Evidence map›Paper›PMID 39820814›Full record

ArticleJournal of medical systems2025

Assessing the Efficacy of ChatGPT Prompting Strategies in Enhancing Thyroid Cancer Patient Education: A Prospective Study.

Qi Xu, Jing Wang, Xiaohui Chen, Jiale Wang, Hanzhi Li, Zheng Wang, Weihan Li, Jinliang Gao, Chen Chen, Yuwan Gao

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Article in Journal of medical systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  4. Artificial intelligence in cancer survivorship: evaluating ChatGPT's performance in rehabilitation-related queries.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
  5. Article
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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

10 authors.

Qi XuDepartment of Breast and Thyroid Surgery, The First Affiliated Hospital of Nanyang Medical College, Nanyang, China. Cookies_white@outlook.com.
Jing WangDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Xiaohui ChenDepartment of Breast and Thyroid Surgery, The Second Affiliated Hospital of Guilin Medical University, Guilin, China.
Jiale WangDepartment of Internal Medicine, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China.
Hanzhi LiDepartment of Breast and Thyroid Surgery, The First Affiliated Hospital of Nanyang Medical College, Nanyang, China.
Zheng WangDepartment of Breast Surgery, Nanyang Central Hospital, Nanyang, China.
Weihan LiDepartment of Thyroid and Breast Surgery, Nanyang Central Hospital, Nanyang, China.
Jinliang GaoDepartment of Thyroid and Breast Surgery, Nanyang Central Hospital, Nanyang, China.
Chen ChenDepartment of Breast Surgery, Nanyang Central Hospital, Nanyang, China.
Yuwan GaoDepartment of Ophthalmology, The First Affiliated Hospital of Nanyang Medical College, Nanyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rise of AI platforms, patients increasingly use them for information, relying on advanced language models like ChatGPT for answers and advice. However, the effectiveness of ChatGPT in educating thyroid cancer patients remains unclear. We designed 50 questions covering key areas of thyroid cancer management and generated corresponding responses under four different prompt strategies. These answers were evaluated based on four dimensions: accuracy, comprehensiveness, human care, and satisfaction. Additionally, the readability of the responses was assessed using the Flesch-Kincaid grade level, Gunning Fog Index, Simple Measure of Gobbledygook, and Fry readability score. We also statistically analyzed the references in the responses generated by ChatGPT. The type of prompt significantly influences the quality of ChatGPT's responses. Notably, the "statistics and references" prompt yields the highest quality outcomes. Prompts tailored to a "6th-grade level" generated the most easily understandable text, whereas responses without specific prompts were the most complex. Additionally, the "statistics and references" prompt produced the longest responses while the "6th-grade level" prompt resulted in the shortest. Notably, 87.84% of citations referenced published medical literature, but 12.82% contained misinformation or errors. ChatGPT demonstrates considerable potential for enhancing the readability and quality of thyroid cancer patient education materials. By adjusting prompt strategies, ChatGPT can generate responses that cater to diverse patient needs, improving their understanding and management of the disease. However, AI-generated content must be carefully supervised to ensure that the information it provides is accurate.

Indexed as

Patient Education as TopicThyroid NeoplasmsComprehensionGenerative Artificial IntelligenceHumansProspective StudiesArtificial intelligenceChatGPTPatient educationThyroid cancer

Identifiers

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.