SynthesisAtencion primaria2026
Synthesis in Atencion primaria, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimThis article presents a systematic review of research on the social effects and controversies surrounding artificial intelligence (AI) in Primary Care (PC).
designSystematic 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.
resultsTen 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.
conclusionsThere 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.