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OBJECTIVE: The present study aimed to characterize profiles of mental health, incorporating both indicators of psychopathology and well-being, among college students and determine whether institutional belonging differentially relates to past month substance use by mental health profile. METHOD: Students (N = 4018; 59.5% female, 74.7% white) completed a survey regarding mental health (i.e., anxiety symptoms, depressive symptoms, stress, flourishing, academic confidence), institutional belonging, and whether they had engaged in any binge drinking of alcohol and use of cannabis and nicotine products, including nicotine vaping, over the past month. RESULTS: Latent profile analyses indicated five profiles of mental health with differing levels of psychopathology and well-being. Greater institutional belonging was only related to higher odds of binge drinking among students in profiles characterized by average or high well-being, irrespective of psychopathology. Among students with overall poor mental health, higher institutional belonging was related to higher odds of nicotine use. Results were generally invariant to campus and year at college. CONCLUSIONS: Our findings highlight that both positive and negative aspects of mental health should be considered when assessing college students' substance use. Greater institutional belonging may incur risk for substance use differentially by mental health, with respect to binge drinking for those with high levels of positive well-being and non-vaping nicotine use for those with overall poor mental health. Because associations emerged between belonging and substance use risk, institutions could consider implementing or raising awareness of alcohol-free, inclusive activities to ensure that students can feel a sense of belonging while abstaining from drinking.
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Co-use of alcohol and cannabis is prevalent and linked with heightened risk for substance-related harms. The current study investigated the role of substance-related pleasure as a reinforcing factor for co-use relative to alcohol or cannabis use. Specifically, we used data from a 21-day diary study of college students to examine day-level associations between co-use and self-reported substance-related pleasure (any, level of pleasure). Participants were 237 college students (65 % female sex at birth, ages 18-24) who reported 1+ alcohol and cannabis co-use occasion. Participants completed daily surveys across 21 consecutive days about yesterday's substance use and experiences of pleasure, yielding 2,086 daily surveys involving alcohol and/or cannabis use. Multilevel models indicated that odds of substance-related pleasure were higher on days with co-use relative to days with single-substance use, and level of pleasure was higher on co-use days relative to cannabis but not alcohol use days. Pleasure may serve as a reinforcing property of co-use that may be related to continued use despite experience of negative consequences. Intensity of pleasure related to co-use appears to be largely driven by use of alcohol. However, given mixed findings concerning level of pleasure, individuals may report co-use increases feelings of pleasure but do not actually experience more pleasure. Pleasure may serve as a viable target in future prevention and intervention programming targeting co-use.
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BACKGROUND: There is evidence that anxiety and stress increased among college students during the COVID-19 pandemic. However, less is known about daily experiences of affect, worry, substance use behaviors, experiences of pleasure, concern over food security, experiences of bias or discrimination, feelings of belongingness, and other indicators of well-being and how they vary across days in this population. OBJECTIVE: This study surveyed a wide range of indicators of health and well-being in daily life over 21 days with a sample of college students in a large university system in the United States during the pandemic. The overall variance in each daily measure was partitioned to reflect the proportion due to (1) between-person differences versus (2) within-person, day-to-day variability. This is important because measures that vary primarily due to between-person differences may be more amenable to interventions that target particular students, whereas measures that vary more due to day-to-day variability may be more amenable to interventions that target day-level contextual factors. METHODS: A sample of 2068 young adult college students (aged 18-24, mean 19.8, SD 1.3 years; 66.6% women) completed a baseline survey; 97.3% (n=2012) then completed up to 21 consecutive daily surveys that assessed a comprehensive set of daily markers of health, behavior, and well-being. The daily diary study produced a total of 33,722 person-days. RESULTS: Among all person-days, a minority were substance use days (eg, 14.5% of days involved alcohol use, 5.6% vaping, and 5.5% cannabis). Experiences of pleasure were reported on most (73.5%) days. Between-person differences explained more than 50% of the variance in numerous indicators of health and well-being, including daily vaping, cannabis use, other illicit substance use, experiences of bias or discrimination, positive affect, negative affect, worry, food insecurity, and feelings of belonging at the university. In contrast, within-person differences explained more than 50% of the variance in daily alcohol use, cigarette use, stress, experiences of pleasure, where the student slept last night, and physical activity. CONCLUSIONS: College student health and well-being are multifaceted, with some aspects likely driven by person-level characteristics and experiences and other aspects by more dynamic, contextual risk factors that occur in daily life. These findings implicate services and interventions that should target individual students versus those that should target days on which students are at high risk for poor experiences or behaviors.
