INTRODUCTION:Middle adolescence involves increasingly complex stressors, yet it remains unclear how coping strategies cluster into distinct profiles, how those profiles change across time, and whether profile structure is comparable across gender. We used latent class and transition analysis across three annual waves to identify coping profiles, model transitions, and examine perceived stress, depressive symptoms, and general self-efficacy by profile. METHODS:Participants were 964 adolescents (mean age = 16.1 years; 56% female) from public high schools in Texas who completed surveys in spring 2011 with two annual follow-ups. The sample self-identified as Hispanic (32%), White (30%), African American (27%), or other (11%). Latent class/transition models estimated profile membership, transitions, and gender differences in prevalence and transition probabilities. RESULTS:Four coping profiles emerged: Minimal Copers, Maximum Copers, Introverted Approach-Avoidant Copers, and Independent Problem-Solving Copers. Profile structure was comparable for females and males, although prevalence and transition differed. At Wave 4, Introverted Approach-Avoidant Copers reported the highest perceived stress and depressive symptoms, whereas Minimal and Independent Problem-Solving Copers reported lower perceived stress and depressive symptoms. Independent Problem-Solving and Maximum Copers reported higher general self-efficacy, whereas Minimal Copers reported the lowest. CONCLUSIONS:Coping in adolescence is heterogeneous and shifts over time, with gender differences in profile prevalence and transitions; findings highlight potential targets for tailored support and self-efficacy enhancement.

Introduction: Deaths of opioid overdose are a serious public health concern throughout the U.S., transcending geographical and demographic categories. While naloxone can reverse an overdose and prevent death, it must be administered in a timely fashion. Efforts to get naloxone widely distributed contribute to harm reduction efforts, but more efficient strategies for recruiting people to carry and administer naloxone will increase the impact and advance prevention science. Yet, most existing programs are not evidence-based. The Opioid Rapid Response System (ORRS) was developed for these purposes. Methods: A randomized controlled trial will be conducted in 9 communities in Pennsylvania, Arizona, and Washington to evaluate ORRS. The RCT will be conducted with pretest and posttest surveys administered to assess the effectiveness of the training. Focus groups will inform the development of the ORRS training. To increase the appeal of naloxone training for volunteers, recruitment strategies will focus on personal and social identity. Conclusion: The Opioid Rapid Response System is a theory-driven program that recruits and trains lay citizens to respond to opioid overdose events. The program has the potential to advance knowledge of lay citizen recruitment and training, and to reduce deaths from overdoses. Trial registration: NCT06238128

The present study examined the role of sexting in adolescents' peer environment and romantic relationships with attention to gender patterns. Thirty adolescent girls and boys (ages 16 or 17) of varying racial/ethnic background residing in Los Angeles or Phoenix participated in in-depth interviews about their experiences and attitudes toward sexting. Thematic analysis was used to analyze the interview data. In total, we identified 5 main themes and 15 subthemes. Participants reported that sexting is normal in their peer groups (Main theme #1 Everyone's Doing It) and that sexting occurs within a cultural milieu of the sexual double standard (Main theme #2 Sexual Double Standard). They described sexting as a part of expressing romantic interest in someone and playing a role in defining and furthering romantic relationships (Main theme #3 Romantic Relationships). Participants also identified social (Main theme #4 Social Consequences) as well as psychological and long-term consequences of sexting (Main theme #5 Psychological or Long-Term Consequences). Findings of this study have implications for educational interventions.

Background/Objectives: Test efficacy of the social emotional learning (SEL)-based Mighty Girls program, a program culturally tailored for English-speaking Hispanic/Latino girls in seventh grade comprised of classroom sessions and a virtual reality computer game. We hypothesized that the curriculum would decrease risky sexual behaviors in a program that can be used as part of a comprehensive sex education curriculum or as a stand-alone program. Methods: A randomized group trial was conducted in which 22 low-income, predominately Hispanic schools within the Miami-Dade County Public School System were randomly assigned to intervention (consented n = 335) and control (consented n = 217) conditions. All study activities occurred after school. Primary outcome measures were resistance self-efficacy, acceptance of dating violence, sexual intentions, and sexual behavior. Assessments occurred at baseline, immediately post-intervention, 3-, 12-, and 24-months post-intervention. Changes in outcomes from baseline to 24 months were modeled using multi-level models to account for nesting of students within schools with full information maximum likelihood to account for missing data and baseline school attendance and enrollment in free and reduced lunch as covariates. Analyses are also controlled for multiple testing. Results: The program had a significant effect on reducing acceptance of dating violence at 24 months post-intervention (estimate = −0.083, p ≤ 0.05), but no effect on resistance self-efficacy, sexual intentions, or sexual behavior (p ≥ 0.58). Conclusion: Study findings demonstrate that a social emotional learning (SEL) curriculum can impact sexual behaviors such as susceptibility to dating violence. Low baseline levels for sexual intentions and behaviors as well as a high baseline of efficacy may have impacted findings for the other outcomes.

