Evidence map›Paper›PMID 41334158›Full record

ArticleJournal of multidisciplinary healthcare2025

Artificial Intelligence Adoption in Surgery: Cognition, Usage Patterns and Implementation Barriers of DeepSeek Among Healthcare Professionals in China's Tertiary Hospitals.

Hua Xie, Xu Dai, Jiao Xie, Shanshan Lei, Jie Zeng, Jiping Yang, Yifeng Zhou

Abstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
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

7 authors.

Hua XieDepartment of Operating, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, 410005, People's Republic of China.
Xu DaiDepartment of Breast and Thyroid Surgery, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, 410005, People's Republic of China.
Jiao XieDepartment of Otolaryngology, Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, People's Republic of China.
Shanshan LeiDepartment of Breast and Thyroid Surgery, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, 410005, People's Republic of China.
Jie ZengDepartment of Breast and Thyroid Surgery, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, 410005, People's Republic of China.
Jiping YangDepartment of Operating, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, 410005, People's Republic of China.
Yifeng ZhouDepartment of Operating, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, 410005, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to investigate the cognition and application status of DeepSeek among surgical medical staff in Class III Grade A hospitals and analyse its influencing factors to optimise its clinical application. Methods: From February to March 2025, a questionnaire survey was conducted among 440 surgical medical staff from Class III Grade A hospitals in 18 provinces in China by a convenience sampling method. The questionnaire covered, among others, basic information, cognition and use status, attitudes and barriers and training needs, and also evaluated the degree of understanding, user experience (operation convenience, results accuracy, system stability) and degree of trust concerning DeepSeek. The SPSS 25.0 software was used for data analysis, which included frequency, percentage, Mann-Whitney Results: A total of 424 valid questionnaires were collected (96.4%). The results indicated that 67.0% of the medical staff understood the basic functions of DeepSeek, and 70.3% used DeepSeek occasionally. It was mainly used for teaching and research support (43.2%), other life services (35.6%) and patient services (29.2%). Multivariate analysis showed that medical staff working in operating rooms and neurosurgery departments, those who were occasional users, and medical staff who primarily used DeepSeek for other life services demonstrated significantly higher levels of knowledge about DeepSeek. Conclusion: Despite widespread awareness of DeepSeek's capabilities (67.0% understanding basic functions), significant implementation gaps persist, with limited clinical utilisation and predominant usage in low-risk applications. Key barriers include insufficient training (94.8% untrained), data privacy concerns (57.5%) and over-reliance fears (58.5%). These findings reveal a substantial untapped potential for AI integration in surgical practice, highlighting critical needs for targeted training interventions, enhanced data security frameworks and staged implementation protocols to bridge the awareness-utilisation gap and facilitate meaningful clinical adoption.

Indexed as

behaviour of useDeepSeekknowledge of technologymulti-centre surveysurgical medical staff

Identifiers

PMID41334158
PMCPMC12666401

What OpenQuestion holds

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LicenceCC BY-NC
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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.