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Objective: The purpose of this study was to elucidate comorbidity between body dissatisfaction and nicotine vaping. Participants: Participants were 121 college students (M age = 20.51 years; 75.0% female; 75.2% White) who participated in a 14-day daily diary study. Methods: Logistic regression was used to test links between baseline trait body dissatisfaction and vaping frequency across 14 days. Multilevel logistic regression was used to test within-person, daily links between body dissatisfaction and nicotine vaping. Results: Each additional unit of trait body dissatisfaction increased the odds of frequent vaping by 33% (95% CI [1.00, 1.77]) and daily vaping by 54% (95% CI [1.10, 2.15]). Within-person, daily associations between body dissatisfaction and vaping were nonsignificant. Conclusions: Body dissatisfaction may increase college students' risk for engaging in frequent nicotine vaping. However, daily changes in body dissatisfaction may not predict same- or next-day vaping. College students with body dissatisfaction may benefit from nicotine interventions.
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PURPOSE: The goal of this study was to inform theory and suicide prevention efforts by examining how the link between attempts to change weight and suicidal ideation varies across adolescence, when it is strongest, and whether there are sex differences. METHODS: Data were from 13,518 youth ages 14-18 years who participated in the 2019 Youth Risk Behavior Survey, a nationally representative study of U.S. high school students. Time-varying effect modeling was used to estimate associations between attempts to change weight and suicidal ideation as continuous functions of age and to test sex differences in these links. RESULTS: The link between attempts to lose weight and suicidal ideation was positive and significant between ages 14.0-17.3 years, with the strongest association at age 15.0 (OR = 2.07). There were no sex differences in this age-varying association. The association between attempts to gain weight and suicidal ideation was positive and age-varying for girls, with the strongest association at age 17.2 years (OR = 2.79). This association was not significant for boys at any age. CONCLUSIONS: Girls and boys who are trying to lose weight and girls who are trying to gain weight may be at elevated risk for suicidal ideation between ages 14 and 18 years. Findings illuminate patterns of association during adolescence and have implications for suicide prevention.
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INTRODUCTION: Drinking intensity among young adults is associated with greater negative alcohol-related consequences, but often studied using categorical drinking thresholds. This study examined how alcohol-related consequences varied as a continuous function of number of drinks consumed, without imposing thresholds, to identify drink ranges for which risk is greatest. METHODS: Analyses included daily surveys from the Young Adult Daily Life study (2019-22) in which individuals reported drinking 1 or more alcoholic drinks (n=5219 days; 832 individuals). Time-varying effect models estimated total number of negative alcohol-related consequences and five individual consequences (hangover, drank more than planned, nausea/vomiting, did something embarrassing, blacked out) as a function of the number of drinks consumed among young adult males and females. RESULTS: Often, increases in the number and prevalence of negative consequences were a nonlinear function of the number of drinks consumed. Females reported few negative consequences on 1-to-3-drink occasions but steep increases in consequences on 4-to-9-drink occasions. Among females, the prevalence of blacking out increased six-fold from 4-drink (3.4%; 95% CI=2.6,4.7) to 9-drink occasions (20.6%; 95% CI=16.1,26.1). Among males, the prevalence of some consequences, while not linear, increased across the full drink range. Blacking out among males increased from 9.6% (95% CI=6.2,14.7) on 10-drink occasions to 23.9% (95% CI=15.0,35.8) on 15-drink occasions. CONCLUSIONS: Substantial heterogeneity is missed when typical drinking categories are used. In particular, variability in consequences across levels of the traditional binge drinking category suggests that important differences in risk may be missed when assessed as a uniform category.
