Evidence map›Paper›PMID 38860862›Full record

ArticleThe journal of spinal cord medicine2025

Assessment of the reliability and usability of ChatGPT in response to spinal cord injury questions.

Fatma Özcan, Merve Örücü Atar, Özlem Köroğlu, Bilge Yılmaz

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Article in The journal of spinal cord medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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0cells of the map it votes in
7citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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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

4 authors.

Fatma ÖzcanDepartment of Physical Medicine and Rehabilitation, University of Health Sciences, Gaziler Physical Medicine and Rehabilitation Training and Research Hospital, Ankara, Turkey.ORCID 0000-0002-0914-0638
Merve Örücü AtarDepartment of Physical Medicine and Rehabilitation, University of Health Sciences, Gaziler Physical Medicine and Rehabilitation Training and Research Hospital, Ankara, Turkey.
Özlem KöroğluDepartment of Physical Medicine and Rehabilitation, University of Health Sciences, Gaziler Physical Medicine and Rehabilitation Training and Research Hospital, Ankara, Turkey.
Bilge YılmazDepartment of Physical Medicine and Rehabilitation, University of Health Sciences, Gaziler Physical Medicine and Rehabilitation Training and Research Hospital, Ankara, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe use of artificial intelligence chatbots to obtain information about patients' diseases is increasing. This study aimed to determine the reliability and usability of ChatGPT for spinal cord injury-related questions.

methodsThree raters simultaneously evaluated a total of 47 questions on a 7-point Likert scale for reliability and usability, based on the three most frequently searched keywords in Google Trends ('general information', 'complications' and 'treatment').

resultsInter-rater Cronbach α scores indicated substantial agreement for both reliability and usability scores (α between 0.558 and 0.839, and α between 0.373 and 0.772, respectively). The highest mean reliability score was for 'complications' (mean 5.38). The lowest average was for the 'general information' section (mean 4.20). The 'treatment' had the highest mean scores for the usability (mean 5.87) and the lowest mean value was recorded in the 'general information' section (mean 4.80).

conclusionThe answers given by ChatGPT to questions related to spinal cord injury were reliable and useful. Nevertheless, it should be kept in mind that ChatGPT may provide incorrect or incomplete information, especially in the 'general information' section, which may mislead patients and their relatives.

Indexed as

Artificial IntelligenceInternetSpinal Cord InjuriesGenerative Artificial IntelligenceHumansReproducibility of ResultsArtificial intelligenceChatGPTReliabilitySpinal cord injury

Identifiers

PMID38860862
PMCPMC12329821

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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.