Social norms of college students engaging in non-medical prescription drug use to get high: What’s sex got to do with it?
Notice bibliographique
Résumé
Background Relationships exist between perceived peer and own use of alcohol, cannabis, and tobacco, particularly when peers and participants are sex-matched. We investigated sex influences on social norms effects for college students’ non-medical prescription drug use (NMPDU). Methods: N = 1986 college students reported on their perceptions of male and female peers’ NMPDU frequency and their own past-month NMPDU. Results: Approximately 3% of students self-reported past month NMPDU, with no sex differences. In a linear mixed model, participants who engaged in NMPDU perceived significantly more frequent peer use. Female participants perceived more frequent peer NMPDU than did male participants, particularly when perceiving male peers’ NMPDU. Significant positive correlations were found between perceived peer NMPDU frequency and participants’ own NMPDU for all peer-participant sex combinations, with no evidence for stronger correlations with sex-matched pairs. Conclusions: While social norm interventions may be effective for college student NMPDU, sex-matching of these interventions is likely unnecessary.Emerging adults (18–25 years) show elevated rates of substance use relative to other age groups.1 Arnett JJ. Emerging adulthood: a theory of development from the late teens through the twenties. Am Psychol. 2000;55(5):469–480. doi:https://doi.org/10.1037/0003-066X.55.5.469.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar] Almost 80% of emerging adults have engaged in past-month alcohol use2 Simons-Morton B, Haynie D, Liu D, Chaurasia A, Li K, Hingson R. The effect of residence, school status, work status, and social influence on the prevalence of alcohol use among emerging adults. J Stud Alcohol Drugs. 2016;77(1):121–132.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar] and approximately 7% have a substance use disorder.3 Qadeer RA, Georgiades K, Boyle MH, Ferro MA. An epidemiological study of substance use disorders among emerging and young adults. Can J Psychiatry. 2019;64(5):313–322. doi:https://doi.org/10.1177/0706743718792189.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar] In the context of the current prescription drug crisis,4 Davison C, Perron M. (2013). First Do No Harm: Responding to Canada’s Prescription Drug Crisis. Ottawa: Canadian Centre on Substance Abuse. [Google Scholar] approximately 14.4% of emerging adults report past-year5 Miech R, Schulenberg J, Johnston L, Bachman J, O’Malley P, Patrick M. (2017). Monitoring the Future National Adolescent Drug Trends in 2017: Findings Released. Ann Arbor, MI: Institute for Social Research, The University of Michigan. Accessed March 30, 2018. [Google Scholar] and 4.8% report past-month non-medical prescription drug use (NMPDU).6 Substance Abuse and Mental Health Services Administration (SAMHSA). (2014). Results from the 2013 National Survey on Drug Use and Health: Summary of National Findings. https://www.samhsa.gov/data/sites/default/files/NSDUHresultsPDFWHTML2013/Web/NSDUHresults2013.pdf. Accessed April 20, 2020. [Google Scholar] NMPDU rates among college students are particularly concerning. Stimulants, opioids, and sedatives/tranquilizers are the most common types of prescriptions taken non-medically among college students, and their past-year prevalence rates of NMPDU for each type of prescription drug has been reported to be 19.6% for stimulants, 17.3% for opioids, and 11.8% for sedatives/tranquilizers.7 Silvestri MM, Knight H, Britt J, Correia CJ. Beyond risky alcohol use: screening non-medical use of prescription drugs at National Alcohol Screening Day. Addict Behav. 2015;43:25–27. doi:https://doi.org/10.1016/j.addbeh.2014.10.027.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar] NMPDU has been associated with numerous adverse consequences among college students such as physical reactions (eg, stomach pain or vomiting), functional or cognitive impairment (eg, academic problems, feeling detached from reality, difficulties speaking), relationship issues (eg, causing emotional harm to loved ones), financial repercussions, dependence, or overdose.8 Holloway KR, Bennett TH, Parry O, Gorden C. Characteristics and consequences of prescription drug misuse among university students in the United Kingdom. J Subst Use. 2014;19(1–2):156–163. doi:https://doi.org/10.3109/14659891.2013.765513.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar],9 Siste K, Nugraheni P, Christian H, Suryani E, Firdaus KK. Prescription drug misuse in adolescents and young adults: an emerging issue as a health problem. Curr Opin Psychiatry. 2019;32(4):320–327. doi:https://doi.org/10.1097/YCO.0000000000000520.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar] The concerning rates of NMPDU and the severity and breadth of associated harms among college students highlight that this phenomenon warrants further investigation.
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 | 0,001 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».