An examination of adolescent engagement in risky behaviours: assessing predictors and intervening in schools
Notice bibliographique
Résumé
Adolescents may engage in risky behaviours as an attempt to manage negative affect and stress during a difficult developmental period, yet using such a maladaptive coping strategy comes at a cost.Given the important potential negative long-term consequences of engaging in risky behaviours, the high prevalence in adolescence, and the clinical implications, there is a need to delineate reliable vulnerability factors, as well as designing and implementing intervention programs.This dissertation is comprised of three manuscripts that collectively contribute to the literature by documenting: (1) personal and environmental factors associated with adolescent risky behaviour engagement; (2) the relationship between different executive function skills and adolescent broad-based engagement in risky behaviours; and (3) the effectiveness of an in-school intervention for adolescents designed to target emotional regulation skills related to risky behaviours.The current research examines adolescents' engagement in risky behaviours in an attempt to identify predictive factors and reduce such engagement through intervention.The three manuscripts are unique as they are the first exploratory examinations of general personal and environmental factors and various executive function skills in relation to broad-based engagement in risky behaviours.Further, the third manuscript is the first attempt to design, implement, and examine the potential benefits for reducing risky behaviours by intervening on a known vulnerability factor.The first manuscript reports on 160 adolescents (46% male and 54% female) between the ages of 12 and 18 (M = 15.17;SD = 1.22) and examined whether personal (i.e., intrapersonal, temperament, symptoms, and coping) and environmental (i.e., interpersonal and negative life events) factors are associated with risky behaviour engagement.Results of the first study indicate that personal factors account for a greater proportion of the variance in risky behaviour engagement as compared to environmental factors.However, while a number of personal factors (i.e., impulsiveness, low anxious symptoms, and poor self-concept clarity) predict adolescent engagement in risky behaviours, the strongest single predictor of risky behaviours is negative life events (i.e., an environmental factor).Furthermore, age-related comparisons indicate that older male adolescents are most likely to engage in risky behaviours.The second manuscript examined broad-based engagement in risky behaviours and the predictive power of different measures of executive function skills among 102 adolescents (48% male and 52% female) between the ages of 12 and 19 (M = 15.07,SD = 1.53).Results indicated that adolescents who exhibited low overall scores on observer-reported executive function were more likely than adolescents who exhibited high levels of executive function to engage in risky behaviours.However, there was no relationship between the performance-based measure of adolescent executive function and risky behaviours.The third manuscript included 41 adolescents (71% male and 29% female) between the ages of 12 and 17 (M = 14.2,SD = 1.4), and examined the efficacy of a pilot program (i.e., Cognitive Emotion Regulation Training Intended for Youth) to improve cognitive emotion regulation, and reduce subsequent engagement in risky behaviours.Participants made significant gains with regard to using adaptive cognitive emotion regulation strategies (e.g., positive reappraisal and refocusing on planning), yet no benefits were found for reducing maladaptive cognitive emotion regulation strategies or risky behaviours.Taken together, findings from these three studies provide insight into vulnerability factors and intervention for adolescent risky behaviour engagement.Also discussed are the implications of this research for school psychologists who work with adolescents who engage in such maladaptive behavioural patterns.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».