Self-complexity and the persistence of depression.
Self-complexity, a measure of the structure of cognition involving the self, was used to predict the persistence of depression in patients diagnosed with major depression. Self-descriptions offered by depressed patients were analyzed using a clustering algorithm to model cognitive structure. Indices of positive and negative self-complexity, derived from the resulting models, were used to predict depressive symptomatology 9 months after the onset of a major depression. Negative self-complexity uniquely predicted subsequent levels of depression even after the effects of initial levels of depression, self-evaluation, and dysfunctional attitudes were statistically removed. Highly complex negative self-representation appears to be associated with poor recovery from a major depressive episode. Future studies examining the relationship between cognition and psychopathology should investigate, in addition to its content, the formal and structural properties of cognition.
Woolfolk
R L
RL
Department of Psychology, Rutgers University, Piscataway, New Jersey 08854-8040, USA.
Gara
M A
MA
Ambrose
T K
TK
Williams
J E
JE
Allen
L A
LA
Irvin
S L
SL
Beaver
J D
JD
D000328:Adult; D001290:Attitude; D001364:Awareness; D003071:Cognition; D003866:Depressive Disorder / Q000175:diagnosis* / Q000523:psychology; D004198:Disease Susceptibility; D005260:Female; D006801:Humans; D007257:Information Theory; D008297:Male; D008960:Models, Psychological; D010555:Personality Inventory / Q000706:statistics & numerical data; D011336:Probability; D011569:Psychiatric Status Rating Scales / Q000706:statistics & numerical data; D012044:Regression Analysis; D012649:Self Concept; D012938:Social Perception