Exploring Primary Care Patients' Perspectives on Artificial Intelligence : Systematic Literature Review and Qualitative Meta-Synthesis - Mundzic, Alisa; Bogdanffy, Robin; Sundemo, David; Sundvall, Pär-Daniel; Widén, Jonathan; Nymberg, Peter ; 0000-0001-9901-0580; Wikberg, Carl; Moberg, Anna; Gunnarsson, Ronny; Entezarjou, Artin ; 0000-0002-7418-8750 (JMIR AI, 2025)
BACKGROUND: The introduction of artificial intelligence (AI) in health care holds great promise, offering the potential to alleviate physicians' workloads and allocate more time for patient interactions. After the emergence of large language models (LLMs), interest in AI has surged in the health care sector, including within primary care. However, patients have expressed concerns about the ethical implications and use of AI in primary care. Understanding patients' perspectives on using AI in primary care is crucial for its effective integration. Despite this, few studies have addressed patients' perspectives on using AI in primary care. OBJECTIVE: This study aimed to synthesize qualitative research on primary care patients' perspectives regarding the use of AI, including LLMs, in primary care. METHODS: A qualitative systematic review, using thematic analysis, was performed in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Databases, including PubMed, Scopus, Web of Science, CINAHL, and PsycINFO, were searched from inception to February 5, 2024. Eligible studies (1) used a qualitative interview research design, (2) explored primary care patients' perspectives on the use of AI in primary care, (3) were written in English, and (4) were published in peer-reviewed scientific journals. Quantitative studies, gray literature, surveys, and studies lacking depth in qualitative analysis were excluded. The Critical Appraisal Skills Program (CASP) checklist was used for quality assessment. RESULTS: Of 1004 studies screened, 6 were included, comprising 170 patients aged 13-91 years from 3 countries. Three themes emerged: "The Relationship with and Actions of AI Systems," "Implementing AI responsibly," and "Training Physicians and Artificial Minds." Patients acknowledged AI's potential benefits but advocated for clinician oversight, safety frameworks, and the preservation of patient autonomy. CONCLUSIONS: This systematic review provides an understanding of patients' perspectives on AI in primary care. We identified heterogeneity in AI definitions across studies. Further research is needed on patients' perspectives across different countries. Notably, our synthesis revealed a significant research gap, as none of the included studies particularly explored patients' perspectives on LLMs, highlighting an important area for future research.
© Alisa Mundzic, Robin Bogdanffy, David Sundemo, Pär-Daniel Sundvall, Jonathan Widén, Peter Nymberg, Carl Wikberg, Anna Moberg, Ronny Gunnarsson, Artin Entezarjou. Originally published in JMIR AI (https://ai.jmir.org).