Background: While laypersons can play a crucial role in administering naloxone in opioid overdoses, they must be recruited and trained to effectively manage overdose events as good Samaritans. This study aimed to examine the effectiveness of a technology-based intervention that recruited and trained laypersons to administer naloxone. Methods: Opioid Rapid Response System (ORRS) was an online recruitment and training intervention which capitalized on social cognitive theory and a digital media engagement model to mobilize laypersons to administer intranasal naloxone. ORRS was developed based on a randomized waitlisted controlled trial (N = 220). This secondary analysis is a within-group, extended-baseline assessment of the waitlisted group (n = 106), considering that they served as their own control prior to receiving the training. ORRS was conducted in five counties of Indiana with adults who did not self-identify as a certified first responder. Five indices were generated from 23 variables: knowledge of overdose signs, knowledge of overdose management, self-efficacy in responding, concerns about responding, and intent to respond. Paired t-test compared changes between 3 timepoints. Results: Three indices had significantly greater increases associated with training compared to extended baseline: recognizing opioid overdose signs (difference = 0.08; 95%CI = 0.02, 0.15; t = 2.48; p = 0.01); knowledge of overdose management (difference = 0.27; 95%CI = 0.18, 0.35; t = 5.99; p < 0.01); and self-efficacy in overdose management (difference = 0.68; 95%CI = 0.45, 0.91; t = 5.78; p < 0.01). Concerns related to overdose management significantly decreased as expected (difference = -1.53; 95%CI = -1.86, -1.21; t = -9.27; p < 0.01). Conclusions: ORRS provided strong support for self-efficacy, concerns, and knowledge related to overdose management, and the digital modality accelerates largescale dissemination.

Based on social cognitive processes (Bandura, 2009), sexualizing media likely provide adolescents with credible role models for their own sexualized self-presentation in other mediated contexts, such as sexting. A survey of 6,093 US adolescents was conducted (Mage = 15.27 years, SD = 1.37; 69.1

Examining teachers' knowledge on a large scale involves addressing substantial measurement and logistical issues; thus, existing teacher knowledge assessments have mainly consisted of selected-response items because of their ease of scoring. Although open-ended responses could capture a more complex understanding of and provide further insights into teachers' thinking, scoring these responses is expensive and time consuming, which limits their use in large-scale studies. In this study, we investigated whether a novel statistical approach, topic modeling, could be used to score teachers' open-ended responses and if so, whether these scores would capture nuances of teachers' understanding. To test this hypothesis, we used topic modeling to analyze teachers' responses to a proportional reasoning task and examined the associations of the topics identified through this method with categories identified by a separate qualitative analysis of the same data as well as teachers' performance on a measure of ratios and proportional relationships. Our findings suggest that topic modeling seemed to capture nuances of teachers' responses and that such nuances differentiated teachers' performance on the same concept. We discuss the implications of this study for education research.

This study investigates the applicability of topic modeling to analyze educational data. Topic modeling is useful because it reveals the latent topic structure underlying a collection of texts. Because metadata provides useful information about the topics, this study explores a way of including metadata as a covariate predicting topics and outcomes by topic in a topic model using a two-step approach. In Study 1, we use structural topic model (STM) and regression model because STM estimates the topic structure and how covariate is related to the topics. In Study 2, supervised Dirichlet allocation (sLDA) model is used to investigate the relationship between topics and the outcome variable: we incorporate sLDA with ANOVA. We demonstrate that the inclusion of multiple metadata improved the interpretability of the topic modeling techniques’ results by examining the relationship among the examinees’ written answers, problem-solving strategies, and scores using the empirical data of 246 middle school mathematics teachers’ written responses to an item.

