Associations over the COVID-19 pandemic period and the mental health and substance use of youth not in employment, education or training in Ontario, Canada: a longitudinal, cohort study
Notice bibliographique
Résumé
BACKGROUND: The economic shutdown and school closures associated with the COVID-19 pandemic have negatively influenced many young people's educational and training opportunities, leading to an increase in youth not in education, employment, or training (NEET) globally and in Canada. NEET youth have a greater vulnerability to mental health and substance use problems, compared to their counterparts who are in school and/or employed. There is limited evidence on the association between COVID-19 and NEET youth. The objectives of this exploratory study included investigating: longitudinal associations between the COVID-19 pandemic and the mental health and substance use (MHSU) of NEET youth; and MHSU among subgroups of NEET and non-NEET youth. METHODS: 618 youth (14-28 years old) participated in this longitudinal, cohort study. Youth were recruited from four pre-existing studies at the Centre for Addiction and Mental Health. Data on MHSU were collected across 11 time points during the COVID-19 pandemic (April 2020-August 2022). MHSU were measured using the CoRonavIruS Health Impact Survey Youth Self-Report, the Global Appraisal of Individual Needs Short Screener, and the PTSD Checklist for DSM-5. Linear Mixed Models and Generalized Estimating Equations were used to analyze associations of NEET status and time on mental health and substance use. Exploratory analyses were conducted to investigate interactions between sociodemographic characteristics and NEET status and time. RESULTS: At baseline, NEET youth were significantly more likely to screen positive for an internalizing disorder compared to non-NEET youth (OR = 1.92; 95%CI=[1.26-2.91] p = 0.002). No significant differences were found between youth with, and without, NEET in MHSU symptoms across the study time frame. Youth who had significantly higher odds of screening positive for an internalizing disorder included younger youth (OR = 1.06, 95%CI=[1.00-1.11]); youth who identify as Trans, non-binary or gender diverse (OR = 8.33, 95%CI=[4.17-16.17]); and those living in urban areas (OR = 1.35, 95%CI=[1.03-1.76]), compared to their counterparts. Youth who identify as White had significantly higher odds of screening positive for substance use problems (OR = 2.38, 95%CI=[1.72-3.23]) compared to racialized youth. CONCLUSIONS: Our findings indicate that sociodemographic factors such as age, gender identity, ethnicity and area of residence impacted youth MHSU symptoms over the course of the study and during the pandemic. Overall, NEET status was not consistently associated with MHSU symptoms over and above these factors. The study contributes to evidence on MHSU symptoms of NEET youth.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».