ArticleFrontiers in medicine2026
A qualitative thematic comparative analysis of independent and AI-supported clinical reflections among medical interns.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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3 authors.
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Abstract
Background: Reflection is fundamental to medical education, supporting clinical reasoning, professional identity formation, and lifelong learning. Although generative artificial intelligence (AI) chatbots have emerged as tools to facilitate reflection, little is known about how AI-supported reflection differs from independent reflective writing. This study compared the characteristics and educational contributions of independent reflective writing and AI-supported reflection among medical interns. Methods: A comparative qualitative quasi-experimental study was conducted with medical interns during an emergency medicine rotation. The control group was instructed to perform reflective writing independently, while the intervention group was tasked to use AI-supported reflections using a purpose-built chatbot to complete reflective writing. Data were analyzed using qualitative content analysis and compared in terms of themes, reflective depth, clinical reasoning, emotional awareness, and professional learning. Results: Twenty-one interns completed independent reflective writing, while eighteen engaged in AI-supported reflection using a chatbot. Although both approaches supported reflective learning, they facilitated distinct dimensions of the reflective process. Independent reflective writing was characterized by greater autonomous meaning-making, critical reflection, ethical reasoning, and systems-level thinking. In contrast, AI-supported reflection was characterized by greater emotional articulation, structured reflective dialogue, and future learning planning, but showed more limited exploration of contextual, ethical, and systems-level issues. Participants' comments embedded within the chatbot interactions suggested that some found the interaction supportive, while repetitive prompting and limited critical exploration emerged as limitations. Conclusions: Independent reflective writing and AI-supported reflections represent complementary rather than interchangeable educational approaches. While independent reflective writing fosters deeper critical reflection, AI primarily functions as a reflective scaffold that supports emotional engagement and structures reflective learning. Integrating AI-assisted reflections with independent writing and faculty-guided debriefing may optimize reflective learning in medical education.
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