A Tutorial on Cognitive Diagnosis Modeling for Characterizing Mental Health Symptom Profiles Using Existing Item Responses.

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.

Brief Alcohol Interventions are Effective through 6 Months: Findings from Marginalized Zero-inflated Poisson and Negative Binomial Models in a Two-step IPD Meta-analysis.

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.

Which is Better for Individual Participant Data Meta-Analysis of Zero-Inflated Count Outcomes, One-Step or Two-Step Analysis? A Simulation Study.

Meta-analysis using individual participant data (IPD) is an important methodology in intervention research because it (a) increases accuracy and precision of estimates, (b) allows researchers to investigate mediators and moderators of treatment effects, and (c) makes use of extant data. IPD meta-analysis can be conducted either via a one-step approach that uses data from all studies simultaneously, or a two-step approach, which aggregates data for each study and then combines them in a traditional meta-analysis model. Unfortunately, there are no evidence-based guidelines for how best to approach IPD meta-analysis for count outcomes with many zeroes, such as alcohol use. We used simulation to compare the performance of four hurdle models (3 one-step and 1 two-step models) for zero-inflated count IPD, under realistic data conditions. Overall, all models yielded adequate coverage and bias for the treatment effect in the count portion of the model, across all data conditions. However, in the zero portion, the treatment effect was underestimated in most models and data conditions, especially when there were fewer studies. The performance of both one- and two-step approaches depended on the formulation of the treatment effects, suggesting a need to carefully consider model assumptions and specifications when using IPD.

Change in alcohol demand following a brief intervention predicts change in alcohol use: A latent growth curve analysis.

BACKGROUND: The association between behavioral economic demand and various alcohol use outcomes is well established. However, few studies have examined whether changes in demand occur following a brief alcohol intervention (BAI), and whether this change predicts alcohol outcomes over the long term. METHODS: Parallel process piecewise latent growth curve models were examined in a sample of 393 heavy drinking emerging adults (60.8% women; 85.2% white; Mage  = 18.77). In these models, two linear slopes represented rates of change in alcohol use, heavy drinking episodes, alcohol-related problems, and demand (intensity and highest expenditure across all price points or Omax ) from baseline to 1 month (slope 1) and 1 month to 16 months (slope 2). Mediation analyses were conducted to estimate the effect of a BAI on 16-month alcohol outcomes through slope 1 demand. RESULTS: A two-session BAI predicted significant reductions in all five outcomes from baseline to 1-month follow-up. Although no further reduction was observed from the 1-month to the 16-month follow-up, there was no regression to baseline levels. Slope 1 demand intensity, but not Omax , significantly mediated the association between BAI and both outcomes-heavy drinking episodes (Est. = -0.23, SE = 0.08, p < 0.01) and alcohol-related problems (Est. = -0.15, SE = 0.07, p < 0.05)-at the 16-month follow-up. CONCLUSIONS: Reducing high valuation of alcohol among heavy drinking emerging adults within the first month following BAI is critical for the long-term efficacy of the intervention. A two-session BAI was associated with enduring reductions in alcohol demand, and the change in demand intensity, but not Omax , was associated with sustained reductions in heavy drinking and alcohol-related problems.

Development and preliminary effectiveness of a smartphone-based, just-in-time adaptive intervention for adults with alcohol misuse who are experiencing homelessness.

BACKGROUND: Adults experiencing homelessness have much higher rates of alcohol misuse than housed individuals. This study describes the development and preliminary effectiveness of a smartphone-based, just-in-time adaptive intervention (JITAI) to reduce alcohol use among adults experiencing homelessness. METHODS: We conducted a pilot trial (N = 41; mean age [SD] = 45.2 [11.5]; 19.5% women) of the Smart-T Alcohol JITAI where participants completed brief ecological momentary assessments (EMAs) each day, received personalized treatment messages following each EMA, and accessed on-demand intervention content for 4 weeks. The prediction algorithm and treatment messages were developed based on an independent but similar sample as part of the trial. We examined three drinking outcomes: daily drinking (yes/no), drinks per day, and heavy episodic drinking, controlling for scores on the Alcohol Use Disorders Identification Test (AUDIT) at baseline, age, and sex using quadratic growth curve models. RESULTS: Over the 4-week period, participants showed a decline in all alcohol use outcomes. Participants also reported high levels of satisfaction with the JITAI. CONCLUSIONS: Use of the Smart-T Alcohol JITAI was well received and provided encouraging evidence that it may reduce any drinking, drinks per day, and heavy episodic drinking among adults experiencing homelessness.

