Measuring the suicidal mind: implicit cognition predicts suicidal behavior.
Suicide is difficult to predict and prevent because people who consider killing themselves often are unwilling or unable to report their intentions. Advances in the measurement of implicit cognition provide an opportunity to test whether automatic associations of self with death can provide a behavioral marker for suicide risk. We measured implicit associations about death/suicide in 157 people seeking treatment at a psychiatric emergency department. Results confirmed that people who have attempted suicide hold a significantly stronger implicit association between death/suicide and self than do psychiatrically distressed individuals who have not attempted suicide. Moreover, the implicit association of death/suicide with self was associated with an approximately 6-fold increase in the odds of making a suicide attempt in the next 6 months, exceeding the predictive validity of known risk factors (e.g., depression, suicide-attempt history) and both patients' and clinicians' predictions. These results provide the first evidence of a behavioral marker for suicidal behavior and suggest that measures of implicit cognition may be useful for detecting and predicting sensitive clinical behaviors that are unlikely to be reported.
Nock
Matthew K
MK
Department of Psychology, Harvard University, USA. nock@wjh.harvard.edu
Park
Jennifer M
JM
Finn
Christine T
CT
Deliberto
Tara L
TL
Dour
Halina J
HJ
Banaji
Mahzarin R
MR
D000328:Adult; D001244:Association; D001293:Attitude to Death; D003071:Cognition; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D008297:Male; D001523:Mental Disorders / Q000453:epidemiology / Q000523:psychology; D008875:Middle Aged; D016017:Odds Ratio; D010555:Personality Inventory / Q000706:statistics & numerical data; D011594:Psychometrics; D012307:Risk Factors; D012649:Self Concept; D013223:Statistics as Topic; D013406:Suicide, Attempted / Q000517:prevention & control / Q000523:psychology* / Q000706:statistics & numerical data