Development of the Structural Model of Adolescent's Risk Behavior

Adolescents and risks: Why not change our paradigm?

Addressing Common Risk and Protective Factors Can Prevent a Wide Range of Adolescent Risk Behaviors

Downwards trends in adolescent risk-taking behaviours in New Zealand: Exploring driving forces for change.

Peer Influences: The Impact of Online and Offline Friendship Networks on Adolescent Smoking and Alcohol Use

Little is known about how physical activity (PA), sedentary behavior, and various adolescent health risk behaviors are associated. The objective of this study was to examine relationships between PA and sedentary behavior patterns and an array of risk behaviors, including leading causes of adolescent morbidity/mortality. Nationally representative self-reported data were collected (National Longitudinal Study of Adolescent Health; wave I: 1994-1995; II: 1996; N = 11957). Previously developed and validated cluster analyses identified 7 homogeneous groups of adolescents sharing PA and sedentary behaviors. Poisson regression predicted the relative risk of health risk behaviors, other weekly activities, and self-esteem across the 7 PA/sedentary behavior clusters controlling for demographics and socioeconomic status. Main outcome measures were adolescent risk behaviors (eg, truancy, cigarette smoking, sexual intercourse, delinquency), other weekly activities (eg, work, academic performance, sleep), self-esteem. Relative to high television (TV) and video viewers, adolescents in clusters characterized by skating and video gaming, high overall sports and sports participation with parents, using neighborhood recreation center, strict parental control of TV, reporting few activities overall, and being active in school were less likely to participate in a range of risky behaviors, ranging from an adjusted risk ratio (ARR) of 0.42 (outcome: illegal drug use, cluster: strict parental control of TV) to 0.88 (outcome: violence, cluster: sports with parents). Active teens were less likely to have low self-esteem (eg, adolescents engaging in sports with parents, ARR: 0.73) and more likely to have higher grades (eg, active in school, ARR: 1.20). Participation in a range of PA-related behaviors, particularly those characterized by high parental sports/exercise involvement, was associated with favorable adolescent risk profiles. Adolescents with high TV/video viewership were less likely to have positive risk behavior outcomes. Enhancing opportunities for PA and sport may have a beneficial effect on leading adolescent risk behaviors.

Purpose:In this study the fitness of apathmodel onsexual riskbehavior in adolescents was examinedincluding therelationshipof the followingsensation seeking, parent-adolescent communication, exposure topornography, friends' attitudes to sex, attitudes to sexual behavior, sexual permissiveness, perceived behavioral control, and sexual behavioral intention. Methods:Theparticipantswere354adolescents. Datawereanalyzed usingtheSPSS and AMOS programs. Results: Parent-adolescent communication, exposure to pornography, friends' attitudes to sex, and sexual behavioral intention showed a direct effect on sexual risk behavior in adolescents, while sensationseeking,exposuretopornography, friends' attitudestosex, attitudestosexual behavior, sexualpermis- siveness, and perceivedbehavioral control showed anindirect effect onsexual risk behavior inadolescents. The modifiedpath model of adolescent'ssexual risk behavior had agood fit withthe data. Conclusion:Based on the outcomes of this study, it is necessary to design intervention programs that emphasize increasing parent- adolescent communication, perceived behavioral control,and sexual behavioral intentionandreducing exposure to pornography, friends' attitudes to sex, attitudes to sexual behavior, and sexual permissiveness in order to decrease adolescent's sexual risk behavior.

Continuing behavioral research has documented the mounting prevalence of child and adolescent health risk behaviors. Fifty pre-service educators were assessed regarding their perception of critical factors that would influence their confidence, comfort, and efficacy levels in dealing with child and adolescent risk behaviors. Study results revealed that administrative support and legal concerns, personal experiences, educational training, the student’s family, professional advice, and student support services influence preservice educators’ reactions to student risk behaviors. Factors essential to enhancing pre-service educators’ confidence, comfort, and efficacy levels include providing opportunities to gain skills in tackling risk behaviors; addressing legal issues, such as confidentiality, student rights, and district policies, within a teacher training program; offering professional advice regarding effective strategies for handling risk behaviors in the classroom and school settings; enlightening campus administrators of the importance of perceived teacher support; as well as informing counselors and other support personnel of their identified role as informational resources.

Background Adolescents’ risk-taking behaviors can have profound impacts on their future health. Few studies have established a relationship between multiple social environmental factors and adolescent risk behaviors. We used structural equation modeling to examine the role of parental monitoring and environmental risks on adolescents’ behavioral intentions and risk behaviors. Methods Data were collected through the baseline survey of a national implementation project among 2205 Grade 6 students in 24 government schools in The Bahamas in 2019. Structural equation modeling examined relations among parental monitoring, environmental risk factors, behavioral intentions, and risk behaviors. Results Students had engaged in various delinquent, substance use, and sexual risks. In the structural equation model, parental monitoring demonstrated direct negative (protective) effects on behavioral intentions and risk behaviors, whereas environmental risk factors had a direct positive effect on adolescent behavioral intentions and risk behaviors. The model had an R2 value of 0.57 for adolescent risk behaviors. Conclusion Parental monitoring and environmental risk factors had strong influences on risk-taking behaviors of early adolescents. Future adolescent health behavior interventions should consider offering additional prevention resources to early adolescents who are exposed to multiple environmental risk factors.