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Alcohol Drinking , Alcoholic Intoxication , Male , Female , Young Adult , Humans , Alcohol Drinking/epidemiology , Alcoholic Beverages/adverse effects , Alcoholic Intoxication/epidemiology , Ethanol , Surveys and QuestionnairesABSTRACT
Objective: Chronic pain is a critical public health issue affecting approximately 20% of the adult population in the United States. Given the opioid crisis, there has been an urgent focus on non-addictive pain management methods including mindfulness-based stress reduction (MBSR). Prior work has successfully used MBSR for pain management. However, ensuring longitudinal engagement in MBSR practices remains a serious challenge. In this work, we explore the utility of a voice interface to support MBSR home practice. Methods: We interviewed 10 mindfulness program facilitators to understand how such a technology might fit in the context of the MBSR class and identify potential usability issues with our prototype. We then used directed content analysis to identify key themes and sub-themes within the interview data. Results: Our findings show that facilitators supported the use of the voice interface for MBSR, particularly for individuals with limited motor function. Facilitators also highlighted the unique affordances of voice interfaces, including perceived social presence, to support sustained engagement. Conclusion: We demonstrate the acceptability of a voice interface to support home practice for MBSR participants among trained mindfulness facilitators. Based on our findings, we outline design recommendations for technologies aiming to provide longitudinal support for mindfulness-based interventions. Future work should further these efforts toward making non-addictive pain management interventions accessible and efficacious for a wide audience of users.
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Time-varying effect modeling (TVEM), a statistical technique for modeling dynamic patterns of change, presents new opportunities to study biobehavioral health processes. TVEM is particularly useful when applied to intensive longitudinal data (ILD) because it permits highly flexible modeling of outcomes over continuous time, as well as of associations between variables and moderation effects. TVEM coupled with ILD is ideal for the study of addiction. This article provides a general overview of using TVEM, particularly when applied to ILD, to better enable addiction scientists to conduct novel analyses that are important to realizing the dynamics of addiction-related processes. It presents an empirical example using ecological momentary assessment data from participants throughout their first 90 days of addiction recovery to estimate the (1) associations between morning craving and same-day recovery outcomes, (2) association between morning positive and negative affect and same-day recovery outcomes and (3) time-varying moderation effects of affect on the association between morning craving and recovery outcomes. We provide a didactic overview in implementing and interpreting the aims and results, including equations, computer syntax and reference resources. Our results highlight how affect operates as both a time-varying risk and protective factor on recovery outcomes, particularly when considered in combination with experiences of craving (i.e. dynamic moderation). We conclude by discussing our results, recent innovations and future directions of TVEM for advancing addiction science, including how 'time' can be operationalized to probe new research questions.
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Behavior, Addictive , Substance-Related Disorders , Humans , Craving , Self Efficacy , Time Factors , AffectABSTRACT
OBJECTIVES: To identify patient risk factors associated with prescription opioid misuse and abuse as well as groupings of misuse and abuse behaviors as measured by the Prescription Opioid Misuse and Abuse Questionnaire (POMAQ). METHODS: Adults with chronic pain requiring long-term treatment with opioids completed the POMAQ and other study questionnaires. Latent class analysis (LCA) was used to examine underlying subgroups exhibiting particular risk profiles. Patient demographic and clinical characteristics were examined as covariates and the concordance between the identified latent classes at-risk classifications and the POMAQ clinical scoring algorithm was assessed. RESULTS: Analysis of data from 809 patients revealed four classes: "chronic pain, low risk" (n = 473, low to no prevalence of POMAQ behaviors), "chronic pain, comorbid condition" (n = 152, high prevalence of anti-anxiety, sleeping pill, and antihistamine use), "at risk" (n = 154, taking more opioids than prescribed and drinking alcohol with opioids more frequently than other groups), and "high risk" (n = 30, highest prevalence of each behavior). The "high risk" group was associated with being younger, less educated, and unemployed compared to other groups. When examining the LCA classes by groups defined by the original POMAQ clinical scoring algorithm, the "high risk" class had the highest proportion of participants identified with abuse behaviors (46.7%), compared to just 4.7% in the "chronic pain, low risk" group. CONCLUSIONS: Findings suggest there are four distinct subgroups of patients defined by chronic opioid misuse and abuse behaviors and support the use of the POMAQ to identify risk factors associated with prescription opioid misuse and abuse.
