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Development and content validity of an AI-assisted simulation scenario for orthotic fabrication in occupational
Duygu Mine Alataş1, Çiğdem Öksüz2, Nilgün Bek3
1Department of Occupational Therapy, Faculty of Health Sciences, Lokman Hekim University, Söğütözü Mh. 2185 Cd. No: 20/J, Çankaya, Ankara, 06510, Türkiye. duygu.alatas@lokmanhekim.edu.tr.
Background:
Developing high-fidelity simulation scenarios is a time-consuming process, and validated resources for complex psychomotor skills such as orthotic fabrication are scarce. This study aimed to examine the content validity index (CVI) of a simulation scenario for anticlaw orthosis fabrication developed with the support of artificial intelligence (AI).
Methods:
A mixed-methods methodological study was conducted in an academic education program in Türkiye. Six subject matter experts with professional experience in hand rehabilitation, orthotics, and simulation-based education participated. A simulation scenario package was structured by the researchers, while the specific scenario flow was generated using a seven-step process supported by the generative AI tool ChatGPT. Expert reviewers evaluated five components, specifically objectives, background, prebriefing, scenario flow, and debriefing, using a 4-point Likert scale and open-ended questions. The item-level content validity index (I-CVI) and scale level content validity index (S-CVI) were calculated.
Results:
The simulation scenario package was evaluated across five core components. The scenario achieved an I-CVI and S-CVI of 1.00. This indicated that all expert reviewers rated the scenario components as content valid by assigning a score of 3 or 4. Qualitative feedback highlighted the need for refinements in clinical fidelity, specific material choices, and safety warnings regarding heat and sharp tools.
Conclusions:
The study provided educators with a comprehensive, ready-to-implement simulation scenario package, including validated learning objectives, prebriefing instructions, the full scenario script developed via AI-assisted methodology, and debriefing guides, that could be adopted to enhance orthotic training in rehabilitation curricula.