title: Using Implicit and Explicit Measures to Predict Nonsuicidal Self-Injury Among Adolescent Inpatients.
abstract: OBJECTIVE
  To examine the use of implicit and explicit measures to predict adolescent nonsuicidal self-injury (NSSI) before, during, and after inpatient hospitalization.
  
  
  METHODS
  Participants were 123 adolescent psychiatric inpatients who completed measures at hospital admission and discharge. The implicit measure (Self-Injury Implicit Association Test [SI-IAT]) and one of the explicit measures pertained to the NSSI method of cutting. Patients were interviewed at multiple time points at which they reported whether they had engaged in NSSI before their hospital stay, during their hospital stay, and within 3 months after discharge.
  
  
  RESULTS
  At baseline, SI-IAT scores differentiated past-year self-injurers and noninjurers (t121 = 4.02, p < .001, d = 0.73). These SI-IAT effects were stronger among patients who engaged in cutting (versus noncutting NSSI methods). Controlling for NSSI history and prospective risk factors, SI-IAT scores predicted patients' subsequent cutting behavior during their hospital stay (odds ratio (OR) = 8.19, CI = 1.56-42.98, p < .05). Patients' explicit self-report uniquely predicted hospital-based and postdischarge cutting, even after controlling for SI-IAT scores (ORs = 1.82-2.34, CIs = 1.25-3.87, p values <.01). Exploratory analyses revealed that in specific cases in which patients explicitly reported low likelihood of NSSI, SI-IAT scores still predicted hospital-based cutting.
  
  
  CONCLUSIONS
  The SI-IAT is an implicit measure that is outcome-specific, a short-term predictor above and beyond NSSI history, and potentially helpful in cases in which patients at risk for NSSI explicitly report that they would not do so in the future. Ultimately, both implicit and explicit measures can help to predict future incidents of cutting among adolescent inpatients.
authors.affiliation: Teachers College, Columbia University, New York. Electronic address: cha@tc.columbia.edu.
authors.forename: Christine B
authors.initials: CB
authors.lastname: Cha
authors.affiliation: Boston Children's Hospital.
authors.forename: Tara M
authors.initials: TM
authors.lastname: Augenstein
authors.affiliation: Boston Children's Hospital.
authors.forename: Katherine H
authors.initials: KH
authors.lastname: Frost
authors.affiliation: Boston Children's Hospital.
authors.forename: Katie
authors.initials: K
authors.lastname: Gallagher
authors.affiliation: Boston Children's Hospital; Harvard Medical School, Boston.
authors.forename: Eugene J
authors.initials: EJ
authors.lastname: D'Angelo
authors.affiliation: Harvard University, Cambridge, MA, Boston Children's Hospital, and the Center on the Developing Child at Harvard University.
authors.forename: Matthew K
authors.initials: MK
authors.lastname: Nock
mesh_terms: D000293:Adolescent; D000067290:Behavior Rating Scale; D005260:Female; D006801:Humans; D007297:Inpatients / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D001523:Mental Disorders / Q000145:classification / Q000150:complications*; D015999:Multivariate Analysis; D011379:Prognosis; D011446:Prospective Studies; D011569:Psychiatric Status Rating Scales; D012307:Risk Factors; D057566:Self Report; D016728:Self-Injurious Behavior / Q000453:epidemiology*
keywords: IAT; prediction; risk factor; self-injury; self-report