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Chronic Pain , Opioid-Related Disorders , Prescription Drug Misuse , Adult , Humans , Chronic Pain/drug therapy , Chronic Pain/epidemiology , Opioid-Related Disorders/drug therapy , Analgesics, Opioid/adverse effects , Surveys and Questionnaires , Risk Factors , Prescription Drug Misuse/adverse effectsABSTRACT
PURPOSE: The prevalence of nicotine vaping is increasing among adolescents and emerging evidence suggests weight concerns may promote risk for vaping. The aims of this study were to investigate whether there is an association between attempting to lose weight and nicotine vaping during adolescence, when this association emerges and is strongest, and whether there are sex differences in this link. METHODS: This study used time-varying effect modeling, an analytic method that estimates regression coefficients as a continuous function of age, to model dynamic associations between weight loss behavior and nicotine vaping across adolescence and sex differences in these links. Data were from 13,677 adolescents (aged 14-18 years, 49.4% female) who participated in the 2019 National Youth Risk Behavior Survey, a nationally representative U.S. RESULTS: Results revealed an age-varying association that differed by sex. Girls who were trying to lose weight were at a higher risk for past 30-day vaping from ages 14.2-15.9 years, with the strongest association at 14.8 years (odds ratio [OR] = 1.92, 95% confidence interval [CI] [1.25, 2.95]). For boys, this association was nonsignificant across age (OR = 1.76, 95% CI [0.91, 3.41] at age 14.0 years). Girls who were trying to lose weight were at a higher risk for frequent vaping (vaping on 20-30 of the past 30 days) from ages 15.2-17.1 years, with the strongest association at 16.1 years (OR = 2.59, 95% CI [1.45, 4.62]). This link was not meaningfully significant at any age for boys (OR = 3.26, 95% CI [0.86, 12.33] at age 14.0 years). DISCUSSION: Girls, but not boys, who are trying to lose weight appear vulnerable to nicotine vaping during adolescence.
Subject(s)
Electronic Nicotine Delivery Systems , Vaping , Humans , Male , Adolescent , Female , Vaping/epidemiology , Weight Loss , Risk-Taking , PrevalenceABSTRACT
Improvements in substance use disorder recovery may be achieved by recognizing that effective interventions do not work equally well for all individuals. Heterogeneity of intervention effects is traditionally examined as a function of a single variable, such as gender or baseline severity. However, responsiveness to an intervention is likely a result of multiple, intersecting factors. Latent class moderation enables the examination of heterogeneity in intervention effects across subgroups characterized by profiles of characteristics. This study analyzed data from adolescents (aged 13 to 18 years old) who needed treatment for cannabis use (n = 14,854) and participated in the Global Appraisal of Individual Needs to evaluate differential effects of substance use services on cannabis use outcomes. We demonstrate an adjusted three-step approach using weights that account for measurement error; sample codes in Mplus and Latent Gold are provided and data are publicly available. Indicators of the latent class moderator comprised six contextual (e.g., recovery environment risk) and individual (e.g., internal mental distress) risk factors. The latent class moderator comprised four subgroups: low risk (21.1%), social risk (21.1%), environmental risk (12.5%), and mixed risk (45.2%). Limited moderation of associations between level of care and any past 90-day cannabis use were observed. In predicting number of cannabis use-days, compared to individuals with low risk, those with environmental risk showed improved outcomes from intensive outpatient care whereas individuals with social risk and mixed risk showed improved outcomes from residential care (all compared to early intervention/outpatient care). Latent class moderation holds potential to elucidate heterogeneity in intervention effectiveness that otherwise may go undetected.
Subject(s)
Substance-Related Disorders , Adolescent , HumansABSTRACT
In intensive longitudinal studies using ecological momentary assessment, mood is typically assessed by repeatedly obtaining ratings for a large set of adjectives. Summarizing and analyzing these mood data can be problematic because the reliability and factor structure of such measures have rarely been evaluated in this context, which-unlike cross-sectional studies-captures between- and within-person processes. Our study examined how mood ratings (obtained thrice daily for 8 weeks; n = 306, person moments = 39,321) systematically vary and covary in outpatients receiving medication for opioid use disorder (MOUD). We used generalizability theory to quantify several aspects of reliability, and multilevel confirmatory factor analysis (MCFA) to detect factor structures within and across people. Generalizability analyses showed that the largest proportion of systematic variance across mood items was at the person level, followed by the person-by-day interaction and the (comparatively small) person-by-moment interaction for items reflecting low arousal. The best-fitting MCFA model had a three-factor structure both at the between- and within-person levels: positive mood, negative mood, and low-arousal states (with low arousal considered as either a separate factor or a subfactor of negative mood). We conclude that (a) mood varied more between days than between moments and (b) low arousal may be worth scoring and reporting separately from positive and negative mood states, at least in a MOUD population. Our three-factor structure differs from prior analyses of mood; more work is needed to understand the extent to which it generalizes to other populations. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Subject(s)
