The continuity of depression symptoms: Use of cluster analysis for profile identification in patient and student samples

doi:10.1016/S0165-0327(00)00253-6

Journal of Affective Disorders

Volume 65, Issue 1, June 2001, Pages 67-73

https://doi.org/10.1016/S0165-0327(00)00253-6 Get rights and content

Abstract

Background: Findings from several sources suggest that depression lies on a continuum whereby mild and severe variants are thought to differ in severity (i.e., quantitatively), but not in kind (i.e., qualitatively). The current study used cluster analysis to extend this work to examination of depression symptom profiles obtained in distressed student ‘analogue’ samples and clinically depressed samples. Method: Patients with major depressive disorder (n=101) provided seed points for the depressed cluster, and 176 non-distressed university students (Beck Depression Inventory score ≤8) provided seed points for the non-depressed cluster. The symptom profiles of three levels of analogue depressed samples were then evaluated (BDI≥9, BDI≥16, and BDI≥21). Results: Only 35.4% of BDI≥9 analogue respondents were empirically sorted to the depression cluster and the majority were assigned to the non-depressed cluster. The proportion assigned to the depression cluster increased to 70.5% and to 86.2% when higher BDI cutoffs of 16 and 21 were examined, respectively. The DSM-IV depression symptom profile of the BDI≥21 group was very similar to the profile defined by clinical patients. Limitations: The study relied solely on self-report to assess symptom severity. Conclusions: It is recommended that higher BDI cutoffs be utilized in analogue depression research than is currently common. On quantitative grounds, analogue subjects who were sorted to the clinically defined depression cluster seem to best represent the idea of depression continuity.

Section snippets

Participants

The clinically depressed sample consisted of 101 adult outpatients with a primary DSM-IV (APA, 1994) diagnosis of major depressive disorder (59 females, 42 males; mean age=44.39 years; S.D.=14.05). All patients were experiencing a DSM-IV-defined major depressive episode and were non-psychotic. Dysthymia (29%), panic disorder (21%) and social phobia (17%) were the most common comorbid conditions.

The non-clinical sample comprised 351 undergraduate university students. The analogue depressed group

Statistical recovery of clinically depressed patients and non-distressed students

It is important to establish the sensitivity of the clustering algorithm (i.e., its ability to identify known cases of depression) if cluster assignments are to be useful. Therefore, the DDS symptom profiles of the 101 clinically depressed patients were analyzed with the clustering procedure, to determine if a high percentage could be ‘recovered’. This requirement was met, with 96.0% being correctly classified. An identical procedure was employed with the non-distressed college students and

Discussion

The marked similarity of the prototypical cluster profiles of the non-depressed, analogue, and clinical samples is reflective of the qualitative similarity previously identified (Cox et al., 1999). The present results shed light on the nature of the quantitative differences in depression symptom continuity in non-clinical and clinical samples. The close match in the DSM-IV depression symptom profiles of the more conservatively selected analogue groups and their clinical counterparts is apparent

Acknowledgements

This research was supported by an operating grant from the Manitoba Health Research Council. The authors are grateful to Sharon Borger for assistance with data collection and analysis, and to Drs. Harvey Keselman and Keith Wilson for their helpful comments on an earlier version of this paper.

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Brief reportThe continuity of depression symptoms: Use of cluster analysis for profile identification in patient and student samples

Abstract

Section snippets

Participants

Statistical recovery of clinically depressed patients and non-distressed students

Discussion

Acknowledgements

J. Affect. Dis.

Behav. Res. Ther.

J. Affect. Dis.

Diagnostic and Statistical Manual of Mental Disorders

Cognitive Therapy of Depression

An inventory for measuring depression

Arch. Gen. Psychiatry

Structured Clinical Interview for DSM-IV axis I Disorders

Brief report
The continuity of depression symptoms: Use of cluster analysis for profile identification in patient and student samples