Trait impulsivity moderates rate of alcohol consumption in daily life.

INTRODUCTION: Rate of alcohol consumption, the speed with which people drink, has been linked to a range of outcomes, including alcohol use disorder symptoms and increased positive affect. However, minimal work has identified who is most likely to drink at elevated rates. Impulsivity is associated with increased attention to positive reinforcers specifically (e.g., positive affect). We therefore examined whether people higher in trait impulsivity engage in faster consumption during drinking episodes. METHODS: Participants were current drinkers (N = 113; 54 people with borderline personality disorder [BPD], a disorder that involves elevated impulsivity, and 59 community people) who completed a 21-day ecological momentary assessment (EMA) protocol. Multilevel models of drinking episodes (Nobservations = 3,444) examined whether self-reported trait impulsivity, measured at baseline, was associated with faster rise in estimated blood alcohol concentration (eBAC) at each follow-up period. RESULTS: All UPPS sub-scales were associated with faster rise in eBAC across a drinking episode. In a multivariate model including all sub-scales as simultaneous predictors, sensation seeking and (lack of) perseverance were independently positively associated with rate of consumption. Additional analyses indicated that greater negative urgency and sensation seeking were associated with faster rises in eBAC in participants with BPD, relative to community comparisons. CONCLUSION: In a sample that captured a wide spectrum of impulsivity, greater impulsivity was associated with drinking alcohol at a faster rate. People higher in sensation seeking and (lack of) perseverance may be prone to drink at faster rates out of a desire to maximize the hedonic effects of alcohol. PUBLIC SIGNIFICANCE STATEMENT: This study finds that people who are more impulsive tend to drink alcohol faster, putting them at greater risk for negative consequences. This may explain, in part, why impulsivity is linked to experiencing alcohol-related problems.

New Frontiers in Prevention Research Models: Commentary on the Special Issue.

Models considered in the current special issue represent valuable additions to the statistical toolbox of prevention researchers for many types of research questions and designs. Their appropriate use, however, depends on critical evaluation relative to previously existing techniques. This evaluation includes (a.) model choice involving "right-sizing" of the model relative to the amount and quality of data at hand, (b.) examination of the external validity of identified associations relative to observed or latent subgroups, (c.) confirmation of the reasonableness of the functional form assumed by the model, and (d.) identification of influential or outlying observations which unduly affect model fit or parameter estimates. Models in this issue allow for testing of new types of hypotheses in prevention research, and can constitute counterarguments to existing statistical practice. These models may, however, in turn be the object of critical examination of counterarguments a reasonable skeptic may offer.

How Robust Is the p Factor? Using Multitrait-Multimethod Modeling to Inform the Meaning of General Factors of Youth Psychopathology.

We used multitrait-multimethod (MTMM) modeling to examine general factors of psychopathology in three samples of youth (Ns = 2119, 303, 592) for whom three informants reported on the youth's psychopathology (e.g., child, parent, teacher). Empirical support for the p-factor diminished in multi-informant models compared with mono-informant models: the correlation between externalizing and internalizing factors decreased and the general factor in bifactor models essentially reflected externalizing. Widely used MTMM-informed approaches for modeling multi-informant data cannot distinguish between competing interpretations of the patterns of effects we observed, including that the p-factor reflects, in part, evaluative consistency bias or that psychopathology manifests differently across contexts (e.g., home vs. school). Ultimately, support for the p-factor may be stronger in mono-informant designs, although it is does not entirely vanish in multi-informant models. Instead, the general factor of psychopathology in any given mono-informant model likely reflects a complex mix of variances, some substantive and some methodological.

Not all symptoms of alcohol dependence are developmentally equivalent: Implications for the false-positives problem.

