Alcohol use trajectories and the ubiquitous cat's cradle: cause for concern?

Longitudinal Trajectories of Physical Teen Dating Perpetration and Trait Anger Expression: A Group-Based Trajectory Approach

Dating violence is often perpetrated among adolescents, which increases the efforts to better understand individual risk factors for preventive efforts. Although multiple forms (i.e., physical and psychological) often coexist, few studies have studied the chronicity and developmental classes of physical teen dating violence and examined whether subtypes of trait anger predict teen dating perpetration over time. Thus, the purpose of the current study is to investigate: (a) the developmental group-based patterns of physical teen dating violence; and (b) whether subtypes of trait anger expression predict association in these classes using the Bullying, Sexual, and Dating Violence Trajectories from Early to Late Adolescence in the Midwestern United States, 2007 to 2013 dataset. Group-based trajectory modeling results identified four classes of teen dating violence perpetration (e.g., Accelerating, Abstaining, Desisting, and High Chronic). Multinomial logistic regression results indicated that expressing anger outwardly was positively associated with Desisting and High Chronic patterns, but not Accelerating patterns. These results suggest that there are four classes of teen dating violence perpetration and underscore the effects of expression of trait anger as a risk factor of teen dating violence perpetration. Practical and theoretical implications are discussed.

Using machine learning to explore the predictors of life satisfaction trajectories in older adults

Life satisfaction is vital for older adults' well-being, impacting various life aspects. It is dynamic, necessitating nuanced approaches to capture its trajectories accurately. This study aimed to explore the diverse trajectories and predictors of life satisfaction among older adults in China using longitudinal data from the China Health and Retirement Longitudinal Study. Latent class growth modeling and growth mixture modeling were employed to identify distinct trajectories of life satisfaction. Machine learning (ML) models were developed to predict different trajectories and identify important predictors of different trajectories. Four distinct trajectories of life satisfaction were identified, showcasing nuanced patterns of life satisfaction that changed over time. ML models, especially random forest, effectively predicted these trajectories. Emotional experiences (particularly the frequency of happiness and loneliness), body mass index, and self-report health emerged as significant predictors of different life satisfaction trajectories. Our finding revealed the importance of focusing on individuals or groups with consistently low life satisfaction and paying more attention to mental and physical health predictors. Our models might guide future targeted preventative treatments.

Late adolescent outcomes of different developmental trajectories of ADHD symptoms in a large longitudinal study

There exists substantial heterogeneity in the developmental trajectories of ADHD symptoms, with distinctions often made between persistent versus remittent, and early- versus late-onset. However, how these trajectories relate to late adolescent functioning and whether, in particular, later onset trajectories mark a milder subtype remains unclear. Building on earlier work that has examined early life predictors of ADHD symptom trajectories up to age 14, we applied latent class growth analysis to data from the UK Millennium Cohort Study (N = 10,262) to evaluate whether developmental trajectories of ADHD symptoms up to age 17 (from age 3) were similar to those identified up to age 14 and associated with differing levels of impairment in peer victimisation, mental health, substance use, and delinquency outcomes at age 17. Our optimal model included five trajectory groups, labelled unaffected (37.6%), mildly affected (34.8%), subclinical remitting (14.4%), adolescent onset (7.6%), and stable high (5.6%). Adolescent onset and stable high trajectories were similarly impaired across all outcomes, other than substance use. Subclinical remitting individuals were impaired on self-esteem and well-being compared to unaffected individuals. By the end of mid-adolescence, those with a later onset have similar impairments to those following an early onset/persistent trajectory. Residual impairment may remain for those on a remitting trajectory.

Assessing the performance of group-based trajectory modeling method to discover different patterns of medication adherence

It is well known that medication adherence is critical to patient outcomes and can decrease patient mortality. The Pharmacy Quality Alliance (PQA) has recognized and identified medication adherence as an important indicator of medication-use quality. Hence, there is a need to use the right methods to assess medication adherence. The PQA has endorsed the proportion of days covered (PDC) as the primary method of measuring adherence. Although easy to calculate, the PDC has however several drawbacks as a method of measuring adherence. PDC is a deterministic approach that cannot capture the complexity of a dynamic phenomenon. Group-based trajectory modeling (GBTM) is increasingly proposed as an alternative to capture heterogeneity in medication adherence. The main goal of this paper is to demonstrate, through a simulation study, the ability of GBTM to capture treatment adherence when compared to its deterministic PDC analogue and to the nonparametric longitudinal K-means. A time-varying treatment was generated as a quadratic function of time, baseline, and time-varying covariates. Three trajectory models are considered combining a cat's cradle effect, and a rainbow effect. The performance of GBTM was compared to the PDC and longitudinal K-means using the absolute bias, the variance, the c-statistics, the relative bias, and the relative variance. For all explored scenarios, we find that GBTM performed better in capturing different patterns of medication adherence with lower relative bias and variance even under model misspecification than PDC and longitudinal K-means.

Counterfactual Mediation Analysis with a Latent Class Exposure

Latent classes are a useful tool in developmental research, however there are challenges associated with embedding them within a counterfactual mediation model. We develop and test a new method "updated pseudo class draws (uPCD)" to examine the association between a latent class exposure and distal outcome that could easily be extended to allow the use of any counterfactual mediation method. UPCD extends an existing group of methods (based on pseudo class draws) that assume that the true values of the latent class variable are missing, and need to be multiply imputed using class membership probabilities. We simulate data based on the Avon Longitudinal Study of Parents and Children, examine performance for existing techniques to relate a latent class exposure to a distal outcome ("one-step," "bias-adjusted three-step," "modal class assignment," "non-inclusive pseudo class draws," and "inclusive pseudo class draws") and compare bias in parameter estimates and their precision to uPCD when estimating counterfactual mediation effects. We found that uPCD shows minimal bias when estimating counterfactual mediation effects across all levels of entropy. UPCD performs similarly to recommended methods (one-step and bias-adjusted three-step), but provides greater flexibility and scope for incorporating the latent grouping within any commonly-used counterfactual mediation approach.

Limitations of two time point data for understanding individual differences in longitudinal modeling - What can difference reveal about change?

Emerging neuroimaging studies investigating changes in the brain aim to collect sufficient data points to examine trajectories of change across key developmental periods. Yet, current studies are often constrained by the number of time points available now. We demonstrate that these constraints should be taken seriously and that studies with two time points should focus on particular questions (e.g., group-level or intervention effects), while complex questions of individual differences and investigations into causes and consequences of those differences should be deferred until additional time points can be incorporated into models of change. We generated underlying longitudinal data and fit models with 2, 3, 4, and 5 time points across 1000 samples. While fixed effects could be recovered on average even with few time points, recovery of individual differences was particularly poor for the two time point model, correlating at r = 0.41 with the true individual parameters - meaning these scores share only 16.8% of variance As expected, models with more time points recovered the growth parameter more accurately; yet parameter recovery for the three time point model was still low, correlating around r = 0.57. We argue that preliminary analyses on early subsets of time points in longitudinal analyses should focus on these average or group-level effects and that individual difference questions should be addressed in samples that maximize the number of time points available. We conclude with recommendations for researchers using early time point models, including ideas for preregistration, careful interpretation of 2 time point results, and treating longitudinal analyses as dynamic, where early findings are updated as additional information becomes available.

