Division of General Internal Medicine, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA.
Center for Advancing Population Science, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI, 53226, USA.
J Gen Intern Med. 2024 Jul;39(9):1642-1648. doi: 10.1007/s11606-024-08742-6. Epub 2024 Apr 2.
The aim of this analysis was to create a parsimonious tool to screen for high social risk using item response theory to discriminate across social risk factors in adults with type 2 diabetes.
Cross-sectional data of 615 adults with diabetes recruited from two primary care clinics were used. Participants completed assessments including validated scales on economic instability (financial hardship), neighborhood and built environment (crime, violence, neighborhood rating), education (highest education, health literacy), food environment (food insecurity), social and community context (social isolation), and psychological risk factors (perceived stress, depression, serious psychological distress, diabetes distress). Item response theory (IRT) models were used to understand the association between a participant's underlying level of a particular social risk factor and the probability of that response. A two-parameter logistic IRT model was used with each of the 12 social determinant factors being added as a separate parameter in the model. Higher values in item discrimination indicate better ability of a specific social risk factor in differentiating participants from each other.
Rate of crime reported in a neighborhood (discrimination 3.13, SE 0.50; item difficulty - 0.68, SE 0.07) and neighborhood rating (discrimination 4.02, SE 0.87; item difficulty - 1.04, SE 0.08) had the highest discrimination.
Based on these findings, crime and neighborhood rating discriminate best between individuals with type 2 diabetes who have high social risk and those with low social risk. These two questions can be used as a parsimonious social risk screening tool to identify high social risk.
本分析旨在创建一个简洁的工具，通过项目反应理论来甄别 2 型糖尿病患者的社会风险因素，从而筛选出高社会风险人群。
本研究使用了来自两家初级保健诊所的 615 名成年糖尿病患者的横断面数据。参与者完成了评估，包括经济不稳定（经济困难）、邻里和建筑环境（犯罪、暴力、邻里评价）、教育（最高教育程度、健康素养）、食物环境（食物不安全）、社会和社区环境（社会孤立）以及心理风险因素（感知压力、抑郁、严重心理困扰、糖尿病困扰）的验证量表。使用项目反应理论（IRT）模型来了解参与者特定社会风险因素的潜在水平与该反应的概率之间的关系。对每个 12 个社会决定因素，使用双参数逻辑 IRT 模型，将每个社会决定因素作为模型中的单独参数添加。项目区分度越高，表明特定社会风险因素在区分参与者方面的能力越强。
报告的邻里犯罪率（区分度 3.13，SE 0.50；项目难度-0.68，SE 0.07）和邻里评价（区分度 4.02，SE 0.87；项目难度-1.04，SE 0.08）具有最高的区分度。
基于这些发现，犯罪和邻里评价在区分具有高社会风险和低社会风险的 2 型糖尿病患者方面表现最佳。这两个问题可以用作一种简洁的社会风险筛查工具，以识别高社会风险。
