A registered report of a two-site study of variations of the flanker task: ERN experimental effects and data quality.

Error-related negativity is a widely used measure of error monitoring, and many projects are independently moving ERN recorded during a flanker task toward standardization, optimization, and eventual clinical application. However, each project uses a different version of the flanker task and tacitly assumes ERN is functionally equivalent across each version. The routine neglect of a rigorous test of this assumption undermines efforts to integrate ERN findings across tasks, optimize and standardize ERN assessment, and widely apply ERN in clinical trials. The purpose of this registered report was to determine whether ERN shows similar experimental effects (correct vs. error trials) and data quality (intraindividual variability) during three commonly used versions of a flanker task. ERN was recorded from 172 participants during three versions of a flanker task across two study sites. ERN scores showed numerical differences between tasks, raising questions about the comparability of ERN findings across studies and tasks. Although ERN scores from all three versions of the flanker task yielded high data quality and internal consistency, one version did outperform the other two in terms of the size of experimental effects and the data quality. Exploratory analyses of the error positivity (Pe) provided tentative support for the other two versions of the task over the paradigm that appeared optimal for ERN. The present study provides a roadmap for how to statistically compare psychometric characteristics of ERP scores across paradigms and gives preliminary recommendations for flanker tasks to use for ERN- and Pe-focused studies.

A Systematic Review of the Relationship Between Traumatic Brain Injury and Disruptions in Heart Rate Variability.

Autonomic nervous system dysfunction is increasingly recognized as a common sequela of traumatic brain injury (TBI). Heart rate variability (HRV) is a specific measure of autonomic nervous system functioning that can be used to measure beat-to-beat changes in heart rate following TBI. The objective of this systematic review was to determine the state of the literature on HRV dysfunction following TBI, assess the level of support for HRV dysfunction following TBI, and determine if HRV dysfunction predicts mortality and the severity and subsequent recovery of TBI symptoms. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Two raters coded each article and provided quality ratings with discrepancies resolved by consensus. Eighty-nine papers met the inclusion criteria. Findings indicated that TBI of any severity is associated with decreased (i.e., worse) HRV; the severity of TBI appears to moderate the relationship between HRV and recovery; decreased HRV following TBI predicts mortality beyond age; HRV disturbances may persist beyond return-to-play and symptom resolution following mild TBI. Overall, current literature suggests HRV is decreased following TBI and may be a good indicator of physiological change and predictor of important outcomes including mortality and symptom improvement following TBI.

Semi-autonomous wound invasion via matrix-deposited, haptotactic cues.

Proper wound healing relies on invasion of fibroblasts via directed migration. While the related experimental and mathematical modeling literature has mainly focused on cell migration directed by soluble cues (chemotaxis), there is ample evidence that fibroblast migration is also directed by insoluble, matrix-bound cues (haptotaxis). Furthermore, numerous studies indicate that fibronectin (FN), a haptotactic ligand for fibroblasts, is present and dynamic in the provisional matrix throughout the proliferative phase of wound healing. In the present work, we show the plausibility of a hypothesis that fibroblasts themselves form and maintain haptotactic gradients in a semi-autonomous fashion. As a precursor to this, we examine the positive control scenario where FN is pre-deposited in the wound matrix, and fibroblasts maintain haptotaxis by removing FN at an appropriate rate. After developing conceptual and quantitative understanding of this scenario, we consider two cases in which fibroblasts activate the latent form of a matrix-loaded cytokine, TGFß, which upregulates the fibroblasts' own secretion of FN. In the first of these, the latent cytokine is pre-patterned and released by the fibroblasts. In the second, fibroblasts in the wound produce the latent TGFß, with the presence of the wound providing the only instruction. In all cases, wound invasion is more effective than a negative control model with haptotaxis disabled; however, there is a trade-off between the degree of fibroblast autonomy and the rate of invasion.

A systematic review of heart rate variability (HRV) biofeedback treatment following traumatic brain injury (TBI).