Patterns and predictors of alcohol misuse trajectories from adolescence through early midlife

We took a multilevel developmental contextual approach and characterized trajectories of alcohol misuse from adolescence through early midlife, examined genetic and environmental contributions to individual differences in those trajectories, and identified adolescent and young adult factors associated with change in alcohol misuse. Data were from two longitudinal population-based studies. FinnTwin16 is a study of Finnish twins assessed at 16, 17, 18, 25, and 35 years (N = 5659; 52% female; 32% monozygotic). The National Longitudinal Study of Adolescent to Adult Health (Add Health) is a study of adolescents from the United States, who were assessed at five time points from 1994 to 2018 (N = 18026; 50% female; 64% White, 21% Black, 4% Native American, 7% Asian, 9% Other race/ethnicity). Alcohol misuse was measured as frequency of intoxication in FinnTwin16 and frequency of binge drinking in Add Health. In both samples, trajectories of alcohol misuse were best described by a quadratic growth curve: Alcohol misuse increased across adolescence, peaked in young adulthood, and declined into early midlife. Individual differences in these trajectories were primarily explained by environmental factors. Several adolescent and young adult correlates were related to the course of alcohol misuse, including other substance use, physical and mental health, and parenthood.

Problematic Alcohol Use Trajectories in U.S. Military Veterans during a Public Health Crisis: Results from a 3-year, Nationally Representative, Longitudinal Study

A growing number of studies have examined alcohol use during the COVID-19 pandemic. However, few longitudinal studies evaluated the prevalence and correlates of different trajectories of problematic alcohol use in vulnerable segments of the population, such as US veterans, over the 3-year course of the COVID-19 pandemic. Data were analyzed from the National Health and Resilience in Veterans Study, a nationally representative, longitudinal study of 2,441 US veterans. Latent growth mixture modeling was used to identify the trajectories and correlates of problematic alcohol use. Four trajectories were identified: consistent (N = 170, weighted 7.2%), decreasing (N = 38, weighted 2.2%), increasing (N = 22, weighted 1.2%), and low (N = 2,211, weighted 89.4%) problematic alcohol use. Greater household income, pre-pandemic drug use disorder (DUD), lower social support, and COVID-19 infection to self or non-household members were associated with an increasing relative to decreasing problematic alcohol use trajectory. Greater household income, adverse childhood experiences (ACEs), pre-pandemic DUD, lower social support, and greater COVID-related social restriction stress were associated with an increasing relative to a low problematic alcohol use trajectory. Younger age, male sex, ACEs, pre-pandemic DUD, lower pre-pandemic and greater decline in protective psychosocial characteristics, COVID-19 infection to non-household member, and lower COVID-related financial stress were associated with a consistent relative to a low problematic alcohol use trajectory. Overall, pre-pandemic greater income, DUD, and lower social support were associated with an increase in problematic alcohol use among US veterans during the COVID-19 pandemic. Results may help inform prevention efforts to mitigate problematic alcohol use during prolonged crises in this population.

Heavy episodic drinking in adolescence and alcohol-related problems in adulthood: A developmental approach to alcohol use across the life course

Heavy episodic drinking (HED) is a major public health concern, and youth who engage in HED are at increased risk for alcohol-related problems that continue into adulthood. Importantly, there is heterogeneity in the onset and course of adolescent HED, as youth exhibit different trajectories of initiation and progression into heavy drinking. Much of what is known about the etiology of adolescent HED and alcohol-related problems that persist into adulthood comes from studies of predominantly White, middle-class youth. Because alcohol use and related problems vary by race/ethnicity and socioeconomic status, it is unclear whether previous findings are relevant for understanding developmental antecedents and distal consequences of adolescent HED for minoritized individuals. In the current study, we utilize a developmental psychopathology perspective to fill this gap in the literature. Using a racially and economically diverse cohort followed from adolescence well into adulthood, we apply group-based trajectory modeling (GBTM) to identify patterns of involvement in HED from age 14 to 17 years. We then investigate developmental antecedents of GBTM class membership, and alcohol-related distal outcomes in adulthood (∼ age 31 years) associated with GBTM class membership. Results highlight the importance of adolescent alcohol use in predicting future alcohol use in adulthood.

Pain Trajectories among U.S. Veterans During COVID-19

Physical pain is highly prevalent among military veterans. As stress can impact pain, COVID-19-related stressors may have heightened pain among veterans. A prospective analysis of pain could advance understanding of how veterans fared during COVID-19 and lend knowledge of risk factors important beyond the pandemic. The present study employs growth mixture modeling with a sample of U.S. veterans high in pain (N = 1,230) followed from just before COVID-19 (February 2020) to 12 months later (February 2021; 81.7% retention). We explored heterogeneous pain trajectories as well as baseline and COVID-19-related predictors of pain. Results revealed 4 pain trajectory classes: 1) Chronic Pain (17.3% of the sample); 2) Decreasing Pain (57.2% of the sample); 3) Stable Mild Pain (19.8% of the sample); and 4) Increasing Pain (5.7% of the sample). Those with childhood trauma exposure were especially likely to report chronic pain. Female and racial/ethnic minority veterans were also relatively likely to fare poorly in pain. Loneliness was associated with subsequent pain among several classes. Most veterans in our sample fared better than expected in terms of pain. However, as those with childhood trauma and certain disadvantaged groups were less likely to fare well, we add to the important literature on disparities in pain. Clinicians should identify whether loneliness and other factors impacted pain during COVID-19 among their patients to inform ongoing, person-centered pain management approaches. PERSPECTIVE: This article presents pain trajectories and correlates of pain among a high-pain sample of U.S. veterans surveyed prior to and during COVID-19. Pain clinicians should screen for childhood trauma and remain vigilant in addressing health disparities.

Depressive symptoms predict trajectories of electronic delivery nicotine systems, cigarette, and cannabis use across 4.5 years among college students

BACKGROUND

This study examined the role of depressive symptoms on trajectories of electronic nicotine delivery systems (ENDS), cigarette, and cannabis use across 4.5 years in a sample of college students aged 18-19 at the initial study wave.

METHODS

Participants were 2,264 students enrolled in one of 24 Texas colleges that participated in a multi-wave study between 2014 and 2019. Latent growth mixture models were fit to identify longitudinal trajectories for past 30-day ENDS, cigarette, and cannabis use over a 4.5-year period. Class membership was regressed on baseline depressive symptoms in multinomial regression models.

RESULTS

Four trajectory classes were identified for each product: abstainer/minimal, decreasing, increasing, and high. Depressive symptoms were associated with a greater likelihood of belonging to the decreasing, increasing, and high trajectory classes relative to the abstainer/minimal class for all products, with the exception of the increasing ENDS class and the decreasing cannabis class.

DISCUSSION

The findings demonstrate that there is considerable similarity across trajectories of ENDS, cigarette, and cannabis use during traditional collegiate years. Furthermore, depressive symptoms increased the likelihood of belonging to substance using trajectory classes for all products.

