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BACKGROUND: The symptoms of major depression (MD) are clinically diverse. Do they form coherent factors that might clarify the underlying nature of this important psychiatric syndrome? METHOD: Symptoms at lifetime worst depressive episode were assessed at structured psychiatric interview in 6008 women of Han Chinese descent, age ⩾30 years with recurrent DSM-IV MD. Exploratory factor analysis (EFA) and confirmatoryfactor analysis (CFA) were performed in Mplus in random split-half samples. RESULTS: The preliminary EFA results were consistently supported by the findings from CFA. Analyses of the nine DSM-IV MD symptomatic A criteria revealed two factors loading on: (i) general depressive symptoms; and (ii) guilt/suicidal ideation. Examining 14 disaggregated DSM-IV criteria revealed three factors reflecting: (i) weight/appetite disturbance; (ii) general depressive symptoms; and (iii) sleep disturbance. Using all symptoms (n = 27), we identified five factors that reflected: (i) weight/appetite symptoms; (ii) general retarded depressive symptoms; (iii) atypical vegetative symptoms; (iv) suicidality/hopelessness; and (v) symptoms of agitation and anxiety. CONCLUSIONS: MD is a clinically complex syndrome with several underlying correlated symptom dimensions. In addition to a general depressive symptom factor, a complete picture must include factors reflecting typical/atypical vegetative symptoms, cognitive symptoms (hopelessness/suicidal ideation), and an agitated symptom factor characterized by anxiety, guilt, helplessness and irritability. Prior cross-cultural studies, factor analyses of MD in Western populations and empirical findings in this sample showing risk factor profiles similar to those seen in Western populations suggest that our results are likely to be broadly representative of the human depressive syndrome.

Original publication

DOI

10.1017/S003329171300192X

Type

Journal article

Journal

Psychol Med

Publication Date

05/2014

Volume

44

Pages

1391 - 1401

Keywords

Adult, China, Depressive Disorder, Major, Factor Analysis, Statistical, Female, Humans, Middle Aged