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Scott A. Baldwin

Researcher at Brigham Young University

Publications -  96
Citations -  6553

Scott A. Baldwin is an academic researcher from Brigham Young University. The author has contributed to research in topics: Generalizability theory & Poison control. The author has an hindex of 35, co-authored 90 publications receiving 5698 citations. Previous affiliations of Scott A. Baldwin include University of Memphis.

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Untangling the alliance-outcome correlation: exploring the relative importance of therapist and patient variability in the alliance.

TL;DR: Clinical implications include therapists monitoring their contribution to the alliance, clinics providing feedback to therapists about their alliances, and therapists receiving training to develop and maintain strong alliances.
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Does marriage and relationship education work? A meta-analytic study.

TL;DR: A lack of racial/ethnic and economic diversity in the samples prevented reliable conclusions about the effectiveness of MRE for disadvantaged couples, a crucial deficit in the body of research.
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Continuing Bonds and Reconstructing Meaning: Mitigating Complications in Bereavement.

TL;DR: An interaction emerged between sense-making and ongoing attachment to the deceased, suggesting that strong continuing bonds predicted greater levels of traumatic and especially separation distress, but only when the survivor was unable to make sense of the loss in personal, practical, existential, or spiritual terms.
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Meta-analysis of MFT interventions.

TL;DR: These meta-analyses support the efficacy of both MFT for distressed couples, and martial and family enrichment, and the concept of meta-analytically supported treatments (MASTs) is introduced, which are treatments that meet certain criteria for efficacy in meta-analysis, and which remedy certain problems in the empirically supported treatment (EST) literature.
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A tutorial on count regression and zero-altered count models for longitudinal substance use data

TL;DR: This article provides a tutorial on methods for analyzing longitudinal substance use data, focusing on Poisson, zero-inflated, and hurdle mixed models, which are types of hierarchical or multilevel models.