Chronic, increasing, and decreasing peer victimization trajectories and the development of externalizing and internalizing problems in middle childhood

Children's peer victimization trajectories and their longitudinal associations with externalizing and internalizing problems were investigated from Grades 2 to 5. Secondary data analysis was performed with the Early Childhood Longitudinal Study (ECLS-K-2011; n = 13,860, M age = 8.1 years old in the spring of Grade 2; 51.1% male, 46.7% White, 13.2% African-American, 25.3% Hispanic or Latino, 8.5% Asian, and 6.1% other or biracial). Children who experienced high and persistent levels of peer victimization (high-chronic victims) exhibited co-occurring externalizing and internalizing problems. Moreover, among high-chronic victims, boys had a more pronounced increase in their externalizing trajectories, and girls had greater increases in their social anxiety trajectories. In contrast, those with decreasing peer victimization across time exhibited signs of recovery, particularly with respect to their social anxiety. These findings elucidated how chronic, increasing, and decreasing victims exhibited distinct patterns in the co-occurring development of their externalizing and internalizing problems, and how findings varied depending on the form of problem behavior and by child sex.

Associations of adult roles and minority stressors with trajectories of alcohol dependence symptoms throughout adulthood among sexual minority women

OBJECTIVE

In the present study, we sought to identify trajectories of symptoms of potential alcohol dependence (AD) among adult sexual minority women (SMW). Theoretical correlates were examined in relation to the empirically identified trajectories.

METHOD

Data were collected at three time points between 2000 and 2012 from SMW drinkers (n = 434) enrolled in a longitudinal study (M Age = 37.49 at baseline, SD = 11.55). Using an accelerated-cohort longitudinal design, latent growth curve mixture models identified homogeneous patterns of any past-year symptoms of potential AD. Correlates of trajectories included alcohol-related developmental risk factors, adult roles, and exposure to minority stressors.

RESULTS

Three trajectories were identified that captured risk of symptoms of potential AD over time, reflecting: (a) relatively consistent, low risk over time; (b) deceleration in risk throughout adulthood; (c) relatively persistent, high risk over time. Consistent with prior work, SMW drinkers who reported higher levels of perceived stigma or masculinity showed persistently high risk of reporting at least one past-year symptom of potential AD.

CONCLUSIONS

Most SMW drinkers report deceleration in risk of AD symptoms over time. Findings have implications for prevention and intervention efforts tailored to SMW drinkers. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A Clinical Psychologist Who Studies Alcohol

In this article, I describe why I believe the study of alcohol use and its consequences is a rich and rewarding area of scholarly activity that touches on multiple disciplines in the life sciences, the behavioral sciences, and the humanities. I then detail the circuitous path I took to become an alcohol researcher and the various challenges I encountered when starting up my research program at the University of Missouri. A major theme of my journey has been my good fortune encountering generous, brilliant scholars who took an interest in me and my career and who helped guide and assist me over the course of my career. I also highlight selected, other professional activities I've been involved in, focusing on editorial work, quality assurance, and governance of professional societies. While the focus is on my training and work as a psychologist, the overarching theme is the interpersonal context that nurtures careers.

Correlates of Alcohol Use Likelihood for Latino Immigrant Youth in an Emerging Context

Using a three-wave prospective longitudinal design spanning 3 years, we assessed alcohol use likelihood trajectories and their correlates among a community sample of Latino immigrant adolescents in the emerging immigrant context of Western Oregon. Results from growth mixture modeling revealed two distinct classes: lower risk youth who reported little likelihood of alcohol use but whose trajectory was increasing, and higher risk youth who reported higher likelihood of alcohol use and whose trajectory was stable. We found significant differences between the two classes such that lower risk youth reported greater levels of Latino cultural orientation and parental monitoring, whereas higher risk youth reported greater levels of family cultural stress and delinquency. Results are discussed in terms of prior research and theory.

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.

Developmental trajectories of autistic social traits in the general population

BACKGROUND

Autistic people show diverse trajectories of autistic traits over time, a phenomenon labelled 'chronogeneity'. For example, some show a decrease in symptoms, whilst others experience an intensification of difficulties. Autism spectrum disorder (ASD) is a dimensional condition, representing one end of a trait continuum that extends throughout the population. To date, no studies have investigated chronogeneity across the full range of autistic traits. We investigated the nature and clinical significance of autism trait chronogeneity in a large, general population sample.

METHODS

Autistic social/communication traits (ASTs) were measured in the Avon Longitudinal Study of Parents and Children using the Social and Communication Disorders Checklist (SCDC) at ages 7, 10, 13 and 16 (N = 9744). We used Growth Mixture Modelling (GMM) to identify groups defined by their AST trajectories. Measures of ASD diagnosis, sex, IQ and mental health (internalising and externalising) were used to investigate external validity of the derived trajectory groups.

RESULTS

The selected GMM model identified four AST trajectory groups: (i) Persistent High (2.3% of sample), (ii) Persistent Low (83.5%), (iii) Increasing (7.3%) and (iv) Decreasing (6.9%) trajectories. The Increasing group, in which females were a slight majority (53.2%), showed dramatic increases in SCDC scores during adolescence, accompanied by escalating internalising and externalising difficulties. Two-thirds (63.6%) of the Decreasing group were male.

CONCLUSIONS

Clinicians should note that for some young people autism-trait-like social difficulties first emerge during adolescence accompanied by problems with mood, anxiety, conduct and attention. A converse, majority-male group shows decreasing social difficulties during adolescence.

Mental-Health Trajectories of U.S. Parents With Young Children During the COVID-19 Pandemic: A Universal Introduction of Risk

Parents of young children were a subgroup of the population identified early in the pandemic as experiencing significant mental-health symptoms. Using a longitudinal sample of 3,085 parents from across the United States who had a child or children age 0 to 5, in the present study, we identified parental mental-health trajectories from April to November 2020 predicted by pre-COVID-19 cumulative risk and COVID-19-specific risk factors. Both growth-mixture modeling and latent-growth-curve modeling were used to test the relationship between risk factors and parent mental health. Pre-COVID-19 cumulative risk and COVID-19-specific risks of financial strain, decreased employment, and increased family conflict were salient risk factors predicting poor mental-health trajectories across both modeling approaches. These finding have public-health implications because prolonged exposure to mental-health symptoms in parents constitutes a risk factor for child development.

Roads Diverged: Developmental Trajectories of Irritability From Toddlerhood Through Adolescence

OBJECTIVE

Irritability is a dimensional trait that manifests from early life and is a robust transdiagnostic risk factor for psychopathology and impairment. A large, national dataset was leveraged to identify and broadly characterize trajectories from toddlerhood through adolescence, which is crucial for timely, targeted interventions.

METHOD

Data on irritability and a broad array of potential factors affecting irritability development from 4,462 children assessed longitudinally at ages 3, 5, 9, and 15 were included. Latent class growth models identified groups of children based on their nonlinear irritability trajectories from toddlerhood to adolescence. LASSO regression then identified key characteristics differentiating trajectory groups.

RESULTS

Five distinct irritability trajectories were identified, two of which were stable, maintaining medium or high irritability from age 3 to 15. Three trajectories showed undulating change over development, with an inflection point at the transition to adolescence (age 9): Most children had consistently low irritability. Two smaller groups started with high irritability at age 3 but diverged, sharply decreasing or increasing until a turning point at age 9. Developmental patterning of harsh/neglectful parenting and child internalizing symptoms most strongly differentiated trajectory groups. Sociodemographic characteristics, attachment style, neighborhood support, cognitive functioning, and genetic variation also differentiated trajectories.

CONCLUSION

The results demonstrated the importance of the transition to adolescence as a critical inflection point for youths with fluctuating irritability trajectories. Identifying these patterns and multiple malleable factors associated with stably high or rising trajectories is an important step toward targeted interventions for the most vulnerable subgroups.

