Lurking or active? The influence of user participation behavior in online mental health communities on the choice and evaluation of doctors

Abstract

Background: Web-based psychological counseling sites have become an important source of health information and expert assistance. Although many studies have suggested the feasibility and effectiveness of online consultation, there is an insufficient understanding of the influence of the distinction of users' participation behaviors online on health behavior decision-making.Objective: This study aimed to investigate whether and how the differences in the online participation behaviors of users affect their doctor selection and evaluation characteristics.Methods: First, we collected information from 7,781 paid consultation clients from a professional mental health service platform in China. Effective indicators and variables were formed through data cleaning and classification. Next, we used a mixed methods research approach that included qualitative text analysis (topic and sentiment) and quantitative statistical analysis (ANOVA).Results: The ANOVA results show that differences in online participation behaviors (diving, searching and socializing) have a significant impact on doctor selection based on consultation price (F7,780=6.05; P = 0.00), online service volume (F7,780=4.76; P = 0.00), online reputation (F7,780=4.30; P = 0.01) and online answers (F7,780=5.76; P = 0.00). When evaluating doctors, the frequency of reviews (F7,780=69.62; P = 0.00) and the average length of the text (F7,780=15.33; P = 0.00) were significantly different among users. Two of the three topics, namely, service attitude (F7,780=28.63; P = 0.00) and self-expression (F7,780=40.83; P = 0.00), had significant effects. In addition, our results show that differences in participating behaviors have a significant impact on both the positive (F7,780=7.30; P = 0.00) and negative (F7,780=9.44; P = 0.00) emotions involved in evaluating doctors.Conclusions: Our findings provide preliminary insights for establishing the relationship between users' online information behavior and health decision-making. Further research should be conducted to verify the validity of the results and help apply them to the design of personalized customized services for the users in an online health community.