OBJECTIVE: Recent studies have examined the extent to which alcohol dependence (AD) criteria prospectively predict the course of AD. Critically, these studies have lacked a developmental perspective. However, the differential performance of criteria by age might indicate overendorsement in younger individuals. The current study examined AD criteria in terms of persistence and prediction of AD course and alcohol use by age in order to identify criteria that are likely to be overly endorsed by younger individuals. METHOD: The current study used longitudinal data from the National Epidemiologic Survey on Alcohol and Related Conditions to depict age differences in rates of new onset, recurrence, and persistence for each AD criterion, thereby showing how these three factors contribute to the overall age-prevalence curve of each criterion. Additionally, we tested age moderation of the predictive association between each criterion at baseline and new onset, recurrence, and persistence of syndromal AD. RESULTS: Some criteria (particularly, persistent desire or unsuccessful efforts to cut down or control drinking, and drinking despite physical/psychological problems) are both less persistent and less predictive of AD course among younger adults compared to older adults. CONCLUSIONS: These findings raise the possibility of elevated rates of false-positive AD among younger adults and suggest ways to improve the assessment of AD criteria. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Acute effect of alcohol on working memory updating.

AIMS: To examine the acute effects of alcohol on working memory (WM) updating, including potential variation across the ascending limb (AL) and descending limb (DL) of the blood alcohol concentration (BAC) time-course. DESIGN: A two-session experiment in which participants were randomly assigned to one of three beverage conditions [alcohol (males: 0.80 g/kg; females: 0.72 g/kg), active placebo (0.04 g/kg) or non-alcohol control (tonic)] and one of two BAC limb testing conditions (AL and DL or DL-only) for the second session, yielding a 3 (beverage) × 2 (time-points tested) × 3 (time-point) mixed factorial design with repeated measures on the latter factor. One of the repeated assessments is 'missing by design' in the DL-only condition. SETTING: A psychology laboratory at the University of Missouri campus in Columbia, MO, USA. PARTICIPANTS: Two hundred thirty-one community-dwelling young adults (51% female; aged 21-34 years) recruited from Columbia, MO, USA, tested between 2011 and 2013. MEASUREMENTS: Latent WM updating performance as indexed by shared variance in accuracy on three WM updating tasks (letter memory, keep track, spatial 2-back) at three time-points. FINDINGS: Multi-group modeling of latent WM updating indicated that performance among participants who consumed placebo or control beverages improved during the second session at time-points corresponding to AL (∆ from baseline in latent mean ± standard error (SE) + 0.5 ± 0.01, P < 0.001) and DL (+ 0.08 ± 0.01, P < 0.001). Alcohol consumption did not impair WM updating (∆ from baseline in latent mean ± SE, at AL: + 0.01 ± 0.01, P = 0.56; at DL: + 0.05 ± 0.01, P < 0.001), but attenuated performance improvements (equality of latent means across beverage groups at AL or DL: Δχ2(1)  ≥ 7.53, P < 0.01). CONCLUSIONS: Acute alcohol-induced impairment in working memory updating may be limited, but dampening of practice effects by alcohol could interfere with the completion of novel, unpracticed tasks.

Delineating Developmental Periods in Adulthood Suggests Age-Related Shifts in the Correlates of Alcohol Use and Problems.

BACKGROUND: Developmental context is related to the propensity to engage in alcohol use, the rate at which alcohol use changes, and the relevance of different risk factors to alcohol use disorder (AUD). Therefore, studies of change should consider developmental nuances, but change is often modeled to follow a uniform pattern, even across distinct developmental periods. METHODS: This study implemented a novel analytic approach to delineate developmental periods of alcohol behavior (n = 478, ages 18 to 35). This approach was further leveraged to examine age-related shifts in the association of impulsivity risk factors (lack of planning, general sensation seeking, alcohol enhancement expectancies) with alcohol behavior (alcohol quantity*frequency, heavy drinking, AUD). RESULTS: A sequence of exploratory and confirmatory latent growth models (LGMs) suggested modeling separate linear change factors for alcohol behavior during the primary college (ages 18 to 21) and postcollege years (21 to 35). Bivariate LGMs estimated correlations for alcohol behavior changes with lack of planning, sensation seeking, and enhancement expectancies during these periods. The rate at which heavy drinking changed during the college years was positively correlated with general sensation seeking and lack of planning during this period (rs = 0.61 to 0.63). These correlations were significantly weaker during the postcollege years (rs = 0.29 to 0.34). Notably, the rate of change in alcohol behavior was strongly correlated with enhancement expectancies during the college (r = 0.45 to 0.70) and postcollege years (r = 0.45 to 0.61). CONCLUSIONS: These findings highlight the importance of sensation seeking and lack of planning with regard to adult alcohol use, particularly in a college environment. There was also a strong link between the rates of change in alcohol behavior and enhancement expectancies across all waves. This study supports the utility of exploratory LGMs for delineating developmental periods of alcohol behavior, which are characterized by different processes.

