Perceptions of AI-CBT: Trust and Barriers in Chinese Postgrads
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866908811128733696 |
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| author | Sio, Chan-in Mann, Alex Fan, Lingxi Cheung, Andrew Lee, Lik-hang |
| author_facet | Sio, Chan-in Mann, Alex Fan, Lingxi Cheung, Andrew Lee, Lik-hang |
| contents | The mental well-being of graduate students is an increasing concern, yet the adoption of scalable support remains uneven. Artificial intelligence-powered cognitive behavioral therapy chatbots (AI-CBT) offer low barrier help, but little is known about how Chinese postgraduates perceive and use them. This qualitative study explored perceptions and experiences of AI-CBT chatbots among ten Chinese graduate students recruited through social media. Semi-structured Zoom interviews were conducted and analyzed using reflexive thematic analysis, with the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB) as sensitizing frameworks. The findings indicate a cautious openness to AI-CBT chatbots: perceived usefulness and 24/7 access supported favorable attitudes, while data privacy, emotional safety, and uncertainty about `fit' for complex problems restricted the intention to use. Social norms (e.g., stigma and peer views) and perceived control (digital literacy, language quality) further shaped adoption. The study offers context-specific information to guide the culturally sensitive design, communication, and deployment of AI mental well-being tools for student populations in China and outlines the design implications around transparency, safeguards, and graduated care pathways. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_03852 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Perceptions of AI-CBT: Trust and Barriers in Chinese Postgrads Sio, Chan-in Mann, Alex Fan, Lingxi Cheung, Andrew Lee, Lik-hang Human-Computer Interaction Artificial Intelligence Computers and Society The mental well-being of graduate students is an increasing concern, yet the adoption of scalable support remains uneven. Artificial intelligence-powered cognitive behavioral therapy chatbots (AI-CBT) offer low barrier help, but little is known about how Chinese postgraduates perceive and use them. This qualitative study explored perceptions and experiences of AI-CBT chatbots among ten Chinese graduate students recruited through social media. Semi-structured Zoom interviews were conducted and analyzed using reflexive thematic analysis, with the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB) as sensitizing frameworks. The findings indicate a cautious openness to AI-CBT chatbots: perceived usefulness and 24/7 access supported favorable attitudes, while data privacy, emotional safety, and uncertainty about `fit' for complex problems restricted the intention to use. Social norms (e.g., stigma and peer views) and perceived control (digital literacy, language quality) further shaped adoption. The study offers context-specific information to guide the culturally sensitive design, communication, and deployment of AI mental well-being tools for student populations in China and outlines the design implications around transparency, safeguards, and graduated care pathways. |
| title | Perceptions of AI-CBT: Trust and Barriers in Chinese Postgrads |
| topic | Human-Computer Interaction Artificial Intelligence Computers and Society |
| url | https://arxiv.org/abs/2602.03852 |