OBJECTIVE: To differentiate clinical and non-clinical depression via a set of symptoms.
METHODS: A sample of 140 patients attending a clinical service for those with mood disorders together with 40 subjects denying ever experiencing a clinical episode of depression were compared, with participants completing a questionnaire capturing many symptoms of depression as well as illness correlates.
RESULTS: A latent class analysis of symptom data identified two classes and with class assignment corresponding strongly with initial clinical versus non-clinical assignment. Univariate analyses identified the extent to which individual symptoms contributed to differentiation. Study data suggested DSM criteria that would benefit from re-writing or of reassignment. Two models for classifying clinical depression were generated. The first involved individuals feeling hopeless and also being suicidal or at risk of self-harm. The second involved a symptom set corresponding to DSM-5 criteria but with only five making significant independent contributions to diagnostic differentiation.
CONCLUSION: The study is heuristic in offering a strategy for more precisely differentiating clinical and non-clinical depression in more representative samples, so allowing resolution of key features, and determining whether a monothetic or polythetic diagnostic symptom criterion model is optimal.