Incipient alcohol use in childhood: Early alcohol sipping and its relations with psychopathology and personality.

Prior research has shown that sipping of alcohol begins to emerge during childhood and is potentially etiologically significant for later substance use problems. Using a large, community sample of 9- and 10-year-olds (N = 11,872; 53% female), we examined individual differences in precocious alcohol use in the form of alcohol sipping. We focused explicitly on features that are robust and well-demonstrated correlates of, and antecedents to, alcohol excess and related problems later in the lifespan, including youth- and parent-reported externalizing traits (i.e., impulsivity, behavioral inhibition and activation) and psychopathology. Seventeen percent of the sample reported sipping alcohol outside of a religiously sanctioned activity by age 9 or 10. Several aspects of psychopathology and personality emerged as small but reliable correlates of sipping. Nonreligious sipping was related to youth-reported impulsigenic traits, aspects of behavioral activation, prodromal psychotic-like symptoms, and mood disorder diagnoses, as well as parent-reported externalizing disorder diagnoses. Religious sipping was unexpectedly associated with certain aspects of impulsivity. Together, our findings point to the potential importance of impulsivity and other transdiagnostic indicators of psychopathology (e.g., emotion dysregulation, novelty seeking) in the earliest forms of drinking behavior.

Combinatorial Optimization of Clustering Decisions: An Approach to Refine Psychiatric Diagnoses.

Using complete enumeration (e.g., generating all possible subsets of item combinations) to evaluate clustering problems has the benefit of locating globally optimal solutions automatically without the concern of sampling variability. The proposed method is meant to combine clustering variables in such a way as to create groups that are maximally different on a theoretically sound derivation variable(s). After the population of all unique sets is permuted, optimization on some predefined, user-specific function can occur. We apply this technique to optimizing the diagnosis of Alcohol Use Disorder. This is a unique application, from a clustering point of view, in that the decision rule for clustering observations into the "diagnosis" group relies on both the set of items being considered and a predefined threshold on the number of items required to be endorsed for the "diagnosis" to occur. In optimizing diagnostic rules, criteria set sizes can be reduced without a loss of significant information when compared to current and proposed, alternative, diagnostic schemes.

Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology.

OBJECTIVE: One of the promises of the experience sampling methodology (ESM) is that a statistical analysis of an individual's emotions, cognitions and behaviors in everyday-life could be used to identify relevant treatment targets. A requisite for clinical implementation is that outcomes of such person-specific time-series analyses are not wholly contingent on the researcher performing them. METHODS: To evaluate this, we crowdsourced the analysis of one individual patient's ESM data to 12 prominent research teams, asking them what symptom(s) they would advise the treating clinician to target in subsequent treatment. RESULTS: Variation was evident at different stages of the analysis, from preprocessing steps (e.g., variable selection, clustering, handling of missing data) to the type of statistics and rationale for selecting targets. Most teams did include a type of vector autoregressive model, examining relations between symptoms over time. Although most teams were confident their selected targets would provide useful information to the clinician, not one recommendation was similar: both the number (0-16) and nature of selected targets varied widely. CONCLUSION: This study makes transparent that the selection of treatment targets based on personalized models using ESM data is currently highly conditional on subjective analytical choices and highlights key conceptual and methodological issues that need to be addressed in moving towards clinical implementation.

Latent resting-state network dynamics in boys and girls with attention-deficit/hyperactivity disorder.

Neuroimaging studies of subjects with ADHD typically show altered functional connectivity in prefrontal, striatal, and several temporal brain regions. While the majority of studies have focused on connectivity that is averaged over time, we investigated the temporal dynamics of brain network changes in resting-state fMRI. Using the ADHD-200 consortium, we characterized the time course of latent state changes using Hidden Markov Modeling, and compared state changes between boys and girls with ADHD along with typically developing controls. Sex differences were found in latent state switching, with boys dwelling longer in a given state than girls, and concurrently having fewer overall state transitions. These sex differences were found in children with ADHD and in typically developing controls. Children with ADHD were also found to be more variable in terms of state transitions than controls. These findings add to the growing literature on neural sex differences and may be related to the sex difference in focal versus diffuse attention.

