Parsing the general and specific components of depression and anxiety with bifactor modeling.
Recent hierarchical models suggest that both general and specific components are needed to fully represent the variation observed among mood and anxiety disorders. However, little is known about the relative size, severity, and psychological meaning of these components. We studied these features through bifactor modeling of the symptoms from the Inventory of Depression and Anxiety Symptoms [IDAS; Watson et al., 2007] in 362 community adults, 353 psychiatric patients, and 673 undergraduates. Results revealed that although all IDAS symptom types loaded prominently both on a general factor as well as specific factors, some symptom groups--such as dysphoria, generalized anxiety, and irritability--were influenced more strongly by the general factor, whereas others--e.g., appetite gain, appetite loss, and low well-being--contained a larger specific component. Second, certain symptom groups--e.g., Suicidality, Panic, Appetite Loss, and Ill Temper--reflected higher severity than other symptom groups. Finally, general factor scores correlated strongly with markers of general distress and negative emotionality. These findings support a hierarchical structure among mood and anxiety symptoms and have important implications for how such disorders are described, assessed, and studied.
Simms
Leonard J
LJ
Department of Psychology, The State University of New York, Buffalo, New York 14221, USA. ljsimms@buffalo.edu
Grös
Daniel F
DF
Watson
David
D
O'Hara
Michael W
MW
D000293:Adolescent; D000328:Adult; D000368:Aged; D001008:Anxiety Disorders / Q000145:classification / Q000175:diagnosis / Q000523:psychology*; D003866:Depressive Disorder / Q000145:classification / Q000175:diagnosis / Q000523:psychology*; D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008960:Models, Psychological; D010555:Personality Inventory / Q000706:statistics & numerical data*; D011594:Psychometrics / Q000706:statistics & numerical data; D012016:Reference Values