Cognitive complexity of self-administered depression measures

Background dministered depression measures are important tools for research and practice, but their utility depends on the quality of the measurements they yield. Respondent comprehension is essential for meaningful measurement and prior studies have used readability indices to assess comprehensibility. Readability, however, is only one aspect of comprehension and empirical evidence shows that comprehension and measurement quality decrease as the cognitive complexity of standardized questions increases. Thus, cognitive complexity may provide a useful guide for selecting measures to maximize measurement quality. s tudy compared the cognitive complexity of 15 self-administered depression measures. Four aspects of cognitive complexity (length, readability, linguistic problems and number) were combined to characterize overall complexity. s es varied considerably. The most cognitively complex measures, likely to be most difficult to comprehend, were the Inventory to Diagnose Depression (IDD), the Hamilton Depression Inventory (HDI, Full and Short Versions), and the Beck Depression Inventory (BDI, BDI-II, BDI-PC). The least complex measures, likely to be easiest to comprehend, were the Harvard National Depression Screening Day Scale (HANDS), the Revised Hamilton Rating Scale for Depression Self-Report Problem Inventory (RHRSD) and the Zung Self-Rated Depression Scale (SDS). This multidimensional approach to assessing complexity and comprehensibility yielded different results than readability indices alone. tions tudy did not include all self-administered depression measures and did not examine the relationship of cognitive complexity to actual responses to depression measures. sions cognitive complexity is likely to limit comprehension and reduce measurement accuracy, it merits consideration in selection of self-administered depression measures.