Actionable Insights: LLM Adoption in Primary Care

According to the PLOS ONE protocol by Pokharel et al. (2026), this planned qualitative study will use semi-structured interviews and the Technology Adoption Behavior (TAB) framework to examine how primary care physicians perceive LLM adoption in clinical practice (PLOS ONE).

• The study protocol was published on August 7, 2026 and states, in the authors' words, "This qualitative study aims to employ a descriptive qualitative design to explore how primary care physicians perceive the adoption of LLMs in the context of their clinical practice." (Pokharel et al., 2026).
• Pokharel et al. (2026) plan to recruit physicians in British Columbia with purposive sampling and expect recruitment and data collection to run from August 1, 2025 to January 31, 2026, a six-month window described in the protocol (PLOS ONE).
• The protocol highlights a national access trend used as context: the number of Canadians without a family doctor rose from about 4.5 million in 2019 to about 6.5 million in 2023, a statistic cited in the study to justify focusing on primary care (Pokharel et al., 2026).

Answer: The PLOS ONE protocol describes a descriptive qualitative study using purposive sampling, semi-structured interviews, and thematic analysis guided by the TAB framework to interrogate physician perceptions of LLMs.

According to Pokharel et al. (2026) in PLOS ONE, the research team will purposively sample family physicians in British Columbia across experience and self-reported LLM use categories (frequent: 50+ uses, occasional: 5–50 uses, and nearly none: <5 uses) to ensure varied perspectives (PLOS ONE).

According to Pokharel et al. (2026) in PLOS ONE, interviews will be recorded, transcribed verbatim, deidentified, and analyzed using a combined deductive and inductive thematic coding approach, with reflexive memos and a multidisciplinary team guiding interpretation.

The protocol notes ethical approval from the UBC Behavioral Research Ethics Board (H25-01658), and the authors report the manuscript was received July 18, 2025 and accepted July 22, 2026 before publication on August 7, 2026 (PLOS ONE).

Answer: The PLOS ONE protocol signals that theory-grounded, transparent qualitative work is needed now to shape safe LLM deployment in primary care.

According to Pokharel et al. (2026) in PLOS ONE, using the TAB framework ties user perceptions, task fit, and environment together and can help transform interview findings into policy-relevant recommendations by showing which perceived barriers affect perceived usefulness and ease of use.

According to Pokharel et al. (2026) in PLOS ONE, purposive sampling across levels of prior LLM use strengthens analytic contrast and helps researchers differentiate concerns tied to unfamiliarity from those tied to observed harms or benefits.

Primary care leaders should note that the protocol connects system pressures (for example the rise from 4.5 million in 2019 to 6.5 million in 2023 of patients without a family doctor) to the potential role of LLMs in administrative relief, but the authors caution that benefits must be weighed against bias, hallucination, and workflow disruption (Pokharel et al., 2026).

Answer: The PLOS ONE protocol by Pokharel et al. (2026) provides a transparent, theory-driven plan to capture how primary care physicians perceive LLM adoption, and AI-enabled qualitative tools can make that plan faster and more auditable (PLOS ONE).

Researchers conducting similar studies should preregister deductive codebooks, use purposive sampling to contrast experience levels, and preserve reflexive memos as the protocol recommends to support nuanced interpretation (Pokharel et al., 2026).

If you are running interviews about clinician experiences with AI, a platform that combines accurate transcription, hybrid coding, and cross-segment visualization can cut synthesis time and improve reproducibility; see Evidano for those capabilities (Evidano Features).

Next step: pilot your interview guide, build a TAB-aligned codebook, and use a reproducible pipeline for transcription and deidentification before analysis. Try our platform to streamline that work: Try Evidano for free.