Peer connectedness and substance use in adolescence: A systematic review and meta-analysis

OBJECTIVE

Adolescents' relationships with their peers play a pivotal role in their substance-use behaviors. As such, decades of research have examined how substance use relates to adolescents' overall levels of closeness to their peers, here termed peer connectedness, with mixed results. This report sought to determine how the operationalizations of peer connectedness and substance use affect the nature of the relationship between them.

METHOD

We used a systematic review strategy to find a comprehensive set of studies investigating the relationship between peer connectedness and substance use. Three-level meta-analytic regression was used to empirically test whether the operationalization of these variables moderates effect sizes across studies.

RESULTS

We found 147 studies, of which 128 were analyzed using multilevel meta-analytic regression models. Operationalizations of peer connectedness varied widely, encompassing sociometric and self-report measures. Of these measures, sociometric indices specifically pertaining to popularity were most strongly predictive of substance use. Less consistent relationships were observed between substance use and sociometric measures of friendship, as well as with self-report measures.

CONCLUSIONS

Being perceived as popular by one's peers is positively related to substance use among adolescents. This relationship is stronger and more consistent than those between substance use and other peer-connectedness variables, underscoring the necessity of operationalizing these constructs specifically and clearly. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Informing Harmonization Decisions in Integrative Data Analysis: Exploring the Measurement Multiverse

Combining datasets in an integrative data analysis (IDA) requires researchers to make a number of decisions about how best to harmonize item responses across datasets. This entails two sets of steps: logical harmonization, which involves combining items which appear similar across datasets, and analytic harmonization, which involves using psychometric models to find and account for cross-study differences in measurement. Embedded in logical and analytic harmonization are many decisions, from deciding whether items can be combined prima facie to how best to find covariate effects on specific items. Researchers may not have specific hypotheses about these decisions, and each individual choice may seem arbitrary, but the cumulative effects of these decisions are unknown. In the current study, we conducted an IDA of the relationship between alcohol use and delinquency using three datasets (total N = 2245). For analytic harmonization, we used moderated nonlinear factor analysis (MNLFA) to generate factor scores for delinquency. We conducted both logical and analytic harmonization 72 times, each time making a different set of decisions. We assessed the cumulative influence of these decisions on MNLFA parameter estimates, factor scores, and estimates of the relationship between delinquency and alcohol use. There were differences across paths in MNLFA parameter estimates, but fewer differences in estimates of factor scores and regression parameters linking delinquency to alcohol use. These results suggest that factor scores may be relatively robust to subtly different decisions in data harmonization, and measurement model parameters are less so.

Psychosocial functioning associated with prescription stimulant and opioid misuse versus illicit drug use among college students

Objective: College students' prescription stimulant and opioid misuse (PSM and POM) share psychosocial risks with other substance use. We sought to extend a prior study of these issues. Methods: National College Health Assessment (2015-2016) participants ages 18-24 years (n = 79,336) reporting 12-month PSM (defined as use of a drug not prescribed to them), 30-day other illicit drug use (non-cannabis), both, or neither, were compared on other substance use, psychopathology, academic adjustment, attention deficit hyperactivity disorder, and chronic pain. Models were repeated for POM. Results: Relative to those who only misused the prescription drug, those who used other illicit drugs had lower odds of chronic pain and academic problems, but higher odds on nearly every other outcome especially if they also misused the prescription drug. Conclusions: Findings suggest PSM and POM are on a continuum of risk shared with illicit drug use, but also are linked to outcomes specific to these drugs' perceived medical purposes.

Coping with COVID-19: the efficacy of disengagement for coping with the chronic stress of a pandemic

BACKGROUND

The COVID-19 pandemic was a novel chronic stressor that necessitated figuring out how to cope with it. We hypothesized that disengagement coping - coping with a stressor by disengaging from it - would be effective because the pandemic featured heightened uncertainty and enduring intensity.

