ArticleFrontiers in public health2026
The anatomy of AI implementation skepticism in Polish healthcare: an explanatory mixed-methods analysis of psychographic barriers among healthcare professionals.
Article in Frontiers in public health, 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Healthcare organizations struggle to scale AI, often attributing failures to a skills gap in the workforce. However, this mixed-methods study of Polish healthcare professionals reveals that professional roles, whether physician or executive, do not predict AI resistance well. Instead, resistance clusters into four psychographic profiles: Skeptics, Cost-Focused, Pragmatists, and Optimists. As its primary novel contribution, this research reveals that what is commonly captured in survey instruments as a "lack of expertise" actually masks distinct organizational defense mechanisms, including institutional exhaustion, fears of legal liability, and operational budget constraints. By demonstrating that stated competency gaps are proxies for systemic distrust rather than simple educational deficits, this study moves beyond traditional barrier counting to challenge demographic-based technology implementation. For healthcare leaders and researchers, the implication is clear: successful AI adoption requires abandoning generic, role-based training in favor of targeted change management that addresses the underlying psychological and structural barriers driving technological resistance.
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.