Predictors Of Class Membership Research Articles

Relationship between Comorbid Drug Use Disorders, Affective Disorders, and Current Smoking

Objective: This study aimed to identify subgroups of adults based on comorbid psychiatric disorders and to examine the relationship with current smoking. Method: The National Epidemiologic Survey on Alcohol and Related Conditions-III, 2012–2013, sampled, recruited, and assessed 36,309 adults, with interviews on drug use and other characteristics. The Alcohol Use Disorder and Associated Disabilities Interview Schedule DSM-5 Version (AUDADIS-5) was used to identify psychiatric conditions. Latent class models were developed based on various psychiatric diagnoses. Multinomial logistic regression estimated the significance of covariates in predicting class membership. Results: Four latent classes optimally distinguished the population: no comorbid conditions (63%), comorbid affective disorders (16%), those with alcohol use disorder (AUD; 17%), and a highly comorbid subgroup (i.e., co-occurring affective and drug use disorders; 4%). Current smoking was about twice as prevalent in the classes defined by psychiatric conditions compared to the group with no comorbid conditions. The highly comorbid class was more likely to be current smokers than the comorbid affective disorders class and the AUD class. Furthermore, the highly comorbid class was younger and had lower income, and the AUD class had a higher proportion of males than the other classes. Conclusions: Cigarette smoking was higher in the nearly 40% of respondents characterized by psychiatric disorders, particularly those with drug use disorders. Correlates of membership in these classes were consistent with known vulnerabilities for smoking, highlighting the need for mental health interventions and future research to explicitly address tobacco cessation in clinical settings based on psychiatric diagnoses.

Effects of cumulative trauma load on long-term trajectories of life satisfaction and health in a population-based study

BackgroundLifetime traumatic events are known to have a detrimental long-term impact on both mental and physical health. Yet, heterogeneity in the stress response regarding well-being in adults is not well understood. This study investigates effects of cumulative trauma on latent trajectories of two indices of well-being, subjective health and life satisfaction in a large representative sample by means of latent variable modelling techniques.MethodsData from the pairfam study wave 2–9, a longitudinal representative survey was used (N = 10,825). Individuals reported on lifetime trauma type exposure on wave 7 and indicated levels of life satisfaction and health at each wave. Different types of latent Variable Mixture Models were applied in an iterative fashion. Conditional models investigated effects of cumulative trauma load.ResultsThe best fitting model indicated three latent trajectories for life, and four for health, respectively. Trauma load significantly predicted class membership: Higher exposure was associated with non-stable trajectories for both indices but followed complex patterns of both improving and decreasing life satisfaction and health. Trauma load also explained variability within classes.ConclusionsThe current study expands on evidence to the long-term development of health and life satisfaction in response to traumatic events from a latent variable modelling perspective. Besides detrimental effect, it also points to functional adaptation after initial decline and increased well-being associated with trauma exposure. Thus, response to traumatic stress is marked by great heterogeneity. Future research should focus on variables beyond exposure to trauma that can further identify individuals prone to trajectories of declining well-being.

Understanding the Early Years of Socioeconomically Disadvantaged Couples' Marriages.

Recent research has identified significant differences in how satisfaction in newlywed relationships progress, with the majority of spouses reporting relatively high marital satisfaction. However, most studies have focused on white, middle class, childless couples, and it is not clear whether these findings hold for socioeconomically disadvantaged couples (those with low educational attainment or income). Further, previous work has largely ignored differences between spouses within the same marriage and the circumstances under which interpersonal processes between spouses are influential to prospective marital satisfaction. Using dyadic growth-mixture modeling and three waves of data from 530 newlywed couples in the Supporting Healthy Marriages study, we simultaneously modeled husbands' and wives' marital satisfaction and identified two classes of couples, labeled the Relatively satisfied class and Husbands' moderate intercept, wives' low, and increasing satisfaction class. Husbands consistently reported better marital satisfaction than their wives regardless of class membership. Wives' perceptions of interpersonal processes during experiences of financial stress predicted class membership. Dissolution rates also differed between classes. We conclude by providing practical implications for working with socioeconomically disadvantaged families.

