Evidence map›Paper›PMID 42769610›Full record

ArticleArchives of rehabilitation research and clinical translation2026

Acceptance and Use of Generative AI in Clinical Rehabilitation: An Interdisciplinary Survey of US Rehabilitation Professionals.

Malachy J Clancy, Erin R Pletcher, Alison Bell, Travis Pollen, Robert Dekerlegand

Abstract read
In one paragraph

Article in Archives of rehabilitation research and clinical translation, 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

5 authors.

Malachy J ClancyDepartment of Occupational Therapy, Thomas Jefferson University, Philadelphia, PA.
Erin R PletcherDepartment of Exercise Science, Thomas Jefferson University, Philadelphia, PA.
Alison BellDepartment of Occupational Therapy, Thomas Jefferson University, Philadelphia, PA.
Travis PollenDepartment of Exercise Science, Thomas Jefferson University, Philadelphia, PA.
Robert DekerlegandDepartment of Physical Therapy, Thomas Jefferson University, Philadelphia, PA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To examine rehabilitation professionals' current clinical use and practice patterns of generative artificial intelligence (GenAI) and examine differences between users and nonusers. Design: Cross-sectional mixed-methods. Setting: Online survey. Participants: A total of 408 professionals responded, with 264 complete surveys (64.7% completion) analyzed quantitatively and 311 valid open-ended responses analyzed qualitatively. The participants included occupational therapists, physical therapists, speech language pathologists, clinical exercise physiologists, and athletic trainers in the United States. Interventions: Not applicable. Main Outcome Measures: Researcher-designed survey based on the Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology. Results: Responses were received from all regions of the US, and were primarily occupational therapists (n=136, 51.5%) and women (n=214, 81.1%). Most participants identified as nonusers (n=154, 58.3%), whereas 41.6% (n=101) reported using GenAI some or most of the time. ChatGPT was the most common platform identified by all participants (n=241, 91.3%). GenAI was recognized by rehabilitation professionals as a tool to support patient care and administrative tasks. Users were significantly more likely than nonusers to perceive GenAI as useful in 5 of 7 domains ( Conclusions: Perceptions of usefulness, ease of use, and the social influence of peers significantly influence rehabilitation professionals' adoption and the use of GenAI within clinical practice.

Indexed as

Athletic trainersGenerative artificial intelligenceOccupational therapyPhysical therapistsRehabilitationSpeech language pathology

Identifiers

PMID42769610
PMCPMC13591089

What OpenQuestion holds

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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.