Evidence map›Paper›PMID 42666561›Full record

ArticleCureus2026

Academic Orthopaedic Surgeons Prefer Peer-Reviewed Guidelines Over Artificial Intelligence and Social Media for Medical Information.

Divya Bhatia, Melissa Romoff, Emily Tse, Asha Timm, Michael S Kim, Emily Mills, Hao-Hua Wu, Sohaib Hashmi, Don Park, Yu-Po Lee

Abstract read
In one paragraph

Article in Cureus, 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

10 authors.

Divya BhatiaResearch, Palos Verdes High School, Palos Verdes Estates, USA.
Melissa RomoffDepartment of Orthopaedic Surgery, University of California, Irvine, School of Medicine, Orange, USA.
Emily TseDepartment of Orthopaedic Surgery, University of California, Irvine, School of Medicine, Orange, USA.
Asha TimmFielding School of Public Health, University of California, Los Angeles, Los Angeles, USA.
Michael S KimDepartment of Orthopaedic Surgery, University of California, Irvine, School of Medicine, Orange, USA.
Emily MillsDepartment of Orthopaedic Surgery, University of California, Irvine, School of Medicine, Orange, USA.
Hao-Hua WuDepartment of Orthopaedic Surgery, University of California, Irvine, School of Medicine, Orange, USA.
Sohaib HashmiDepartment of Orthopaedic Surgery, University of California, Irvine, School of Medicine, Orange, USA.
Don ParkDepartment of Orthopaedic Surgery, University of California, Irvine, School of Medicine, Orange, USA.
Yu-Po LeeDepartment of Orthopaedic Surgery, University of California, Irvine, School of Medicine, Orange, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objective Patients increasingly seek recommendations for improved health and wellness, as well as medical advice, through social media and large language models (LLMs), yet the quality of these sources varies considerably. Effective clinical communication requires an understanding of how patients engage with online medical content, as these sources may shape expectations even before a clinical encounter. However, to date, no study has assessed how orthopaedic surgeons themselves use these same resources. Hence, this study aimed to evaluate orthopaedic surgeons' self-reported use of LLMs, social media, and peer-reviewed clinical resources for patient care and personal medical care, along with the perceived understandability and helpfulness of each source. Methods In this cross-sectional study, an electronic survey was administered to a convenience sample of all orthopaedic surgeons at a single academic institution. Respondents indicated whether they had ever used LLMs (e.g., ChatGPT), social media platforms (e.g., TikTok, Instagram), or peer-reviewed clinical resources (e.g., guidelines from the North American Spine Society (NASS)) for patient care or their own medical care. Those who reported use were asked whether each source was easy to understand and helpful. Proportions are reported with 95% Wilson confidence intervals (CIs). McNemar's exact test was used to compare paired utilization rates across sources and contexts, while Fisher's exact test was employed to compare comprehensibility between distinct user subgroups. All analyses were exploratory given the pilot design. Results Sixteen orthopaedic surgeons completed the survey. Peer-reviewed clinical guidelines were used by 15 surgeons (93.8%; 95% CI: 71.7%-98.9%) for patient care and 14 (87.5%; 95% CI: 64.0%-96.5%) for personal care, significantly more frequently than LLMs or social media for both contexts (all p ≤ 0.016). LLMs were used by five surgeons (31.2%; 95% CI: 14.2%-55.6%) for patient care and seven (43.8%; 95% CI: 23.1%-66.8%) for personal care. LLM use for personal care was significantly more frequent than social media use (p = 0.031). Social media use was rare, reported by two surgeons (12.5%) for patient care and one (6.2%) for personal care. Every surgeon who used an LLM in either context rated it as helpful, and the majority found it easy to understand. Comprehensibility ratings did not differ significantly between LLM users and guideline users for either patient care (80.0% vs. 66.7%; p = 1.000) or personal care (85.7% vs. 64.3%; p = 0.613). Concordance analysis showed that 14 of 16 surgeons used guidelines in both contexts, whereas eight had never used an LLM and 14 had never used social media in either setting. Conclusions Academic orthopaedic surgeons demonstrate a strong and statistically significant preference for peer-reviewed clinical guidelines over LLMs and social media for both personal and patient medical care. LLMs occupy an intermediate position in surgeons' information-seeking preferences and were rated as helpful by all users, suggesting cautious but growing adoption. Social media use for medical purposes was rare among surgeons, contrasting sharply with published estimates exceeding 70% among the general public. This disconnect, with patients seeking orthopaedic information on platforms where expert content is scarce, represents a clinically meaningful gap.

Indexed as

artificial intelligence in medicineeffects of social medialarge language modelorthopaedic surgeryscience communication

Identifiers

PMID42666561
PMCPMC13522249

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.