Do Brief Alcohol Interventions Reduce Driving After Drinking Among College Students? A Two-step Meta-analysis of Individual Participant Data.

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.

A Structural Equation Modeling Approach to Meta-analytic Mediation Analysis Using Individual Participant Data: Testing Protective Behavioral Strategies as a Mediator of Brief Motivational Intervention Effects on Alcohol-Related Problems.

This paper introduces a meta-analytic mediation analysis approach for individual participant data (IPD) from multiple studies. Mediation analysis evaluates whether the effectiveness of an intervention on health outcomes occurs because of change in a key behavior targeted by the intervention. However, individual trials are often statistically underpowered to test mediation hypotheses. Existing approaches for evaluating mediation in the meta-analytic context are limited by their reliance on aggregate data; thus, findings may be confounded with study-level differences unrelated to the pathway of interest. To overcome the limitations of existing meta-analytic mediation approaches, we used a one-stage estimation approach using structural equation modeling (SEM) to combine IPD from multiple studies for mediation analysis. This approach (1) accounts for the clustering of participants within studies, (2) accommodates missing data via multiple imputation, and (3) allows valid inferences about the indirect (i.e., mediated) effects via bootstrapped confidence intervals. We used data (N = 3691 from 10 studies) from Project INTEGRATE (Mun et al. Psychology of Addictive Behaviors, 29, 34-48, 2015) to illustrate the SEM approach to meta-analytic mediation analysis by testing whether improvements in the use of protective behavioral strategies mediate the effectiveness of brief motivational interventions for alcohol-related problems among college students. To facilitate the application of the methodology, we provide annotated computer code in R and data for replication. At a substantive level, stand-alone personalized feedback interventions reduced alcohol-related problems via greater use of protective behavioral strategies; however, the net-mediated effect across strategies was small in size, on average.

Ecological Momentary Assessment of Alcohol Consumption and Its Concordance with Transdermal Alcohol Detection and Timeline Follow-Back Self-report Among Adults Experiencing Homelessness.

BACKGROUND: Studies of alcohol use presume valid assessment measures. To evaluate this presumption, we examined the concordance of alcohol use as measured by ecological momentary assessment (EMA) self-reports, transdermal alcohol concentration readings via the Secure Continuous Remote Alcohol Monitor (SCRAM), and retrospective self-reports via the Timeline Follow-Back (TLFB) among adults experiencing homelessness. METHODS: Forty-nine adults who reported alcohol misuse (mean age = 47, SD = 9; 57% Black; 82% men) were recruited from a homeless shelter. For 4 weeks, alcohol use was assessed: (i) 5 times or more per day by EMA, (ii) every 30 minutes by a SCRAM device worn on the ankle, and (iii) by TLFB for the past month at the end of the study period. There were 1,389 days of observations of alcohol use and alcohol use intensity for 49 participants. RESULTS: EMA and SCRAM alcohol use data agreed on 73% of days, with an interrater agreement Kappa = 0.46. A multilevel analysis of concordance of 3 measures for alcohol use yielded statistically significant correlations of 0.40 (day level) and 0.63 (person level) between EMA and SCRAM. Alcohol use was detected on 49, 38, and 33% of days by EMA, SCRAM, and TLFB, respectively. For alcohol use intensity, EMA and SCRAM resulted in statistically significant correlations of 0.46 (day level) and 0.78 (person level). The concordance of TLFB with either EMA or SCRAM was weak, especially at the day level. CONCLUSIONS: This is the first study to examine concordance of alcohol use estimates using EMA, SCRAM, and TLFB methods in adults experiencing homelessness. EMA is a valid approach to quantifying alcohol use, especially given its relatively low cost, low participant burden, and ease of use. Furthermore, any stigma associated with wearing the SCRAM or reporting alcohol use in person may be attenuated by using EMA, which may be appealing for use in studies of stigmatized and underserved populations.

A bias correction method in meta-analysis of randomized clinical trials with no adjustments for zero-inflated outcomes.

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.

Getting to the Heart of Low Sensitivity to Alcohol: Context Moderates Low Cardiovascular Response to Alcohol in Persons With a Family History of Alcohol Use Disorder.