DESIGN

We assessed the disengagement strategies of distraction - taking a break from a stressor - and avoidance - avoiding thoughts and feelings associated with a stressor - and emotional well-being outcomes (positive/negative emotions, stress) in three waves one week apart (305 participants completed all three waves).

RESULTS

Distraction was one of the most frequently endorsed coping strategies. The results of multi-level models and cross-lagged panel models showed that participants who used distraction habitually experienced better emotional well-being overall and that using distraction led to better emotional well-being that week, but did not predict increases in well-being from one week to the next. Those who used avoidance also experienced better emotional well-being that week, but habitual use of avoidance was associated with worse emotional well-being overall.

CONCLUSIONS

These findings suggest that in the midst of chronic stressors like this pandemic, the disengagement coping strategy of distraction is popular and effective for temporarily improving people's well-being.

Positive distraction in daily activities as a predictor of good coping: A "day in the life" during the COVID-19 pandemic

Introduction

The early part of the coronavirus pandemic (COVID-19) was a chronic stressor that led to decreased life satisfaction, increased psychopathology, and decreased social interaction, making it important to study coping strategies that stimulate increases in emotional well-being. Previous research has demonstrated that disengagement coping may be beneficial in scenarios where engagement coping is too difficult or not possible. We hypothesized that disengagement coping would be related to good emotional well-being (high positive emotions and/or perceived control, lower negative emotions and/or stress), with distraction (taking a break from a stressor) related to better emotional well-being than is avoidance (avoiding thoughts and feelings associated with a stressor).

Methods

Using a daily reconstruction method that represents a "day in the life" of people in the United States during the early stages of the COVID-19 pandemic, we assessed people's (N = 329) activities, their intention to distract from or avoid the stressor during these activities, emotions, and thoughts about and motivation to deal with COVID.

Results

Between-subjects' analyses revealed that habitual distraction did not predict any outcomes, while habitual avoidance related to poorer emotional well-being. Within-subject analyses, however, demonstrated that engaging in distraction (and to a smaller extent, avoidance) was associated with better concurrent emotional well-being and less thinking about COVID. Furthermore, the intent to distract/avoid was more reliable in predicting emotional outcomes than was the activity type.

Conclusion

These findings suggest that disengagement from stress can be an adaptive coping behavior during global pandemics and possibly other chronic stressors with similar attributes.

Internalizing and externalizing pathways to high-risk substance use and geographic location in Australian adolescents

One specific instantiation of the storm-and-stress view of adolescence is the idea that “normal” adolescence involves high-risk substance use behaviors. However, although uptake of some substance use behaviors is more common during adolescence than other life stages, it is clear that not all adolescents engage in risky substance use—and among those who do, there is much variation in emotional, behavioral, and contextual precursors of this behavior. One such set of predictors forms the internalizing pathway to substance use disorder, whereby internalizing symptoms in childhood such as negative affect and anxiety set off a chain of consequences culminating in high-risk substance use in late adolescence. However, findings linking internalizing symptoms to substance use are mixed, and it is clear that this link varies across adolescents and contexts. One heretofore unanswered question is whether and how geographic location, specifically whether the adolescent lives in an urban or rural location, moderates this link. The current report is a secondary analysis of data from the Longitudinal Study of Australian Children (LSAC; N = 2,285), in which we examined the link between internalizing symptoms in childhood and initiation of substance use through age 19. Using a multiple event process survival mixture model (MEPSUM), we identified three trajectories of substance use initiation in adolescence: one (65.7% of the sample) characterized by near-complete abstinence until late adolescence, another (27.2%) by earlier initiation of alcohol, nicotine, and cannabis, and another (7.2%) by early initiation of these substances and later initiation of more hazardous drugs such as cocaine and methamphetamine. Although childhood externalizing symptoms increased the risk of being in the second or third class, internalizing symptoms decreased risk when rural and non-rural adolescents were considered together. Few effects of rurality were found, but the negative relationship between internalizing at age 10 and high-risk substance use was only observed among non-rural adolescents. This finding, which was inconsistent with our initial predictions that rurality might confer higher risk for substance use, instead suggests a potentially protective effect of internalizing symptoms for engagement in risky substance use which may differ based on an adolescent’s geographical context.

