncovering the nuanced role of psychological attributes in shaping review consistency, and also offers actionable insights for e-Health platforms.

Suggested Citation

  • Chen, Qin & Jin, Jiahua & Yan, Xiangbin, 2026. "Exploring the relationship between textual reviews and ratings of patients in online healthcare communities: The psychological attribute perspective," Technological Forecasting and Social Change, Elsevier, vol. 223(C).
  • Handle: RePEc:eee:tefoso:v:223:y:2026:i:c:s0040162525004810
    DOI: 10.1016/j.techfore.2025.124450
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