Patterns and predictors of PTSD in treatment-seeking African refugees and asylum seekers: A latent class analysis.

Despite the empirical and clinical relevance of understanding posttraumatic stress disorder (PTSD) heterogeneity in refugees and asylum-seekers, very few studies have examined the manner in which PTSD symptoms manifest in such populations. This study sought to investigate patterns and predictors of DSM-5 PTSD in a treatment-seeking sample of African refugees. Participants were 122 African refugees and asylum-seekers living in Italy who completed measures of trauma exposure and PTSD symptoms. Latent class analysis (LCA) was used to identify PTSD symptom profiles, and predictors of class membership were identified via multinomial logistic regression. Among participants, 79.5% had a probable diagnosis of PTSD. Three PTSD classes were identified by LCA: Pervasive (32.0%) with high probabilities of all symptoms, high-Threat (45.9%) with higher probabilities of intrusions and avoidance symptoms, moderate-Avoidance (22.1%) with high probability of thoughts/feelings avoidance. None of the examined variables (legal status, gender, age, education, months spent in Italy, number of traumatic events, employment) significantly predicted class membership with the relevant exception of reception conditions. Specifically, living in large reception centres (over 1,000 people) significantly predicted Pervasive PTSD class membership compared to high/Threat PTSD class and to moderate/Avoidance class. This study provides evidence for distinct patterns of PTSD symptomatology in refugees and asylum seekers. We identified three classes which present both qualitative and quantitative differences in symptoms: Pervasive class, high-Threat class and a new moderate class, characterised by avoidance symptoms. Reception conditions contributed to the emergence of the Pervasive PTSD profile characterised by the symptoms highest severity. These findings highlight that stressors in the post-migration environment, as inadequate reception conditions in large facilities, may have detrimental effect on refugees' mental health. We emphasise the importance for host countries to implement reception models that provide effective protection and integration to this vulnerable population.

Profiles of Nicotine and Cannabis Exposure among Young Adults with Asthma

There is a paucity of data on nicotine and cannabis use among young adults (YAs) with asthma. This study aimed to do the following among YAs with asthma: (1) describe YAs’ active and passive exposure to nicotine and cannabis; (2) identify latent classes of active use of nicotine and cannabis; and (3) explore predictors of class membership (i.e., demographics, parental and friend use of nicotine and cannabis, and hours of environmental exposure to tobacco smoke, e-cigarette vapor, and marijuana smoke). YAs with asthma (N = 178) self-reported on nicotine and cannabis exposure and the included covariates. Latent class analysis was used to identify latent classes of lifetime nicotine and cannabis use. High rates of nicotine and cannabis use among YAs with asthma were found: 37% reporting a lifetime history of using both nicotine and cannabis. Regarding past year use, 25% had smoked cigarettes, 40% had used e-cigarettes, and 35% had used cannabis. Five classes of lifetime use were identified. The largest class was a non-user class (53%); the other four classes indicate concerning patterns of nicotine and cannabis use. The most consistent predictor of being in a class characterized by more nicotine and cannabis exposure (versus being in the non-user class) was past week exposure to cannabis smoke. This is the first study to identify classes of lifetime nicotine and cannabis use, and examine predictors of class membership, among YAs with asthma. There is a critical need to address environmental and active tobacco and marijuana exposure among YAs with asthma.

Examining Patterns of Interpersonal Violence, Structural and Social Exclusion, Resilience, and Arrest among Young Transgender Women

Young transgender women aged 16–29 years experience high rates of carceral involvement, warranting greater inclusion of this community within decarceration research and practice. The present study investigates patterns of violence, exclusion, resilience, and arrest among a sample of 298 transgender women aged 16–29 years in Chicago, Illinois, and Boston, MA. Women in the sample reported high rates of arrest, violence, and exclusion. Latent class analysis (LCA) was used to identify classes with similar response patterns to items assessing violence, exclusion, resilience, and arrest. A three-class model was selected to best represent the data, including: (a) “High Violence and Exclusion/High Arrest”; (b) “Low Arrest”; and (c) “Moderate Violence and Exclusion/High Arrest.” Race and perceived gender expression significantly predicted class membership. Findings illustrate the heterogeneity of young transgender women’s experiences, suggesting that a variety of tailored decarceration program and policy interventions are required to meet the differing needs of young transgender women.

