Mental and physical health and well-being of Canadian employees who were working from home during the COVID-19 pandemic
Notice bibliographique
Résumé
BACKGROUND: The COVID-19 pandemic has drastically changed various aspects of our lives, including how we work. Since the start of the pandemic, numerous organizations in Canada have mandated their employees to work from home (WFH) on a full-time basis. The rapid rise in the number of remote workers and the possibility for WFH continuing in the future signifies the importance of understanding the health and well-being of employees working from home over the course of the pandemic in Canada. We present the findings of two surveys (initial and 6-month follow-up) to examine the health and well-being of WFH employees during the COVID-19 pandemic in Canada. We analyzed the changes in mental and physical health and well-being of employees who were working from home between two time points during the pandemic. METHODS: Initial survey was completed between October 2020 and December 2020 (n = 1617); follow-up survey was completed between May 2021 and June 2021 (n = 382). We calculated the frequencies for survey questions involving demographics, WFH preferences, workstation setup training, employment situation, provision of hardware technologies, provision and usage of software technologies, and organization's return to work plan. We conducted Wilcoxon signed-rank tests to analyze the within-individual changes in mental and physical health and well-being of the 382 respondents who completed both the initial and follow-up surveys. RESULTS: Our analyses showed significant changes in various aspects of employee mental and physical health and well-being. Burnout, stress, general mental health, and job insecurity levels significantly decreased between the two time periods. Work-related sedentary behaviour reduced over time; however, the average proportion of time spent sitting during work hours was more than 80% in both surveys. Employees received more help and feedback from their colleagues and experienced a better sense of community with their co-workers over time. CONCLUSION: The findings can inform workers and organizations on the changes in mental and physical health and well-being of employees working from home during the pandemic. By understanding the changes in worker health and well-being, employers can develop effective strategies and implement policies that help protect employees' health and well-being.
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 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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,003 | 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 ».