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Are chatbots acceptable in mental health promotion and care? A cross-sectional study of mental healthcare professionals

Research output: Contribution to journalArticlepeer-review

Abstract

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 analyzed 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 ‘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.
Original languageEnglish
Pages (from-to)1-59
Number of pages59
JournalBehaviour and Information Technology
Early online date27 Aug 2026
DOIs
Publication statusPublished online - 27 Aug 2026

Bibliographical note

© 2026 The Author(s).

Funding

The first author has received personal working funds from The Finnish Cultural Foundation, North Savo Regional Fund.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Digital mental health
  • Technology adoption
  • mental health chatbots
  • Healthcare professionals
  • UTAUT framework

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