Gender and Sexual Identities Predicting Patterns of Co-occurring Health Risks Among Sexual Minority Youth: a Latent Class Analysis Approach.

Behavioral health disparities (e.g., substance use, mental health) exist for gender nonconforming (GNC) and sexual minority youth; however, there is limited knowledge on disparities that may be unique among youth who identify as both a sexual and gender minority. This study utilized a diverse sample of GNC and cisgender sexual minority youth seeking crisis services to examine co-occurrence of behavioral health outcomes. Surveys were administered with youth (aged 12-24, N = 592), and latent class analyses were applied. Two latent class regression models were conducted to examine how gender and sexual identity separately (independent effect; Model 1) and configurations of gender and sexual identity (Model 2) predicted class membership. Analyses resulted in a four-class solution: High All (17.6%), High Substance Use and Moderate Mental Health (10.6%), Low All (20.1%), and High Suicide and High Mental Health (51.7%). In our first model, youth who identified as GNC had 2.11 higher odds of being in the High Suicide and High Mental Health class compared to the Low All class; however, sexual identity was not a significant predictor. In the second model, individuals identifying as GNC gay or lesbian or GNC pansexual had 1.95 and 2.57 higher odds, respectively, of being in the High Suicide and High Mental Health class compared to the Low All class. Our study suggests the information on gender and sexual identities together are more helpful in identifying youth at risk for co-occurring negative health outcomes. Implications for prevention approaches are described.

Homophobic bullying victimization trajectories: The roles of perpetration, sex assigned at birth, and sexuality.

There is a paucity of research on developmental trajectories of bias-based aggression. We examined homophobic bullying victimization trajectories among high school students (N = 3,064; M age = 13.67; Girls = 50.2%) and how these developmental pathways vary as a function of factors like homophobic bullying perpetration, sex assigned at birth, and sexuality. Using data from a 3-wave longitudinal investigation over a 2-year period, we utilized latent growth mixture modeling to explore the aforementioned trajectories. Findings suggested that there were three distinct classes characterized by high initial rates and declines over time, low initial rates, and increases over time, and low, stable, rate across time. Furthermore, results indicated that homophobic bullying perpetration, sex assigned at birth, and sexuality all predicted class membership.

How Peer Conflict Profiles and Socio-Demographic Factors Influence Type 1 Diabetes Adaptation.

This study aimed to (a) validate the factor structure for a measure of peer conflict in youth with type 1 diabetes (T1D); (b) determine empirical patterns of peer conflict in terms of context (friend vs. nonfriend) and content (diabetes-specific vs. general) within a broader context of socio-demographic factors; and (c) examine how these patterns and socio-demographic factors relate to adolescents' T1D adherence, quality of life, and glycemic control (HbA1c). Youth with T1D (N = 178), ages 12-18, reported demographic variables, illness duration, adherence, quality of life, and peer conflict. HbA1c was extracted from medical records. Confirmatory factor analysis validated a factor structure for the Diabetes Peer Conflict Scale (DPCS) and latent profile analysis (LPA) determined profiles of peer conflict. A four-factor structure emerged for the DPCS: general friend conflict, general nonfriend conflict, T1D friend conflict, and T1D nonfriend conflict. Using these factors as indicators in LPA, four profiles were confirmed: (a) Low Overall Conflict (LOC) and (b) Moderate Overall Conflict (MOC), (c) a Nonfriend Conflict (NFC), and (d) a Friend Conflict (FC) profile. Differences were not identified between diabetes specific versus general conflict. Socio-demographic variables did not predict class membership. The LOC profile reported the highest quality of life and best glycemic control, whereas the FC profile reported the lowest adherence behaviors. Conclusions: Peer conflict uniquely contributes to diabetes adaptation above and beyond socio-demographic and illness factors.