The influence of sample selection on the structure of psychopathology symptom networks: An example with alcohol use disorder.

Increasingly, the structure of mental disorders has been studied in the form of a network, characterizing how symptoms or criteria interact with and influence each other. Many studies of psychiatric symptoms and diagnostic criteria employ community or population-based surveys using co-occurrence of the symptoms/criteria to form the networks. However, given the overall low prevalence rates of mental disorders and their symptoms in the general population, most of those surveyed may not exhibit or endorse any symptoms and yet are often included in network analyses. Consequently, because network models are built on associations between symptoms/criteria, much of the observed variability is driven by individuals who are asymptomatic. Using data from the National Epidemiological Survey of Alcohol and Related Conditions (NESARC) Wave 2 and NESARC-III, we explore the effect of these "asymptomatic" observations on the estimated relations among diagnostic criteria of alcohol use disorder to determine the effects of such observations on estimated networks. We do so using the eLasso tool, as well as with traditional measures of correlation between binary variables (the Φ coefficient and odds ratio). We find that when the proportion of asymptomatic individuals are systematically culled from the sample, the estimated pairwise relations are often significantly affected, even changing signs in some cases. Our findings indicate that researchers should carefully consider the population(s) included in their sample and the implications it has on their interpretations of pairwise similarity estimates and resulting generalizability and reproducibility of estimates of network structures. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Evidence-Based Treatment Strategies in Youth Mental Health Services: Results from a National Survey of Providers.

Previous surveys indicate infrequent use of evidence-based treatment (EBT) manuals in usual care youth mental health, but the extent to which providers use core and common EBT strategies and what contextual factors impact EBT strategy implementation need further study. In a national, multidisciplinary survey of 1092 youth-serving providers, providers reported regular use of many EBT strategies. Provider learning theory orientation, more recent degree, more standardized and ongoing assessment use, more positive attitudes toward innovation and evidence, fewer low-income clients, and perceptions that their agency valued quality care and provided fewer training resources predicted more frequent EBT strategy use.

Method effects of the relation between family history of alcoholism and parent reports of offspring impulsive behavior.

There is an extensive, albeit inconsistent, literature on the relation between parental alcoholism and offspring impulsive behavior. The reasons for this inconsistency are likely multiple but it seems probable that method effects due to different methodological approaches might explain some of the inconsistencies. Offspring behavior is typically assessed based on informant reports. However, no specific method has been demonstrated as optimal for analyzing informant reports, and conclusions may differ depending on the method used. The present study compared findings derived from a multi-informant method proposed by Bauer et al. (2013) to other structural equation models. Participants came from Wave 7 of the Alcohol, Health and Behavior study and included mother and father reports of offspring impulsive behavior on the Health and Behavior Questionnaire (Armstrong, Goldstein, & the MacArthur Working Group on Outcome Assessment, 2003). There were 368 offspring (50% female, age range 3-17 years, meanage = 6.78, SDage = 3.07) from 205 families. The multi-informant model and the single-reporter models each provided a good fit of the data; however, findings differed based on the approach employed. Specifically, the mother-only report model found that offspring with a family history of alcoholism (FHA) were more impulsive compared to offspring without a FHA; no effect of FHA was found in the other single-reporter models. Ratings of offspring impulsive behavior were higher on the father perspective factor suggesting alcoholic fathers were biased in their reports. These findings highlight the relation between FHA and impulsive behavior varies depending on the analytic method used.

Alcohol effects on response inhibition: Variability across tasks and individuals.

