Psychological distress during the COVID-19 pandemic in Canada
Notice bibliographique
Résumé
BACKGROUND: During major pandemics such as COVID-19, the fear of being infected, uncertain prognoses, and the imposition of restrictions may result in greater odds of emotional and psychological distress. Hence, the present study examines the predictors of psychological distress during the COVID-19 pandemic in Canada, and how they differ by gender. METHODS: Data of 2,756 adults aged 18 years and above from a cross-sectional online survey conducted between July and October 2020 was used for this study. A multivariable logistic regression analysis was carried out. The results were presented as adjusted odds ratio (aOR) with their respective confidence interval (CI). RESULTS: Lower odds of psychological distress were found among males compared to females and among individuals aged 45-64 or 65-84 years compared to those aged 18-44. The odds of psychological distress decreased with a rise in income, with individuals whose annual income was greater than or equal to $100,000 being less likely to experience psychological distress compared to those whose income was less than $20,000. The odds of psychological distress were higher among residents of Ontario compared to residents of Quebec. Similarly, the odds of psychological distress were higher among individuals who reported experiencing COVID-19 symptoms compared to those who did not report any COVID-19 symptoms. The disaggregated results by gender showed that age, province, and self-reported COVID-19 symptoms had significant associations with psychological distress in both males and females, but these effects were more pronounced among females compared to males. In addition, income was negatively associated with psychological distress for both males and females, with this effect being stronger among males. CONCLUSION: Five exposure variables (gender, age, province, experiencing COVID-19 symptoms, and total annual income in 2019) significantly predicted the likelihood of reporting psychological distress during the COVID-19 pandemic in Canada. Clearly, there is an imminent need to provide mental health support services to vulnerable groups. Additionally, interventions and policies aimed at combating psychological distress during pandemics such as COVID-19 should be gender specific.
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 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 ».