2018
DOI: 10.1007/s11121-018-0942-1
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Empirically Based Mean Effect Size Distributions for Universal Prevention Programs Targeting School-Aged Youth: A Review of Meta-Analyses

Abstract: This review of reviews presents an empirically based set of mean effect size distributions for judging the relative impact of the effects of universal mental health promotion and prevention programs for school-age youth (ages 5 through 18) across a range of program targets and types of outcomes. Mean effect size distributions were established by examining the findings from 74 meta-analyses of universal prevention and promotion programs that included more than 1100 controlled outcome studies involving over 490,… Show more

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Cited by 104 publications
(91 citation statements)
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“…In general, results suggest these CBT Tech interventions are efficacious at reducing alcohol use when delivered as a stand‐alone treatment or when tested as an addition to usual care. The overall magnitude of pooled effects was small as defined by Cohen (), but these benchmarks should be considered only in the absence of an empirically derived distribution of effect sizes for a given population (Tanner‐Smith et al., ). The largest pooled effects found here ( g = 0.3) were produced from studies that evaluated CBT Tech interventions as an add‐on to TAU compared to TAU only.…”
Section: Discussionmentioning
confidence: 99%
“…In general, results suggest these CBT Tech interventions are efficacious at reducing alcohol use when delivered as a stand‐alone treatment or when tested as an addition to usual care. The overall magnitude of pooled effects was small as defined by Cohen (), but these benchmarks should be considered only in the absence of an empirically derived distribution of effect sizes for a given population (Tanner‐Smith et al., ). The largest pooled effects found here ( g = 0.3) were produced from studies that evaluated CBT Tech interventions as an add‐on to TAU compared to TAU only.…”
Section: Discussionmentioning
confidence: 99%
“…The effect size is a robust estimator to analyze intervention effects at an individual level, but it is not the best indicator to analyze the social impact of universal interventions (Greenberg & Abenavoli, 2017). A recent review of meta-analyses concludes that Cohen's d effect size is not appropriate for interpreting the magnitude of effects of universal prevention programs aimed at school-age youth (Tanner-Smith et al, 2018). Universal prevention programs are aimed at populations that may not have any symptoms or high levels of risk.…”
Section: Discussionmentioning
confidence: 99%
“…According with Tanner-Smith et al (2018), effects sizes of universal programs with youth are especially low when they are specifically aimed at preventing substance use (P25 = 0.05, median = 0.07, P75 = 0.11) or alcohol use (P25 = 0.05, median = 0.10, P75 = 0.15). Considering these distributions of effects, Mantente REAL shows relatively high effects sizes on alcohol outcomes, above the values associated with the 75th percentile for programs with these characteristics.…”
Section: Discussionmentioning
confidence: 99%
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“…Fortunately, many evidence-based substance use prevention programs exist. A review of evidencebased interventions for preventing substance use and abuse among youth highlights numerous exemplary prevention programs that can be implemented at the individual, group, family, school or community level (Griffin & Botvin, 2010;Knight et al, 2019;Shelton, 2005;Tanner-Smith, Durlak, & Marx, 2018).…”
Section: Introductionmentioning
confidence: 99%