Navigating Nephrology's Decline Through a GPT-4 Analysis of Internal Medicine Specialties in the United States: Qualitative Study.

IF 3.2 Q1 EDUCATION, SCIENTIFIC DISCIPLINES JMIR Medical Education Pub Date : 2024-10-10 DOI:10.2196/57157

Jing Miao, Charat Thongprayoon, Oscar Garcia Valencia, Iasmina M Craici, Wisit Cheungpasitporn

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Abstract

Background: The 2024 Nephrology fellowship match data show the declining interest in nephrology in the United States, with an 11% drop in candidates and a mere 66% (321/488) of positions filled.

Objective: The study aims to discern the factors influencing this trend using ChatGPT, a leading chatbot model, for insights into the comparative appeal of nephrology versus other internal medicine specialties.

Methods: Using the GPT-4 model, the study compared nephrology with 13 other internal medicine specialties, evaluating each on 7 criteria including intellectual complexity, work-life balance, procedural involvement, research opportunities, patient relationships, career demand, and financial compensation. Each criterion was assigned scores from 1 to 10, with the cumulative score determining the ranking. The approach included counteracting potential bias by instructing GPT-4 to favor other specialties over nephrology in reverse scenarios.

Results: GPT-4 ranked nephrology only above sleep medicine. While nephrology scored higher than hospice and palliative medicine, it fell short in key criteria such as work-life balance, patient relationships, and career demand. When examining the percentage of filled positions in the 2024 appointment year match, nephrology's filled rate was 66%, only higher than the 45% (155/348) filled rate of geriatric medicine. Nephrology's score decreased by 4%-14% in 5 criteria including intellectual challenge and complexity, procedural involvement, career opportunity and demand, research and academic opportunities, and financial compensation.

Conclusions: ChatGPT does not favor nephrology over most internal medicine specialties, highlighting its diminishing appeal as a career choice. This trend raises significant concerns, especially considering the overall physician shortage, and prompts a reevaluation of factors affecting specialty choice among medical residents.

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通过对美国内科专科的 GPT-4 分析了解肾脏病学的衰退：定性研究。

背景：2024 年肾脏病学研究员匹配数据显示，美国人对肾脏病学的兴趣在下降，候选人减少了 11%，仅有 66%（321/488）的职位被填补：本研究旨在利用领先的聊天机器人模型 ChatGPT 分析影响这一趋势的因素，以深入了解肾脏病学与其他内科专业的吸引力对比：该研究使用 GPT-4 模型对肾脏病学和其他 13 个内科专业进行了比较，根据智力复杂性、工作与生活的平衡、程序参与、研究机会、患者关系、职业需求和经济报酬等 7 项标准对每个专业进行了评估。每项标准的分数从 1 到 10 分不等，累计分数决定排名。该方法包括通过指示 GPT-4 在反向情景中偏向其他专科而非肾脏科来抵消潜在的偏见：结果：GPT-4 对肾脏病学的排名仅高于睡眠医学。虽然肾脏病学的得分高于临终关怀和姑息医学，但在工作与生活的平衡、患者关系和职业需求等关键标准上却不尽如人意。在考察 2024 年任命年匹配的职位填补率时，肾脏病学的填补率为 66%，仅高于老年医学的 45%（155/348）。肾脏内科在智力挑战和复杂性、程序参与、职业机会和需求、研究和学术机会以及经济补偿等 5 项标准中的得分下降了 4%-14%：结论：与大多数内科专科相比，ChatGPT 并不青睐肾脏病学，这表明肾脏病学作为一种职业选择的吸引力正在下降。这一趋势引起了人们的极大关注，特别是考虑到整体医生短缺的问题，并促使人们重新评估影响住院医生选择专业的因素。

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