Statistical significance is the least interesting thing about the results. You should describe the results in terms of measures of magnitude -not just, does a treatment affect people, but how much does it affect them.-Gene V. Glass 1The primary product of a research inquiry is one or more measures of effect size, not P values.-Jacob Cohen 2 T hese statements about the importance of effect sizes were made by two of the most influential statistician-researchers of the past half-century. Yet many submissions to Journal of Graduate Medical Education omit mention of the effect size in quantitative studies while prominently displaying the P value. In this paper, we target readers with little or no statistical background in order to encourage you to improve your comprehension of the relevance of effect size for planning, analyzing, reporting, and understanding education research studies. What Is Effect Size?In medical education research studies that compare different educational interventions, effect size is the magnitude of the difference between groups. The absolute effect size is the difference between the average, or mean, outcomes in two different intervention groups. For example, if an educational intervention resulted in the improvement of subjects' examination scores by an average total of 15 of 50 questions as compared to that of another intervention, the absolute effect size is 15 questions or 3 grade levels (30%) better on the examination. Absolute effect size does not take into account the variability in scores, in that not every subject achieved the average outcome.In another example, residents' self-assessed confidence in performing a procedure improved an average of 0.4 point on a Likert-type scale ranging from 1 to 5, after simulation training. While the absolute effect size in the first example appears clear, the effect size in the second example is less apparent. Is a 0.4 change a lot or trivial? Accounting for variability in the measured improvement may aid in interpreting the magnitude of the change in the second example.Thus, effect size can refer to the raw difference between group means, or absolute effect size, as well as standardized measures of effect, which are calculated to transform the effect to an easily understood scale. Absolute effect size is useful when the variables under study have intrinsic meaning (eg, number of hours of sleep). Calculated indices of effect size are useful when the measurements have no intrinsic meaning, such as numbers on a Likert scale; when studies have used different scales so no direct comparison is possible; or when effect size is examined in the context of variability in the population under study.Calculated effect sizes can also quantitatively compare results from different studies and thus are commonly used in meta-analyses. Why Report Effect Sizes?The effect size is the main finding of a quantitative study. While a P value can inform the reader whether an effect exists, the P value will not reveal the size of the effect. In reporting and interpreting stu...

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Objective: Topiramate has been shown to reduce drinking and heavy drinking in alcohol-dependent individuals whose goal was to stop drinking. The present study evaluated the efficacy and tolerability of topiramate in heavy drinkers whose treatment goal was to reduce drinking to safe levels. Method: We randomly assigned 138 individuals (62.3% male) to receive 12 weeks of treatment with topiramate (N=67), at a maximal daily dosage of 200 mg, or matching placebo (N=71), both groups receiving brief counseling to reduce drinking and increase abstinent days. We hypothesized that topiramate-treated patients would be better able to achieve these goals and predicted that, based on prior research, the effects would be moderated by a single nucleotide polymorphism (rs2832407) in GRIK1, encoding the kainate GluK1 receptor subunit. Results: The rate of treatment completion was 84.9% and equal by treatment group. Topiramate treatment significantly reduced heavy drinking days (p<0.001) and increased abstinent days (p=0.032) relative to placebo. The topiramate group also had lower concentrations of the liver enzyme γ-glutamyltranspeptidase and lower scores on a measure of alcohol-related problems than the placebo group. In a European-American subsample (N=122), topiramate’s effect on heavy drinking days (p=0.004) was significantly greater than for placebo only in rs2832407 C-allele homozygotes. Conclusions: These findings support the use of topiramate 200 mg/day to reduce heavy drinking in problem drinkers. The moderator effect of rs2832407, if validated, would facilitate the identification of heavy drinkers who are likely to respond well to topiramate treatment and provide an important personalized treatment option. The pharmacogenetic findings also implicate the kainate receptor in the mechanism of topiramate’s effects on heavy drinking. www.clinicaltrials.gov registration: NCT00626925