The Role of Social Position Within Peer Groups in Distress-Motivated Smoking Among Adolescents

OBJECTIVE

The relationship between smoking and adolescents' peer relationships is complex, with studies showing increased risk of smoking for adolescents of both very high and very low social position. A key question is whether the impact of social position on smoking depends on an adolescent's level of coping motives (i.e., their desire to use smoking to mitigate negative affect).

METHOD

We assessed how social position predicts nicotine dependence in a longitudinal sample (N = 3,717; 44.8% male; mean age = 13.41 years) of adolescent lifetime smokers measured between 6th and 12th grades. Using both social network analysis and multilevel modeling, we assessed this question at the between-person and within-person level, hypothesizing that within-person decreases in social position would lead to increased risk of nicotine dependence among those with high levels of coping motives.

RESULTS

In contrast to our hypotheses, only interactions with the between-person measures of social position were found, with a slight negative relationship at low levels of coping motives. In addition, the main effect of coping motives was considerably stronger than that of social position at the between-person level, and social position had no significant within-person main effect on nicotine dependence risk.

CONCLUSIONS

These results suggest that adolescents with higher overall levels of social position among their peers may have slightly decreased risk for nicotine dependence, but only when coping motives are low. Counter to expectations, higher levels of nicotine dependence risk were not linked to fluctuations in social position.

Do We Know Whether We're Happier? Corroborating Perceived Retrospective Assessments of Improvements in Well-Being

To what extent do our beliefs about how our well-being has improved over time correspond to observed changes? Participants (N = 1,247 from Qualtrics Panels) completed questionnaires measuring dispositional well-being and ill-being (depressive symptoms) at three time points over the course of one year, as well as 44 weekly assessments of state well-being and ill-being over 52 weeks. They additionally completed measures of perceived improvements in well-being and ill-being at Weeks 45 and 52 as well as a measure of broad personality traits. We estimated latent change scores and latent growth curves, which allowed us to obtain more accurate estimates of the convergence between retrospective improvements and veridical change compared to past methods utilized. Stability in both global and state well-being and ill-being were observed. People who agreed more strongly that their well-being had improved (or their ill-being had increased) tended to show greater increases in actual well-being (or ill-being) across the past year. Additionally, we observed meaningful relationships between personality traits and perceived improvements. On average, people have some insight in assessing whether they became happier (or unhappier) over one year.

Coping With COVID-19: The Benefits of Anticipating Future Positive Events and Maintaining Optimism

In early 2020, the COVID-19 pandemic forced a large portion of the world into quarantine, leading to an extensive period of stress making it necessary to explore regulatory techniques that are effective at stimulating long-lasting positive emotion. Previous research has demonstrated that anticipating positive events produces increases in positive emotion during discrete stressors. We hypothesized that state and trait positive anticipation during the COVID-19 pandemic would be associated with increased positive emotions. We assessed how often participants thought about a future positive/negative/neutral event, activity, or goal through a daily reconstruction method that represented a "day in the life" of people in the United States during the early stages of the COVID-19 pandemic. The results of multi-level modeling and mediational analyses demonstrated that higher optimism, one form of trait positive anticipation, was related to higher state positive anticipation, which was in turn related to higher positive emotions during the current episode, which persisted to the next episode. In addition, both optimism and state positive anticipation were related to adaptive responses to the pandemic. These findings suggest that anticipation of future emotional experiences and hopefulness for the future can be a powerful predictor of positive emotions during global pandemics and perhaps other similar chronic stressors.

