Personality, Attachment, and Help-Seeking as Predictors of Attitudes Toward AI in Psychotherapy

Sadaf  Hajghaffari; Mahnaz Majidi

Authors

Sadaf Hajghaffari Department of Clinical Psychology, SR.C., Islamic Azad University, Tehran, Iran Author https://orcid.org/0009-0002-0164-4134
Mahnaz Majidi Department of Clinical Psychology, SR.C., Islamic Azad University, Tehran, Iran Corresponding Author https://orcid.org/0000-0001-7498-571X

Keywords:

Artificial Intelligence, Help-Seeking Behavior, Object Attachment, Patient Acceptance of Health Care, Personality Disorders, Psychotherapy

Abstract

Objective: The present study aimed to predict attitudes toward the use of artificial intelligence in psychological treatment based on maladaptive personality traits and attachment styles, with the mediating role of attitudes toward professional psychological help-seeking.

Methods and Materials: This descriptive-correlational study employed a path modeling approach. The statistical population consisted of students from the Islamic Azad University, Science and Research Branch, aged 18 to 35, selected through convenience sampling. The research instruments included the Attitudes toward the Use of Artificial Intelligence in Therapy Scale, attachment styles and the short form of the Personality Inventory for DSM-5–Brief Form (PID-5-BF), and the Professional Psychological Help-Seeking Attitude Scale.

Findings: The results of the structural model analysis indicated that certain personality traits, such as negative affect, were significantly associated with attitudes toward the use of artificial intelligence. Additionally, complex and significant relationships between attachment styles and attitudes toward AI in therapy were revealed. Moreover, the mediating role of attitudes toward professional help-seeking revealed an interesting pattern in explaining these relationships.

Conclusion: The findings suggested that individuals’ psychological characteristics played a crucial role in shaping their attitudes toward emerging therapeutic technologies. These insights can guide future research aimed at designing interventions that are better suited to individuals’ psychological needs.

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