BACKGROUND: Low sensitivity to alcohol in persons with a family history of alcoholism (FH+), compared to those without (FH-), contributes to risk for alcohol use disorder (AUD). However, sensitivity of FH+ cardiovascular response to alcohol is not well understood. This gap is significant because cardiovascular processes contribute to emotional regulation and stress response problems theorized to be central to the development and persistence of AUD. This study compared changes in heart rate (HR) and HR variability (HRV) between FH groups after consuming alcohol and control beverages and examined how these changes were moderated by emotional and alcohol-related contexts. METHODS: Young adults (N = 165) with FH+ (n = 110) or FH- (n = 55) each completed 2 sessions, separated by 1 week. They received one of 3 different beverages (alcohol, placebo, and told-no-alcohol) in each session. Electrocardiogram data were recorded during pre-beverage consumption and post-beverage consumption baselines, and then during 4 picture cue tasks (neutral, positive, negative, and alcohol-related). Generalized estimating equations were used to examine differences in cardiovascular reactivity (changes in HR and HRV power at ~ 0.1 Hz) across FH groups, beverage conditions, and picture cue tasks. RESULTS: A significant beverage condition × cue task × FH interaction effect on HRV was observed. The FH+ group, compared to the FH- group, showed (a) significantly less HRV suppression in specific cue contexts following alcohol, (b) a mixed pattern of more and less HRV suppression across cue contexts following placebo, and (c) a similar HRV reactivity pattern in the told-no-alcohol condition across cue tasks. For HR, there were no significant effects involving FH. CONCLUSIONS: Diminished cardiovascular sensitivity to oral alcohol in FH+ persons varied within a given drinking episode depending on emotional and alcohol-related features of the context, suggesting that environmental characteristics play a role in the expression of low sensitivity to alcohol among FH+ individuals.

The association between protective behavioral strategies and alcohol-related problems: An examination of race and gender differences among college drinkers.

This study examined race and gender differences in use of specific types of protective behavioral strategies (PBS) and the moderating effects of race and gender on the relationship between PBS use and alcohol problems, controlling for alcohol use, among a large sample of Asian, Black, and White college drinkers. There were significant racial and gender differences in the types of PBS used. Moderation analyses indicated that PBS were more protective for women than men against experiencing alcohol-related problems. There were no significant race effects or race-by-gender interaction effects on alcohol problems. Implementing PBS may be beneficial for all college students.

Brief motivational interventions for college student drinking may not be as powerful as we think: an individual participant-level data meta-analysis.

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.

A computational physiology approach to personalized treatment models: the beneficial effects of slow breathing on the human cardiovascular system.

Heart rate variability biofeedback intervention involves slow breathing at a rate of ∼6 breaths/min (resonance breathing) to maximize respiratory and baroreflex effects on heart period oscillations. This intervention has wide-ranging clinical benefits and is gaining empirical support as an adjunct therapy for biobehavioral disorders, including asthma and depression. Yet, little is known about the system-level cardiovascular changes that occur during resonance breathing or the extent to which individuals differ in cardiovascular benefit. This study used a computational physiology approach to dynamically model the human cardiovascular system at rest and during resonance breathing. Noninvasive measurements of heart period, beat-to-beat systolic and diastolic blood pressure, and respiration period were obtained from 24 healthy young men and women. A model with respiration as input was parameterized to better understand how the cardiovascular processes that control variability in heart period and blood pressure change from rest to resonance breathing. The cost function used in model calibration corresponded to the difference between the experimental data and model outputs. A good match was observed between the data and model outputs (heart period, blood pressure, and corresponding power spectral densities). Significant improvements in several modeled cardiovascular functions (e.g., blood flow to internal organs, sensitivity of the sympathetic component of the baroreflex, ventricular elastance) were observed during resonance breathing. Individual differences in the magnitude and nature of these dynamic responses suggest that computational physiology may be clinically useful for tailoring heart rate variability biofeedback interventions for the needs of individual patients.

Drinking game play among first-year college student drinkers: an event-specific analysis of the risk for alcohol use and problems.

