A common measurement scale for self-report instruments in mental health care: T scores with a normal distribution

The diversity of measures in clinical psychology hampers a straightforward interpretation of test results, complicates communication with the patient, and constitutes a challenge to the implementation of measurement-based care. In educational research and assessment, it is common practice to convert test scores to a common metric, such as T scores. We recommend to apply this also in clinical psychology and propose and test a procedure to arrive at T scores approximating a normal distribution, that can be applied to individual test scores. We established formulas to estimate normalized T scores from raw scale scores by regressing IRT-based theta scores on raw scores. With data from large population and clinical samples, we established crosswalk formulas. Their validity was investigated by comparing calculated T scores with IRT-based T scores. IRT and formulas yielded very similar T scores, supporting the validity of the latter approach. Theoretical and practical advantages and disadvantages of both approaches to convert scores to a common metric and alternative approaches are discussed. Provided that scale characteristics allow for their computation, T scores will help to better understand measurement results, which makes it easier for patients and practitioners to use test results in joint decision-making about the course of treatment.