Latent Dirichlet Allocation (LDA) is a probabilistic model to analyze textual data. It was originally developed for corpora containing large amount of textual data, such as large sets of journal abstracts, blogs, and newspaper articles. Recently, LDA has been applied in psychological and educational measurement fields to analyze examinees’ responses to open-ended items on assessments. The amount of textual data found in educational measurement scenarios, however, is notably less than the amount of data originally used for LDA. The observed data, therefore, may not be enough to accurately recover the parameters. Thus, it is important to explore how various priors influence the parameter recovery of the LDA model. In this study, we investigated the effects of prior hyperparameters parameter on recovery through a simulation using various conditions that are common in educational assessment settings. Specifically, five sets of priors ranging from highly informative to noninformative were used. For each set of priors, four factors were manipulated and all factors were crossed for a total of 108 conditions. The four factors used in this study were: number of unique words (3 levels: 250, 500, and 750 words), average response length (3 levels: 5, 25, and 50 words per document), number of documents (3 levels: 100, 250, and 500 documents), and number of topics (3 levels: 3, 4, and 5 topics). The results of the simulation showed that the prior specification of the LDA model influenced the parameter recovery rates.

A substantial body of research has explored the relationship between passive information seeking and youths’ beliefs about and use of substances. To date, however, little work has explored other dimensions of youth information behavior (such as active information seeking, information needs, and information use) and substance use. The aim of this study was to pilot the use of an information behavior scale in order to examine the association between youth information behavior and self-reported substance use, as well as use-related expectancies. Youth 12–17 years of age (N = 446) across eight U. S. states completed self-report measures of their information behavior and their use of and expectancies regarding the following: cigarettes; electronic vapor products; chewing tobacco, snuff, dip, or snus; cigars, cigarillos, or little cigars; alcohol; and marijuana. Regression models were conducted to examine the relationship between information behavior, substance use, and substance use expectancies. Results indicated that information behavior was associated with expectancies for tobacco and vaping products, but not for alcohol or marijuana. There was no significant association between information behavior and actual substance use. Results have implications for the development and implementation of both information behavior measures and substance use prevention programs.

We examined sociodemographic and psychosocial risk factors that moderate the (poly) substance use and dating violence victimization and perpetration relationship among emerging adults. Using an ethnically diverse sample (N = 698), we used latent class analyses to identify mutually exclusive groups based on monthly and past-year substance use. We then examined these groups as they relate to dating violence victimization and perpetration and the moderating effect of various risk factors. Five classes were identified based on substance use patterns: (a) Regular Alcohol use, (b) Polysubstance use, (c) Heavy Alcohol and Marijuana use, (d) Mild Alcohol use, and (e) Occasional Alcohol and Marijuana use classes. Participants in the Polysubstance use class were the most likely to perpetrate dating violence followed by Heavy Alcohol and Marijuana use, Occasional Alcohol and Marijuana use, Regular Alcohol, and Mild Alcohol use classes. Similarly, participants in the Polysubstance use class were the most likely to be victims of dating violence followed by Occasional Alcohol and Marijuana, Heavy Alcohol and Marijuana, Regular Alcohol, and Mild Alcohol use classes. Depending on substance use class, gender, ethnicity, socioeconomic status, history of dating violence, and trauma symptoms differentially influenced dating violence perpetration and victimization at 1-year follow-up. Our findings support the need to comprehensively address dating violence among emerging adults. Intimate partner violence prevention and intervention programs may benefit from targeting emerging adults who misuse substances and incorporating substance use interventions into dating violence prevention efforts.

Background and Objectives: The opioid epidemic has permeated all strata of society over the last two decades, especially within the adolescent student athletic environment, a group particularly at risk and presenting their own challenges for science and practice. This paper (a) describes the development of a web-based intervention called the Student Athlete Wellness Portal that models effective opioid misuse resistance strategies and (b) details the findings of a single-group design to test its effectiveness. Materials and Methods: Formative research included 35 student athletes residing in the United States, ages 14 to 21, who had been injured in their school-based sport. They participated in in-depth qualitative interviews to explore narratives relating to their injuries and pain management plans. Inductive analyses of interview transcripts revealed themes of the challenges of being a student athlete, manageable vs. unmanageable pain, and ways to stay healthy. These themes were translated into prevention messages for the portal, which was then tested in a single-group design. Results: Users of the portal (n = 102) showed significant decreases in their willingness to misuse opioids and increases in their perceptions of opioid risks. Conclusions: This manuscript illuminates the processes involved in translating basic research knowledge into intervention scripts and reveals the promising effects of a technology-based wellness portal.

