Evidence map›Paper›PMID 41634082›Full record

ArticleScientific reports2026

Expectations and concerns of primary healthcare patients in rural areas and small towns in Poland regarding artificial intelligence.

Justyna Kęczkowska, Małgorzata Płaza, Gabriela Henrykowska

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Justyna KęczkowskaKielce University of Technology, Kielce, Poland.
Małgorzata PłazaKielce University of Technology, Kielce, Poland.
Gabriela HenrykowskaDepartment of Epidemiology and Public Health, Medical University of Lodz, ul. Żeligowskiego 7/9, 90-752, Lodz, Poland. gabriela.henrykowska@umed.lodz.pl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of artificial intelligence (AI) into healthcare presents transformative opportunities, but patient perspectives, particularly from digitally excluded populations, remain underexplored. This study aimed to analyze the awareness, acceptance and concerns regarding the use of AI in healthcare among primary care patients in rural and small-town regions of Poland. This is characteristic of the country, as over 60% of its population lives in such regions. It also sought to identify the demographic and psychosocial determinants of trust in AI. A cross-sectional survey was conducted using a paper questionnaire distributed to 545 adult patients in three primary care facilities in towns with populations below 20,000. Demographics, digital literacy, and attitudes towards AI were assessed. Statistical analyses included non-parametric tests and ordinal logistic regression. Most of the respondents expressed neutrality (43%) or a negative (31%) attitudes toward AI. Only 12.7% had direct experience with AI, and full trust in AI-assisted diagnoses was low (5.9%). Education was the strongest predictor of a positive AI attitude (P < 0.001); age was also significant (P = 0.04), while gender and place of residence were not. Most patients (86%) emphasized the importance of medical staff support.Patients in areas of low digital literacy approach AI with cautious optimism, valuing its potential but requiring human oversight. To foster an equitable adoption of AI, communication and education efforts must address patient concerns and expectations.

Indexed as

Artificial IntelligenceHealth Knowledge, Attitudes, PracticePrimary Health CareRural PopulationAdolescentAdultAgedAged, 80 and overCross-Sectional StudiesFemaleHumansMaleMiddle AgedPolandSurveys and QuestionnairesYoung Adult

Identifiers

PMID41634082
PMCPMC12921287

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.