Chu Yi-Tang, Huang Ru-Yi, Chen Tara Tai-Wen, Lin Wei-Hsuan, Tang James TaoQian, Lin Chi-Wei, Huang Chi-Hsien, Lin Chung-Ying, Chen Jung-Sheng, Kurtz-Rossi Sabrina, Sørensen Kristine
Department of Holistic Medicine, E-Da Hospital, Kaohsiung, Taiwan.
Department of Family and Community Medicine, E-Da Hospital, Kaohsiung, Taiwan.
Digit Health. 2022 Nov 4;8:20552076221136372. doi: 10.1177/20552076221136372. eCollection 2022 Jan-Dec.
Implementation of artificial intelligence (AI) in medical decision-making is still in early development. We developed an AI robot intervention prototype with a health literacy-friendly interface that uses interactive voice response (IVR) surveying to assist in decision-making for weight loss. The weight-specific health literacy instrument (WSHLI) and Shared Decision-Making Questionnaire (SDMQ) were used to measure factors influencing weight-loss decisions. Factors associated with participants choosing to lose weight were analyzed using logistic regression, and factors influencing the selection of specific weight-loss plans were examined with one-way analysis of variance. Our study recruited 144 overweight or obese adults (69.4% women, 58.3% with body mass index (BMI) ≥ 24). After interacting with the AI robot, 78% of the study population made the decision to lose weight. SDMQ score was a significant factor positively influencing the decision for weight-loss (odds ratio [OR]: 2.16, 95% confidence interval [CI]: 1.09-4.29, = 0.027). Individuals who selected self-monitored lifestyle modification (mean ± SD: 11.52 ± 1.95) had significantly higher health literacy than those who selected dietician-assisted plan (9.92 ± 2.30) and physician-guided treatment (9.60 ± 1.52) (both = 0.001). The study results demonstrated that our prototype AI robot can effectively encourage individuals to make decisions regarding weight management and that both WSHLI and SDMQ scores affect the choice of weight-loss plans.
人工智能(AI)在医疗决策中的应用仍处于早期发展阶段。我们开发了一种具有健康素养友好界面的人工智能机器人干预原型,该原型使用交互式语音应答(IVR)调查来辅助减肥决策。使用特定体重健康素养工具(WSHLI)和共同决策问卷(SDMQ)来衡量影响减肥决策的因素。使用逻辑回归分析与参与者选择减肥相关的因素,并通过单因素方差分析检查影响特定减肥计划选择的因素。我们的研究招募了144名超重或肥胖成年人(69.4%为女性,58.3%的体重指数(BMI)≥24)。与人工智能机器人互动后,78%的研究人群做出了减肥决定。SDMQ得分是对减肥决策有积极影响的显著因素(优势比[OR]:2.16,95%置信区间[CI]:1.09 - 4.29,P = 0.027)。选择自我监测生活方式改变的个体(均值±标准差:11.52±1.95)的健康素养显著高于选择营养师辅助计划的个体(9.92±2.30)和医生指导治疗的个体(9.60±1.52)(两者P = 0.001)。研究结果表明,我们的人工智能机器人原型可以有效地鼓励个体做出体重管理决策,并且WSHLI和SDMQ得分都会影响减肥计划的选择。