Self-rated health in adolescence as a predictor of 'multi-illness' in early adulthood: A prospective registry-based Norwegian HUNT study.

Self-rated health (SRH) is a marker of future health and a possible predictor of future multimorbidity, which is a major challenge for population health and health care. There is a lack of studies on adolescent SRH and patterns of health problems across the transitional period from adolescence to early adulthood. Therefore, this study aimed to identify groups of people with similar health problems in early adulthood and explore the predictive value of adolescent SRH on the group classification after a period of 10–19 years. Data from 8828 adolescents participating in the Young HUNT-1 survey (1995–1997) were linked to the Norwegian registry of general practitioner (GP) claims, which includes diagnoses recorded in GP consultations in 2006–2014. We used latent class analysis (LCA) to identify groups of patients with similar health problems in early adulthood and explored SRH as a predictor of class membership using latent class regression, adjusting for baseline chronic disease, frequency of health care attendance, sex and age. The mean age at baseline was 16 years, and 50% of the participants were female. SRH was reported as very good by 28%, good by 61% and not good by 11%. We identified five groups of patient classification (classes): Healthy (35%), Infections and general problems (26%), Musculoskeletal problems (21%), Psychological problems (6%) and Multi-illness (13%). We found a gradual increase in the probability of belonging to the Healthy class with better SRH, and an inverse pattern for the Psychological and Multi-illness classes. This pattern remained after adjusting for baseline variables. In conclusion, there is a clear association between adolescent SRH and the risk of having multi-illness in early adulthood, seen as a proxy for later multimorbidity. This finding warrants greater attention to SRH in adolescence as a possible indicator in targeted prevention of future health problems.

A mother-centered evaluation of breast pumps

Existing literature outlines mothers' negative experiences with breast pumps, yet a gap exists of which breast pump characteristics are important to mothers. Identifying which breast pump characteristics are important to breast pumping mothers, and any variation between mothers who do or do not work outside of the home, will help identify user needs. A survey collected information on mothers' experiences with breast pumps and impressions of their characteristics. Latent Class Analysis (LCA) was used to determine whether there were possible groupings of impressions of these characteristics. The LCA identified a two-class model with mothers' age as a significant covariate. Portability, ease of use, low-weight, fast milk extraction, comfortability, low-noise, and discreet were all found to be important to one group of mothers, while only portability, ease of use, fast milk extraction, and comfortability were found to be important to another group of mothers. Mothers' work status was not a significant covariate but did predict class membership when considered as a grouping variable in conjunction with age. Breast pumping mothers' needs were found to differ based on their work status and age together, and collecting and considering these different needs is vital to creating redesigns that improve mothers’ breast pumping experience.

Mild Traumatic Brain Injury as a Predictor of Classes of Youth Internalizing and Externalizing Psychopathology.

Mild traumatic brain injury (mTBI), is a developing public health problem. Evidence suggests that youth who suffer a mTBI experience worse outcomes than similar adults. However, the structure of long-term symptoms associated with mTBI is not well understood. The current study aims to determine if classes of youth psychopathology can be predicted by mTBI status. The current study analyzed a large sample of children and adolescents from the Project on Human Development in Chicago Neighborhoods (n = 2978) to examine trajectories of psychopathologies. Using data from the Achenbach Childhood Behavior Checklist, latent classes of internalizing and externalizing psychopathology were identified. Multinomial logistic regression models were used to examine if mTBI predicted class membership, while controlling for a number of variables associated with psychopathology. The results of the current study suggest that mTBI may be an important transdiagnostic risk factor associated with developmental patterns of internalizing and externalizing psychopathology.

Multidimensional dependency subgroups in community-dwelling older adults: A latent class analysis.