Opioid-Related Disorders , Outpatients , Affect , Cross-Sectional Studies , Humans , Opioid-Related Disorders/diagnosis , Opioid-Related Disorders/drug therapy , Reproducibility of ResultsABSTRACT
BACKGROUND: Substance use and use disorders in the United States have had significant and devastating impacts on individuals and communities. This escalating substance use crisis calls for urgent and innovative solutions to effectively detect and provide interventions for individuals in times of need. Recent mobile health (mHealth)-based approaches offer promising new opportunities to address these issues through ubiquitous devices. However, the design rationales, theoretical frameworks, and mechanisms through which users' perspectives and experiences guide the design and deployment of such systems have not been analyzed in any prior systematic reviews. OBJECTIVE: In this paper, we systematically review these approaches and apps for their feasibility, efficacy, and usability. Further, we evaluate whether human-centered research principles and techniques guide the design and development of these systems and examine how the current state-of-the-art systems apply to real-world contexts. In an effort to gauge the applicability of these systems, we also investigate whether these approaches consider the effects of stigma and privacy concerns related to collecting data on substance use. Lastly, we examine persistent challenges in the design and large-scale adoption of substance use intervention apps and draw inspiration from other domains of mHealth to suggest actionable reforms for the design and deployment of these apps. METHODS: Four databases (PubMed, IEEE Xplore, JMIR, and ACM Digital Library) were searched over a 5-year period (2016-2021) for articles evaluating mHealth approaches for substance use (alcohol use, marijuana use, opioid use, tobacco use, and substance co-use). Articles that will be included describe an mHealth detection or intervention targeting substance use, provide outcomes data, and include a discussion of design techniques and user perspectives. Independent evaluation will be conducted by one author, followed by secondary reviewer(s) who will check and validate themes and data. RESULTS: This is a protocol for a systematic review; therefore, results are not yet available. We are currently in the process of selecting the studies for inclusion in the final analysis. CONCLUSIONS: To the best of our knowledge, this is the first systematic review to assess real-world applicability, scalability, and use of human-centered design and evaluation techniques in mHealth approaches targeting substance use. This study is expected to identify gaps and opportunities in current approaches used to develop and assess mHealth technologies for substance use detection and intervention. Further, this review also aims to highlight various design processes and components that result in engaging, usable, and effective systems for substance use, informing and motivating the future development of such systems. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35749.
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OBJECTIVE: Simultaneous use of alcohol and marijuana (SAM) is common among U.S. college students, but little research has examined specific substance use behaviors during SAM use episodes. This study identified latent classes of SAM users based on their SAM, alcohol-only, and marijuana-only use episodes. METHOD: College student SAM users (N = 284; 50.7% female; M age = 19.8 years) completed up to five surveys each day across two 4-week bursts. Latent class analysis (LCA) was used to characterize SAM users based on seven latent class indicators of use behavior. Sex was examined in relation to latent class membership. RESULTS: Five unique classes emerged: Frequent Marijuana-Focused SAM users (21%); Frequent Alcohol-Initiating SAM users (29%); Heavy-Drinking Infrequent SAM users (12%); Moderate SAM users (29%); and Light Infrequent SAM users (9%). These groups were differentiated primarily by their frequency of SAM use, form of marijuana, whether marijuana was used on non-SAM occasions, and whether consequences were experienced. Groups differed significantly by sex. CONCLUSIONS: College student SAM users are heterogeneous with respect not only to their degree of SAM use but also in their pattern of drinking, type of marijuana use, relative focus on alcohol versus marijuana, and risk of experiencing acute negative consequences. Describing this heterogeneity is an important step toward developing interventions for different types of users.
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Cannabis , Marijuana Smoking , Marijuana Use , Alcohol Drinking/epidemiology , Diaries as Topic , Ethanol , Female , Humans , Male , Marijuana Smoking/epidemiology , Marijuana Use/epidemiology , Young AdultABSTRACT
OBJECTIVE: The COVID-19 pandemic has potential for long-lasting effects on college students' well-being. We examine changes from just before to during the pandemic in indicators of health and well-being and comprehensive profiles of health and well-being, along with links between covariates and profiles during the pandemic. PARTICIPANTS: 1,004 students participated in a longitudinal study that began in November 2019. METHODS: Latent class analysis identified health and well-being profiles at both waves; covariates were included in relation to class membership. RESULTS: Mental health problems increased, whereas substance use, sexual behavior, physical inactivity, and food insecurity decreased. Six well-being classes were identified at each wave. Baseline class membership, sociodemographic characteristics, living situation, ethnicity, coping strategies, and belongingness were associated with profile membership at follow-up. CONCLUSIONS: COVID-19 has had significant and differential impacts on today's students; their health and well-being should be considered holistically when understanding and addressing long-term effects of this pandemic.