The broader impact of new trends in adolescent substance use: A special section editorial summary

The focus of this special section of Addictive Behaviors is on how new trends in substance use have a broader impact on youth development, most notably on the use of other substances or psychosocial functioning. These eight articles focus on recent changes in the prevalence of e-cigarettes, stimulants, and prescription opiates as well as the implications of changing legislation for recreational marijuana use. These studies also focus on how using these substances is associated with continued use of the same and other forms of drugs, advertising trends, and psychosocial functioning. This editorial summarizes these articles and offers key directions for future research.

Psychosocial functioning among college students who misuse stimulants versus other drugs

The misuse of prescription stimulants (e.g., Ritalin, Adderall) is a large and growing problem on college campuses. Emerging research examines not only the demographic predictors of stimulant misuse but also the potentially role that stimulant misuse plays in a college student's overall functioning and mental health. To better understand the experiences specifically linked with stimulant misuse rather than substance use more broadly, we tested whether psychosocial functioning differed across four groups of college students: those who do not misuse stimulants or other hard drugs; those who misuse both stimulants and other hard drugs; those who misuse stimulants but not other hard drugs; and those who misuse other hard drugs but not stimulants (N = 1534; 40.3% male; 33.9% ethnic minority). Those who misused stimulants reported higher levels of impulsivity, as well as substance use consequences, than those who did not use any hard drugs. However, these differences were exacerbated among those who misused stimulants and other hard drugs. Taken together, these findings suggest that stimulant misuse typically occurs in a broader pattern of substance use, and that stimulant misusers generally fall along a continuum of substance use severity in terms of psychosocial functioning.

Social network isolation mediates associations between risky symptoms and substance use in the high school transition

The current study examined whether social status and social integration, two related but distinct indicators of an adolescent's standing within a peer network, mediate the association between risky symptoms (depressive symptoms and deviant behavior) and substance use across adolescence. The sample of 6,776 adolescents participated in up to seven waves of data collection spanning 6th to 12th grades. Scores indexing social status and integration were derived from a social network analysis of six schools and subsequent psychometric modeling. Results of latent growth models showed that social integration and status mediated the relation between risky symptoms and substance use and that risky symptoms mediated the relation between social standing and substance use during the high school transition. Before this transition, pathways involving deviant behavior led to high social integration and status and in turn to substance use. After this transition, both deviant behavior and depressive symptoms led to low social integration and status and in turn greater substance use. These findings suggest that the high school transition is a risky time for substance use related to the interplay of increases in depressive symptoms and deviant behavior on the one hand and decreases in social status and integration on the other.

A Latent Variable Approach to Measuring Social Dynamics in Adolescence

In the study of adolescent health, it is useful to derive indices of social dynamics from sociometric data, and to use these indices as predictors of health risk behaviors. In this manuscript, we introduce a flexible latent variable model as a novel way of obtaining estimates of social integration and social status from school-based sociometric data. Such scores provide the flexibility of a regression-based approach while accounting for measurement error in sociometric indicators. We demonstrate the utility of these factor scores in testing complex hypotheses through a combination of structural equation modeling and survival models, showing that deviance mediates the relationship between social status and smoking onset hazard at the transition to high school.

Assessing the Robustness of Mixture Models to Measurement Noninvariance

Recent work reframes direct effects of covariates on items in mixture models as differential item functioning (DIF) and shows that, when present in the data but omitted from the fitted latent class model, DIF can lead to overextraction of classes. However, less is known about the effects of DIF on model performance-including parameter bias, classification accuracy, and distortion of class-specific response profiles-once the correct number of classes is chosen. First, we replicate and extend prior findings relating DIF to class enumeration using a comprehensive simulation study. In a second simulation study using the same parameters, we show that, while the performance of LCA is robust to the misspecification of DIF effects, it is degraded when DIF is omitted entirely. Moreover, the robustness of LCA to omitted DIF differs widely based on the degree of class separation. Finally, simulation results are contextualized by an empirical example.

