Mental Health Hospitalizations in Canadian Children, Adolescents, and Young Adults Over the COVID-19 Pandemic
Notice bibliographique
Résumé
Importance: The COVID-19 pandemic resulted in multiple socially restrictive public health measures and reported negative mental health impacts in youths. Few studies have evaluated incidence rates by sex, region, and social determinants across an entire population. Objective: To estimate the incidence of hospitalizations for mental health conditions, stratified by sex, region, and social determinants, in children and adolescents (hereinafter referred to as youths) and young adults comparing the prepandemic and pandemic-prevalent periods. Design, Setting, and Participants: This Canadian population-based repeated ecological cross-sectional study used health administrative data, extending from April 1, 2016, to March 31, 2023. All youths and young adults from 6 to 20 years of age in each of the Canadian provinces and territories were included. Data were provided by the Canadian Institute for Health Information for all provinces except Quebec; the Institut National d'Excellence en Santé et en Services Sociaux provided aggregate data for Quebec. Exposures: The COVID-19-prevalent period, defined as April 1, 2020, to March 31, 2023. Main Outcomes and Measures: The main outcome measures were the prepandemic and COVID-19-prevalent incidence rates of hospitalizations for anxiety, mood disorders, eating disorders, schizophrenia or psychosis, personality disorders, substance-related disorders, and self-harm. Secondary measures included hospitalization differences by sex, age group, and deprivation as well as emergency department visits for the same mental health conditions. Results: Among Canadian youths and young adults during the study period, there were 218 101 hospitalizations for mental health conditions (ages 6 to 11 years: 5.8%, 12 to 17 years: 66.9%, and 18 to 20 years: 27.3%; 66.0% female). The rate of mental health hospitalizations decreased from 51.6 to 47.9 per 10 000 person-years between the prepandemic and COVID-19-prevalent years. However, the pandemic was associated with a rise in hospitalizations for anxiety (incidence rate ratio [IRR], 1.11; 95% CI, 1.08-1.14), personality disorders (IRR, 1.21; 95% CI, 1.16-1.25), suicide and self-harm (IRR, 1.10; 95% CI, 1.07-1.13), and eating disorders (IRR, 1.66; 95% CI, 1.60-1.73) in females and for eating disorders (IRR, 1.47; 95% CI, 1.31-1.67) in males. In both sexes, there was a decrease in hospitalizations for mood disorders (IRR, 0.84; 95% CI, 0.83-0.86), substance-related disorders (IRR, 0.83; 95% CI, 0.81-0.86), and other mental health disorders (IRR, 0.78; 95% CI, 0.76-0.79). Conclusions and Relevance: This cross-sectional study of Canadian youths and young adults found a rise in anxiety, personality disorders, and suicidality in females and a rise in eating disorders in both sexes in the COVID-19-prevalent period. These results suggest that in future pandemics, policymakers should support youths and young adults who are particularly vulnerable to deterioration in mental health conditions during public health restrictions, including eating disorders, anxiety, and suicidality.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».