DIVERSITY & INCLUSION STATEMENT

We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. One or more of the authors of this paper self-identifies as living with a disability. One or more of the authors of this paper received support from a program designed to increase minority representation in science. We actively worked to promote sex and gender balance in our author group. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group.

Associations of attention problems and family context in childhood and adolescence with young adult daily smoking: General and smoking-specific family contexts

BACKGROUND

The potential heterogeneity in daily smoking across young adulthood has been relatively understudied. Relatedly, the unique and joint associations of earlier risk factors with young adults' daily smoking largely remain unknown. To address these gaps, this work identified subgroups of daily smoking trajectories during young adulthood and linked them to earlier attention problems and smoking-specific and general family context.

METHODS

Data came from the Seattle Social Development Project, a longitudinal study following a community sample (N = 808). Participants' daily smoking was measured from ages 21-33. Earlier attention problems were assessed at ages 14-16 and 18. Earlier smoking-specific and general family factors were assessed at ages 10-16 and 18.

RESULTS

Growth mixture models produced four profiles: chronic daily smokers, increasers, decreasers, and no-daily smokers. Results from multinomial logistic regressions revealed that earlier attention problems and smoking-specific family factors may contribute to daily smoking in the early 20 s, whereas earlier general family context provided protection for trajectories of daily smoking characterized by changes in the late 20 s and early 30 s DISCUSSION: Selective prevention strategies that expand people's repertoire of healthy options to address attention problems might be helpful, considering the possibility of using tobacco as means to mitigate attention problems. Our findings also highlight the importance of nurturing earlier general family context, a relatively overlooked dimension in smoking prevention efforts, to facilitate young adult smokers' desistence from daily smoking, particularly those who have attention problems in adolescence.

Does group-based trajectory modeling estimate spurious trajectories?

BACKGROUND

Group-based trajectory modelling (GBTM) is increasingly used to identify subgroups of individuals with similar patterns. In this paper, we use simulated and real-life data to illustrate that GBTM is susceptible to generating spurious findings in some circumstances.

METHODS

Six plausible scenarios, two of which mimicked published analyses, were simulated. Models with 1 to 10 trajectory subgroups were estimated and the model that minimized the Bayes criterion was selected. For each scenario, we assessed whether the method identified the correct number of trajectories, the correct shapes of the trajectories, and the mean number of participants of each trajectory subgroup. The performance of the average posterior probabilities, relative entropy and mismatch criteria to assess classification adequacy were compared.

RESULTS

Among the six scenarios, the correct number of trajectories was identified in two, the correct shapes in four and the mean number of participants of each trajectory subgroup in only one. Relative entropy and mismatch outperformed the average posterior probability in detecting spurious trajectories.

CONCLUSION

Researchers should be aware that GBTM can generate spurious findings, especially when the average posterior probability is used as the sole criterion to evaluate model fit. Several model adequacy criteria should be used to assess classification adequacy.

Trajectories of Substance Use and Well-being in Early and Middle Adolescence Shaped by Social Connectedness

Increasing substance use and decreasing well-being are typical in adolescence, yet how social contexts shape disparate development during this time is less well-understood. A latent growth class analysis was conducted that identified groups of early (N = 706; Age_m  = 12.20) and middle (N = 666; Age_m  = 14.38) adolescents distinguished by rates of substance use and well-being over three years. In both cohorts, the largest group reported low substance use and high well-being, with a smaller group exhibiting maladaptive trajectories for both substance use and well-being. Two additional groups were identified during middle adolescence characterized by either low well-being or high substance use. Family connectedness was a protective factor, while high peer connectedness was a risk factor for substance-use groups and low peer connectedness for languishing.

Trajectories of childhood social isolation in a nationally representative cohort: Associations with antecedents and early adulthood outcomes

Background

This study examined early life antecedents of childhood social isolation, whether these factors accounted for poor outcomes of isolated children, and how these associations varied according to patterns of stability and change in childhood isolation.

Methods

Participants included 2232 children from the Environmental Risk (E-Risk) Longitudinal Twin Study. We conducted growth mixture modelling (GMM) on combined parent and teacher reports of children's social isolation when children were 5, 7, 10 and 12 years, and we assessed associations with age-5 antecedents and age-18 outcomes using regression analyses.

Results

We identified three linear developmental trajectories of increasing (4.75%), decreasing (5.25%) and low stable (90.00%) social isolation. Age-5 attention deficit hyperactivity disorder (ADHD) symptoms, emotional problems, prosocial behaviours, maternal personality (openness) and size of school were associated with the decreasing trajectory of social isolation. When controlling for these antecedents, increasingly isolated children were still more likely to experience ADHD symptoms, loneliness, lower job optimism and lower physical activity at age 18.

Conclusions

Isolated children follow distinct patterns of change over childhood and isolation seems most detrimental to health at the time it is experienced. Social isolation can be a valuable indicator of co-occurring problems and provide targets for mental health intervention in young people.

Longitudinal associations of emerging adults' drinking trajectories with their behavior, health, education and work outcomes 1, 4, and 9 years later

BACKGROUND

To characterize emerging adults' drinking trajectories and their prospective association with later behavior, health, education, and work outcomes in later young adulthood.

METHODS

This study used a selected cohort (N = 1622) from rounds 3-10 (aged 18-25), 11 (aged 26), 14 (aged 29), and 17 (aged 34) of the US National Longitudinal Survey of Youth 1997. Latent class growth modeling was used to identify trajectories of drinking (days ≥1 drink in the last 30 days) during emerging adulthood (aged 18-25) using data from rounds 3-10. Multinomial and linear regressions compared identified trajectory classes to outcomes measured 1, 4, and 9 years later. Covariates included sex, race, and urbanicity.

RESULTS

Six drinking trajectories were identified: Abstainers (28.42%), Moderate Increasers (24.78%), Light Experimenters (11.96%), Heavy Experimenters (9.86%), Escalators (17.26%), and Heavy Users (7.71%). Compared to abstainers, emerging adults in other classes had significantly (p < .05 to.001) higher odds of binge drinking, smoking, and marijuana use at later rounds. Compared to abstainers, escalators had significantly higher education and income later. No significant difference in physical or mental health was found.

CONCLUSION

Drinking behaviors formed during emerging adulthood continue into later lifetime periods in adulthood. The experimenters shifted their drinking behaviors to greater smoking and marijuana use, while heavy users supplemented their drinking behavior. Interventions in emerging adulthood (particularly ages 19-21), the period when individuals are becoming more independent but malleable, may mitigate adverse effects of alcohol overuse and improve later life behaviors and career outcomes.

Latent Classes of Substance Use in Young Adults - A Systematic Review

Background: This systematic review provides an overview of studies on latent classes related to the substance use among young adults (18-25 years). Identifying these classes helps to detect high-risk groups, setting a base for selective prevention.Methods: This systematic literature review included peer-reviewed studies (published up to February, 2021) that identified latent classes and investigated predictors of latent classes relating to the use of marijuana, alcohol and/or other substances within samples of young adults.Results: Twenty studies (sample sizes N = 171 to N = 21945) met the inclusion criteria. 14 studies identified 'low-level engagers', 'light alcohol and tobacco use', 'heavy alcohol and tobacco use' and 'heavy use/polysubstance use' classes. Four studies differentiated within the 'heavy/polysubstance' class and found 'traditional clubdrugs', 'hallucinogens' and 'wide-range illicit drugs' classes. Male gender and white race predicted membership of the 'heavy use/polysubstance use' class consistently across studies. Other predictors of polysubstance use that were consistent across studies were peer substance use, depressive symptoms, parental drinking and participating in an honor society.Conclusions: The investigated predictors of class membership provide insight into social settings and characteristics that predict heavy use or polysubstance use. They can contribute to the development of effective prevention interventions by allowing for a more targeted approach.