OBJECTIVE: Autonomic nervous system dysregulation is a common consequence of traumatic brain injury (TBI). Heart rate variability (HRV) is a cost-effective measure of autonomic nervous system functioning, with studies suggesting decreased HRV following moderate-to-severe TBI. HRV biofeedback treatment may improve post-TBI autonomic nervous system functioning and post-injury emotional and cognitive functioning. We provide a systematic evidence-based review of the state of the literature and effectiveness of HRV biofeedback following TBI. METHOD: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Two coders coded each article and provided quality ratings. Seven papers met inclusion criteria. All studies included a measure of emotional functioning and 5 studies (63%) included neuropsychological outcomes. RESULTS: Participants completed 11 sessions of HRV biofeedback on average (range = 1 to 40). HRV biofeedback was associated with improved HRV following TBI. There was a positive relationship between increased HRV and TBI recovery following biofeedback, including improvements in cognitive and emotional functioning, and physical symptoms such as headaches, dizziness, and sleep problems. CONCLUSION: The literature on HRV biofeedback for TBI is promising, but in its infancy; effectiveness is unclear due to poor-to-fair study quality, and potential publication bias (all studies reported positive results).

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.

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.

The data-processing multiverse of event-related potentials (ERPs): A roadmap for the optimization and standardization of ERP processing and reduction pipelines.

In studies of event-related brain potentials (ERPs), numerous decisions about data processing are required to extract ERP scores from continuous data. Unfortunately, the systematic impact of these choices on the data quality and psychometric reliability of ERP scores or even ERP scores themselves is virtually unknown, which is a barrier to the standardization of ERPs. The aim of the present study was to optimize processing pipelines for the error-related negativity (ERN) and error positivity (Pe) by considering a multiverse of data processing choices. A multiverse analysis of a data processing pipeline examines the impact of a large set of different reasonable choices to determine the robustness of effects, such as the impact of different decisions on between-trial standard deviations (i.e., data quality) and between-condition differences (i.e., experimental effects). ERN and Pe data from 298 healthy young adults were used to determine the impact of different methodological choices on data quality and experimental effects (correct vs. error trials) at several key stages: highpass filtering, lowpass filtering, ocular artifact correction, reference, baseline adjustment, scoring sensors, and measurement procedure. This multiverse analysis yielded 3,456 ERN scores and 576 Pe scores per person. An optimized pipeline for ERN included a 15 Hz lowpass filter, ICA-based ocular artifact correction, and a region of interest (ROI) approach to scoring. For Pe, the optimized pipeline included a 0.10 Hz highpass filter, 30 Hz lowpass filter, regression-based ocular artifact correction, a -200 to 0 ms baseline adjustment window, and an ROI approach to scoring. The multiverse approach can be used to optimize pipelines for eventual standardization, which would support efforts toward establishing normative ERP databases. The proposed process of analyzing the data-processing multiverse of ERP scores paves the way for better refinement, identification, and selection of data processing parameters, ultimately improving the precision and utility of ERPs.

Treatment engagement and effectiveness of an internet-delivered cognitive behavioral therapy program at a university counseling center.

Objective: Technology can provide affordable, accessible mental health care and some research suggests internet-delivered Cognitive Behavior Therapy (iCBT) can be an effective treatment for various problems and can be an affordable, accessible alternative to traditional treatments. Advantages of iCBT over face-to-face therapy include lower cost, no travel time, easy access, no waitlists, and trackable progress. To our knowledge there have been no studies of iCBT programs used during the course of routine care. This study evaluated the usage and effectiveness of one iCBT program, SilverCloud (SC), in a university counseling center. Methods: Participants (N = 5568) were students at a large, private western university. Participants were either self-referred to the program, chose to enroll at intake as a standalone intervention, or were referred by their treating clinician as an adjunct to regular treatment. Data was analyzed using regression models with robust standard errors that allowed us to take into account the fact that there may be an effect of participants seeing the same therapist. Results: Results indicated that all three groups had comparable outcomes. However, usage was generally low (less than 10% of the program) and SC usage accounted for less than 1% of the variance in outcome. Conclusions: These results suggest that internet-delivered therapy may be a viable alternative to in-person therapy.

Evaluating Within-Person Change in Implicit Measures of Alcohol Associations: Increases in Alcohol Associations Predict Increases in Drinking Risk and Vice Versa.

