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Causal Relationships Between the Use of AI, Therapeutic Alliance, and Job Engagement Among Psychological Service Practitioners

Year: 2024

Type: article

Abstract: Despite the significant increase in studies on AI applications in many aspects of life, its applications in mental health services still require further studies. This study aimed to test a proposed structural model of the relationships between AI use, therapeutic alliance, and job engagement by PLS-SEM. The descriptive method was applied. The sample consisted of (382) mental health service providers in Saudi Arabia, including 178 men and 204 women between 25 and 50 (36.32 ± 6.43) years old. The Artificial Intelligence Questionnaire, the Therapeutic Alliance Scale, and the Job Engagement Scale were applied in this study. The results showed the structural model’s predictability for using AI and the therapeutic alliance in predicting job engagement and explaining the causal relationships between them compared to the indicator average and linear models. The study also found a strong positive overall statistically significant effect (p < 0.05) of the use of AI on therapeutic alliance (0.941) and job engagement (0.930) and a positive overall average statistically significant effect (p < 0.05) of the therapeutic alliance on job engagement (0.694). These findings indicated the importance of integrating AI applications and therapeutic alliance skills into training and professional development plans.

Source: Behavioral Sciences

DOI: 10.3390/bs15010021

Authors: Boshra A. Arnout, Sami M. Alshehri

Institutions: Zagazig University, King Khalid University

Language: English

Topic: Psychotherapy Techniques and Applications

Subfield: Clinical Psychology

Field: Psychology

Domain: Social Sciences

SDGs: Good health and well-being, Decent work and economic growth

Open Access status: gold

Estimated APC paid: $2,501