INTEGRATING ARTIFICIAL INTELLIGENCE IN CLINICAL PSYCHOLOGY: ENHANCING DIAGNOSTIC ACCURACY AND TREATMENT PERSONALIZATION

Abstract

Introduction: Clinical psychologists reported that AI seems to have the promising capacity to improve diagnostic processes and individualized approaches to therapies. The purpose of this research is to explore mental health practitioners’ views on how AI can enhance diagnostic accuracy and the ways different clients could benefit from AI applications.

Objectives: The research objective of the investigation will therefore centre around and seek to uncover the following: The current awareness that mental health professionals have about AI The extent to which these mental health professionals consider AI to be useful The important factors that are likely to inform its usage among these mental health professionals.

Methods: A cross-sectional quantitative survey was administered to fifty psychologists, fifty psychiatrists, one hundred AI researchers, and fifty counsellors. A structured questionnaire was used to assess the awareness of the participants regarding AI, the role they perceived this technology in the diagnosing process, and the challenges likely to be encountered in implementing this technology. For data analysis, various measures were used such as descriptive analysis, correlation analysis as well as reliability analysis using Cronbach’s Alpha coefficients. With factor analysis, the basic components or the underlying factors in the perceptions of AI systems were established.

Results: The results highlighted variability in the attitudes to AI among the participants and low levels of relationship between knowledge about AI and thoughts as to its efficiency. From the numerical data analyzed, it was possible to determine that the Cronbach’s Alpha score stands at 0. A raw scale reliability value of 067 meant low internal consistency of the survey items. Through using factor analysis, two main factors were determined, which may be characterized by varying levels of trust and interest towards AI.

Conclusion: Despite the potential benefits of utilizing AI as a tool in the accurate diagnoses of psychological disorders and the personalization of treatment, its application in clinical psychology is limited by issues to do with ethicality, trust, and feasibility. These barriers and therefore, the conscious effort to develop and increase patients’ understanding of Artificial Intelligence integration will be critical in the systematic incorporation of such an innovation into the mental health care systems.