We used the developmental systems model to deduce a definition of female early adolescent sexual desire. We evaluated a measure of this phenomenon with a secondary analysis of data from a randomized group sexual health intervention trial involving low-income, English-speaking, seventh grade Latinas enrolled in a Miami-Dade County public school (n = 542). As part of this study, girls completed a four-item early adolescent sexual desire (EASD) measure. Study findings supported internal consistency (Cronbach's alpha = .81 to .82) and stability over a 1-month period (r = .74). Developmental sensitivity was supported by a decline in stability over 12- (r = .66) and 24-month periods (r = .56). Validity was supported by correlations with puberty changes, sexual intentions, sexting, and sexual behavior, and hypothesized mean differences associated with dating and preference for shoes culturally associated with female sexual attractiveness (p < .01). Research implications include validation work with other ethnic/racial groups and using the EASD as a starting point for a measurement continuum tracking development of sexual desire across adolescence and into adulthood. Directions for future research also include measuring the development of sexual desire in boys and transgendered youth across adolescence and into adulthood.

Past research has demonstrated that romantic attachment insecurity is a risk factor for dating violence in adolescence. However, few studies to date have longitudinally examined whether earlier relational experience, such as perceived closeness with parents, may serve as an antecedent of this relationship. To examine longitudinal associations among youths’ perceived closeness with parents, romantic attachment insecurity, and perpetration of dating violence in adolescence. Adolescents ( N = 1016) were recruited from seven public high schools in south Texas and reported on their perceived closeness with parents, romantic attachment styles, and perpetration of physical and psychological dating violence at three assessments between 2010 and 2014. Data were analyzed using structural equation modeling. Adolescents’ romantic attachment anxiety, but not attachment avoidance, significantly mediated the relationship between low perceived closeness with parents and the perpetration of physical and psychological dating violence in late adolescence. Multi-group analyses showed the mediation model only held for females but not males, and for Hispanic youth but not for Non-Hispanic White, African American, and youth of other races and ethnicities. Through its link to romantic attachment anxiety, perceived closeness with parents could play an important role in the perpetration of dating violence in adolescence, especially for girls and Hispanic youth. Findings suggest that dating violence interventions may benefit from targeting aspects of parent–child relationships.

Introduction: Smoking research demonstrates that parents can influence their adolescent’s tobacco smoking perceptions and behaviors, but little is known about the protective effects of different parenting practices on adolescent vaping. In this study we investigate how adolescent perceptions of parents’ knowledge of their activities and parental media mediation are associated with adolescents’ perceptions of vaping and adolescent vaping behaviors. Method: Six hundred thirty-nine youth (65.7% female, average age: 14.71 years old) recruited through 4-H clubs in nine states participated in a study evaluating a substance use intervention program. Because the evaluation design could influence participants, we used only baseline data. An online self-reported survey was administrated. Most youth self-identified as White (87.3%) and only handful youth indicated Asian (3.4%), African American (3.4%), American Indian (1.1%), and other or unreported (4.8%). Approximately 60% of youth lived in small town or rural areas in US. Results: Analyses revealed that parental knowledge was positively related with adolescent perceived harm of vaping and perceived prevalence of vaping, but was negatively related with perceived acceptability of vaping and social expectancy of vaping. In addition, youth who reported greater parental media mediation were more likely to perceive the harm of vaping and less likely to vape compared with youth with lower parental media mediation. Conclusion: These findings suggest that parental education about vaping, including those promoting conversations regarding vaping and vaping ads, may be important to the prevention of adolescent vaping.