Revisiting trajectories of BMI in youth: An in-depth analysis of differences between BMI and other adiposity measures

OBJECTIVE

Body mass index (BMI) is used to identify trajectories of adiposity in youth, but it does not distinguish fat- from fat-free-mass. There are other inexpensive measures of adiposity which might better capture fat-mass in youth The objective of this study is to examine differences between sex-specific trajectories of BMI and other adiposity indicators (subscapular and triceps skinfold thickness, waist circumference, waist-to-height ratio) which may better capture fat-mass in youth.

METHODS

Data come from four cycles of a longitudinal cohort of 1293 students in Montréal, Canada at ages 12, 15, 17 and 24. Group-based trajectory models identified sex-specific adiposity trajectories among participants with data in ≥3 cycles (n = 417 males; n = 445 females).

RESULTS

There were six trajectory groups in males and females for all five indicators, except for waist circumference (seven) in both sexes and triceps skinfold thickness (four) and waist-to-height ratio (five) in females. Most trajectories indicated linear increases; only the skinfold thickness indicators identified a decreasing trajectory. While all indicators identified a trajectory with high levels of adiposity, they differed in the number and relative size of trajectories pertaining to individuals in lower half of the adiposity distribution.

CONCLUSION

BMI is a satisfactory indicator of adiposity in youth if the aim of the trajectory analysis is to identify youth with excess adiposity, a known risk factor for cardiometabolic outcomes in adulthood.

Longitudinal predictors of suicidal ideation: Emerging to early adulthood

Few studies have examined the longitudinal trajectory of suicidal ideation (SI) in community samples, particularly during emerging adulthood. Additionally, there is scant data on predictors of longer-term course of SI across this period. We examined multiple domains of adolescent psychosocial and clinical functioning as predictors of SI trajectory and explored whether biological sex moderates those associations. The data came from the Oregon Adolescent Depression Project. Participants completed self-reports of psychosocial and clinical functioning and interviews assessing psychopathology in mid-late adolescence. SI was assessed using up to seven annual mailer assessments spanning ages 19-31. Multilevel growth models found that SI declined across emerging adulthood. Multiple indices of adolescent functioning were associated with higher levels of SI three years later. Few adolescent functioning constructs predicted faster reductions in SI, and no constructs predicted slower longitudinal reductions (or increases) in SI. Similar associations were found when controlling for adolescent SI. Lastly, we found little evidence for sex differences in these associations. This work shows that adolescent functioning is largely associated with initial and enduring levels of SI. Moreover, associations were similar between sexes. Given the modest associations found across long periods of time, future research should focus on proximal risk factors for SI.

Heavy alcohol consumption before and after negative life events in late mid-life: longitudinal latent trajectory analyses

Background

People who experience negative life events report more heavy alcohol consumption compared with people without these experiences, but little is known about patterns of change within this group. This study aims to identify trajectories of heavy alcohol consumption before and after experiencing either divorce, or severe illness or death in the family. Furthermore, the aim is to examine characteristics of individuals belonging to each trajectory.

Methods

Longitudinal study of public sector employees from the Finnish Retirement and Aging Study with up to 5 years of annual follow-ups (n=6783; eligible sample n=1393). Divorce and severe illness or death in the family represented negative life events. Heavy alcohol consumption was categorised as >14 units/week.

Results

Based on latent trajectory analysis, three trajectories of heavy drinking were identified both for divorce and for severe illness or death in the family: ‘No heavy drinking’ (82% illness/death, 75% divorce), ‘Constant heavy drinking’ (10% illness/death, 13% divorce) and ‘Decreasing heavy drinking’ (7% illness/death, 12% divorce). Constant heavy drinkers surrounding illness or death in the family were more likely to be men, report depression and anxiety and to smoke than those with no heavy drinking. Constant heavy drinkers surrounding divorce were also more likely to be men and to report depression compared with those with no heavy drinking.

Conclusions

Most older workers who experience divorce or severe illness or death in the family have stable drinking patterns regarding heavy alcohol consumption, that is, most do not initiate or stop heavy drinking.

Maternal Parenting Behaviors Amplify Environmental Influences on Developmental Trajectories of Alcohol Use During Adolescence

Compared to peer alcohol use, less is known on how parenting practices may modify genetic and environmental contributions to alcohol use longitudinally across adolescence. This study examined whether two maternal parenting behaviors, supervision and harsh parenting, may suppress or amplify genetic and environmental influences on three distinct developmental trajectories of adolescent alcohol use: normative increasing, early-onset, and low trajectories. Participants were drawn from a longitudinal study of a population-based twin sample (N = 842, 84% European descent, 52.7% female). Adolescents self-reported their past year alcohol use at ages 13, 14, 15, and 17 years, and their mothers reported their supervision and harsh parenting when twins were 13, 15, and 17 years old. Maternal supervision amplified non-shared environmental influence on the normative increasing and early-onset trajectories, whereas maternal harsh parenting amplified shared environmental influence on the early-onset trajectory and non-shared environmental influence on the low trajectory, respectively. The findings suggest maternal parenting practices as a potent developmental context that modulates the environmental influences of other proximal processes on adolescent alcohol use, and suggest that family-based parenting-focused intervention could be especially beneficial for adolescents following the early-onset trajectory.

Cigarette smoking trajectories in adolescent smokers: Does the time axis metric matter?

INTRODUCTION

Most studies modeling adolescent cigarette smoking trajectories use age as the time axis, possibly obscuring depiction of the natural course of cigarette smoking. We used a simulated example and real data to contrast smoking trajectories obtained from models that used time since smoking onset or calendar time (age) as the time axis.

METHODS

Data were drawn from a longitudinal investigation of 1293 grade 7 students (mean age 12.8 years) recruited from 10 high schools in Montreal, Canada in 1999-2000, who were followed into young adulthood. Cigarette consumption was measured every 3 months during high school, and again at mean age 20.4 and 24.0. Analyses using time since onset of smoking as the time metric was restricted to 307 incident smokers; analysis using calendar time included 645 prevalent and incident smokers. Smoking status and nicotine dependence (ND) were assessed at mean age 20.4 and 24.0. Simulated data mimicked the real study during high school.

RESULTS

Use of different time metrics resulted in different numbers and shapes of trajectories in the simulated and real datasets. Participants in the calendar time analyses reported more ND in young adulthood, reflecting inclusion of 388 prevalent smokers who had smoked for longer durations.

CONCLUSIONS

Choosing the right time metric for trajectory analysis should be balanced against research intent. Trajectory analyses using the time since onset metric depict the natural course of smoking in incident smokers. Those using calendar time offer a snapshot of smoking across age during a given time period.

IMPLICATIONS

This study uses simulated and real data to show that trajectory analyses of cigarette smoking that use calendar time (e.g., age) versus time since onset as the time axis metric tell a different story. Trajectory analyses using the time since onset metric depict the natural course of smoking in incident smokers. Those using calendar time offer a snapshot of smoking across age during a given time period. Choosing the right time metric should be balanced against research intent.

