MIDAS Project Publication Abstracts
Sheeran, T., Zimmerman, M. Case identification
of depression with self-report questionnaires. Psychiatry Research,
2005, 109, 51-59.
Many self-report measures that are used to identify cases of depression
are symptom severity measures that are adopted for diagnostic purposes
by use of cutoff scores. A troublesome problem with this approach
is that optimal cutoff scores often vary across studies, which increases
the difficulty of cross-study comparisons. This study evaluated
the performance of a DSM-IV based depression screening scale, the
Diagnostic Inventory for Depression. We compared the diagnostic
performance of two different approaches to scoring the DID: a cutoff
scoring approach and a standardized, DSM-IV symptom summation algorithm.
Clinical diagnosis based on a semi-structured interview was the
standard of comparison. Receiver operating characteristic (ROC)
analysis indicated that a DID cutoff score performed comparably
to the DID algorithmic approach in identifying cases. This finding
is in contrast to prior research which suggested that algorithmic
approaches might improve test performance over the cutoff score
approach. The manner by which a user might choose the appropriate
scale scoring method for case identification is discussed.
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