Considerable research has investigated the acute effects of alcohol on response inhibition, but a number of issues remain unresolved. Given that most studies use only a single laboratory task to assess inhibition, it is often difficult to determine whether alcohol's effects are task specific or generalize across measures of the same construct. Moreover, relatively few studies have directly compared effects of alcohol under ascending and descending blood alcohol concentrations (BACs), and those that have often failed to disentangle BAC limb effects from the effects of repeated testing. This study was intended to provide a test of alcohol's effects on behavioral inhibition using multiple laboratory measures in a relatively large sample and comparing effects under ascending and descending BAC. Young adults (N = 216) completed three commonly used inhibition tasks (Stroop, antisaccade, and stop-signal) at baseline and again 1-3 weeks later under one of three beverage conditions (alcohol, placebo or control) and one of two BAC limb conditions (ascending/descending or descending only). Findings indicated considerable specificity in alcohol's effects. Relative to control and placebo conditions, antisaccade performance suffered under both ascending and descending BAC and stop-signal reaction time (RT) suffered only under descending BAC. The Stroop RT interference effect was not affected by alcohol, though alcohol did impair response accuracy on incongruent Stroop trials. Baseline performance moderated effects of alcohol on both antisaccade accuracy and Stroop interference, suggesting the importance of individual differences. The current findings suggest that more specificity is required in characterizing acute effects of alcohol on inhibitory control. (PsycINFO Database Record

Associations between executive functioning, affect-regulation drinking motives, and alcohol use and problems.

Motivation to use alcohol to regulate positive and negative affect and deficits in cognitive control (i.e., executive functions [EFs]) have both been associated with increased alcohol involvement and alcohol-related consequences. Although dual-process models predict that affect-driven motivations and cognitive control should interact to determine alcohol involvement and alcohol-related consequences, this intersection has remained largely unexplored. The present study examined the extent to which effects of enhancement and coping drinking motives on alcohol use, heavy drinking, and alcohol-related consequences are moderated by individual differences in three theorized components of EF. We anticipated, in general, that drinking motives would more strongly predict alcohol use, heavy drinking, and alcohol-related consequences among individuals low versus high in cognitive control-EF. Participants (N = 801) completed a battery of nine EF tasks, as well as measures of drinking motives, alcohol use, heavy drinking, and alcohol-related negative consequences. A baseline structural model indicated that (a) both enhancement motives and coping motives predicted alcohol use and heavy drinking, (b) both enhancement and coping motives exerted their effects on alcohol-related consequences both directly and indirectly via alcohol use, and (c) shifting-specific abilities were modestly positively associated with heavy drinking. Most important for the aims of the study, latent variable interaction analyses failed to provide consistent evidence that better EF abilities attenuate the effects of drinking motives on alcohol use, heavy drinking, and alcohol-related consequences, as predicted. (PsycINFO Database Record

Developmental Etiologies of Alcohol Use and Their Relations to Parent and Peer Influences Over Adolescence and Young Adulthood: A Genetically Informed Approach.

BACKGROUND: Distinct changes in alcohol use etiologies occur during adolescence and young adulthood. Additionally, measured environments known to influence alcohol use such as peers and parenting practice can interact or be associated with this genetic influence. However, change in genetic and environmental influences over age, as well as how associations with measured environments change over age, is understudied. METHODS: The National Longitudinal Study of Adolescent Health (Add Health) sibling subsample was used to examine data-driven biometric models of alcohol use over ages 13 to 27. Associations between friends' drinking, parental autonomy granting, and maternal closeness were also examined. RESULTS: The best-fitting model included a 5-factor model consisting of early (ages 13 to 20) and overall (ages 13 to 27) additive genetic and unique environmental factors, as well as 1 overall common environment factor. The overall additive genetic factor and the early unique environment factor explained the preponderance of mean differences in the alcohol use over this portion of the life span. The most important factors explaining variance attributed to alcohol use changed over age. Additionally, friend use had the strongest associations with genetic and environmental factors at all ages, while parenting practices had almost no associations at any age. CONCLUSIONS: These results supplement previous studies indicating changes in genetic and environmental influences in alcohol use over adolescence and adulthood. However, prior research suggesting that constraining exogenous predictors of genetic and environmental factors to have effects of the same magnitude across age overlooks the differential role of factors associated with alcohol use during adolescence. Consonant with previous research, friend use appears to have a more pervasive influence on alcohol use than parental influence during this age. Interventions and prevention programs geared toward reducing alcohol use in younger populations may benefit from focus on peer influence.