Prediction of eating disorder treatment response trajectories via machine learning does not improve performance versus a simpler regression approach

OBJECTIVE

Patterns of response to eating disorder (ED) treatment are heterogeneous. Advance knowledge of a patient's expected course may inform precision medicine for ED treatment. This study explored the feasibility of applying machine learning to generate personalized predictions of symptom trajectories among patients receiving treatment for EDs, and compared model performance to a simpler logistic regression prediction model.

METHOD

Participants were adolescent girls and adult women (N = 333) presenting for residential ED treatment. Self-report progress assessments were completed at admission, discharge, and weekly throughout treatment. Latent growth mixture modeling previously identified three latent treatment response trajectories (Rapid Response, Gradual Response, and Low-Symptom Static Response) and assigned a trajectory type to each patient. Machine learning models (support vector, k-nearest neighbors) and logistic regression were applied to these data to predict a patient's response trajectory using data from the first 2 weeks of treatment.

RESULTS

The best-performing machine learning model (evaluated via area under the receiver operating characteristics curve [AUC]) was the radial-kernel support vector machine (AUCRADIAL = 0.94). However, the more computationally-intensive machine learning models did not improve predictive power beyond that achieved by logistic regression (AUCLOGIT = 0.93). Logistic regression significantly improved upon chance prediction (MAUC[NULL] = 0.50, SD = .01; p <.001).

DISCUSSION

Prediction of ED treatment response trajectories is feasible and achieves excellent performance, however, machine learning added little benefit. We discuss the need to explore how advance knowledge of expected trajectories may be used to plan treatment and deliver individualized interventions to maximize treatment effects.

Trajectories of Emotional and Conduct Problems and Their Association With Early High School Achievement and Engagement for Adolescents With ADHD

Objective: This study aimed to (a) identify longitudinal trajectories of emotional and conduct problems from middle childhood to early adolescence in a sample of 130 adolescents diagnosed with ADHD and (b) examine trajectories in relation to early adolescent academic achievement and engagement. Method: Group-based trajectory models (GBTMs) were constructed from the parent-rated strengths and difficulties questionnaire (SDQ) subscales of emotional and conduct problems at three time points, mean ages 10.7 years, 11.6 years, and 13.7 years. Associations between trajectories and adolescent academic achievement and engagement were examined using multivariate regression. Results: Four distinct trajectories were identified within each domain. High-persistent problem trajectories in each domain were associated with poorer achievement and lower school engagement compared with adolescents following persistent-low problem trajectories. Conclusion: Findings highlight the importance of early assessment and management of comorbid emotional and conduct problems for children with ADHD as they predict school difficulties during early high school. (J. of Att. Dis. XXXX; XX(X) XX-XX).

Examining the time-varying association of negative affect and covariates with craving during treatment for prescription opioid dependence with two types of mixed models

Opioid use disorders are chronic and relapse is common. Both negative affect and craving have been suggested antecedents of relapse and have been shown to demonstrate within- and between-person variability, as well as association with each other. The present study extends previous research by examining the covariation of negative affect and craving both within-day and at the person-level during 12 days of treatment among opioid-dependent patients. Ecological momentary assessment (EMA) data were collected from 73 participants starting between 10 and 14 days after admission to an inpatient treatment facility. These data were analyzed using multivariate multilevel models and time-varying effect models. Results demonstrated strong association between negative affect and craving. Within-day, negative affect and craving were most associated in the early afternoon. At the person-level, association between negative affect and craving declined during the first week of data collection. Following this initial decline in association, negative affect and craving increasingly covaried during days 8-12 of data collection. To our knowledge, this is the first study to report a lagged increase in the association between negative affect and craving among patients during inpatient treatment for opioid dependence. Implications for research and treatment providers are discussed.

Examining the time-varying association of negative affect and covariates with craving during treatment for prescription opioid dependence with two types of mixed models

Opioid use disorders are chronic and relapse is common. Both negative affect and craving have been suggested antecedents of relapse and have been shown to demonstrate within- and between-person variability, as well as association with each other. The present study extends previous research by examining the covariation of negative affect and craving both within-day and at the person-level during 12 days of treatment among opioid-dependent patients. Ecological momentary assessment (EMA) data were collected from 73 participants starting between 10 and 14 days after admission to an inpatient treatment facility. These data were analyzed using multivariate multilevel models and time-varying effect models. Results demonstrated strong association between negative affect and craving. Within-day, negative affect and craving were most associated in the early afternoon. At the person-level, association between negative affect and craving declined during the first week of data collection. Following this initial decline in association, negative affect and craving increasingly covaried during days 8-12 of data collection. To our knowledge, this is the first study to report a lagged increase in the association between negative affect and craving among patients during inpatient treatment for opioid dependence. Implications for research and treatment providers are discussed.

Post-traumatic growth as positive personality change: Challenges, opportunities, and recommendations

OBJECTIVE

Post-traumatic growth typically refers to enduring positive psychological change experienced as a result of adversity, trauma, or highly challenging life circumstances. Critics have challenged insights from much of the prior research on this topic, pinpointing its significant methodological limitations. In response to these critiques, we propose that post-traumatic growth can be more accurately captured in terms of personality change-an approach that affords a more rigorous examination of the phenomenon.

METHOD

We outline a set of conceptual and methodological questions and considerations for future work on the topic of post-traumatic growth.

RESULTS

We provide a series of recommendations for researchers from across the disciplines of clinical/counseling, developmental, health, personality, and social psychology and beyond, who are interested in improving the quality of research examining resilience and growth in the context of adversity.

CONCLUSION

We are hopeful that these recommendations will pave the way for a more accurate understanding of the ubiquity, durability, and causal processes underlying post-traumatic growth.

Improving convergence in growth mixture models without covariance structure constraints

Growth mixture models are a popular method to uncover heterogeneity in growth trajectories. Harnessing the power of growth mixture models in applications is difficult given the prevalence of nonconvergence when fitting growth mixture models to empirical data. Growth mixture models are rooted in the random effect tradition, and nonconvergence often leads researchers to modify their intended model with constraints in the random effect covariance structure to facilitate estimation. While practical, doing so has been shown to adversely affect parameter estimates, class assignment, and class enumeration. Instead, we advocate specifying the models with a marginal approach to prevent the widespread practice of sacrificing class-specific covariance structures to appease nonconvergence. A simulation is provided to show the importance of modeling class-specific covariance structures and builds off existing literature showing that applying constraints to the covariance leads to poor performance. These results suggest that retaining class-specific covariance structures should be a top priority and that marginal models like covariance pattern growth mixture models that model the covariance structure without random effects are well-suited for such a purpose, particularly with modest sample sizes and attrition commonly found in applications. An application to PTSD data with such characteristics is provided to demonstrate (a) convergence difficulties with random effect models, (b) how covariance structure constraints improve convergence but to the detriment of performance, and (c) how covariance pattern growth mixture models may provide a path forward that improves convergence without forfeiting class-specific covariance structures.

