According to the PLOS ONE study by Pokharel et al. (2026), primary care physicians' views on large language models (LLMs) are understudied and important for safe clinical adoption. The primary keyword "physician perceptions of LLMs" frames this post for researchers and research operations teams who need practical methods to collect, transcribe, code, and synthesize interview data. According to the PLOS ONE protocol (Pokharel et al., 2026), the authors propose semi-structured interviews and a combined deductive-inductive thematic analysis driven by a new Technology Adoption Behavior (TAB) framework, and they plan to recruit physicians in British Columbia between August 1, 2025 and January 31, 2026. This post explains the study's methods, exact numerical timelines and thresholds, and how AI-enabled qualitative research tools can accelerate trustworthy synthesis while preserving ethical safeguards.
Topics
- physician perceptions of LLMs
- qualitative study LLM adoption
- LLM adoption in primary care
- AI-enabled qualitative research
- physician attitudes to AI
Keep reading
- Commentary on NewsPhysician Perceptions of LLMs: Adoption in Primary CarePractical explainer of physician perceptions of LLMs from a PLOS One protocol (7 Aug 2026). Learn methods, timelines, and how AI-enabled qualitative research accelerates insight.
- Commentary on NewsStudy Protocol: Physician Perceptions of LLMsReview of a PLOS One protocol on primary care physician perceptions of LLMs, with dates, sample metrics, and AI-enabled qualitative research guidance.
- Commentary on NewsPhysician Perceptions of LLMs: Qualitative AnalysisWhat primary care physicians think about LLM adoption and how AI-enabled qualitative research can speed insight. Learn methodological takeaways and next steps.