Use latent class analysis (LCA) to identify patterns of multidimensional dependency in a sample of older adults and assess sociodemographic, predictors of class membership. Longitudinal data were used from the Mexican Health and Aging Study (MHAS). 7,920 older adults, 55% women, were recruited. LCA were used to identify meaningful subgroups. LCA was conducted using MPlus version. The final class model was chosen based on the comparison of multiple fit statistics and theoretical parsimony, with models of increasing complexity analyzed sequentially until the best fitting model was identified. Covariates were incorporated to explore the association between these variables and class membership. Three classes groups based on the nine indicators were identified: "Active older adults" was comprised of 64% of the sample participants, "Relatively independent" and "Physically impaired" were comprised of 26% and 10% of the sample. The "Active older adults" profile comprised the majority of respondents who exhibited high endorsement rates across all criteria. The profiles of the "Active older adults" and "Relatively independent" were comparatively more uniform. Finally, respondents belonging to the "Physically impaired" profile, the smallest subgroup, encompassed the individuals most susceptible to a poor dependency profile. These findings highlighted the usefulness to adopt a person-centered approach rather than a variable-centered approach, suggesting directions for future research and tailored interventions approaches to older adults with particular characteristics. Based on patterns of multidimensional dependency, this study identified a typology of dependency using data from a large, nationally representative survey.

Is it Getting Better or Worse? Health‐Oriented Leadership and Psychological Capital as Resources for Sustained Health in Newcomers

During the transition from university to work, young adults face a stressful period in which leadership behavior serves as a guideline. Positive leadership behavior has the potential to increase internal resources, such as positive psychological capital (PsyCap). The research question addressed in this paper is if health‐oriented leadership and PsyCap as resources jointly influence the physical and mental health of novice teachers during the transition to work. In a longitudinal study, 776 novice teachers responded to three questionnaires with a time lag of 10 weeks during the first 5 months of their occupational experience. Results of a latent class growth analysis show that three trajectories of physical health and four trajectories of mental health can be distinguished. Health‐oriented leadership and PsyCap predict class membership separately, and the relationship between health‐oriented leadership and class membership is mediated by PsyCap. This implies that training supervisors in health‐oriented leadership can help novice teachers cope with stressors during their teacher training. Applying latent class growth models in this line of research is novel and adds to the understanding of internal and external resources in the process of adaptation to major life events, such as the transition from university to work.

Cognitive predictors of grief trajectories in the first months of loss: A latent growth mixture model.

Objective: The identification of modifiable cognitive antecedents of trajectories of grief is of clinical and theoretical interest. Method: The study gathered 3-wave data on 275 bereaved adults in the first 12–18 months postloss (T1 = 0–6 months, T2 = 6–12 months, T3 = 12–18 months). Participants completed measures of grief severity, cognitive factors (loss-related memory characteristics, negative appraisals, unhelpful coping strategies, and grief resilience), as well as measures of interpersonal individual differences (attachment and dependency). Latent growth mixture modeling was used to identify classes of grief trajectories. Predictors of class membership were identified using multinomial logistic regression and multigroup structural equation modeling. Results: Four latent classes were identified: 3 high grief classes (Stable, Low Adaptation, and High Adaptation) and a low grief class (Low Grief). When considered separately, variance in all four cognitive factors predicted membership of the high grief classes. When considered together, membership of the high grief classes was predicted by higher mean scores on memory characteristics. More negative appraisals predicted low or no adaptation from high grief severity. Losing a child also predicted membership to the stable class. Fast adaptation of high grief was predicted by a pattern of high memory characteristics but low engagement with unhelpful coping strategies. Conclusions: The findings have implications for clinical practice and point to early cognitive predictors of adaptation patterns in grief. Findings are consistent with cognitive models highlighting the importance of characteristics of memory, negative appraisals, and unhelpful coping strategies in the adaptation to highly negative life events.