AIMS: Implicit measures of alcohol associations (i.e. measures designed to assess associations that are fast/reflexive/impulsive) have received substantial research attention. Alcohol associations related to the self (drinking identity), the effects of alcohol (alcohol excite) and appetitive inclinations (alcohol approach) have been found to predict drinking cross-sectionally and over time. A critical next step in this line of research and the goal of this study is to evaluate whether increases in the strength of these associations predict increases in drinking and vice versa. These hypotheses were tested in a sample of first- and second-year US university students: a sample selected because this time period is associated with initiation and escalation of drinking, peak levels of alcohol consumption and severe alcohol-related negative consequences. SHORT SUMMARY: This study's purpose was to evaluate whether increases in the strength of alcohol associations with the self (drinking identity), excitement (alcohol excite) and approach (alcohol approach) as assessed by implicit measures predicted subsequent increases in drinking risk and vice versa using a longitudinal, university student sample. Results were consistent with hypotheses. METHODS: A sample of 506 students' (57% women) alcohol associations and alcohol consumption were assessed every 3 months over a 2-year period. Participants' consumption was converted to risk categories based on NIAAA's criteria: non-drinkers, low-risk drinkers and high-risk drinkers. A series of cross-lagged panel models tested whether changes in alcohol associations predicted subsequent change in drinking risk (and vice versa). RESULTS: Across all three measures of alcohol associations, increases in the strength of alcohol associations were associated with subsequent increases in drinking risk and vice versa. CONCLUSION: Results from this study indicate bi-directional relationships between increases in alcohol associations (drinking identity, alcohol excite and alcohol approach) and subsequent increases in drinking risk. Intervention and prevention efforts may benefit from targeting these associations.

Comparing Approaches to Mobile Depression Assessment for Measurement-Based Care: Prospective Study.

BACKGROUND: To inform measurement-based care, practice guidelines suggest routine symptom monitoring, often on a weekly or monthly basis. Increasingly, patient-provider contacts occur remotely (eg, by telephone and Web-based portals), and mobile health tools can now monitor depressed mood daily or more frequently. However, the reliability and utility of daily ratings are unclear. OBJECTIVE: This study aimed to examine the association between a daily depressive symptom measure and the Patient Health Questionnaire-9 (PHQ-9), the most widely adopted depression self-report measure, and compare how well these 2 assessment methods predict patient outcomes. METHODS: A total of 547 individuals completed smartphone-based measures, including the Patient Health Questionnaire-2 (PHQ-2) modified for daily administration, the PHQ-9, and the Sheehan Disability Scale. Multilevel factor analyses evaluated the reliability of latent depression based on the PHQ-2 (for repeated measures) between weeks 2 and 4 and its correlation with the PHQ-9 at week 4. Regression models predicted week 8 depressive symptoms and disability ratings with daily PHQ-2 and PHQ-9. RESULTS: The daily PHQ-2 and PHQ-9 are highly reliable (range: 0.80-0.88) and highly correlated (r=.80). Findings were robust across demographic groups (age, gender, and ethnic minority status). Daily PHQ-2 and PHQ-9 were comparable in predicting week 8 disability and were independent predictors of week 8 depressive symptoms and disability, though the unique contribution of the PHQ-2 was small in magnitude. CONCLUSIONS: Daily completion of the PHQ-2 is a reasonable proxy for the PHQ-9 and is comparable to the PHQ-9 in predicting future outcomes. Mobile assessment methods offer researchers and clinicians reliable and valid new methods for depression assessment that may be leveraged for measurement-based depression care.

Open access meta-analysis for psychotherapy research.

Meta-analysis has played a key role in psychotherapy research for nearly 40 years. There is now an opportunity for technology to assist with transparent and open meta-analyses. The authors describe an open-access database of effect sizes and a corresponding web application for performing meta-analyses, viewing the database, and downloading effect sizes. The initial databases provide effect sizes for family therapy for delinquency studies and for alliance-outcome correlations in individual psychotherapy. Disciplinary norms about data sharing and openness are shifting. Furthermore, meta-analyses of behavioral interventions have been criticized for lacking transparency and openness. The database and web application are aimed at facilitating data sharing and improving the transparency of meta-analyses. The authors conclude with a discussion of future directions for the database.

Task-specific relationships between error-related ERPs and behavior: Flanker, Stroop, and Go/Nogo tasks.

