Brief motivational intervention (BMI) and personalized feedback intervention (PFI) are individual-focused brief alcohol intervention approaches that have been proven efficacious for reducing alcohol ...use among college students and young adults. Although the efficacy of these two intervention approaches has been well established, little is known about the factors that may modify their effects on alcohol outcomes. In particular, high school drinking may be a risk factor for continued and heightened use of alcohol in college, and thus may influence the outcomes of BMI and PFI. The purpose of this study was to investigate whether high school drinking was associated with different intervention outcomes among students who received PFI compared to those who received BMI. We conducted moderation analyses examining 348 mandated students (60.1% male; 73.3% White; and 61.5% first-year student) who were randomly assigned to either a BMI or a PFI and whose alcohol consumption was assessed at 4-month and 15-month follow-ups. Results from marginalized zero-inflated Poisson models showed that high school drinking moderated the effects of PFI and BMI at the 4-month follow-up but not at the 15-month follow-up. Specifically, students who reported no drinking in their senior year of high school consumed a 49% higher mean number of drinks after receiving BMI than PFI at the 4-month follow-up. The results suggest that alcohol consumption in high school may be informative when screening and allocating students to appropriate alcohol interventions to meet their different needs.
Many clinical endpoint measures, such as the number of standard drinks consumed per week or the number of days that patients stayed in the hospital, are count data with excessive zeros. However, the ...zero‐inflated nature of such outcomes is sometimes ignored in analyses of clinical trials. This leads to biased estimates of study‐level intervention effect and, consequently, a biased estimate of the overall intervention effect in a meta‐analysis. The current study proposes a novel statistical approach, the Zero‐inflation Bias Correction (ZIBC) method, that can account for the bias introduced when using the Poisson regression model, despite a high rate of inflated zeros in the outcome distribution of a randomized clinical trial. This correction method only requires summary information from individual studies to correct intervention effect estimates as if they were appropriately estimated using the zero‐inflated Poisson regression model, thus it is attractive for meta‐analysis when individual participant‐level data are not available in some studies. Simulation studies and real data analyses showed that the ZIBC method performed well in correcting zero‐inflation bias in most situations.
An overlooked sequela of HIV risk is trauma exposure, yet few HIV interventions address trauma exposure, mental health, and substance misuse. In a two-arm randomized controlled trial 73 Native ...American women were randomized to a culturally-adapted Cognitive Processing Therapy (CPT) or 6-weeks waitlist. Outcomes assessed: PTSD symptom severity, alcohol use frequency, substance abuse or dependence diagnosis, and high-risk sexual behavior defined as vaginal/anal intercourse (a) under the influence of alcohol and/or illicit substances, (b) with a partner who was concurrently sexually active with someone else, and/or (c) with more than one partner in the past 6 weeks. Among immediate intervention participants, compared to waitlist participants, there were large reductions in PTSD symptom severity, high-risk sexual behavior, and a medium-to-large reduction in the frequency of alcohol use. CPT appears to improve mental health and risk behaviors, suggesting that addressing PTSD may be one way of improving HIV-risk related outcomes.
Summary
Many clinical endpoint measures, such as the number of standard drinks consumed per week or the number of days that patients stayed in the hospital, are count data with excessive zeros. ...However, the zero‐inflated nature of such outcomes is sometimes ignored in analyses of clinical trials. This leads to biased estimates of study‐level intervention effect and, consequently, a biased estimate of the overall intervention effect in a meta‐analysis. The current study proposes a novel statistical approach, the Zero‐inflation Bias Correction (ZIBC) method, that can account for the bias introduced when using the Poisson regression model, despite a high rate of inflated zeros in the outcome distribution of a randomized clinical trial. This correction method only requires summary information from individual studies to correct intervention effect estimates as if they were appropriately estimated using the zero‐inflated Poisson regression model, thus it is attractive for meta‐analysis when individual participant‐level data are not available in some studies. Simulation studies and real data analyses showed that the ZIBC method performed well in correcting zero‐inflation bias in most situations.
Objective
American Indian and Alaskan Natives (AIAN) are regenerating cultural knowledge and practices to adapt westernized evidence-based interventions to address health concerns such as substance ...use. This study describes the process of selecting, adapting, and implementing motivational interviewing plus cognitive behavior therapy (motivational interviewing + Skills Training; MIST) for use in a combined substance use intervention with a rural, Northwest tribal community.
Methods
An established community and academic partnership worked together to make culturally mindful changes to MIST. The partnership incorporated community leaders/Elders (n = 7), providers (n = 9), and participants (n = 50) to implement an iterative process of adapting and implementing the adapted form of MIST.
Results
Key adaptations included presenting concepts grounded in tribal values, providing examples from the community perspective, and incorporating cultural customs and traditions. Overall, the MIST adaptation was favorably received by participants, and the adaptation appeared feasible.
Conclusions
Adapted MIST appeared to be an acceptable intervention for this Native American community. Future research should evaluate the interventions efficacy in reducing substance use among this and other Native American communities. Future clinical research should consider strategies outlined in this adaptation as a potential process for working with Native American communities to implement culturally appropriate interventions.
