Screening for Depression in Medical Settings: Are Specific Scales Useful?

There are two broad strategies for screening and quantifying depression in medical settings. The first approach is replying upon measures developed in psychiatric samples, and the second approach is to concede that symptoms are substantially different and to develop customized scales. Here we discuss the merits of several specific scales for measuring depression in physical settings and make the case for scales tailored to specific populations. A subsequent chapter (Babaei and Mitchell) will present a contrasting position. There are two broad strategies for screening and quantifying depression in medical settings. The first approach involves using measures developed in psychiatric samples and assuming that their relevance holds. The second approach is to concede that there are intrinsic limitations to extrapolating those ‘‘general’’ measures to medically ill populations. In the former case the hypothesis is that symptoms of depression are essentially the same when depression occurs with and without physical illness. In the latter case the hypothesis is the symptoms are substantially different. Pursuing the latter, there are two key concerns. Firstly, such an approach assumes some constancy to the nature of depression across differing psychiatric and medical settings. Depression, however, is difficult enough to define in psychiatric patient samples. Even ignoring the debate as to whether depression is viewed as comprising a set of subtypes or is best modeled along a continuum, quantifying clinical depression remains problematic, as detailed elsewhere in this book. Over the past few decades, clinical depression has most commonly been viewed as synonymous with major depression, but, as numerous studies have shown, comparable symptomatic distress and disability associated with major depression and minor depression—and even with subsyndromal depression—begs an obvious question: Can imposing a cutoff score on a dimensional measure of depression accurately distinguish true cases and true non-cases in a psychiatric sample? Further, assuming that a cutoff is derived with an acceptable classification rate, can we extrapolate decision rules derived from psychiatric samples to screen and quantify depression caseness in the medically ill? As measures that have been widely used for decades (such as the Zung and the Beck Depression Inventory) generate widely differing cutoff scores across psychiatric, general practice, and medical settings, there would appear to be quantitatively and possibly qualitative differences to the nature of depression in medical contexts, making general measure extrapolation problematic.