Literature DB >> 35176503

Design and methodology for an integrative data analysis of coping power: Direct and indirect effects on adolescent suicidality.

Antonio A Morgan-López1, Heather L McDaniel2, Catherine P Bradshaw2, Lissette M Saavedra3, John E Lochman4, Chelsea A Kaihoi2, Nicole P Powell4, Lixin Qu4, Anna C Yaros3.   

Abstract

As suicide rates have risen in the last decade, there has been greater emphasis on targeting early risk conditions for suicidality among youth and adolescents as a form of suicide "inoculation". Two particular needs that have been raised in this nascent literature are a) the dearth of examination of early intervention effects on distal suicide risk that target externalizing behaviors and b) the need to harmonize multiple existing intervention datasets for greater precision in modeling intervention effects on low base rate outcomes such as suicidal behaviors. This project, entitled "Integrative Data Analysis of Coping Power (CP): Effects on Adolescent Suicidality", funded by the National Institute of Mental Health (NIMH), will harmonize and analyze data from 11 randomized controlled trials of CP (total individual-level N = 3183, total school-level N = 189). CP is an empirically-supported, child- and family-focused preventive intervention that focuses on reducing externalizing more broadly among youth who exhibit early aggression, which makes it ideally suited to targeting externalizing pathways to suicidality. The project utilizes three measurement and data analysis frameworks that have emerged across multiple independent disciplines: integrative data analysis (IDA), random treatment effects multilevel modeling (RTE-MLM), and propensity score weighting (PSW). If successful, the project will a) provide initial evidence that CP would have gender-specific indirect effects on suicidality through reductions in externalizing for boys and reductions in internalizing for girls and b) identify optimal conditions under which CP is delivered (e.g., groups, individuals, online) across participants on reductions in suicidality and other key intermediate endpoints.
Copyright © 2022 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Early intervention; Integrative data analysis; Meta-analysis of individual patient data; Suicide prevention

Mesh:

Year:  2022        PMID: 35176503      PMCID: PMC9018598          DOI: 10.1016/j.cct.2022.106705

Source DB:  PubMed          Journal:  Contemp Clin Trials        ISSN: 1551-7144            Impact factor:   2.261


  57 in total

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2.  Age- and sex-related risk factors for adolescent suicide.

Authors:  D A Brent; M Baugher; J Bridge; T Chen; L Chiappetta
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3.  Alternative Approaches to Addressing Non-Normal Distributions in the Application of IRT Models to Personality Measures.

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4.  Developmental approach to prevent adolescent suicides: research pathways to effective upstream preventive interventions.

Authors:  Peter A Wyman
Journal:  Am J Prev Med       Date:  2014-09       Impact factor: 5.043

5.  Differences in early childhood risk factors for juvenile-onset and adult-onset depression.

Authors:  Sara R Jaffee; Terrie E Moffitt; Avshalom Caspi; Eric Fombonne; Richie Poulton; Judith Martin
Journal:  Arch Gen Psychiatry       Date:  2002-03

Review 6.  Prevention Programs to Augment Family and Child Resilience Can Have Lasting Effects on Suicidal Risk.

Authors:  David Brent
Journal:  Suicide Life Threat Behav       Date:  2016-04

7.  The Correspondence Between Causal and Traditional Mediation Analysis: the Link Is the Mediator by Treatment Interaction.

Authors:  David P MacKinnon; Matthew J Valente; Oscar Gonzalez
Journal:  Prev Sci       Date:  2020-02

8.  Psychiatric diagnosis in child and adolescent suicide.

Authors:  D Shaffer; M S Gould; P Fisher; P Trautman; D Moreau; M Kleinman; M Flory
Journal:  Arch Gen Psychiatry       Date:  1996-04

9.  Vital Signs: Trends in State Suicide Rates - United States, 1999-2016 and Circumstances Contributing to Suicide - 27 States, 2015.

Authors:  Deborah M Stone; Thomas R Simon; Katherine A Fowler; Scott R Kegler; Keming Yuan; Kristin M Holland; Asha Z Ivey-Stephenson; Alex E Crosby
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2018-06-08       Impact factor: 17.586

10.  A study of alternative approaches to non-normal latent trait distributions in item response theory models used for health outcome measurement.

Authors:  Niels Smits; Oğuzhan Öğreden; Mauricio Garnier-Villarreal; Caroline B Terwee; R Philip Chalmers
Journal:  Stat Methods Med Res       Date:  2020-03-11       Impact factor: 3.021

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  1 in total

1.  Mitigating Multiple Sources of Bias in a Quasi-Experimental Integrative Data Analysis: Does Treating Childhood Anxiety Prevent Substance Use Disorders in Late Adolescence/Young Adulthood?

Authors:  Lissette M Saavedra; Antonio A Morgan-López; Stephen G West; Margarita Alegría; Wendy K Silverman
Journal:  Prev Sci       Date:  2022-09-03
  1 in total

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