Jagemann Inga, Wensing Ole, Stegemann Manuel, Hirschfeld Gerrit
School of Business, University of Applied Sciences and Arts Bielefeld, Bielefeld, Germany.
JMIR Form Res. 2024 Jan 12;8:e46402. doi: 10.2196/46402.
There is great interest in using artificial intelligence (AI) to screen for skin cancer. This is fueled by a rising incidence of skin cancer and an increasing scarcity of trained dermatologists. AI systems capable of identifying melanoma could save lives, enable immediate access to screenings, and reduce unnecessary care and health care costs. While such AI-based systems are useful from a public health perspective, past research has shown that individual patients are very hesitant about being examined by an AI system.
The aim of this study was two-fold: (1) to determine the relative importance of the provider (in-person physician, physician via teledermatology, AI, personalized AI), costs of screening (free, 10€, 25€, 40€; 1€=US $1.09), and waiting time (immediate, 1 day, 1 week, 4 weeks) as attributes contributing to patients' choices of a particular mode of skin cancer screening; and (2) to investigate whether sociodemographic characteristics, especially age, were systematically related to participants' individual choices.
A choice-based conjoint analysis was used to examine the acceptance of medical AI for a skin cancer screening from the patient's perspective. Participants responded to 12 choice sets, each containing three screening variants, where each variant was described through the attributes of provider, costs, and waiting time. Furthermore, the impacts of sociodemographic characteristics (age, gender, income, job status, and educational background) on the choices were assessed.
Among the 383 clicks on the survey link, a total of 126 (32.9%) respondents completed the online survey. The conjoint analysis showed that the three attributes had more or less equal importance in contributing to the participants' choices, with provider being the most important attribute. Inspecting the individual part-worths of conjoint attributes showed that treatment by a physician was the most preferred modality, followed by electronic consultation with a physician and personalized AI; the lowest scores were found for the three AI levels. Concerning the relationship between sociodemographic characteristics and relative importance, only age showed a significant positive association to the importance of the attribute provider (r=0.21, P=.02), in which younger participants put less importance on the provider than older participants. All other correlations were not significant.
This study adds to the growing body of research using choice-based experiments to investigate the acceptance of AI in health contexts. Future studies are needed to explore the reasons why AI is accepted or rejected and whether sociodemographic characteristics are associated with this decision.
利用人工智能（AI）筛查皮肤癌备受关注。皮肤癌发病率上升以及训练有素的皮肤科医生日益短缺推动了这一趋势。能够识别黑色素瘤的人工智能系统可以挽救生命，使人们能够立即进行筛查，并减少不必要的护理和医疗保健成本。虽然这种基于人工智能的系统从公共卫生角度来看很有用，但过去的研究表明，个体患者对接受人工智能系统检查非常犹豫。
本研究的目的有两个：（1）确定提供者（面对面医生、远程皮肤病学医生、人工智能、个性化人工智能）、筛查成本（免费、10欧元、25欧元、40欧元；1欧元 = 1.09美元）和等待时间（立即、1天、1周、4周）作为影响患者选择特定皮肤癌筛查方式的属性的相对重要性；（2）调查社会人口统计学特征，尤其是年龄，是否与参与者的个人选择存在系统关联。
采用基于选择的联合分析，从患者角度检查医疗人工智能在皮肤癌筛查中的接受度。参与者对12个选择集做出回应，每个选择集包含三种筛查变体，每个变体通过提供者、成本和等待时间的属性进行描述。此外，评估了社会人口统计学特征（年龄、性别、收入、工作状态和教育背景）对选择的影响。
在383次点击调查链接中，共有126名（32.9%）受访者完成了在线调查。联合分析表明这三个属性在影响参与者选择方面的重要性大致相当，其中提供者是最重要的属性。检查联合属性的个体部分价值显示，由医生治疗是最受欢迎的方式，其次是与医生进行电子咨询和个性化人工智能；三种人工智能水平得分最低。关于社会人口统计学特征与相对重要性之间的关系，只有年龄与属性提供者 的重要性呈显著正相关（r = 0.21，P = 0.02），即年轻参与者对提供者的重视程度低于年长参与者。所有其他相关性均不显著。
本研究为越来越多使用基于选择的实验来调查人工智能在健康领域接受度的研究增添了内容。未来需要开展研究，以探索人工智能被接受或拒绝的原因，以及社会人口统计学特征是否与这一决定相关。
