WELLBEING INDICATORS OF HEALTH CARE PROVIDERS AND THE INTENTION TO LEAVE THEIR POSITIONS: A CROSS-SECTIONAL STUDY FROM SASKATCHEWAN, CANADA, DURING THE COVID-19 PANDEMIC
Notice bibliographique
Résumé
Background: The coronavirus disease 2019 (Covid-19) pandemic adversely affected health care providers’ (HCPs) wellbeing. This study explored the association between HCPs’ wellbeing indicators and the intention to leave their current position in the western Canadian province of Saskatchewan during the Covid-19 pandemic. Methods: A cross-sectional study was conducted among registered nurses (RNs), physicians, and respiratory therapists (RTs) between December 2021 and April 2022 via SurveyMonkey®. The online survey included demographics, validated scales to measure job satisfaction, burnout, moral distress, risk of depression, and resilience and a question about the HCPs’ intentions to leave their current position within the next year. Logistic regression models explored the association between the intention to leave the current position and HCPs’ wellbeing indicators. Adjusted odds ratios (AORs) and 95% confidence intervals (95%CI) were reported. Result: Of 1,497 participants, 38.6% considered leaving their positions within the next year. HCPs reported high levels of resilience and moral distress. However, HCPs were neither satisfied nor dissatisfied with their jobs. Additionally, 60.5% were at risk of depression, and 71.7% reported one or more symptoms of burnout. Controlling by gender, age group, having children, redeployment, burnout, and resilience levels, the odds of considering leaving the position decreased by 0.55 (95%CI 0.43-0.70) per unit of increase in the level of job satisfaction. HCPs experiencing high moral distress were more likely to leave their positions (AOR=3.97, 95%CI 2.93-5.39). RNs were more likely to consider leaving the position than physicians (AOR=1.68, 95%CI 1.13-2.50). Age interacted with gender, and burnout interacted with having children. Older women were more likely to leave the position than younger women. Although younger men were more likely to leave the position than men in the oldest age group. Moreover, the difference between those without and with children in the probability of considering leaving the position was wider among HCPs with no symptoms of burnout in comparison to the gap observed in the groups of HCPs with burnout. Conclusion: The level of job satisfaction is an indicator of HCPs’ retention. Distress levels and being RNs could predict HCPs’ intention to leave their positions. These findings could inform health care policies that enhance HCPs’ wellbeing and support initiatives that prevent high turnover rates during and after the pandemic.
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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) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».