Simplifying the implementation of modern scale scoring methods with an automated R package: Automated moderated nonlinear factor analysis (aMNLFA)

When generating scores to represent latent constructs, analysts have a choice between applying psychometric approaches that are principled but that can be complicated and time-intensive versus applying simple and fast, but less precise approaches, such as sum or mean scoring. We explain the reasons for preferring modern psychometric approaches: namely, use of unequal item weights and severity parameters, the ability to account for local dependence and differential item functioning, and the use of covariate information to more efficiently estimate factor scores. We describe moderated nonlinear factor analysis (MNLFA), a relatively new, highly flexible approach that allows analysts to develop precise factor score estimates that address limitations of sum score, mean score, and traditional factor analytic approaches to scoring. We then outline the steps involved in using the MNLFA scoring approach and discuss the circumstances in which this approach is preferred. To overcome the difficulty of implementing MNLFA models in practice, we developed an R package, aMNLFA, that automates much of the rule-based scoring process. We illustrate the use of aMNLFA with an empirical example of scoring alcohol involvement in a longitudinal study of 6998 adolescents and compare performance of MNLFA scores with traditional factor analysis and sum scores based on the same set of 12 items. MNLFA scores retain more meaningful variation than other approaches. We conclude with practical guidelines for scoring.

Longitudinal associations between conflict monitoring and emergent academic skills: An event-related potentials study

Identifying the links between specific cognitive functions and emergent academic skills can help determine pathways to support both early academic performance and later academic achievement. Here, we investigated the longitudinal associations between a key aspect of cognitive control, conflict monitoring, and emergent academic skills from preschool through first grade, in a large sample of socioeconomically diverse children (N = 261). We recorded event-related potentials (ERPs) during a Go/No-Go task. The neural index of conflict monitoring, ΔN2, was defined as larger N2 mean amplitudes for No-Go versus Go trials. ΔN2 was observed over the right hemisphere across time points and showed developmental stability. Cross-lagged panel models revealed prospective links from ΔN2 to later math performance, but not reading performance. Specifically, larger ΔN2 at preschool predicted higher kindergarten math performance, and larger ΔN2 at kindergarten predicted higher first-grade math performance, above and beyond the behavioral performance in the Go/No-Go task. Early academic skills did not predict later ΔN2. These findings provided electrophysiological evidence for the contribution of conflict monitoring abilities to emergent math skills. In addition, our findings suggested that neural indices of cognitive control can provide additional information in predicting emergent math skills, above and beyond behavioral task performance.

Recovering Predictor-Criterion Relations Using Covariate-Informed Factor Score Estimates

Although it is currently best-practice to directly model latent factors whenever feasible, there remain many situations in which this approach is not tractable. Recent advances in covariate-informed factor score estimation can be used to provide manifest scores that are used in second-stage analysis, but these are currently understudied. Here we extend our prior work on factor score recovery to examine the use of factor score estimates as predictors both in the presence and absence of the same covariates that were used in score estimation. Results show that whereas the relation between the factor score estimates and the criterion are typically well recovered, substantial bias and increased variability is evident in the covariate effects themselves. Importantly, using covariate-informed factor score estimates substantially, and often wholly, mitigates these biases. We conclude with implications for future research and recommendations for the use of factor score estimates in practice.

An Empirical Assessment of the Sensitivity of Mixture Models to Changes in Measurement

The current study explored the extent to which variations in self-report measures across studies can produce differences in the results obtained from mixture models. Data (N = 854) come from a laboratory analogue study of methods for creating commensurate scores of alcohol- and substance-use-related constructs when items differ systematically across participants for any given measure. Items were manipulated according to four conditions, corresponding to increasing levels of alteration to item stems, response options, or both. In Study 1, results from latent class analyses (LCA) of alcohol consequences were compared across the four conditions, revealing differences in class enumeration and configuration. In Study 2, results from factor mixture models (FMM) of alcohol expectancies were compared across two of the conditions, revealing differences in patterns and magnitude of the factor loadings and thresholds. The results suggest that even subtle differences in measurement can have substantively meaningful effects on mixture model results.

