Blease Charlotte, Kharko Anna, Bernstein Michael, Bradley Colin, Houston Muiris, Walsh Ian, D Mandl Kenneth
General Medicine and Primary Care, Beth Israel Deaconess Medical Center, Boston, MA, United States.
Healthcare Sciences and e-Health, Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden.
JMIR Med Educ. 2023 Mar 20;9:e42639. doi: 10.2196/42639.
The potential for digital health technologies, including machine learning (ML)-enabled tools, to disrupt the medical profession is the subject of ongoing debate within biomedical informatics.
We aimed to describe the opinions of final-year medical students in Ireland regarding the potential of future technology to replace or work alongside general practitioners (GPs) in performing key tasks.
Between March 2019 and April 2020, using a convenience sample, we conducted a mixed methods paper-based survey of final-year medical students. The survey was administered at 4 out of 7 medical schools in Ireland across each of the 4 provinces in the country. Quantitative data were analyzed using descriptive statistics and nonparametric tests. We used thematic content analysis to investigate free-text responses.
In total, 43.1% (252/585) of the final-year students at 3 medical schools responded, and data collection at 1 medical school was terminated due to disruptions associated with the COVID-19 pandemic. With regard to forecasting the potential impact of artificial intelligence (AI)/ML on primary care 25 years from now, around half (127/246, 51.6%) of all surveyed students believed the work of GPs will change minimally or not at all. Notably, students who did not intend to enter primary care predicted that AI/ML will have a great impact on the work of GPs.
We caution that without a firm curricular foundation on advances in AI/ML, students may rely on extreme perspectives involving self-preserving optimism biases that demote the impact of advances in technology on primary care on the one hand and technohype on the other. Ultimately, these biases may lead to negative consequences in health care. Improvements in medical education could help prepare tomorrow's doctors to optimize and lead the ethical and evidence-based implementation of AI/ML-enabled tools in medicine for enhancing the care of tomorrow's patients.
包括机器学习工具在内的数字健康技术对医疗行业造成冲击的可能性，是生物医学信息学领域正在讨论的话题。
我们旨在描述爱尔兰医学专业最后一年学生对于未来技术在执行关键任务时取代全科医生或与全科医生协同工作的潜力的看法。
在2019年3月至2020年4月期间，我们采用便利抽样法，对医学专业最后一年学生进行了基于纸质问卷的混合方法调查。该调查在爱尔兰4个省的7所医学院中的4所进行。定量数据采用描述性统计和非参数检验进行分析。我们使用主题内容分析法研究自由文本回复。
3所医学院的最后一年学生中，共有43.1%（252/585）做出回应，1所医学院的数据收集因与COVID-19大流行相关的干扰而终止。关于预测从现在起25年后人工智能/机器学习对初级保健的潜在影响，所有接受调查的学生中约一半（127/246，51.6%）认为全科医生的工作变化极小或根本不会改变。值得注意的是，不打算进入初级保健领域的学生预测人工智能/机器学习将对全科医生的工作产生重大影响。
我们提醒，若没有关于人工智能/机器学习进展的坚实课程基础，学生可能会依赖极端观点，这些观点一方面存在自我保护的乐观偏差，低估技术进步对初级保健的影响，另一方面存在技术炒作。最终，这些偏差可能在医疗保健中导致负面后果。医学教育的改进有助于让未来的医生做好准备，以优化并引领基于人工智能/机器学习的工具在医学中的道德且循证实施，从而提升对未来患者的护理。
