Is Motivational Interviewing Effective at Reducing Alcohol Misuse in Young Adults? A Critical Review of Foxcroft et al. (2014)

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Abstract

Foxcroft, Coombes, Wood, Allen, and Almeida Santimano (2014) recently conducted a meta-analysis evaluating the effectiveness of motivational interviewing (MI) in reducing alcohol misuse for youth up to Age 25. They concluded that the overall effect sizes of MI in this population were too small to be clinically meaningful. The present article critically reviews the Foxcroft et al. meta-analysis, highlighting weaknesses such as problems with search strategies, flawed screening and reviews of full-text articles, incorrect data abstraction and coding, and, accordingly, improper effect size estimation. In addition, between-study heterogeneity and complex data structures were not thoughtfully considered or handled using best practices for meta-analysis. These limitations undermine the reported estimates and broad conclusion made by Foxcroft et al. about the lack of MI effectiveness for youth. We call for new evidence on this question from better-executed studies by independent researchers. Meta-analysis has many important utilities for translational research. When implemented well, the overall effectiveness, as well as different effectiveness for different populations, can be examined via meta-analysis. Emerging methods utilizing individual participant-level data, such as integrative data analysis, may be particularly helpful for identifying the sources of clinical and methodological heterogeneity that matter. The need to better understand the mechanisms of alcohol interventions has never been louder in the addiction field. Through more concerted efforts throughout all phases of generating evidence, we may achieve largescale evidence that is efficient and robust and provides critical answers for the field.

Original languageEnglish
Pages (from-to)836-846
Number of pages11
JournalPsychology of Addictive Behaviors
Volume29
Issue number4
DOIs
StatePublished - 1 Dec 2015

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Motivational Interviewing
Meta-Analysis
Young Adult
Alcohols
Benchmarking
Translational Medical Research
Population
Research Personnel

Keywords

  • alcohol interventions
  • brief motivational interventions
  • college students
  • integrative data analysis
  • meta-analysis

Cite this

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title = "Is Motivational Interviewing Effective at Reducing Alcohol Misuse in Young Adults? A Critical Review of Foxcroft et al. (2014)",
abstract = "Foxcroft, Coombes, Wood, Allen, and Almeida Santimano (2014) recently conducted a meta-analysis evaluating the effectiveness of motivational interviewing (MI) in reducing alcohol misuse for youth up to Age 25. They concluded that the overall effect sizes of MI in this population were too small to be clinically meaningful. The present article critically reviews the Foxcroft et al. meta-analysis, highlighting weaknesses such as problems with search strategies, flawed screening and reviews of full-text articles, incorrect data abstraction and coding, and, accordingly, improper effect size estimation. In addition, between-study heterogeneity and complex data structures were not thoughtfully considered or handled using best practices for meta-analysis. These limitations undermine the reported estimates and broad conclusion made by Foxcroft et al. about the lack of MI effectiveness for youth. We call for new evidence on this question from better-executed studies by independent researchers. Meta-analysis has many important utilities for translational research. When implemented well, the overall effectiveness, as well as different effectiveness for different populations, can be examined via meta-analysis. Emerging methods utilizing individual participant-level data, such as integrative data analysis, may be particularly helpful for identifying the sources of clinical and methodological heterogeneity that matter. The need to better understand the mechanisms of alcohol interventions has never been louder in the addiction field. Through more concerted efforts throughout all phases of generating evidence, we may achieve largescale evidence that is efficient and robust and provides critical answers for the field.",
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