Using Sibling Differences to Estimate Effects of Parenting on Adolescent Sexual Risk Behaviors

Peer-relationship patterns and their association with types of child abuse and adolescent risk behaviors among youth at-risk of maltreatment

Precision prevention is increasingly important in HIV prevention research to move beyond universal interventions to those tailored for high-risk individuals. The current study was designed to develop machine learning algorithms for predicting adolescent HIV risk behaviours. Comprehensive longitudinal data on adolescent risk behaviours, perceptions, peer and family influence, and neighbourhood risk factors were collected from 2564 grade-10 students at baseline followed for 24 months over 2008-2012. Machine learning techniques [support vector machine (SVM) and random forests] were applied to innovatively leverage longitudinal data for robust HIV risk behaviour prediction. In this study, we focused on two adolescent risk behaviours: had ever had sex and had multiple sex partners. Twenty percent of the data were withheld for model testing. The SVM model with cost-sensitive learning achieved the highest sensitivity, at 79.1%, specificity of 75.4% with AUC of 0.86 in predicting multiple sex partners on the training data (10-fold cross-validation), and sensitivity of 79.7%, specificity of 76.5% with AUC of 0.86 on the testing data. The random forest model obtained the best performance in predicting had ever had sex, yielding the sensitivity of 78.5%, specificity of 73.1% with AUC of 0.84 on the training data and sensitivity of 82.7%, specificity of 75.3% with AUC of 0.87 on the testing data. Machine learning methods can be used to build effective prediction model(s) to identify adolescents who are likely to engage in HIV risk behaviours. This study builds a foundation for targeted intervention strategies and informs precision prevention efforts in school-setting.

Composite scores offer the advantage of summarizing across multiple sexual risk behaviors to both simplify results and better capture the influence of core contextual, interpersonal, and intrapersonal dynamics that affect multiple sexual risk behaviors. There is inconsistency in how researchers utilize composite scores with minimal guidance on the advantages and disadvantages of frequently used approaches. Strengths and weaknesses of each approach are discussed in the context of assessing adolescent sexual risk behavior. A latent variable model and three commonly used composites were applied to data combined across four clinical trials (n = 1322; 50% female). Findings suggested that the latent variable approach was limited due to minimal correlations among sexual risk behaviors, that choice of composite had minimal impact on cross-sectional results so long as there is sufficient variability in risk behavior in the sample, but composite choice could impact results from clinical trials particularly for subgroup analyses. There are unique challenges to creating composites of adolescent risk behavior, including the fluidity and infrequency of adolescent sexual relationships that result in many participants reporting no sexual behavior at any given assessment and a low correlation between the number of partners and condomless sex acts. These challenges impede application of data-driven approaches to defining sexual risk composites. Recommendations to improve consistency in reporting include: (1) reporting each type of risk behavior separately prior to forming a composite, (2) aggregating across assessments to increase the chance of observing sexual risk behaviors, and (3) continued work toward a unified definition of adolescent sexual risk behavior that can guide the development of appropriate measurement models.

Afterword: Teen Driving

This study investigated associations among adolescents' self-esteem in 6 domains (peers, school, family, sports/athletics, body image and global self-worth) and risk behaviours related to substance use, bullying, suicidality and sexuality. A multistage stratified sampling strategy was used to select a representative sample of 939 English-, Afrikaans- and Xhosa-speaking students in Grades 8 and 11 at public high schools in Cape Town, South Africa. Participants completed the multidimensional Self-Esteem Questionnaire (SEQ; DuBois, Felner, Brand, Phillips, & Lease, 1996) and a self-report questionnaire containing items about demographic characteristics and participation in a range of risk behaviours. It included questions about their use of tobacco, alcohol, cannabis, solvents and other substances, bullying, suicidal ideation and attempts, and risky sexual behaviour. Data was analysed using a series of logistic regression models, with the estimation of model parameters being done through generalised estimation equations. Scores on each self-esteem scale were significantly associated with at least one risk behaviour in male and female adolescents after controlling for the sampling strategy, grade and race. However, specific self-esteem domains were differentially related to particular risk behaviours. After taking the correlations between the self-esteem scales into account, low self-esteem in the family and school contexts and high self-esteem in the peer domain were significantly independently associated with multiple risk behaviours in adolescents of both sexes. Low body-image self-esteem and global self-worth were also uniquely associated with risk behaviours in girls, but not in boys. Overall, the findings suggest that interventions that aim to protect adolescents from engaging in risk behaviours by increasing their self-esteem are likely to be most effective and cost-efficient if they are aimed at the family and school domains.

Background: This study investigated associations among adolescents’ self‐esteem in 6 domains (peers, school, family, sports/athletics, body image and global self‐worth) and risk behaviours related to substance use, bullying, suicidality and sexuality. Method: A multistage stratified sampling strategy was used to select a representative sample of 939 English‐, Afrikaans‐ and Xhosa‐speaking students in Grades 8 and 11 at public high schools in Cape Town, South Africa. Participants completed the multidimensional Self‐Esteem Questionnaire (SEQ; ) and a self‐report questionnaire containing items about demographic characteristics and participation in a range of risk behaviours. It included questions about their use of tobacco, alcohol, cannabis, solvents and other substances, bullying, suicidal ideation and attempts, and risky sexual behaviour. Data was analysed using a series of logistic regression models, with the estimation of model parameters being done through generalised estimation equations. Results: Scores on each self‐esteem scale were significantly associated with at least one risk behaviour in male and female adolescents after controlling for the sampling strategy, grade and race. However, specific self‐esteem domains were differentially related to particular risk behaviours. After taking the correlations between the self‐esteem scales into account, low self‐esteem in the family and school contexts and high self‐esteem in the peer domain were significantly independently associated with multiple risk behaviours in adolescents of both sexes. Low body‐image self‐esteem and global self‐worth were also uniquely associated with risk behaviours in girls, but not in boys. Conclusions: Overall, the findings suggest that interventions that aim to protect adolescents from engaging in risk behaviours by increasing their self‐esteem are likely to be most effective and cost‐efficient if they are aimed at the family and school domains.