Identifying individuals with highest social risk in adults with type 2 diabetes using item response theory

Objective: 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.

Methods: 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.

Results: 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.

Conclusions: 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.