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Identifying Individuals with Highest Social Risk in Adults with Type 2 Diabetes Using Item Response Theory

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Abstract

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.

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Data Availability

Data used for this study may be available on request from LEE.

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Funding

Effort for this study was partially supported by National Institute of Diabetes and Digestive Kidney Disease (R01DK118038, R01DK120861, PI: Egede), National Institute for Minority Health and Health Disparities (R01MD013826, PI: Egede/Walker; R01MD018012, PI: Egede/Linde; and R01MD017574, PI: Egede/Linde).

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Authors and Affiliations

  1. Division of General Internal Medicine, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA

    Leonard E. Egede MD, MS, Rebekah J. Walker PhD & Joni S. Williams MD, MPH

  2. Center for Advancing Population Science, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI, 53226, USA

    Leonard E. Egede MD, MS, Rebekah J. Walker PhD & Joni S. Williams MD, MPH

  3. Department of Health Policy & Management, Texas A&M School of Public Health, 212 Adriance Lab Rd, College Station, TX, 77843, USA

    Sebastian Linde PhD, MPhil, MSc

Authors
  1. Leonard E. Egede MD, MS
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  2. Rebekah J. Walker PhD
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  3. Sebastian Linde PhD, MPhil, MSc
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  4. Joni S. Williams MD, MPH
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Contributions

LEE obtained funding for the study, designed the study, and analyzed the data. All authors participated in interpreting the results. RJW, SL, and JSW drafted the article. All authors critically revised the manuscript for intellectual content and approved the final manuscript.

Corresponding author

Correspondence to Leonard E. Egede MD, MS.

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Egede, L.E., Walker, R.J., Linde, S. et al. Identifying Individuals with Highest Social Risk in Adults with Type 2 Diabetes Using Item Response Theory. J GEN INTERN MED (2024). https://doi.org/10.1007/s11606-024-08742-6

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