Evidence map›Paper›PMID 40275241›Full record

ArticleBMC medical education2025

Generative artificial intelligence in physiotherapy education: great potential amidst challenges- a qualitative interview study.

Yvonne Lindbäck, Karin Schröder, Torkel Engström, Karin Valeskog, Sofi Sonesson

Abstract read
In one paragraph

Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

5 authors.

Yvonne LindbäckUnit of Physiotherapy, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden. yvonne.lindback@liu.se.ORCID http://orcid.org/0000-0002-1498-0498
Karin SchröderUnit of Physiotherapy, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0000-0002-5673-9133
Torkel EngströmUnit of Physiotherapy, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0009-0001-7856-6798
Karin ValeskogUnit of Physiotherapy, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0009-0008-8689-8582
Sofi SonessonUnit of Physiotherapy, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0000-0001-8670-5666

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenerative Artificial Intelligence (GAI) has significantly impacted education at all levels, including health professional education. Understanding students' experiences is essential to enhancing AI literacy, adapting education to GAI, and implementing GAI technology. Therefore, the aim was to explore physiotherapy students' experiences of and thoughts on GAI in their education, and its potential implications for their future careers in healthcare.

methodsQualitative descriptive design. Focus groups were conducted, using a semi-structured interview guide, at the Physiotherapy program at Linköping University, Sweden, from March to April 2024. The 15 students were organized into three focus groups, one for each education year. The data was analyzed using inductive content analysis.

resultsAn overarching theme "GAI-Great potential if navigating the challenges" emerged from three categories: 1) "Areas of GAI use in the learning process": Students viewed GAI as a tool for introduction and inspiration, assimilating course content and enhancing clinical reasoning and problem-solving; 2) "Optimizing GAI use in education": Students found GAI to be timesaving, tailored, and as a virtual study partner and teacher. They discussed the pros and cons of learning, concerns on permitted GAI usage, the need for a critical approach, and how individual experiences and interests influenced their interactions with GAI; 3) "Future with GAI in education and profession": Students believed future GAI would be more reliable, use subject-specific GAI models and enhance health care delivery, but also pose risks related to profit motives and knowledge gaps.

conclusionPhysiotherapy students found GAI beneficial for learning and clinical reasoning but expressed concerns about its impact on learning quality. They emphasized the importance of a critical approach when using GAI and the need for organizational support, including supporting permitted GAI use. Students believed that future advanced GAI models could provide accurate and reliable educational tools and healthcare tools supporting documentation and evidence-based decision-making. However, potential risks include business profit motives and knowledge gaps. Navigating these challenges is essential to fully leveraging GAI's benefits in education and physiotherapy practice. Therefore, fostering a critical approach and ensuring robust organizational support is crucial for maximizing the positive impact of GAI in physiotherapy.

Indexed as

Artificial IntelligencePhysical Therapy SpecialtyStudents, Health OccupationsAdultFemaleFocus GroupsGenerative Artificial IntelligenceHumansInterviews as TopicMaleQualitative ResearchSwedenYoung AdultFocus group interviewsGenerative artificial intelligenceHealth and medical educationPhysiotherapyQualitative methodStudent perspective

Identifiers

PMID40275241
PMCPMC12020151

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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.