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August 30, 2026Quality of Life ResearchOpen Access

Mapping the Problem Areas in Diabetes (PAID) and Diabetes Distress Scale (DDS) to the EQ-5D-5L in diabetes care

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Authors

PAPablo ArijaNDNicholas DurnoJWJie Wang

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Overview

Cross-sectional modeling demonstrates accurate estimation of EQ-5D-5L utilities from diabetes distress measures in adults with diabetes, facilitating health economic evaluations.

Key Points

  • Develop and validate mapping algorithms to estimate EQ-5D-5L health state utility values from the Problem Areas in Diabetes (PAID-20) and Diabetes Distress Scale (DDS-17) instruments for economic evaluations.
  • Analyzed cross-sectional survey data from 662 adults with diabetes in Germany who completed the PAID-20, DDS-17, and EQ-5D-5L questionnaires.
  • Developed direct mapping models via Tobit and censored least absolute deviation (CLAD) regressions alongside indirect mapping via proportional and partial proportional odds regressions.
  • Selected model predictors using item correlations and backward stepwise selection with clinical covariates, validating performance using 10-fold cross-validation.
  • The top-performing direct mapping model combined PAID-20, DDS-17, and covariates using CLAD regression, yielding a root mean square error (RMSE) of 0.146 and a mean absolute error (MAE) of 0.09.
  • Direct Tobit models using PAID-20 with covariates achieved an RMSE of 0.159 (MAE 0.117), while DDS-17 with covariates achieved an RMSE of 0.164 (MAE 0.121).
  • Indirect mapping models produced higher prediction errors across specifications, with RMSE values between 0.187 and 0.21 and MAE values between 0.124 and 0.141.

Cite This Study

Arija et al. (2026) studied this question.

synapsesocial.com/papers/6a93f14b6c1a8fb52e79e2adhttps://doi.org/10.1007/s11136-026-04361-2
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