Subject(s)
COVID-19 , Substance-Related Disorders , COVID-19/epidemiology , Humans , Longitudinal Studies , Pandemics , Students/psychology , Substance-Related Disorders/epidemiologyABSTRACT
Just-in-time adaptive interventions (JITAIs) are time-varying adaptive interventions that use frequent opportunities for the intervention to be adapted-weekly, daily, or even many times a day. The microrandomized trial (MRT) has emerged for use in informing the construction of JITAIs. MRTs can be used to address research questions about whether and under what circumstances JITAI components are effective, with the ultimate objective of developing effective and efficient JITAI. The purpose of this article is to clarify why, when, and how to use MRTs; to highlight elements that must be considered when designing and implementing an MRT; and to review primary and secondary analyses methods for MRTs. We briefly review key elements of JITAIs and discuss a variety of considerations that go into planning and designing an MRT. We provide a definition of causal excursion effects suitable for use in primary and secondary analyses of MRT data to inform JITAI development. We review the weighted and centered least-squares (WCLS) estimator which provides consistent causal excursion effect estimators from MRT data. We describe how the WCLS estimator along with associated test statistics can be obtained using standard statistical software such as R (R Core Team, 2019). Throughout we illustrate the MRT design and analyses using the HeartSteps MRT, for developing a JITAI to increase physical activity among sedentary individuals. We supplement the HeartSteps MRT with two other MRTs, SARA and BariFit, each of which highlights different research questions that can be addressed using the MRT and experimental design considerations that might arise. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Randomized Controlled Trials as Topic , Humans , Data Analysis , Research DesignABSTRACT
Background: Substance use disorders (SUDs) and mental health disorders may change and co-occur in complex patterns across adult ages, but these processes can be difficult to capture with traditional statistical approaches.Objective: To elucidate disorder prevalence and comorbidities across adult ages by using time-varying effect models (TVEMs), latent class analysis (LCA), and modeling latent class prevalences as complex functions of age.Methods: Data were drawn from participants who are 18-65 years old in the National Epidemiologic Survey on Alcohol and Related Conditions III (n = 30,999; 51% women) and a subsample who reported a past-year post-traumatic stress disorder (PTSD), mood, anxiety, or SUD based on DSM-5 diagnoses (n = 11,279). TVEM and LCA were used to examine age trends and comorbidity patterns across ages.Results: SUD prevalence peaked at age 23 (31%) and decreased thereafter, while mental health disorder prevalence was stable (20%-26% across all ages). The prevalence of five classes of individuals based on specific combinations of mental health and SUDs varied by age: the Alcohol Use Disorder class had the highest prevalence at age 26, whereas the Mood and Anxiety Disorder classes peaked around age 63. Interestingly, the Poly-Disorder class prevalence was greatest at age 18 but decreased sharply across young adulthood; however, the prevalence of the other high comorbidity class, PTSD with Mood or Anxiety Disorder, remained fairly constant across age, peaking at age 44.Conclusions: Multimorbid mental health disorders (excluding SUDs) persist in prevalence across adult ages. LCA, TVEM, and their integration together hold substantial potential to advance addiction research.