Genotype-environment correlation by intervention effects underlying middle childhood peer rejection and associations with adolescent marijuana use

Aggressive behavior in middle childhood can contribute to peer rejection, subsequently increasing risk for substance use in adolescence. However, the quality of peer relationships a child experiences can be associated with his or her genetic predisposition, a genotype-environment correlation (rGE). In addition, recent evidence indicates that psychosocial preventive interventions can buffer genetic predispositions for negative behavior. The current study examined associations between polygenic risk for aggression, aggressive behavior, and peer rejection from 8.5 to 10.5 years, and the subsequent influence of peer rejection on marijuana use in adolescence (n = 515; 256 control, 259 intervention). Associations were examined separately in control and intervention groups for children of families who participated in a randomized controlled trial of the family-based preventive intervention, the Family Check-Up . Using time-varying effect modeling (TVEM), polygenic risk for aggression was associated with peer rejection from approximately age 8.50 to 9.50 in the control group but no associations were present in the intervention group. Subsequent analyses showed peer rejection mediated the association between polygenic risk for aggression and adolescent marijuana use in the control group. The role of rGEs in middle childhood peer processes and implications for preventive intervention programs for adolescent substance use are discussed.

Covariance pattern mixture models: Eliminating random effects to improve convergence and performance

Growth mixture models (GMMs) are prevalent for modeling unknown population heterogeneity via distinct latent classes. However, GMMs are riddled with convergence issues, often requiring researchers to atheoretically alter the model with cross-class constraints simply to obtain convergence. We discuss how within-class random effects in GMMs exacerbate convergence issues, even though these random effects rarely help answer typical research questions. That is, latent classes provide a discretization of continuous random effects, so including additional random effects within latent classes can unnecessarily complicate the model. These random effects are commonly included in order to properly specify the marginal covariance; however, random effects are inefficient for patterning a covariance matrix, resulting in estimation issues. Such a goal can be achieved more simply through covariance pattern models, which we extend to the mixture model context in this article (covariance pattern mixture models, or CPMMs). We provide evidence from theory, simulation, and an empirical example showing that employing CPMMs (even if they are misspecified) instead of GMMs can circumvent the computational difficulties that can plague GMMs, without sacrificing the ability to answer the types of questions commonly asked in empirical studies. Our results show the advantages of CPMMs with respect to improved class enumeration and less biased class-specific growth trajectories, in addition to their vastly improved convergence rates. The results also show that constraining the covariance parameters across classes in order to bypass convergence issues with GMMs leads to poor results. An extensive software appendix is included to assist researchers in running CPMMs in Mplus.

Testing a Socioecological Model of Relapse and Recovery from Alcohol Problems

This study tests a socioecological model of relapse and recovery using latent class growth mixture modeling to identify neighborhood, social network and individual-level predictors of alcohol dependence trajectories among a large, longitudinal sample of problem drinkers recruited from substance use treatment settings. We identified four distinct alcohol dependence trajectories: Stable Recovery/Low (Class 1); Relapsing/Rising (Class 2); Late Recovery/Declining (Class 3); and Chronic/High (Class 4). Neighborhood context (poverty and density of bars), social network characteristics (less involvement with Alcoholics Anonymous [AA], continued affiliation with heavy drinkers), and individual predisposing (psychiatric severity) and need (returning to treatment) characteristics each distinguished individuals in the Relapsing/Rising class from individuals in the Stable Recovery/Low class. Social network characteristics (AA involvement and continued affiliation with heavy drinkers) were the primary distinguishing factors for individuals in the Chronic/High class compared to the Late Recovery/Declining class. Study findings can be used to promote recovery and help prevent relapse by: guiding development of community-level interventions to improve social and physical environments; identifying potentially modifiable factors (social network support for sobriety, participation in self-help) to reduce negative consequences among problem drinkers who remain in high-risk neighborhoods; and contributing to ongoing discussions about new and continued licensing of alcohol outlets and regulation of alcohol sales to prevent alcohol problems in high-risk areas and among high-risk people.

Discrete time measures versus trajectories of drinking frequency across adolescence as predictors of binge drinking in young adulthood: a longitudinal investigation

OBJECTIVES

We compared discrete time measures with trajectories of adolescent drinking frequency as predictors of sustained binge drinking in young adulthood.

DESIGN

Prospective longitudinal study.

SETTING

10 high schools in Montréal, Canada.

PARTICIPANTS

1293 high-school students followed from mean (SD) age 12 (0.6) to 24 (0.7) years.

PRIMARY OUTCOME MEASURES

Patterns of drinking frequency (self-reports every 3 months from ages 12 to 17) identified using group-based trajectory modelling. Sustained binge drinking was defined as binging monthly or more often at both ages 20 and 24.

ANALYSES

Using logistic regression, sustained binge drinking was regressed on trajectory group membership and on four discrete time measures (frequency of drinking at age 12; frequency of drinking at age 17; age at drinking onset; age at onset of drinking monthly or more often).

RESULTS

We identified seven drinking trajectories: late triers (15.2%), decreasers (9.5%), late escalators (10.4%), early slow escalators (16.5%), steady drinkers (14.4%), early rapid escalators (15.8%) and early frequent drinkers (18.2%). Sustained binge drinking was reported by 260 of 787 participants (33.0%) with complete data at both ages 20 and 24. Decreasers did not differ from late triers; all other patterns were associated with higher odds of sustained binge drinking (adjusted ORs: AORs=1.4-17.0). All discrete time measures were associated with sustained binge drinking, notably frequency at age 12 (a bit to try and drinking monthly: (AORs=2.6 (1.7; 3.9) and 2.8 (1.3; 6.1), respectively), age of drinking onset <13 years (AOR=7.6 (3.0; 24.1)), and any age of onset of drinking monthly or more often (AORs=5.1-8.2).

CONCLUSION

Youth at risk of sustained binge drinking as young adults can be identified with indicators of early drinking as early as 7th grade (aged 12-13 years). Identification of easy-to-obtain indicators can facilitate screening and intervention efforts.

A systematic review of cigarette smoking trajectories in adolescents

Trajectory analyses differentiate subgroups of smokers based on early patterns of cigarette use, but no study has summarized this literature. We systematically reviewed the literature on adolescent cigarette smoking trajectories to document the number and shapes of trajectories identified, assess if certain study characteristics influence the number or shapes of trajectories identified, summarize factors associated with and outcomes of trajectory group membership, and assess whether the results of trajectory analyses help identify windows of opportunity for intervention. We searched PubMed and EMBASE (1/1/1980 to 1/11/2018) and identified 1695 articles. Forty-three articles with data from 37 unique datasets were retained. Each trajectory was categorized into one of three groups (i.e., low-stable, increasing, other). Number of trajectories ranged from 2 to 6 (mode = 4); 44-76% of participants were low-stable cigarette consumers, 11-21% increased consumption, and 3-11% were categorized as "other." Number of data points, smoking indicator used, and time axis influenced the number of trajectories identified. Only two articles depicted the natural course of smoking since onset. Factors associated with trajectory membership included age, sex/gender, race/ethnicity, parental education, behavior problems, depression, academic performance, baseline cigarette use, parental and friends smoking, alcohol use, and cannabis use. Outcomes included illicit drug and alcohol use. Beyond parsimoniously describing cigarette smoking patterns, it is not clear whether trajectory analyses offer increased insight into the natural course, determinants or outcomes of cigarette smoking in ways that inform the development of intervention.

