AUTHOR=Naji Gehad Mohammed Ahmed , Yuan Foo , Azzura Nurul , Danish Fajer , Ateeq Ali , Ibrahim Siddig Balal , Hakimi Halimaton , Abdollah Aziah Binti , Iskandar Yulita Hanum P 

TITLE=Factors influencing perceived benefits and behavioral intention to use mental health chatbots among professional employees: an empirical study

JOURNAL=Frontiers in Digital Health

VOLUME=Volume 7 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2025.1606273

DOI=10.3389/fdgth.2025.1606273

ISSN=2673-253X

ABSTRACT=PurposeThis study explores factors influencing Malaysian professionals' intentions to use mental health chatbots by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Theory of Planned Behaviour (TPB). It examines UTAUT factors' direct effects on usage intention and the mediating role of perceived benefits, along with the moderating influence of attitudes towards chatbots.Research design & methodologyThe study collects data from 351 professional employees in Malaysia using an online survey and analyses it using structural equation modelling (SEM).FindingsThe study outcomes indicate that UTAUT factors significantly influence perceived benefits (β = 0.793, p < 0.001; R2 = 0.601). However, perceived benefits did not significantly predict behavioural intention (β = 0.107, p = 0.464; R2 = 0.449). Attitudes towards chatbots showed only a weak moderating effect on the UTAUT–perceived benefit relationship (β = 0.009, p = 0.094), while other hypothesised moderating effects were not supported. These findings suggest a more complex interplay of factors influencing the adoption of mental health chatbots in professional settings than previously assumed.ConclusionThese findings challenge the assumption that perceived benefits alone drive adoption. They suggest a more complex interplay of factors influencing behavioural intention, indicating that trust, privacy, and credibility may play more critical roles in shaping adoption decisions.ImplicationsThe study provides valuable insights for developers and implementers of mental health technologies. While UTAUT factors are crucial in shaping perceived benefits, the lack of a direct link to behavioural intention highlights the need to explore additional psychological and contextual factors. Future research should consider longitudinal designs and probabilistic sampling to enhance generalisability and causal inference.