Patterns of Healthcare Discrimination Among Transgender Help-Seekers

Affirmative health care is imperative to address health and mental health disparities faced by transgender communities. Yet, transgender help-seekers experience discrimination that precludes their access to and participation in care. This study uses latent class analysis to examine patterns of healthcare discrimination among transgender help-seekers. Predictors of class membership are investigated to identify subpopulations at highest risk for healthcare discrimination. Data were obtained from the 2015 U.S. Transgender Survey and analyzed in 2019. Ten healthcare experiences were included as latent class indicators. Latent class analysis and regression were performed in Mplus, version 8 to identify latent subgroups and examine the relationship between respondent characteristics and the latent classes. The final sample included 23,541 respondents. A 3-class model fit best: Class 1 experienced overt discrimination and interfaced with providers with limited trans-competence; Class 2 did not experience healthcare discrimination or report issues related to providers' trans-competence; and Class 3 did not experience discrimination but had providers with low trans-competence. Transmen and respondents who were out as trans to their providers and reported psychological distress, suicidal thoughts, and disabilities were more likely to be members of Class 1 or 3 than Class 2. Experiences of healthcare discrimination are not homogeneous across transgender help-seekers. Predictors of the latent classes indicated that transgender help-seekers holding an additional marginalized identity may be at higher risk for healthcare discrimination or care from providers with limited trans-competence. Targeted engagement and education interventions might improve these transgender help-seekers' access to and connections with care.

Prediction of rapid amyloid and phosphorylated‐Tau accumulation in cognitively healthy individuals.

To test the hypothesis that among cognitively healthy individuals, distinct groups exist in terms of amyloid and phosphorylated-tau accumulation rates; that if rapid accumulator groups exist, their membership can be predicted by Alzheimer's disease (AD) risk factors, and that time points of significant increase in AD protein accumulation will be evident. The analysis reports data from 263 individuals from the BIOCARD and 184 individuals from the Baltimore Longitudinal Study of Aging with repeated cerebrospinal fluid (CSF) and positron emission tomography (PET) sampling, respectively. We used latent class mixed-effect models to identify distinct classes of amyloid (CSF and PET) and p-Tau (CSF) accumulation rates and generalized additive modeling to investigate non-linear changes to AD biomarkers. For both amyloid and p-Tau latent class models we confirmed the existence of two separate classes: accumulators and non-accumulators. The accumulator and non-accumulator groups differed significantly in terms of baseline AD protein levels and slope of change. APOE ε4 carrier status and episodic memory predicted amyloid class membership. Non-linear models revealed time points of significant increase in the rate of amyloid and p-Tau accumulation whereby APOE ε4 carrier status associated with earlier age at onset of rapid accumulation. The current analysis demonstrates the existence of distinct classes of amyloid and p-Tau accumulators. Predictors of class membership were identified but the overall accuracy of the models was modest, highlighting the need for additional biomarkers that are sensitive to early disease phenotypes.

Understanding Elementary Classroom Teachers' Use of Movement Integration Resources.

Movement integration (MI)—infusing physical activity (PA) into normal classroom time during school—is an evidence-based strategy to support public health goals and enhance educational outcomes for elementary children. However, few elementary classroom teachers in the United States appear to be using MI resources. In order to understand teachers’ MI resource use, this study’s purpose was 3-fold: (a) to examine teachers’ perceptions about MI and MI resources, (b) to identify teachers’ latent class membership based on their perceptions, and (c) to determine the extent to which teachers’ MI preferences, demographics, background, and school context predict class membership. We recruited a national sample of participants (N = 420) who completed an electronic survey including six sections: perceived benefits of MI, perceived barriers to using MI resources, satisfaction with MI resources, perceived importance of different MI resource characteristics, MI resource preferences, and participant demographics, background, and school context. Data analysis consisted of descriptive analyses, exploratory factor analysis, confirmatory factor analysis, latent profile analysis, and multinomial regression analysis. Participants mostly agreed about the benefits of MI and were satisfied with the MI resources they were using but had varying perceptions about the presence of barriers to using MI resources. Participants rated the integration of an MI resource with the academic curriculum, the amount of time required for teacher training, the type of training materials provided, and the timing of the training as the most important characteristics they would consider before adopting a resource. Factor analyses supported single factor solutions for perceived benefits, perceived barriers, and satisfaction, and a three-factor solution for perceived importance of different MI resource characteristics (Curriculum Integration, Training Logistics, and Feasibility). Based on these factors, we identified five latent classes of teachers. Regression results showed that desirable latent class membership depended on certain MI preferences and demographic, background, and school context characteristics. Teacher educators and interventionists should consider teachers’ MI perceptions, the nature of MI trainings, teacher characteristics, and school context in efforts to increase teachers’ use of MI resources. Further research is needed to explore the intrinsic value of MI for teachers, given MI’s education- and public health-related benefits.

