Comparative Efficacy of AI LLMs in Clinical Social Work: ChatGPT-4, Gemini, Copilot

TAŞKIRAN TEPE H., ASLANTÜRK H.

RESEARCH ON SOCIAL WORK PRACTICE, 2025 (SSCI) identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2025
  • Doi Number: 10.1177/10497315241313071
  • Journal Name: RESEARCH ON SOCIAL WORK PRACTICE
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, ASSIA, Child Development & Adolescent Studies, CINAHL, EBSCO Education Source, Education Abstracts, ERIC (Education Resources Information Center), Psycinfo, Public Affairs Index, Social services abstracts, Sociological abstracts, Violence & Abuse Abstracts
  • Anadolu University Affiliated: Yes

Abstract

Purpose This study examines the comparative efficacy of three AI large language models (LLMs)-ChatGPT-4, Gemini, and Microsoft Copilot-in clinical social work.Method By presenting scenarios of varying complexities, the study assessed their performance using the Ate & scedil;man Readability Index and a Likert-type accuracy scale.Results Results showed that Gemini had the highest accuracy, while Microsoft Copilot excelled in readability. Significant differences were found in accuracy scores (p = .003), although readability differences were not statistically significant (p = .054). No correlation was found between case complexity and either accuracy or readability.Discussion Despite the differences, none of the models fully met all accuracy standards, indicating areas for further improvement. The findings suggest that while LLMs offer promise in social work, they require refinement to better meet the field's needs.