Evidence map›Paper›PMID 41259713›Full record

ReviewJMIR AI2025

Exploring Primary Care Patients' Perspectives on Artificial Intelligence: Systematic Literature Review and Qualitative Meta-Synthesis.

Alisa Mundzic, Robin Bogdanffy, David Sundemo, Pär-Daniel Sundvall, Jonathan Widén, Peter Nymberg, Carl Wikberg, Anna Moberg, Ronny Gunnarsson, Artin Entezarjou

Abstract readReview
In one paragraph

Review in JMIR AI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Alisa MundzicGeneral Practice/Family Medicine, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Guldhedsgatan 5A, Gothenburg, 413 20, Sweden, 46 768969024.ORCID http://orcid.org/0009-0009-9164-4744
Robin BogdanffyGeneral Practice/Family Medicine, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Guldhedsgatan 5A, Gothenburg, 413 20, Sweden, 46 768969024.ORCID http://orcid.org/0009-0008-9628-2765
David SundemoGeneral Practice/Family Medicine, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Guldhedsgatan 5A, Gothenburg, 413 20, Sweden, 46 768969024.ORCID http://orcid.org/0000-0002-5871-1636
Pär-Daniel SundvallGeneral Practice/Family Medicine, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Guldhedsgatan 5A, Gothenburg, 413 20, Sweden, 46 768969024.ORCID http://orcid.org/0000-0001-9889-509X
Jonathan WidénResearch, Education, Development & Innovation, Primary Health Care, Region Vastra Gotaland, Gothenburg, Sweden.ORCID http://orcid.org/0009-0005-8584-0862
Peter NymbergCenter for Primary Health Care Research, Department of Clinical Sciences, Lund University, Malmö, Sweden.ORCID http://orcid.org/0000-0001-9901-0580
Carl WikbergGeneral Practice/Family Medicine, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Guldhedsgatan 5A, Gothenburg, 413 20, Sweden, 46 768969024.ORCID http://orcid.org/0000-0002-6494-5922
Anna MobergDepartment of Health, Medicine and Caring Sciences, Linkoping University, Linköping, Sweden.ORCID http://orcid.org/0000-0001-5431-8469
Ronny GunnarssonGeneral Practice/Family Medicine, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Guldhedsgatan 5A, Gothenburg, 413 20, Sweden, 46 768969024.ORCID http://orcid.org/0000-0001-9183-3072
Artin EntezarjouGeneral Practice/Family Medicine, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Guldhedsgatan 5A, Gothenburg, 413 20, Sweden, 46 768969024.ORCID http://orcid.org/0000-0002-7418-8750

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

artificial intelligencegenerative AIlarge language modelsmachine learningnatural language processingpatient perspectivesprimary health carequalitative meta-synthesissystematic review

Identifiers

PMID41259713
PMCPMC12629519

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.