A Note on the Use of Mixture Models for Individual Prediction

Mixture models capture heterogeneity in data by decomposing the population into latent subgroups, each of which is governed by its own subgroup-specific set of parameters. Despite the flexibility and widespread use of these models, most applications have focused solely on making inferences for whole or sub-populations, rather than individual cases. The current article presents a general framework for computing marginal and conditional predicted values for individuals using mixture model results. These predicted values can be used to characterize covariate effects, examine the fit of the model for specific individuals, or forecast future observations from previous ones. Two empirical examples are provided to demonstrate the usefulness of individual predicted values in applications of mixture models. The first example examines the relative timing of initiation of substance use using a multiple event process survival mixture model whereas the second example evaluates changes in depressive symptoms over adolescence using a growth mixture model.

A multidimensional model of mothers' perceptions of parent alcohol socialization and adolescent alcohol misuse

We assessed a multidimensional model of parent alcohol socialization in which key socialization factors were considered simultaneously to identify combinations of factors that increase or decrease risk for development of adolescent alcohol misuse. Of interest was the interplay between putative risk and protective factors, such as whether the typically detrimental effects on youth drinking of parenting practices tolerant of some adolescent alcohol use are mitigated by an effective overall approach to parenting and parental modeling of modest alcohol use. The sample included 1,530 adolescents and their mothers; adolescents' mean age was 13.0 (SD = .99) at the initial assessment. Latent profile analysis was conducted of mothers' reports of their attitude toward teen drinking, alcohol-specific parenting practices, parental alcohol use and problem use, and overall approach to parenting. The profiles were used to predict trajectories of adolescent alcohol misuse from early to middle adolescence. Four profiles were identified: 2 profiles reflected conservative alcohol-specific parenting practices and 2 reflected alcohol-tolerant practices, all in the context of other attributes. Alcohol misuse accelerated more rapidly from Grade 6 through 10 in the 2 alcohol-tolerant compared with conservative profiles. Results suggest that maternal tolerance of some youth alcohol use, even in the presence of dimensions of an effective parenting style and low parental alcohol use and problem use, is not an effective strategy for reducing risky adolescent alcohol use. (PsycINFO Database Record

Using latent class growth analysis to form trajectories of premorbid adjustment in schizophrenia

Premorbid adjustment varies widely among individuals with schizophrenia and has been shown to bear significantly on prodrome and onset characteristics, and on cognition, symptoms, and functioning after onset. The current analysis focused on the Premorbid Adjustment Scale, a retrospective measure assessing social and academic function at several time points from early childhood to illness onset. In an effort to explore discrete developmental subtypes, we applied latent class growth analysis to data from the Premorbid Adjustment Scale in our sample of individuals with schizophrenia (N = 208), finding three latent trajectory classes. The first of these classes showed consistently adequate-to-good social and academic functioning before onset; the second showed initially good function and deterioration with time until onset; the third showed poor functioning in childhood that deteriorated further during the years up to diagnosis. The classes differed significantly in terms of age of onset, processing speed, and functioning after onset. There were no significant differences in symptomatology. Our findings illustrate a potentially powerful methodological approach to the problem of heterogeneity in schizophrenia research, and add weight to the notion that aspects of premorbid history may be useful for subtyping schizophrenia patients. The potential implications of this subtyping strategy, including those pertaining to potential genetics studies, are discussed.

Intra-individual variability across neuropsychological tasks in schizophrenia: a comparison of patients, their siblings, and healthy controls

Recently, higher degrees of intra-individual variability (IIV) across neuropsychological tasks have been linked to risk for developing schizophrenia. Extending these findings to examine not only disease risk but genetic susceptibility to schizophrenia, we examined IIV across five factor-based cognitive scores in a sample of schizophrenia patients, their unaffected siblings, and healthy volunteers. IIV was significantly different among probands, siblings, and controls, with groups showing decreasing variability in that order. In addition, modest associations between IIV, age, and functioning ability were found. In light of these results, IIV indices might represent useful tools in understanding cognition in schizophrenia.