Subject(s)
Mental Disorders , Substance-Related Disorders , Adolescent , Adult , Aged , Comorbidity , Female , Humans , Latent Class Analysis , Male , Mental Disorders/diagnosis , Mental Disorders/epidemiology , Mental Health , Middle Aged , Prevalence , Substance-Related Disorders/epidemiology , Young AdultABSTRACT
INTRODUCTION: Subjective ratings of cannabis effects are important predictors of use-related consequences. However, psychometric research is fairly limited, particularly for measures to capture variability in daily life when diverse modes of cannabis administration and co-substance use are common. METHODS: This study evaluated the predictive utility of a revised item to assess perceived cannabis effects and examined modes of cannabis administration and alcohol and nicotine co-use as moderators. Participants were 106 young adults (18-25 years; 51% female) who completed up to 14 consecutive daily reports of substance use (n = 1405 person-days). Two measures of subjective effects were examined: a standard item (0-100 rating of "how high do you feel?") and a revised item that uses four crowd-sourced anchor points ranging from relaxed (0), calm/chill (33), high (67), and stoned/baked (100). The items shared substantial variance (Pseudo-R2 = 59.5%), however, the revised item showed greater within-person variability (77.0% vs. 68.8%) and stronger day-level associations with consumption levels (Pseudo-R2 = 25.0% vs. 16.7%). RESULTS: The cannabis consumption-subjective effects link was weaker on blunt-only days compared to vape-only days. Subjective cannabis effects were higher on nicotine co-use days after controlling for cannabis consumption; neither alcohol nor nicotine co-use moderated the cannabis consumption-subjective effects link. DISCUSSION: The revised subjective cannabis effects item is a viable alternative to the standard item among young adults who engage in simultaneous alcohol and cannabis use. CONCLUSIONS: Future research focused on characterizing the variability in cannabis effects is needed.
Subject(s)
Cannabis , Hallucinogens , Cannabinoid Receptor Agonists , Ethanol , Female , Humans , Language , Male , Young AdultABSTRACT
At the population level, use of multiple substances (or "co-use") is prevalent in young adulthood and linked with increased risk for experiencing substance-related harms. Less understood is the heterogeneity of substance use behaviors within individuals and across days, as well as the proximal predictors of these daily use patterns. The present study applied latent class analysis to daily diary data to identify daily substance use patterns and compare day-level class membership based on day-level stress and positive and negative affect among a higher-risk sample of young adult substance users. Participants (n = 152) completed up to 13 daily assessments of stress, affect, and substance use behavior. Among substance use days, five classes of days were identified: cannabis (some alcohol; 43% of days), alcohol-only (26%), vaping (some alcohol, cannabis; 24%), stimulant + alcohol (some cannabis, vaping; 4%), and cigarette-only (3%) days. Days with lower levels of perceived stress were significantly more likely to be alcohol-only Days relative to being days characterized by cigarette use, cannabis use, or multiple drug combinations. Days with higher levels of stress and negative affect were more likely to be cigarette-only days relative to cannabis and vaping days. Study findings document the wide range of substance use and co-use behaviors exhibited among young adults in daily life and highlight the importance of considering risk factors that correspond to days of problematic use patterns.
Subject(s)
Cannabis , Substance-Related Disorders , Vaping , Adult , Ethanol , Humans , Latent Class Analysis , Risk Factors , Substance-Related Disorders/epidemiology , Young AdultABSTRACT
OBJECTIVES: Anhedonia can accompany substance use disorders (SUDs); its severity may vary by substance type, severity of SUD symptoms, or psychiatric comorbidity. The goal of this study was to clarify the contribution of each. METHODS: Data were from participants aged 18 to 65 years in the National Epidemiologic Survey on Alcohol and Related Conditions III (n = 30,999; 51% women), a cross-sectional, nationally representative sample reporting lifetime DSM-5 symptoms and lifetime anhedonia. We used logistic regression to test how anhedonia was associated with specific SUDs and psychiatric disorders in respondents with one lifetime diagnosis. We used latent class analysis to assess the association of anhedonia with patterns of comorbidity in all respondents. RESULTS: Opioid use disorder (OUD) had the greatest odds of anhedonia relative to other SUDs (ORs [95% CIs]): mild alcohol use disorder (AUD) ( 3.33 [1.74, 6.38]), moderate/severe AUD ( 2.73 [1.41, 5.30]), and cannabis use disorder ( 3.21 [1.43, 7.19]), though not significantly greater than stimulant use disorder ( 2.44 [.88, 6.73]). Anhedonia was more likely in mood disorders and posttraumatic stress disorder (PTSD) than in any SUD, except for PTSD versus OUD (OR [95% CIs] = .98 [.47, 2.02]). In latent class analysis analyses, the poly disorder class, which included SUDs and other diagnoses, had greater odds of anhedonia than the Poly SUD (ORs [95% CIs] = 1.62 [1.25, 2.09] and AUD 2.89 [2.40, 3.48]) classes. CONCLUSIONS: People with OUD or a lifetime history of mood disorder or PTSD may be most likely to present to SUD treatment with anhedonia.