Patterns of Problem Behaviors and Predictors of Class Membership among Adolescents in the Republic of Korea: A Latent Class Analysis

Although subgroups of adolescent problem behaviors (PBs) may exist and have different characteristics, most available studies have focused on exploring a single PB. Thus, we aimed to investigate latent classes of adolescent PBs and to identify important predictors of latent class membership. We analyzed nationally representative secondary data—Waves 4 and 5 of the Korean Children & Youth Panel Survey—obtained from the 2010 cohort of seventh graders and their parents. Specifically, using seven PBs (e.g., daily smoking, monthly drinking, and sexual intercourse) measured in Wave 5, we conducted a latent class analysis (LCA) to identify the model that best fit the data. In the next step, we conducted an LCA with covariates to investigate Wave-4 predictors of latent class membership. In our study, a three-latent-class model best fit the data: the Low Risk class (78%) characterized by low probabilities of engagement in all PBs, Non-Habitual Alcohol Use class (14%), and Habitual Cigarette and Alcohol Use class (7%). In addition, successful predictors of latent class membership included gender, parental education, friendships, relationships with teachers, parental affection, abuse inflicted by parents, and aggression. Health professionals should develop interventions tailored to each homogeneous subgroups of PBs in order to obtain more effective outcomes. Additionally, when developing these interventions, they should consider multilevel characteristics (e.g., individual, peer, and parental factors) that differentiate these subgroups.

Using Latent Class Analysis to Examine Susceptibility to Various Tobacco Products Among Adolescents.

Most tobacco use is initiated during adolescence and susceptibility is an important predictor of initiation. Research is needed to understand susceptibility across tobacco products among youth to inform prevention efforts. We surveyed 2945 students from four Southeastern Connecticut high schools in 2017. We assessed susceptibility to future use of seven different tobacco products (ie, cigarettes, e-cigarettes, hookah, cigars, cigarillos, blunts, and smokeless tobacco) among youth who had never used a tobacco product. Susceptibility was coded as any response other than "definitely not" to three items assessing (1) curiosity, (2) willingness to experiment with the product in the future, and (3) willingness to try if offered by a friend. Latent class analysis was used to identify patterns of susceptibility across multiple tobacco products and sociodemographic predictors of these classes. Among n = 1246 youth who had never tried a tobacco product, 51.2% (n = 638) were susceptible to at least one product and 29.1% (n = 363) were susceptible to two or more products (average among susceptible youth: M = 2.4 products, SD = 1.7, range 1-7). Latent class analysis identified three classes: youth who were: (1) susceptible to all products (5.6%), (2) susceptible to e-cigarettes, hookah, and blunts (23.6%), and (3) mostly non-susceptible to all products (70.8%). In a multivariable model, demographic variables and peer tobacco use predicted class membership. We observed high rates of susceptibility to non-traditional tobacco products among youth, and many youth were susceptible to more than one product. Targeting susceptibility across multiple tobacco products may be important for reducing youth tobacco use. Patterns of polytobacco use susceptibility were identified among youth who had never previously used tobacco products. Many youth were susceptible to more than one product and we observed three distinct classes of susceptibility among youth: those who were mostly non-susceptible, those who were susceptible to alternative or non-traditional tobacco products (e-cigarettes, hookah, and blunts), and those who were susceptible to all tobacco products. These findings suggest the importance of addressing susceptibility across multiple tobacco products.