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AIMS: Major depressive disorders are common, with substantial impact on individuals/society. Brief scales for depression severity, based on a small number of characteristics all of which are necessary for diagnosis, have been recommended in self-reported versions for clinical work or research when aiming to quickly and accurately measure depression. We have examined psychometric properties of a brief 6-item version of the Symptom Checklist (SCL), the Symptom Checklist core depression scale (SCL-CD6) and aimed to identify a cut-point for epidemiological research. METHODS: The psychometric evaluation of the SCL-CD6 was mainly performed by a Mokken analysis of unidimensionality in a random sample of 1476 residents in the Stockholm County, aged 18-64 years. The standardization of SCL-CD6 was based on ROC analysis, using the Major Depression Inventory as index of validity. Predictive validity was subsequently assessed using register data on hospital admissions and purchases of prescribed medications linked to a sample of 5985 participants in the Swedish Longitudinal Occupational Survey of Health (SLOSH). RESULTS: The SCL-CD6 obtained a coefficient of homogeneity of 0.70 by Mokken analysis, which indicates high unidimensionality and a meaningful dimensional measure of depression severity. By ROC we identified a score of 17 or higher (total range 0-24) as the best cut-point for major depression (sensitivity 0.68, specificity 0.98) which predicted subsequent purchases of antidepressants as well as hospitalisations with a depressive episode. CONCLUSIONS: The SCL-CD6 was found a valid depression scale with higher unidimensionality than longer epidemiological instruments and thus particularly suitable for assessment in larger population surveys.
Hanson et al. (Tue,) studied this question.