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Adolescent Suicide Attempt Prevention: Predictors of Response to a Cognitive–Behavioral Family and Youth Centered Intervention
Author(s) -
Babeva Kali.,
Klomhaus Alexandra M.,
Sugar Catherine A.,
Fitzpatrick Olivia,
Asarnow Joan R.
Publication year - 2020
Publication title -
suicide and life‐threatening behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.544
H-Index - 90
eISSN - 1943-278X
pISSN - 0363-0234
DOI - 10.1111/sltb.12573
Subject(s) - depression (economics) , clinical psychology , intervention (counseling) , suicide attempt , psychological intervention , psychology , behavioral activation , cognition , logistic regression , psychiatry , poison control , suicide prevention , medicine , medical emergency , economics , macroeconomics
Objective Suicide is a leading cause of adolescent death. Recent data support the efficacy of cognitive–behavioral treatments with strong family components for reducing suicide risk; however, not all youth benefit from current interventions. Identifying predictors of treatment response can inform treatment selection and optimize benefits. Method This study examines predictors of response to a DBT‐informed cognitive–behavioral family treatment (SAFETY), among 50 youth with recent suicide attempts/self‐harm. Youth and parents were assessed at baseline and post‐treatment. Results Results indicated medium‐to‐large effect sizes for SAFETY on youth suicidal behavior (SB; defined as suicide attempts, aborted attempts, and planning), depression, hopelessness, social adjustment, and parental depression. Classification tree analysis, with a correct classification rate of 93.3%, and follow‐up logistic analyses indicated that 35% of youths reporting active SB at baseline reported active SB at post‐treatment, whereas post‐treatment SB was rare among youths whose active suicidality had resolved by the baseline assessment (5%). Among youths reporting baseline SB, those endorsing sleep problems were more likely to report post‐treatment SB (53%) versus those without sleep problems (0%). Conclusions These findings highlight the potential value of personalized treatment approaches based on pretreatment characteristics and the significance of baseline SB and sleep problems for predicting treatment response.

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