Literature DB >> 28550456

What Doesn't Work for Whom? Exploring Heterogeneity in Responsiveness to the Family Check-Up in Early Childhood Using a Mixture Model Approach.

William E Pelham1, Thomas J Dishion2,3, Jenn-Yun Tein2, Daniel S Shaw4, Melvin N Wilson5.   

Abstract

This study applied latent class analysis to a family-centered prevention trial in early childhood to identify subgroups of families with differential responsiveness to the Family Check-Up (FCU) intervention. The sample included 731 families with 2-year-olds randomized to the FCU or control condition and followed through age 5 with yearly follow-up assessments. A two-step mixture model was used to examine whether specific constellations of family characteristics at age 2 (baseline) were related to intervention response across ages 3, 4, and 5. The first step empirically identified latent classes of families based on several family risk and adjustment variables selected on the basis of previous research. The second step modeled the effect of the FCU on longitudinal change in children's problem behavior in each of the empirically derived latent classes. Results suggested a five-class solution, where a significant intervention effect of moderate to large size was observed in one of the five classes-the class characterized by child neglect, legal problems, and parental mental health issues. Pairwise comparisons revealed that the intervention effect was significantly greater in this class of families than in two other classes that were generally less at risk for the development of child disruptive behavior problems, albeit still low-income. Thus, findings suggest that (a) the FCU is most successful in reducing child problem behavior in more highly distressed, low-income families, and (b) the FCU may have little impact for relatively low-risk, low-income families. Future directions include the development of a brief screening process that can triage low-income families into groups that should be targeted for intervention, redirected to other services, monitored prospectively, or left alone.

Entities:  

Keywords:  Intervention response; Latent class analysis; Moderation

Mesh:

Year:  2017        PMID: 28550456      PMCID: PMC5693624          DOI: 10.1007/s11121-017-0805-1

Source DB:  PubMed          Journal:  Prev Sci        ISSN: 1389-4986


  25 in total

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2.  Prevention of problem behavior through annual family check-ups in early childhood: intervention effects from home to early elementary school.

Authors:  Thomas J Dishion; Lauretta M Brennan; Daniel S Shaw; Amber D McEachern; Melvin N Wilson; Booil Jo
Journal:  J Abnorm Child Psychol       Date:  2014

3.  Predictors of Participation in the Family Check-Up Program: a Randomized Trial of Yearly Services from Age 2 to 10 Years.

Authors:  Justin D Smith; Cady Berkel; Katherine A Hails; Thomas J Dishion; Daniel S Shaw; Melvin N Wilson
Journal:  Prev Sci       Date:  2018-07

Review 4.  Strategy of outcome research in psychotherapy.

Authors:  G L Paul
Journal:  J Consult Psychol       Date:  1967-04

Review 5.  Developmental theories of parental contributors to antisocial behavior.

Authors:  D S Shaw; R Q Bell
Journal:  J Abnorm Child Psychol       Date:  1993-10

6.  Who disrupts from placement in foster and kinship care?

Authors:  Patricia Chamberlain; Joe M Price; John B Reid; John Landsverk; Phillip A Fisher; Mike Stoolmiller
Journal:  Child Abuse Negl       Date:  2006-04-05

7.  Predictors of parent training efficacy for child externalizing behavior problems--a meta-analytic review.

Authors:  Sandra M Reyno; Patrick J McGrath
Journal:  J Child Psychol Psychiatry       Date:  2006-01       Impact factor: 8.982

8.  The family check-up with high-risk indigent families: preventing problem behavior by increasing parents' positive behavior support in early childhood.

Authors:  Thomas J Dishion; Daniel Shaw; Arin Connell; Frances Gardner; Chelsea Weaver; Melvin Wilson
Journal:  Child Dev       Date:  2008 Sep-Oct

9.  Empirically derived subtypes of adolescent depression: latent profile analysis of co-occurring symptoms in the Treatment for Adolescents with Depression Study (TADS).

Authors:  Keith C Herman; Rick Ostrander; John T Walkup; Susan G Silva; John S March
Journal:  J Consult Clin Psychol       Date:  2007-10

10.  A transactional approach to preventing early childhood neglect: The Family Check-Up as a public health strategy.

Authors:  Thomas J Dishion; Chung Jung Mun; Emily C Drake; Jenn-Yun Tein; Daniel S Shaw; Melvin Wilson
Journal:  Dev Psychopathol       Date:  2015-11
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  13 in total

1.  Who Benefits from Community Mental Health Care? Using Latent Profile Analysis to Identify Differential Treatment Outcomes for Youth.

Authors:  F Tony Bonadio; Carolyn Tompsett
Journal:  J Youth Adolesc       Date:  2018-07-04

2.  Predictors of Participation in the Family Check-Up Program: a Randomized Trial of Yearly Services from Age 2 to 10 Years.

Authors:  Justin D Smith; Cady Berkel; Katherine A Hails; Thomas J Dishion; Daniel S Shaw; Melvin N Wilson
Journal:  Prev Sci       Date:  2018-07

3.  Effects of the Family Check-Up on reducing growth in conduct problems from toddlerhood through school age: An analysis of moderated mediation.

Authors:  Elizabeth C Shelleby; Daniel S Shaw; Thomas J Dishion; Melvin N Wilson; Frances Gardner
Journal:  J Consult Clin Psychol       Date:  2018-10

4.  Supporting Strategic Investment in Social Programs: a Cost Analysis of the Family Check-Up.

Authors:  Margaret R Kuklinski; D Max Crowley; Thomas J Dishion; Melvin N Wilson; William E Pelham; Daniel S Shaw
Journal:  Prev Sci       Date:  2020-02

5.  Secondary Analysis to Inform the Development of Adaptive Preventive Interventions.

Authors:  Ahnalee M Brincks; Tatiana Perrino; George W Howe
Journal:  Clin Child Fam Psychol Rev       Date:  2022-08-04

6.  Parent and Child Risk Profiles as Predictors of Response to a Conduct Problem Preventive Intervention.

Authors:  Timothy F Piehler; Jingchen Zhang; Michael L Bloomquist; Gerald J August
Journal:  Prev Sci       Date:  2022-04-29

7.  Baseline Targeted Moderation in a Trial of the Family Check-Up 4 Health: Potential Explanations for Finding Few Practical Effects.

Authors:  Justin D Smith; Allison J Carroll; Emily Fu; Cady Berkel
Journal:  Prev Sci       Date:  2021-06-22

8.  Latent Impulsivity Subtypes in Substance Use Disorders and Interactions with Internalizing and Externalizing Co-Occurring Disorders.

Authors:  Rodrigo Marín-Navarrete; Aldebarán Toledo-Fernández; Luis Villalobos-Gallegos; Carlos Roncero; Nestor Szerman; María Elena Medina-Mora
Journal:  Front Psychiatry       Date:  2018-02-09       Impact factor: 4.157

9.  The ADHD teen integrative data analysis longitudinal (TIDAL) dataset: background, methodology, and aims.

Authors:  Margaret H Sibley; Stefany J Coxe
Journal:  BMC Psychiatry       Date:  2020-07-08       Impact factor: 3.630

10.  Understanding Who Benefits from Parenting Interventions for Children's Conduct Problems: an Integrative Data Analysis.

Authors:  Patty Leijten; Maartje Raaijmakers; Leoniek Wijngaards; Walter Matthys; Ankie Menting; Maud Hemink-van Putten; Bram Orobio de Castro
Journal:  Prev Sci       Date:  2018-05
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