Covid-19 pandemic-related changes in teleworking, emotional exhaustion, and occupational burnout: a cross-sectional analysis of a cohort study
Notice bibliographique
Résumé
BACKGROUND: The COVID-19 pandemic prompted significant shifts to teleworking, raising questions about potential impacts on employee wellbeing. This study examined the association between self-reported changes to teleworking frequency (relative to before the pandemic) and two indicators of occupational burnout: emotional exhaustion and professionally diagnosed burnout. METHODS: Data were derived from two samples from a digital cohort study based in Geneva, Switzerland: one population-based, and one from a sample of workers who were likely mobilized in the early stages of the COVID-19 pandemic. Emotional exhaustion was measured using the Maslach Burnout Inventory (EE-MBI), while self-reported diagnosed burnout was assessed by asking participants if they had received a professional diagnosis of occupational burnout within the previous 12 months. Participants were categorized based on self-reported telework frequency changes: "no change," "increase," "decrease," "never telework," and "not possible to telework." Adjusted regression models for each of the study samples were used to estimate associations between telework changes and burnout outcomes, accounting for sociodemographic, household, and work-related factors. RESULTS: In the population-based sample of salaried employees (n = 1,332), the median EE-MBI score was 14 (interquartile range: 6-24), and 7.3% reported diagnosed burnout. Compared to those reporting no change in telework frequency (19% of the sample), those reporting a decrease (4%) and those reporting that teleworking was not possible (28.7%) had significantly higher emotional exhaustion scores (adjusted beta (aβ) 5.26 [95% confidence interval: 1.47, 9.04] and aβ 3.51 [0.44, 6.59], respectively) and additionally reported higher odds of diagnosed burnout (adjusted odds ratio (aOR) 10.59 [3.24, 34.57] and aOR 3.42 [1.22, 9.65], respectively). "Increased" (28.9%) and "never" (19.4%) telework statuses were not significantly associated with burnout outcomes. These trends were mirrored in the "mobilized-workers" sample, with the exception that those reporting that teleworking was not possible did not report significantly higher odds of diagnosed burnout compared to those reporting no change in telework frequency. CONCLUSIONS: Decreased teleworking frequency and not having the possibility of telework were associated with higher emotional exhaustion and diagnosed burnout. As organizations reconsider their telework policies in a post-pandemic era, they should consider the impact of such organizational changes on employee wellbeing.
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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 | 0,008 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,004 |
| 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) | 0,001 | 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 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 ».