1.Perceptions of generative artificial intelligence integration in clinical training among occupational therapy interns in Manila, Philippines: A qualitative study protocol.
Nikka Karla Santos ; Maria Ruby FARIÑAS ; Sean James Eire BEHAN ; Ryza Mikyla AGRAVIADOR ; Eladia Denise BUQUING ; Josiah Myron DIOSANTA ; Kristin Chloe EVANGELIO ; Ma. Dulce Regina SANTIAGO
Philippine Journal of Allied Health Sciences 2026;9(2):39-45
BACKGROUND
Generative artificial intelligence (GenAI) is increasingly integrated into healthcare, including occupational therapy (OT), with potential applications in its service delivery and clinical decision-making. While GenAI offers promising educational and clinical support, its generative nature introduces risks related to contextual accuracy, transparency, and ethical use, particularly within supervised clinical training settings where professional judgment is still developing. Empirical research examining GenAI integration in OT clinical training remains limited, especially within the Philippine context.
OBJECTIVEThis is a protocol for a study which aims to explore the perceptions of OT interns in Manila, Philippines, regarding GenAI integration in clinical training, including perceived benefits, challenges, and ethical considerations, guided by Rogers’ Diffusion of Innovations Theory
METHODSThis qualitative study protocol describes an exploratory design that will be used to gather rich and contextualized insights from 24 to 32 OT interns enrolled in universities in Manila with established institutional AI-use policies. Data will be collected through semi-structured online focus group discussions (FGD). Thematic analysis will be used with assistance from atlas.ti.
EXPECTED RESULTSThe study is expected to generate meaningful themes that describe the perceptions of OT interns regarding the integration of GenAI within supervised clinical training contexts. Results are expected to reflect how interns perceive the role of GenAI in supporting clinical decision-making, as well as its perceived challenges and ethical concerns related to institutional policies, data privacy, reliability, and variability in AI-generated outputs.
Human ; Therapeutics ; Universities ; Volition ; Philippines ; Clinical Decision-making ; Artificial Intelligence

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