Cross-sectional study finds divided professional willingness to recommend mental health chatbots in Finland, highlighting perceived risks and demand for assistive roles.
Although chatbots are increasingly used in mental health, Finnish professionals’ perceptions remain unknown. This cross-sectional study (n = 784) applied a modified UTAUT model to explore their perceptions of chatbots and their willingness to recommend them to clients or patients. Data were collected using non-probability sampling and analysed with confirmatory factor analysis, multinomial logistic regression, and descriptive statistics. Within the next five years, 51% of respondents were somewhat or very unlikely to recommend chatbots, whereas 49% were somewhat or very likely to do so. Perceived potential of chatbots was strongly associated with the recommendation intention (p < 0.001). Higher facilitating conditions (users’ skills, device availability; p = 0.003) and higher age increased recommendation willingness (B = 0.051, p = 0.004) with the age effect concentrating on the ‘somewhat likely’ category. Perceived risks statistically significantly hindered willingness to recommend a chatbot across all outcome categories (p = 0.010 to <0.001). Comprehensibility (72%) and professionalism (69%) were perceived as the most important chatbot features. Chatbots were seen as particularly suitable for assistive tasks such as sending reminders (77%) and instructing exercises (70%). Mental health professionals need training on chatbots’ benefits, risks, and underlying technologies. In the sensitive mental health context, chatbots’ roles should be clearly delimited, supporting their deployment in assistive, low-risk tasks.
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Nieminen et al. (2026) studied this question.
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