Latent Dirichlet Allocation (LDA; Blei et al., J Mach Learn Res 3:993–1022, 2003) is a probabilistic topic model that has been used to detect the latent structure of examinees’ responses to constructed-response (CR) items. In general, LDA parameters are estimated using Gibbs sampling or variational expectation maximization (VEM). Relatively little evidence exists, however, regarding the accuracy of either algorithm in the context of educational research, such as small numbers of latent topics, small numbers of documents, short average lengths of documents, and small numbers of unique words. Thus, this simulation study evaluates and compares the accuracy of parameters estimates using Gibbs sampling and VEM in corpora typical of educational tests employing CR items. Simulated conditions include number of documents (300, 700, and 1000 documents), average answer length (20, 50, 100, and 180 words per document), vocabulary of unique words in a corpus (350 and 650 unique words), and number of latent topics (3, 4, 5, 6, and 7 topics). Accuracy of estimation was evaluated with root mean square error. Results indicate both Gibbs sampling and VEM recovered parameter estimates well but Gibbs sampling was more accurate when average text length was small.

Adaptive learning offers real attention to individual students’ differences and fits different needs from students. This study proposes a bi-level recommendation system with topic models, gradient descent, and a content-based filtering algorithm. In the first level, the learning materials were analyzed by a topic model, and topic proportions to each short item in each learning material were yielded as representation features. The second level contains a measurement component and a recommendation strategy component which employ gradient descent and content-based filtering algorithm to analyze personal profile vectors and make an individualized recommendation. An empirical data consists of cumulative assessments that were used as a demonstration of the recommendation process. Results have suggested that the distribution to the estimated values in the person profile vectors were related to the ability estimation from the Rasch model, and students with similar profile vectors could be recommended with the same learning material.

Introduction: A sizable minority of youth are sexting; however there are likely large individual differences in sexting and sexual behaviors, yet to be captured. A Latent Class Analysis was used to identify subgroups of youth characterized by differential engagement in sexting and sexual behaviors. Methods: Participants were an ethnically diverse sample of 894 youth (55.8% female; Mage = 17.04, SD = 0.77) from a longitudinal survey study in southeast Texas. Latent classes were identified through participants? responses to the following indicator variables: sending, receiving, and requesting sexts, sexual activity, contraception use, ? three partners, and substance use prior to sexual activity. Gender, ethnicity, impulsivity, and living situation were analyzed as predictors, and depressive symptoms as an outcome, of class membership. Results: The analysis revealed four distinct classes: No sexting-Low sex (42.2%), Sexting-Low sex (4.5%), No sexting-Moderately risky sex (28.3%), and Sexting-Moderately risky sex (24.9%). Gender and ethnicity predicted class membership wherein females and ethnic minority youth were less likely to be in groups displaying higher rates of sexting. Impulsivity and living situation predicted class membership, such that youth reporting higher impulsivity and living in a situation other than with two biological parents were less likely to be in classes displaying low sexting and sexual behaviors. Group membership predicted depressive symptoms. Conclusions: Results suggest that not all youth who are sexting are having sex, and not all youth who are having sex are sexting. Evidence of individual differences in youth sexual behaviors should inform educational initiatives aimed at teaching youth about sexual and online health.

Over the past decade, topic models have been used to analyze students’ responses to constructed-response items. Analyzing students’ responses using topic models has been shown to yield similar results to a qualitative analysis. As the use of topic models increases in the educational setting, it is important to assess the performance of the underlying statistical mechanism. Simulation studies are an essential tool when evaluating the performance of a statistical model. Using a simulation study to assess performance of topic models, such as the latent Dirichlet allocation (LDA) model, requires generating simulated text responses rather than scored responses. LDA and other related topic models, such as the supervised latent Dirichlet allocation model, assumes a generative process for construction of responses. Topic models also assume that the text data follows a bag-of-words distribution. These key assumptions allow generating simulated text responses to be possible. In this paper we demonstrate the simulation process for topic models followed by a simulation study that assesses the sample size needed to recover the parameters of the LDA model.

The use of constructed-response and performance-oriented items is becoming increasingly more common in educational measurement. These items may be in the form of written essays or short answers and may appear in both high- and low-stakes assessments. Constructed responses may be scored by human raters or through an automated scoring engine. Topic modeling provides a tool for mining textual data in an effort to detect the latent semantic structures. The supervised Latent Dirichlet Allocation model (sLDA) is widely used in text analysis. In this study, we examine and compare the utility of different sLDA models for detecting the latent topic structure and scoring on a test of English and language arts.