Harmonizing PTSD Severity Scales Across Instruments and Sites

Objective: The variety of instruments used to assess posttraumatic stress disorder (PTSD) allows for flexibility, but also creates challenges for data synthesis. The objective of this work was to use a multisite mega analysis to derive quantitative recommendations for equating scores across measures of PTSD severity. Method: Empirical Bayes harmonization and linear models were used to describe and mitigate site and covariate effects. Quadratic models for converting scores across PTSD assessments were constructed using bootstrapping and tested on hold out data. Results: We aggregated 17 data sources and compiled an n = 5,634 sample of individuals who were assessed for PTSD symptoms. We confirmed our hypothesis that harmonization and covariate adjustments would significantly improve inference of scores across instruments. Harmonization significantly reduced cross-dataset variance (28%, p <.001), and models for converting scores across instruments were well fit (median R² = 0.985) with an average root mean squared error of 1.46 on sum scores. Conclusions: These methods allow PTSD symptom severity to be placed on multiple scales and offers interesting empirical perspectives on the role of harmonization in the behavioral sciences.