BACKGROUND: College students who play drinking games (DGs) more frequently report higher levels of alcohol use and experience more alcohol-related harm. However, the extent to which they are at risk for increased consumption and harm as a result of DG play on a given event after accounting for their typical DG participation, and typical and event drinking, is unclear. OBJECTIVES: We examined whether first-year students consumed more alcohol and were more likely to experience consequences on drinking occasions when they played DGs. METHODS: Participants (n = 336) completed up to six web-based surveys following weekend drinking events in their first semester. Alcohol use, DG play, and consequences were reported for the Friday and Saturday prior to each survey. Typical DG tendencies were controlled in all models. Typical and event alcohol use were controlled in models predicting risk for consequences. RESULTS: Participants consumed more alcohol on DG versus non-DG events. All students were more likely to experience blackout drinking consequences when they played DGs. Women were more likely to experience social-interpersonal consequences when they played DGs. CONCLUSION: DG play is an event-specific risk factor for increased alcohol use among first-year students, regardless of individual DG play tendencies. Further, event DG play signals increased risk for blackout drinking consequences for all students, and social-interpersonal consequences for women, aside from the amount of alcohol consumed on those occasions as well as typical drinking behaviors. Prevention efforts to reduce high-risk drinking may be strengthened by highlighting both event- and person-specific risks of DG play.

A Peer-Led High School Transition Program Increases Graduation Rates Among Latino Males.

The present study investigated the impact of a manualized high school transition program, the Peer Group Connection (PGC) program, on the graduation rate at a low-income, Mid-Atlantic high school. The program utilized twelfth grade student peer leaders to create a supportive environment for incoming ninth grade students. Results of a randomized control trial demonstrated that male students who participated in the program during ninth grade were significantly more likely to graduate from high school within four years than male students in the control group (81% versus 63%). Findings suggest that peers can be effective in delivering a school-based, social emotional learning intervention and that it is possible to intervene in the ninth grade to influence the probability of high school graduation.

Log-Linear and Configural Analysis of Intra-Individual Time Series under Consideration of Serial Dependence.

Serial dependence often prevents researchers from obtaining unbiased parameter estimates. In this article, we propose taking serial dependence into account, and exploiting the information that comes with serial dependence. This can be done in the form of shifted variables that are included in addition to the original variables, when models are specified. This way, models become more complex but relations can be considered that, otherwise, cannot be analyzed. Two fields of application are discussed. The first is log-linear modeling. This method is variable-oriented, but it has found applications in person-oriented research. The gain from including shifted variables in log-linear models is that new, specific variable relations can be analyzed. The second field is that of Configural Frequency Analysis. This method is person-oriented, and it allows researchers to detect local relations that, without consideration of shifted variables, cannot be detected. Application examples are given in the context of single-case analysis.

The selection of statistical models for reporting count outcomes and intervention effects in brief alcohol intervention trials: A review and recommendations.

Understanding the efficacy and relative effectiveness of a brief alcohol intervention (BAI) relies on obtaining a credible intervention effect estimate. Outcomes in BAI trials are often count variables, such as the number of drinks consumed, which may be overdispersed (i.e., greater variability than expected based on a given model) and zero-inflated (i.e., greater probability of zeros than expected based on a given model). Ignoring such distribution characteristics can lead to biased estimates and invalid statistical conclusions. In this critical review, we identified and reviewed 64 articles that reported count outcomes from a systematic review of BAI trials for adolescents and young adults from 2013 to 2018. Given many statistical models to choose from when analyzing count outcomes, we reviewed the models used and reporting practices in the BAI trial literature. A majority (61.3%) of analyses with count outcomes used linear models despite violations of normality assumptions; 75.6% of outcome variables demonstrated clear overdispersion. We provide an overview of available count models (Poisson, negative binomial, zero-inflated or hurdle, and marginalized zero-inflated Poisson regression) and formulate practical guidelines for reporting outcomes of BAIs. We provide a visual step-by-step decision guide for selecting appropriate statistical models and reporting results for count outcomes. We list accessible resources to help researchers select an appropriate model with which to analyze their data. Recent advances in count distribution-based models hold promise for evaluating count outcomes to gauge the efficacy and effectiveness of BAIs and identify critical covariates in alcohol epidemiologic research. We recommend that researchers report the distributional properties of count outcomes, such as the proportion of zero counts, and select an appropriate statistical analysis for count outcomes using the provided decision tree. By following these recommendations, future research may yield more accurate, transparent, and reproducible results.

Treatment outcomes of a combined cognitive behavior therapy and pharmacotherapy for a sample of women with and without substance abuse histories on an acute psychiatric unit: do therapeutic alliance and motivation matter?

