The quality traits of artificial intelligence operations in predicting mental healthcare professionals’ perceptions: A case study in the psychotherapy division

As advancements in healthcare technologies continue to emerge, the integration of AI-Technology has brought about significant transformations in various healthcare sectors. While substantial advancements have been made in applying AI to enhance physical health, its implementation in the field of mental health is still in its early stages. This descriptive study aims to address this gap by exploring the perspectives of mental health professionals (MHPs) on the acceptance and utilization of AI technology. Unified Theory of Acceptance and Use of Technology (UTAUT) was utilized to assess MHPs’ attitudes and beliefs towards AI implementation in psychotherapeutic practices. The sample was compromised of 349 MHPs. The findings reveal the task characteristic (TC) domain as the most influential domain, followed by Performance expectancy (PE), Behavioural intentions (BI), Personal innovativeness in IT (PT), Social influence (SI), Effort expectancy (EE), Perceived substitution crisis (PSC), Technology characteristic (TECH), and Initial trust (IT). The study also identifies statistically significant differences in AI usage based on gender variable, with females demonstrating a higher level of AI usage in comparison to males. Furthermore, the study highlights diverse applications of AI in the field of mental health, including AI-assisted assessments (AAA), chatbots for psychotherapy support (CPS), and data analytics for personalized treatment recommendations (DAPTR). By incorporating mental healthcare professionals’ (MHPs) perspectives, this research significantly contributes to a comprehensive understanding of the acceptance and utilization of AI technology in psychotherapy. The findings offer valuable insights into MHPs’ perceptions, concerns, and perceived advantages associated with integrating AI technology within clinical settings in the field of mental health.