Psychosocial Work Conditions and Mental Health: Examining Differences Across Mental Illness and Well-Being Outcomes
Notice bibliographique
Résumé
OBJECTIVES: Psychosocial work conditions are determinants of mental illness among worker populations. However, while the focus on negative aspects of mental health has generated important contributions to the development of workplace interventions, there is less evidence on the factors that support the positive aspects of mental well-being. This study aimed to examine the association between psychosocial work conditions and mental health outcomes among a representative sample of Canadian workers; and to assess whether the relationships are consistent across measures of mental illness versus mental well-being. METHODS: Population-based data were obtained from the cross-sectional 2012 Canadian Community Health Survey. Psychosocial work conditions were measured using an abbreviated version of the Job Content Questionnaire. For mental illness, we focused on major depressive episodes, generalized anxiety disorders, and bipolar disorders in the past 12 months, as measured using Composite International Diagnostic Interview criteria. Mental well-being was defined as having flourishing mental health, based on items from the Mental Health Continuum-Short Form. Regression models provided odds ratios (ORs) and fitted probabilities for the relationship between work conditions and mental health, adjusting for covariates. RESULTS: Higher levels of job control, social support, and job security were associated with being free of disorders (ORs ranging from 1.08 to 1.15) as well as having flourishing mental health (ORs ranging from 1.10 to 1.14). Lower physical effort was associated with decreased odds of having flourishing mental health (OR 0.89). Psychological demands were not associated with any of the mental health outcomes in the fully-adjusted models. The overall pattern of these relationships was consistent across the two outcome models, although there was evidence of heterogeneity on the absolute probability scale. Specifically, there was a relatively stronger relationship between job control/social support/physical demands and well-being outcomes, compared with disorder outcomes. CONCLUSIONS: Psychosocial work conditions were associated with both negative and positive measures of mental health. However, mental illness and mental well-being may represent complementary, yet distinct, aspects in relation to psychosocial work conditions. Interventions targeting the psychosocial work environment may serve to improve both of these dimensions, although the measurement and examination of specific dimensions may be required to obtain an integrated and comprehensive understanding of mental health in the workplace.
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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) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,004 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».