Evidence map›Paper›PMID 39184635›Full record

ArticleCureus2024

The Role of Artificial Intelligence in the Primary Prevention of Common Musculoskeletal Diseases.

Selkin Yilmaz Muluk, Nazli Olcucu

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

2 authors.

Selkin Yilmaz MulukPhysical Medicine and Rehabilitation, Antalya City Hospital, Antalya, TUR.
Nazli OlcucuPhysical Medicine and Rehabilitation, Antalya Atatürk State Hospital, Antalya, TUR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMusculoskeletal disorders (MSDs) are a leading cause of disability worldwide, with a growing burden across all demographics. With advancements in technology, conversational artificial intelligence (AI) platforms such as ChatGPT (OpenAI, San Francisco, CA) have become instrumental in disseminating health information. This study evaluated the effectiveness of ChatGPT versions 3.5 and 4 in delivering primary prevention information for common MSDs, emphasizing that the study is focused on prevention and not on diagnosis.

methodsThis mixed-methods study employed the CLEAR tool to assess the quality of responses from ChatGPT versions in terms of completeness, lack of false information, evidence support, appropriateness, and relevance. Responses were evaluated independently by two expert raters in a blinded manner. Statistical analyses included Wilcoxon signed-rank tests and paired samples t-tests to compare the performance across versions.

resultsChatGPT-3.5 and ChatGPT-4 effectively provided primary prevention information, with overall performance ranging from satisfactory to excellent. Responses for low back pain, fractures, knee osteoarthritis, neck pain, and gout received excellent scores from both versions. Additionally, ChatGPT-4 was better than ChatGPT-3.5 in terms of completeness (p = 0.015), appropriateness (p = 0.007), and relevance (p = 0.036), and ChatGPT-4 performed better across most medical conditions (p = 0.010).

conclusionsChatGPT versions 3.5 and 4 are effective tools for disseminating primary prevention information for common MSDs, with ChatGPT-4 showing superior performance. This study underscores the potential of AI in enhancing public health strategies through reliable and accessible health communication. Advanced models such as ChatGPT-4 can effectively contribute to the primary prevention of MSDs by delivering high-quality health information, highlighting the role of AIs in addressing the global burden of chronic diseases. It is important to note that these AI tools are intended for preventive education purposes only and not for diagnostic use. Continuous improvements are necessary to fully harness the potential of AI in preventive medicine. Future studies should explore other AI platforms, languages, and secondary and tertiary prevention measures to maximize the utility of AIs in global health contexts.

Indexed as

artificial intelligence (ai)chatgptdigital healthmusculoskeletal disordersprimary prevention

Identifiers

PMID39184635
PMCPMC11344583

What OpenQuestion holds

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LicenceCC BY
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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.