Performance monitoring has been widely studied during different forced-choice response tasks. Participants typically show longer response times (RTs) and increased accuracy following errors, but there are inconsistencies regarding the connection between error-related event-related brain potentials (ERPs) and behavior, such as RT and accuracy. The specific task in any given study could contribute to these inconsistencies, as different tasks may require distinct cognitive processes that impact ERP-behavior relationships. The present study sought to determine whether task moderates ERP-behavior relationships and whether these relationships are robustly observed when tasks and stimuli are treated as random effects. ERPs and behavioral indices (RTs and accuracy) recorded during flanker, Stroop, and Go/Nogo tasks from 180 people demonstrated a task-specific effect on ERP-behavior relationships, such that larger previous-trial error-related negativity (ERN) predicted longer RTs and greater likelihood of a correct response on subsequent trials during flanker and Stroop tasks but not during Go/Nogo task. Additionally, larger previous-trial error positivity (Pe) predicted faster RTs and smaller variances of RTs on subsequent trials for Stroop and Go/Nogo tasks but not for flanker task. When tasks and stimuli were treated as random effects, ERP-behavior relationships were not observed. These findings support the need to consider the task used for recording performance monitoring measures when interpreting results across studies.

Writing about the future self to shift drinking identity: An experimental investigation.

College student drinking is prevalent and costly to public and personal health, leading to calls to identify and target novel mechanisms of behavior change. We aimed to manipulate drinking identity (a cognitive risk factor for hazardous drinking) via three sessions of narrative writing about a future self. We tested whether writing could shift drinking identity and would be accompanied by changes in alcohol consumption and problems. Participants were college students meeting hazardous drinking criteria (N = 328; Mage = 20.15; 59% women, 40% men, 1% gender-diverse; 60% white; 23% Asian; 12% multiple races; 2% other racial groups; 8% identified as Hispanic/Latino/a/x). The study had a 2 [narrative writing topic: low-risk drinker vs. reduced smartphone use] × 2 [writing perspective: first person vs. non-first-person] × 2 [social network instruction: instructed to include vs. not] factorial design. Outcomes were drinking identity, drinking refusal self-efficacy, alcohol consumption, alcohol-related problems, and craving. Participants completed three writing sessions and online follow-up assessments at 2, 4, and 12 weeks. The study is a registered clinical trial; hypotheses and analyses were preregistered (https://osf.io/vy2ep/). Contrary to predictions, narrative writing about a future self as a low-risk drinker did not significantly impact outcomes. Null results extended to expected interactions with writing perspective and social network instructions. The narrative writing task did not shift drinking or alcohol-related outcomes. Future experimental work may benefit from greater flexibility in conceptualizing a future self, recruiting individuals interested in behavior change, and more sensitive measures of drinking identity.

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.

Is informal practice associated with outcomes in loving-kindness and compassion training? Evidence from pre-post and daily diary assessments.

We investigated whether informal meditation practice (i.e., self-reported application of meditative techniques outside a period of formal meditation) was associated with outcomes in smartphone-based loving-kindness and compassion training. Meditation-naïve participants (n = 351) with clinically elevated symptoms completed measures of psychological distress, loneliness, empathy, and prosociality at baseline and following a two-week intervention. Informal practice, psychological distress, and loneliness were also assessed daily. Steeper increases in informal practice had small associations with pre-post improvements in distress (r = -.18, p = .008) and loneliness (r = -.19, p = .009) but not empathy or prosociality. Using a currently recommended approach for establishing cross-lagged effects in longitudinal data (latent curve model with structured residuals), higher current-day informal practice was associated with decreased next-day distress with a very small effect size (ßs = -.06 to -.04, p = .018) but not decreased next-day loneliness. No cross-lagged associations emerged from distress or loneliness to informal practice. Findings suggest that further investigation into a potential causal role of informal practice is warranted. Future studies experimentally manipulating informal practice are needed.

Investigating cognitive and motivational proximal outcomes in a randomized clinical trial of writing about the future self to reduce drinking.

BACKGROUND: Drinking identity (the extent to which one links the self with drinking alcohol) is a unique risk factor for college students' hazardous drinking that is not directly targeted by existing interventions. We conducted a study that aimed to decrease drinking identity among college students with hazardous drinking. We adapted a writing task about the future self and tested whether three writing sessions could decrease drinking identity and change drinking. We also investigated whether two additional factors (writing perspective and inclusion of participants' social networks) would enhance task impact. The present study evaluated whether posited proximal cognitive and motivational outcomes (drinking identity, self-efficacy, readiness to change, and drinking intentions) changed immediately after each writing session. METHOD: The study is a randomized clinical trial in which hypotheses and analyses were pre-registered. Participants were 328 college students who met hazardous drinking criteria. The study had a 2 (narrative writing topic: low-risk drinker vs. reduced smartphone use) × 2 (writing perspective: first-person vs. non-first-person) × 2 (social network instruction: instructed to include vs. not) factorial design. Proximal outcomes were drinking identity, self-efficacy, readiness to change, and drinking intentions. The clinical outcome was alcohol consumption. Participants completed three laboratory sessions at weekly intervals that included the writing task and pre- and post-task assessments. RESULTS: Results were largely null, except that readiness to reduce drinking was higher in the low-risk drinker condition and increased over the lab sessions. Time effects indicated that reductions in drinking identity, drinking intentions, and alcohol consumption, and increases in self-efficacy were observed but did not change above and beyond control conditions. CONCLUSIONS: Findings indicate the need to strengthen the writing task and select a more appropriate control task to target proposed proximal outcomes. Future studies might try personalizing the task, evaluating its efficacy with individuals motivated to change their drinking, and using a control task that does not involve imagining a future self.

