Inteligencia artificial en atención primaria: efectos y controversias sociales. Revisión sistemática de la bibliografía

AIM: This article presents a systematic review of research on the social effects and controversies surrounding artificial intelligence (AI) in Primary Care (PC). DESIGN: Systematic review conducted in accordance with the PRISMA 2020 guidelines. DATA SOURCES: A search was performed in the Scopus and Web of Science databases using keywords and disciplinary filters. STUDY SELECTION: A total of 703 publications were identified, of which 63 were ultimately included. Publications from 2015 to 2025 were selected if they addressed the social effects of AI in PC and employed qualitative, quantitative, mixed-methods approaches, or conceptual contributions. Clinical studies were excluded. DATA EXTRACTION: An inductive (non-automated) thematic analysis of the abstracts was conducted for all included articles to identify primary and secondary themes. Full-text readings were subsequently carried out to enrich the analysis. RESULTS: Ten themes were identified: (1) professionals' perceptions, perspectives, and attitudes; (2) patients' perceptions, perspectives, and attitudes; (3) future imaginaries; (4) ethics; (5) physician-patient relationship; (6) impact on management; (7) policy and governance; (8) bias and equity; (9) user experience with prototypes; and (10) job precarity. CONCLUSIONS: There is a considerable gap between studies focusing on perceptions and potentialities and empirical studies examining the social effects of AI in PC. Moreover, most analyses are based on prototype studies that have not been routinely implemented in PC settings.