Service quality optimization of online mental health communities: A KANO-IPA model approach

As an important extension of mental health services, online mental health communities (OMHC) have become vital to access psychological support, share experiences and seek professional help. To enhance OMHC user satisfaction and promote the sustainable development of the industry, this study investigated the key elements of service quality within OMHCs and develops optimization strategies to inform practice.

This study collected user comments from the "One Psychology" online community. Based on this data, Latent Dirichlet Allocation (LDA) topic modeling was conducted to establish a framework of service quality elements. Furthermore, the Kano- Importance Performance Analysis (Kano-IPA) model is employed for the classification and priority evaluation of these elements.

This research proposes a framework for service quality in OMHCs by identifying its core elements. The findings reveal that users place high expectations on attractive quality elements such as content diversity and personalization, while emphasizing one-dimensional quality elements including privacy security and interactivity. Additionally, professionalism, effectiveness and system stability are identified as must-be quality elements. The priority sequence for service quality optimization is effectiveness, responsiveness, peer support, interactivity, stability, professionalism and simplicity.

To optimize the service quality of OMHCs, it is essential to respond to users' demands in a hierarchical manner: prioritize ensuring the stability and reliability of must-be elements, strive to enhance the performance of one-dimensional quality elements, and explore potential attractive elements in a timely manner to create pleasant surprises for users. Meanwhile, efforts should be made to strengthen technology empowerment, resource integration, responsive support and emotional mutual assistance. This study enriches the research related to the service quality of OMHCs and provides theoretical foundations and practical guidelines for service quality optimization.