Quantifying collective motion patterns in mesenchymal cell populations using topological data analysis and agent-based modeling.

Fibroblasts in a confluent monolayer are known to adopt elongated morphologies in which cells are oriented parallel to their neighbors. We collected and analyzed new microscopy movies to show that confluent fibroblasts are motile and that neighboring cells often move in anti-parallel directions in a collective motion phenomenon we refer to as "fluidization" of the cell population. We used machine learning to perform cell tracking for each movie and then leveraged topological data analysis (TDA) to show that time-varying point-clouds generated by the tracks contain significant topological information content that is driven by fluidization, i.e., the anti-parallel movement of individual neighboring cells and neighboring groups of cells over long distances. We then utilized the TDA summaries extracted from each movie to perform Bayesian parameter estimation for the D'Orsgona model, an agent-based model (ABM) known to produce a wide array of different patterns, including patterns that are qualitatively similar to fluidization. Although the D'Orsgona ABM is a phenomenological model that only describes inter-cellular attraction and repulsion, the estimated region of D'Orsogna model parameter space was consistent across all movies, suggesting that a specific level of inter-cellular repulsion force at close range may be a mechanism that helps drive fluidization patterns in confluent mesenchymal cell populations.

Disentangling the within- and between-person aspects of implicit alcohol associations on hazardous drinking.

Indirect measures have been used to assess the strength of automatically activated, alcohol-related associations and their relation to hazardous drinking. However, little is known about the longitudinal contributions of between-person and within-person components of implicit alcohol associations (IAAs) to college students' hazardous drinking over time. This study examined how within- and between-person variability in three measures of IAA (drinking identity, alcohol approach, and alcohol excite) are related to hazardous drinking while controlling for their explicit, self-report counterparts. First- and second-year U.S. college students (N = 506; 57% female) completed web-based assessments once every 3 months up to eight assessments, which included IAA measures (Implicit Association Tests), explicit counterparts of the IAAs, and self-reported hazardous drinking (alcohol consumption, problems, and risk of alcohol use disorder). Bayesian generalized multilevel models were used to examine between- and within-person associations among IAA, their explicit counterparts, and hazardous drinking. Results showed that between persons, mean levels of all three IAAs were positively associated with hazardous drinking over time. Once their explicit, self-report counterparts were included, however, only drinking identity IAA remained significant. Within persons, increases in drinking identity IAA were associated with increases in subsequent hazardous drinking risk, even after controlling for its explicit counterpart. These results suggest the importance of disentangling and simultaneously investigating between- and within-person processes in IAAs. Although the between-person component of IAAs may play a larger role in the prediction of hazardous drinking, examining the within-person component of IAA, at least for drinking identity, also appears to be important. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Maturing Out: Between- and Within-Persons Changes in Social-Network Drinking, Drinking Identity, and Hazardous Drinking Following College Graduation.

Many college students reduce hazardous drinking (HD) following graduation without treatment. Identifying cognitive mechanisms facilitating this "natural" reduction in HD during this transition is crucial. We evaluated drinking identity as a potential mechanism and tested whether within-person changes in one's social network's drinking were linked to within-person changes in drinking identity and subsequent within-person changes in HD. A sample of 422 undergraduates reporting HD was followed from six months before until two years after graduation. Their drinking, drinking identity, and social networks were assessed online. Within-person changes in drinking identity did not mediate the relationship between within-person changes in social network drinking and personal HD, though significant positive between-person associations among all constructs were found. Instead, there was some evidence that within-person changes in drinking identity followed changes in HD, suggesting that drinking identity may function as a marker versus mechanism of "natural" HD reduction during transition out of college.