BACKGROUND AND OBJECTIVES: Women with comorbid psychiatric and substance abuse problems (PwSA) experience more consequences from their use and typically have the poorest prognosis and outcome, compared to those with psychiatric problems but without substance abuse problems (PwoSA). The present study examined outcomes of a combined intensive inpatient cognitive behavior therapy (CBT) and pharmacotherapy program for women with PwSA and PwoSA. METHODS: Sample consisted of 117 women on a women-only acute inpatient unit (PwSA = 50, PwoSA = 67). RESULTS: Women in both groups made significant improvements in psychological functioning. High motivation at admission and therapeutic alliance at discharge were associated with improved psychological functioning at discharge for both groups. SCIENTIFIC SIGNIFICANCE: Findings provide preliminary support for the efficacy of a combined CBT and pharmacotherapy program for women with psychiatric diagnoses on a women-only acute inpatient unit, and for pre-treatment motivation and therapeutic alliance as important correlates of better treatment outcomes.

Negative mood and alcohol problems are related to respiratory dynamics in young adults.

This study examined the relationship of negative affect and alcohol use behaviors to baseline respiration and respiratory response to emotional challenge in young adults (N = 138, 48 % women). Thoracic-to-abdominal ratio, respiratory frequency and variability, and minute volume ventilation were measured during a low-demand baseline task, and emotional challenge (viewing emotionally-valenced, emotionally-neutral, and alcohol-related pictures). Negative mood and alcohol problems principal components were generated from self-report measures of negative affect and mood, alcohol use, and use-related problems. The negative mood component was positively related to a thoracic bias when measured throughout the study (including baseline and picture exposure). There was generally greater respiratory activity in response to the picture cues, although not specifically in response to the content (emotional or alcohol-related) of the picture cues. The alcohol problems component was positively associated with respiratory reactivity to picture cues, when baseline breathing patterns were controlled. Self-report arousal data indicated that higher levels of negative mood, but not alcohol problems, were associated with greater arousal ratings overall. However, those with alcohol problems reported greater arousal to alcohol cues, compared to emotionally neutral cues. These results are consistent with theories relating negative affect and mood to breathing patterns as well as the relationship between alcohol problems and negative emotions, suggesting that the use of respiratory interventions may hold promise for treating problems involving negative affect and mood, as well as drinking problems.

Do brief motivational interventions increase motivation for change in drinking among college students? A two-step meta-analysis of individual participant data.

BACKGROUND: Brief motivational interventions (BMIs) are one of the most effective individually focused alcohol intervention strategies for college students. Despite the central theoretical role of motivation for change in BMIs, it is unclear whether BMIs increase motivation to change drinking behavior. We conducted a two-step meta-analysis of individual participant data (IPD) to examine whether BMIs increase motivation for change. N = 5903;59% women, 72% White) from Project INTEGRATE. The BMIs included individually delivered motivational interviewing with personalized feedback (MI + PF), stand-alone personalized feedback (PF), and group-based motivational interviewing (GMI). METHODS: We included 15 trials of BMI (N = 5903;59% women, 72% White) from Project INTEGRATE. The BMIs included individually-delivered motivational interviewing with personalized feedback (MI + PF), stand-alone personalized feedback (PF), and group-based motivational interviewing (GMI). Different measures and responses used in the original trials were harmonized. Effect size estimates were derived from a model that adjusted for baseline motivation and demographic variables for each trial (step 1) and subsequently combined in a random-effects meta-analysis (step 2). RESULTS: The overall intervention effect of BMIs on motivation for change was not statistically significant (standard mean difference [SMD]: 0.026, 95% CI: [-0.001, 0.053], p = 0.06, k = 19 comparisons). Of the three subtypes of BMIs, GMI, which tended to provide motivation-targeted content, had a statistically significant intervention effect on motivation, compared with controls (SMD: 0.055, 95% CI: [0.007, 0.103], p = 0.025, k = 5). By contrast, there was no evidence that MI + PF (SMD = 0.04, 95% CI: [-0.02, 0.10], k = 6, p = 0.20) nor PF increased motivation (SMD = 0.005, 95% CI: [-0.028, 0.039], k = 8, p = 0.75), compared with controls. Post hoc meta-regression analysis suggested that motivation sharply decreased each month within the first 3 months postintervention (b = -0.050, z = -2.80, p = 0.005 for k = 14). CONCLUSIONS: Although BMIs provide motivational content and normative feedback and are assumed to motivate behavior change, the results do not wholly support the hypothesis that BMIs improve motivation for change. Changing motivation is difficult to assess during and following interventions, but it is still a theoretically important clinical endpoint. Further, the evidence cautiously suggests that changing motivation may be achievable, especially if motivation-targeted content components are provided.