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The neurotransmitter serotonin (5-HT) has been shown to regulate alcohol consumption in both animals and humans. Since activity of the 5-HT transporter protein (5-HTT) regulates 5-HT levels, the gene encoding this protein may contribute to the risk of alcohol dependence (AD). Studies of the association to AD of a functional insertion-deletion polymorphism in the 5-HTT-linked promoter region (5-HTTLPR) have yielded inconsistent results. We conducted a meta-analysis of data from 17 published studies (including 3,489 alcoholics and 2,325 controls) investigating the association between 5-HTTLPR alleles and AD. The frequency of the short (S) allele at 5-HTTLPR was significantly associated with AD [odds ratio (OR) = 1.18, 95% CI = 1.03-1.33). Moreover, a greater association with the S allele was seen among individuals with AD complicated by either a co-morbid psychiatric condition or an early-onset or more severe AD subtype [OR = 1.34 (95% CI = 1.11-1.63)]. Allelic variation at 5-HTTLPR contributes to risk for AD, with the greatest effect observed among individuals with a co-occurring clinical feature.

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Despite the pervasive use of social media by young adults, there is comparatively little known about whether, and how, engagement in social media influences this group's drinking patterns and risk of alcohol-related problems. We examined the relations between young adults' alcohol-related social media engagement (defined as the posting, liking, commenting, and viewing of alcohol-related social media content) and their drinking behavior and problems. We conducted a systematic review and meta-analysis of studies evaluating the association of alcohol consumption and alcohol-related problems with alcohol-related social media engagement. Summary baseline variables regarding the social media platform used (e.g., Facebook and Twitter), social media measures assessed (e.g., number of alcohol photographs posted), alcohol measures (e.g., Alcohol Use Disorders Identification Test and Timeline Follow back Interview), and the number of time points at which data were collected were extracted from each published study. We used the Q statistic to examine heterogeneity in the correlations between alcohol-related social media engagement and both drinking behavior and alcohol-related problems. Because there was significant heterogeneity, we used a random-effects model to evaluate the difference from zero of the weighted aggregate correlations. We used metaregression with study characteristics as moderators to test for moderators of the observed heterogeneity. Following screening, 19 articles met inclusion criteria for the meta-analysis. The primary findings indicated a statistically significant relationship and moderate effect sizes between alcohol-related social media engagement and both alcohol consumption (r = 0.36, 95% CI: 0.29 to 0.44, p < 0.001) and alcohol-related problems (r = 0.37, 95% CI: 0.21 to 0.51, p < 0.001). There was significant heterogeneity among studies. Two significant predictors of heterogeneity were (i) whether there was joint measurement of alcohol-related social media engagement and drinking behavior or these were measured on different occasions and (ii) whether measurements were taken by self-report or observation of social media engagement. We found moderate-sized effects across the 19 studies: Greater alcohol-related social media engagement was correlated with both greater self-reported drinking and alcohol-related problems. Further research to determine the causal direction of these associations could provide opportunities for social media-based interventions with young drinkers aimed at reducing alcohol consumption and alcohol-related adverse consequences.

GABA A receptors are involved in the subjective effects of alcohol. Endogenous neuroactive steroids interact with GABA A receptors to mediate several behavioral effects of alcohol in rodents. Based on a haplotypic association of alcohol dependence with the gene encoding the GABA A receptor a-2 subunit (GABRA2), we examined whether GABRA2 alleles are associated with the subjective response to alcohol. We also examined whether finasteride (a 5-a steroid reductase inhibitor), which blocks the synthesis of some neuroactive steroids, reduces the subjective response to alcohol. In all, 27 healthy social drinkers (15 males) completed a randomized, double-blind, placebo-controlled study of high-dose finasteride. After being pretreated with study drug, subjects consumed three alcoholic drinks. Subjective effects were measured repeatedly over the ascending blood alcohol curve. To examine the moderating role of genetic variation in GABRA2, a single-nucleotide polymorphism that was informative in association studies was included as a factor in the analysis. Subjects homozygous for the more common A-allele (n ¼ 7) showed more subjective effects of alcohol than did individuals with one or two copies of the alcohol dependence-associated G-allele (n ¼ 20, including two homozygotes). Among the A-allele homozygotes, there was a greater reduction in several subjective effects during the finasteride session compared to the placebo session. These findings provide preliminary evidence that the risk of alcoholism associated with GABRA2 alleles may be related to differences in the subjective response to alcohol. The effects of finasteride provide indirect evidence for a mediating role of neuroactive steroids in some of the subjective effects of alcohol.