In research applications, mental health problems such as alcohol-related problems and depression are commonly assessed and evaluated using scale scores or latent trait scores derived from factor ...analysis or item response theory models. This tutorial paper demonstrates the use of cognitive diagnosis models (CDMs) as an alternative approach to characterizing mental health problems of young adults when item-level data are available. Existing measurement approaches focus on estimating the general severity of a given mental health problem at the scale level as a unidimensional construct without accounting for other symptoms of related mental health problems. The prevailing approaches may ignore clinically meaningful presentations of related symptoms at the item level. The current study illustrates CDMs using item-level data from college students (40 items from 719 respondents; 34.6% men, 83.9% White, and 16.3% first-year students). Specifically, we evaluated the constellation of four postulated domains (i.e., alcohol-related problems, anxiety, hostility, and depression) as a set of attribute profiles using CDMs. After accounting for the impact of each attribute (i.e., postulated domain) on the estimates of attribute profiles, the results demonstrated that when items or attributes have limited information, CDMs can utilize item-level information in the associated attributes to generate potentially meaningful estimates and profiles, compared to analyzing each attribute independently. We introduce a novel visual inspection aid, the lens plot, for quantifying this gain. CDMs may be a useful analytical tool to capture respondents’ risk and resilience for prevention research.
Background
For over 2 decades, brief motivational interventions (BMIs) have been implemented on college campuses to reduce heavy drinking and related negative consequences. Such interventions include ...in‐person motivational interviews (MIs), often incorporating personalized feedback (PF), and stand‐alone PF interventions delivered via mail, computer, or the Web. Both narrative and meta‐analytic reviews using aggregate data from published studies suggest at least short‐term efficacy of BMIs, although overall effect sizes have been small.
Methods
This study was an individual participant‐level data (IPD) meta‐analysis of 17 randomized clinical trials evaluating BMIs. Unlike typical meta‐analysis based on summary data, IPD meta‐analysis allows for an analysis that correctly accommodates the sampling, sample characteristics, and distributions of the pooled data. In particular, highly skewed distributions with many zeroes are typical for drinking outcomes, but have not been adequately accounted for in existing studies. Data are from Project INTEGRATE, one of the largest IPD meta‐analysis projects to date in alcohol intervention research, representing 6,713 individuals each with 2 to 5 repeated measures up to 12 months postbaseline.
Results
We used Bayesian multilevel over dispersed Poisson hurdle models to estimate intervention effects on drinks per week and peak drinking, and Gaussian models for alcohol problems. Estimates of overall intervention effects were very small and not statistically significant for any of the outcomes. We further conducted post hoc comparisons of 3 intervention types (individual MI with PF, PF only, and group MI) versus control. There was a small, statistically significant reduction in alcohol problems among participants who received an individual MI with PF. Short‐term and long‐term results were similar.
Conclusions
This study questions the efficacy and magnitude of effects of BMIs for college drinking prevention and intervention and suggests a need for the development of more effective intervention strategies.
To evaluate and optimize brief alcohol interventions (BAIs), it is critical to have a credible overall effect size estimate as a benchmark. Estimating such an effect size has been challenging because ...alcohol outcomes often represent responses from a mixture of individuals: those at high risk for alcohol misuse, occasional nondrinkers, and abstainers. Moreover, some BAIs exclusively focus on heavy drinkers, whereas others take a universal prevention approach. Depending on sample characteristics, the outcome distribution might have many zeros or very few zeros and overdispersion; consequently, the most appropriate statistical model may differ across studies. We synthesized individual participant data (IPD) from 19 studies in Project INTEGRATE (Mun et al.,
2015b
) that randomly allocated participants to intervention and control groups (
N
= 7,704 participants, 38.4% men, 74.7% White, 58.5% first-year students). We sequentially estimated marginalized zero-inflated Poisson (Long et al.,
2014
) or negative binomial regression models to obtain covariate-adjusted, study-specific intervention effect estimates in the first step, which were subsequently combined in a random-effects meta-analysis model in the second step. BAIs produced a statistically significant 8% advantage in the mean number of drinks at both 1–3 months (
RR
= 0.92, 95%
CI
= 0.85, 0.98) and 6 months (
RR
= 0.92, 95%
CI
= 0.85, 0.99) compared to controls. At 9–12 months, there was no statistically significant difference in the mean number of drinks between BAIs and controls. In conclusion, BAIs are effective at reducing the mean number of drinks through at least 6 months post intervention. IPD can play a critical role in deriving findings that could not be obtained in original individual studies or standard aggregate data meta-analyses.
Abstract
Aims
College students who drink are at an increased risk of driving after drinking and alcohol-involved traffic accidents and deaths. Furthermore, the persistence of driving after drinking ...over time underscores a need for effective interventions to prevent future drunk driving in adulthood. The present study examined whether brief alcohol interventions (BAIs) for college students reduce driving after drinking.
Methods
A two-step meta-analysis of individual participant data (IPD) was conducted using a combined sample of 6801 college students from 15 randomized controlled trials (38% male, 72% White and 58% first-year students). BAIs included individually delivered Motivational Interviewing with Personalized Feedback (MI + PF), Group Motivational Interviewing (GMI), and stand-alone Personalized Feedback (PF) interventions. Two outcome variables, driving after two+/three+ drinks and driving after four+/five+ drinks, were checked, harmonized and analyzed separately for each study and then combined for meta-analysis and meta-regression analysis.
Results
BAIs lowered the risk of driving after four+/five+ drinks (19% difference in the odds of driving after drinking favoring BAIs vs. control), but not the risk of driving after two+/three+ drinks (9% difference). Subsequent subgroup analysis indicated that the MI + PF intervention was comparatively better than PF or GMI.
Conclusions
BAIs provide a harm reduction approach to college drinking. Hence, it is encouraging that BAIs reduce the risk of driving after heavy drinking among college students. However, there may be opportunities to enhance the intervention content and timing to be more relevant for driving after drinking and improve the outcome assessment and reporting to demonstrate its effect.
Short Summary: BAIs have been a prevailing intervention strategy to prevent harm from drinking among college students. We found that BAIs statistically significantly lowered the risk of driving after four+/five+ drinks in a two-step meta-analysis of IPD. We provide clinical and methodological suggestions to enhance the effect.
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