Evidence map›Paper›PMID 42785740›Full record

ArticleJournal of medical Internet research2026

AI in Neurological Health Care: Qualitative Study of Patient and Public Perceptions.

Tina Bedenik, Orna Fennelly, Kathleen Bennett

Abstract read
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Article in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Tina BedenikData Science Centre, School of Population Health, RCSI University of Medicine and Health Sciences, Dublin, Leinster, Ireland.ORCID https://orcid.org/0000-0002-5865-0263
Orna FennellyDigital Health Department, Children's Health Ireland, Dublin, Leinster, Ireland.ORCID https://orcid.org/0000-0002-8692-900X
Kathleen BennettData Science Centre, School of Population Health, RCSI University of Medicine and Health Sciences, Dublin, Leinster, Ireland.ORCID https://orcid.org/0000-0002-2861-7665

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGlobally, health systems face increasing challenges due to improved life expectancy, rising levels of disease, greater expectations for health care, and growing expenditure. AI-based technologies are increasingly used to support clinical decision-making and contribute to effective delivery of care. AI has significant potential in terms of diagnostics and treatment for preventive and personalized medicine, including progressive, nonprogressive, or neurodivergent conditions affecting the brain, spinal cord, and nerves. Although AI has been extensively applied to several areas of health, its application to neurological conditions remains limited.

objectiveThis qualitative study explores the perspectives of patients and the public impacted by neurological conditions on the use of AI in health care in Ireland. It focused on the benefits and concerns regarding AI implementation to inform effective and safe use of AI in clinical decision-making.

methodsWe conducted a qualitative cross-sectional study using focus groups of patients and the public (family members). A combination of purposive and snowball sampling was used in participant recruitment. The sample consisted of 15 participants involved in 2 focus groups, most commonly with conditions including early-onset Parkinson disease, epilepsy, and multiple sclerosis. Qualitative data were transcribed, and thematic data analysis was undertaken using NVivo (version 12; Lumivero) software.

resultsThe main benefits of AI in clinical decision-making included improved diagnostics and treatment for neurological health care, increased patient involvement in care and decision-making, and resource efficiency. Participants believed that AI-powered systems could assist with information collation and decision-making, and AI could be an aid in simple repetitive tasks, allowing clinicians more time for clinical work. The concerns included preparedness of the national health data ecosystem, harm resulting from AI application, and overreliance on AI resulting in deskilling. Participants were generally supportive of AI in clinical decision-making; however, their support was conditional on a stringent regulatory framework and human supervision over AI use.

conclusionsNeurological conditions have a significant impact on the lives of patients and their families, with large resource implications for the health care system. AI has the potential to contribute to significant benefits, such as improved diagnostics, resource efficiency, novel insights, and improved provision of health care. However, the health care system needs to focus on the readiness and availability of health data. This study highlights the importance of preparing health systems for the expansion of AI systems, including supporting clinicians and patients in the appropriate and safe implementation of AI in health care.

Indexed as

Artificial IntelligenceNervous System DiseasesAdultAgedCross-Sectional StudiesFemaleFocus GroupsHumansIrelandMaleMiddle AgedQualitative ResearchAIartificial intelligenceclinical decision-makinghealth dataIrelandqualitative research

Identifiers

PMID42785740

What OpenQuestion holds

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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 OpenQuestion graph.