Elevated rate of alcohol consumption in borderline personality disorder patients in daily life.

RATIONALE: Borderline personality disorder (BPD) is highly associated with alcohol use disorder, but little is known about how BPD individuals consume alcohol or the immediate effects of their consumption. There is therefore a need for research investigating drinking behavior in BPD. OBJECTIVES: The current study examined rate of alcohol consumption in BPD (N = 54) and community individuals (COM; N = 59) within ecologically valid drinking episodes. We hypothesized that rate of consumption would be elevated in BPD individuals. We further hypothesized that rate of consumption would be positively associated with subjective stimulation, but not sedation, and that stimulation would be associated with increased positive affect (PA) and reduced negative affect (NA). METHODS: Ambulatory assessment was used to assess rate of consumption, subjective alcohol response, and affect in the moment (N observations = 3444). Rate of consumption was defined as change in estimated blood alcohol concentration (eBAC) relative to drinking episode start. Multilevel modeling was used to test hypotheses. RESULTS: As hypothesized, BPD individuals demonstrated a faster increase in eBAC than COM individuals. Rate of consumption was associated with subjective stimulation, but not sedation, in both groups. Stimulation was associated with increased PA in both groups and reduced NA in the BPD group. CONCLUSIONS: BPD individuals consumed alcohol more rapidly than COM individuals. Faster consumption may serve as a means for BPD individuals to maximize the rewarding pharmacological effects of alcohol and to increase positive and reduce negative affect.

Age of initiation and substance use progression: A multivariate latent growth analysis.

An individual's age at first substance use may be associated with their risk for progression toward heavier substance involvement. To our knowledge, however, no studies within nationally representative samples have examined the relation between the timing of initiation and progression in use of multiple substances. The present study employed a sample of 9,421 participants from the National Longitudinal Study of Adolescent to Adult Health who reported on their ages of tobacco, alcohol, and cannabis initiation; frequency of tobacco, alcohol, and cannabis use; and quantity of tobacco and alcohol use across 4 waves. We fit latent growth models to examine (a) associations between the age of initiation and initial status and rate of change in substance involvement, and (b) the degree to which the timing of first substance use accounted for differences in trajectories. There were significant relations between all ages of initiation and rates of change in tobacco (ßs = -0.21 to -0.31, ps < .01) and alcohol use frequency (ßs = 0.14 to 0.31, ps < .001), age of cannabis initiation and rate of change in tobacco use quantity (ß = 0.23, p < .01), and age of tobacco initiation and rate of change in cannabis use frequency (ß = -0.14, p < .01). After adjusting for age of initiation, significant associations were observed between trajectories for tobacco and alcohol (r = .43, p < .0001) and alcohol and cannabis (r = .20, p < .05). Results highlight differences in within- and cross-substance relations between the age of initiation and rate of change in use across substances. They suggest that differences in substance use trajectories are partly accounted for by age at first use. (PsycINFO Database Record

Multilevel Models for Intensive Longitudinal Data with Heterogeneous Autoregressive Errors: The Effect of Misspecification and Correction with Cholesky Transformation.

Intensive longitudinal studies, such as ecological momentary assessment studies using electronic diaries, are gaining popularity across many areas of psychology. Multilevel models (MLMs) are most widely used analytical tools for intensive longitudinal data (ILD). Although ILD often have individually distinct patterns of serial correlation of measures over time, inferences of the fixed effects, and random components in MLMs are made under the assumption that all variance and autocovariance components are homogenous across individuals. In the present study, we introduced a multilevel model with Cholesky transformation to model ILD with individually heterogeneous covariance structure. In addition, the performance of the transformation method and the effects of misspecification of heterogeneous covariance structure were investigated through a Monte Carlo simulation. We found that, if individually heterogeneous covariances are incorrectly assumed as homogenous independent or homogenous autoregressive, MLMs produce highly biased estimates of the variance of random intercepts and the standard errors of the fixed intercept and the fixed effect of a level 2 covariate when the average autocorrelation is high. For intensive longitudinal data with individual specific residual covariance, the suggested transformation method showed lower bias in those estimates than the misspecified models when the number of repeated observations within individuals is 50 or more.