Evidence map›Paper›PMID 41958846›Full record

ArticleDigital health

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

Hua Yang, Wanting Li

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hua YangDepartment of Management Science and Engineering, School of Business and Management, Jilin University, Changchun, P. R. China.ORCID https://orcid.org/0000-0001-9571-5583
Wanting LiDepartment of Management Science and Engineering, School of Business and Management, Jilin University, Changchun, P. R. China.ORCID https://orcid.org/0009-0001-8410-8806

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: 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. Methods: 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. Results: 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. Conclusion: 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.

Indexed as

Kano-IPA modelLDA topic modelonline mental health communities (OMHC)service qualityuser comments

Identifiers

PMID41958846
PMCPMC13058207

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.