ELSA 2014 Cohort: Risk Factors Associated With Heavy Episodic Drinking Trajectories in Argentinean College Students

Heavy episodic drinking (HED) is highly prevalent in college students. In Argentina, there is a notable lack of longitudinal studies examining drinking trajectories. The present study identified HED trajectories in Argentinean college students during the first 3 years of college (seven waves) and examined the association between risk factors for alcohol use and HED trajectories. The sample was composed of 1,240 college students [63.1% women, aged 18–25 years (M = 19.1 ± 1.7)] who completed at least three waves (the first data collection and ≥2 follow-ups). For 3 years, participants completed seven surveys that measured HED frequency, age of drinking onset, drunkenness occurrence, trait impulsivity, family history of alcohol abuse, stressful life events, and perceived peer’s drinking. Latent Class Growth Analysis (LCGA) and Multinomial Logistic Regression (MLR) were used to identify the pattern and number of HED trajectories and to explore which risk factors better distinguished between the trajectories, respectively. Six HED trajectories were identified: Heavy Stable Frequency, Moderate Stable Frequency, Moderate Decreasing Frequency, Stable Infrequent, Decreasing Infrequent, and No-HED. Younger age of drinking onset, alcohol intoxication, greater perception of peer drinking frequency and higher levels of impulsivity (i.e., sensation seeking, lack of premeditation, and positive urgency) increased the probability of belonging to the trajectories with more frequent HED. These trajectories partially coincide with those identified in studies from other cultures. Unlike previous studies, we did not find a trajectory with increasing/ascending HED frequency. This may be related to contextual/cultural variables unique to Argentina, like differences in the age when the peak in alcohol consumption is reached or the legal minimum age to buy alcoholic beverages in this country, and the idiosyncratic elements that characterize college life in Argentina. This work represents a step forward in the identification of risk factors differentiating between different HED trajectories, and help understand changes in alcohol use during college, in an understudied population.

Class enumeration false positive in skew-t family of continuous growth mixture models

Growth Mixture Modeling (GMM) has gained great popularity in the last decades as a methodology for longitudinal data analysis. The usual assumption of normally distributed repeated measures has been shown as problematic in real-life data applications. Namely, performing normal GMM on data that is even slightly skewed can lead to an over selection of the number of latent classes. In order to ameliorate this unwanted result, GMM based on the skew t family of continuous distributions has been proposed. This family of distributions includes the normal, skew normal, t, and skew t. This simulation study aims to determine the efficiency of selecting the “true” number of latent groups in GMM based on the skew t family of continuous distributions, using fit indices and likelihood ratio tests. Results show that the skew t GMM was the only model considered that showed fit indices and LRT false positive rates under the 0.05 cutoff value across sample sizes and for normal, and skewed and kurtic data. Simulation results are corroborated by a real educational data application example. These findings favor the development of practical guides of the benefits and risks of using the GMM based on this family of distributions.

Untangling Influences in the Longitudinal Relationship Between Depressive Symptoms and Drinking Frequency in High School

PURPOSE

In young people, alcohol consumption and depressive symptoms are related, but the temporal ordering of the relationship is an open question. Previous studies have not disaggregated influences of interindividual and intraindividual components affecting the relationship. We investigated whether a reciprocal relationship between frequency of alcohol use and depressive symptoms exists in the general population of adolescents after removing interindividual influences.

METHODS

A total of 1,293 Canadian adolescents provided data on depressive symptoms and frequency of alcohol use every 3 months from grade 7 to 11 (1999-2005) for a total of 20 cycles. We used latent curve models with structured residuals, which disaggregate interindividual and intraindividual components to assess the directionality of the relationship.

RESULTS

Both drinking frequency and depressive symptoms increased linearly and quadratically over time, with significant interindividual variation around the origin and rate of change. Intercepts and slopes for drinking frequency and depressive symptoms differed by sex and age. After controlling for sex, age, maternal education, sensation seeking, impulsivity and clustering by school, a significant positive association was observed between depressive symptoms and drinking frequency 3 months later (.032 [.004, .060]; p = .024), but no association was observed between drinking frequency and subsequent depressive symptoms (.011 [-.006 to .029]; p = .193).

CONCLUSIONS

Our data provide longitudinal evidence that changes in depressive symptoms exceeding one's "normal" level predict increases in drinking frequency. This suggests that teaching youth to recognize and cope with mood changes would be worthwhile.

Child Maltreatment, Fathers, and Adolescent Alcohol and Marijuana Use Trajectories

Background: Little is known about heterogeneity in developmental trajectories of alcohol and marijuana use among at-risk youth. Objective: This study aims to examine how child maltreatment and father structural factors at different stages in the life course are associated with different patterns of alcohol and marijuana use trajectories. Methods: A sample of youth (N = 903) were drawn from the Longitudinal Studies of Child Abuse and Neglect (LONGSCAN). Latent class growth analysis was employed to assess heterogeneity in patterns of adolescent alcohol and marijuana use. In addition, binary logistic regression analysis was performed to examine child maltreatment and father structural factors across different developmental stages as predictors of membership in the identified alcohol and marijuana use trajectory classes. Results: For both alcohol and marijuana use, two distinct latent classes were identified: stable no/low alcohol use (74%) vs. increasing alcohol use (26%); stable no/low marijuana use (85%) vs. increasing marijuana use (15%). Emotional abuse during early childhood and physical abuse during adolescence predicted membership in the increasing alcohol use and the increasing marijuana use classes. The presence of father in the home during early childhood was associated with lower likelihood of being in the increasing alcohol use class. Conclusions: Our findings highlight the importance of understanding the etiology of adolescent substance use through a developmental lens. Screening of exposure to child maltreatment across different developmental stages and interventions promoting father engagement during early childhood might help mitigate the risk of adolescent alcohol and marijuana use.

Trajectories of injection drug use among people who use drugs in Vancouver, Canada, 1996-2017: growth mixture modeling using data from prospective cohort studies

BACKGROUND AND AIMS

Injection drug use patterns are known to change over time, although such long-term changes have not been well described. We sought to characterize longitudinal trajectories of injection drug use and identify associated factors.

DESIGN

Data were derived from the Vancouver Injection Drug Users Study and AIDS Care Cohort to evaluate the Exposure to Survival Services study, two prospective cohorts involving people who inject drugs in Vancouver, Canada between 1996 and 2017. Growth mixture modeling was applied to identify distinct injection drug use trajectories. Multinomial logistic regression was used to identify baseline factors associated with each trajectory.

SETTING

Canada.

PARTICIPANTS

A total of 2057 participants who reported having used illicit drugs via injection in the past 6 months at the baseline visit were included in the study. The median time since first injection drug use at baseline was 14.8 years (quartile 1-quartile 3: 6.5-24.3).

MEASUREMENTS

Information regarding self-reported injection drug use during the past 6 months was collected at baseline and semi-annually thereafter via interviewer-administered questionnaires.

FINDINGS

Participants were followed for a median of 113.4 months (quartile 1-quartile 3: 63.4-161.7). Five trajectories were identified: persistent high frequency injection (507, 24.6%); high frequency injection with late decrease (374, 18.2%); gradual cessation (662, 32.2%); early cessation with late relapse (227, 11.0%); and early cessation (287, 14.0%). Factors found to be associated with distinct trajectories included: daily heroin injection, binge injection drug use, age, not being in a stable relationship and year of study enrollment.

CONCLUSIONS

People who used drugs in Vancouver, Canada from 1996 to 2017 appeared to follow five drug use trajectories, ranging from persistent high frequency use to early cessation. Almost 25% of participants remained high-frequency injectors over the study period.