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Enregistrement W2976013761 · doi:10.1136/vr.105146

Meaningful work and well‐being: a study of the positive side of veterinary work

2019· article· en· W2976013761 sur OpenAlex

Pourquoi ce travail est dans la base

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affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.
aboutLe titre ou le résumé porte un signal canadien du lexique géographique.

Notice bibliographique

RevueVeterinary Record · 2019
Typearticle
Langueen
DomaineHealth Professions
ThématiqueVeterinary Practice and Education Studies
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésBurnoutWell-beingMental healthWork (physics)MedicineDistressSituational ethicsJob satisfactionPsychologyNursingSocial psychologyClinical psychologyPsychiatry

Résumé

récupéré en direct d'OpenAlex

OBJECTIVES: Mental health is a growing concern in many healthcare professions, including veterinary medicine, as research suggests that veterinarians report higher levels of distress, burnout and suicidal ideation than other healthcare occupations and the general public. A recent literature review found that about twice as many articles published on veterinary wellness refer to the negative aspects of mental health (eg, stress and depression) compared with the positive aspects of well-being. Little attention has been devoted to examining the positive aspects of veterinarians' work, and few models have been developed to explain their well-being. This paper empirically assesses a veterinary model of work-derived well-being based on the theory of eudaimonia. Eudaimonic well-being reflects having fulfilling work that contributes to the greater good. Three core clusters of job characteristics are hypothesised relevant to veterinarian well-being that include: actualising self, helping others (animals or people) and a sense of belonging (to team or profession). In addition, meaningful work is proposed as the mechanism through which situational job characteristics may exert a positive influence on well-being. METHODS: Survey data from 376 veterinarians in clinical practice were analysed using path analysis. DISCUSSION: Meaningful work is important in understanding the well-being of veterinarians. Job characteristics (self-actualising work, helping animals and people and a sense of belonging) contribute to a sense of meaningful work, which in turn is related to eudaimonic well-being. Excessive job demands (work overload, financial demands and physical health risks) appear less relevant in understanding meaningful work but are clearly important in having negative consequences for veterinarians' well-being.While strategies that cultivate meaningful work may be effective in nurturing veterinarians' well being, several limitations of this study should be noted. First, due to the cross-sectional data, definitive statements about the causal ordering of variables cannot be made. Second, the data were derived from a single source such that monomethod bias may be an issue. Third, the data rely on self-report measures and the responses may be influenced by social desirability or response biases. Lastly, while the sample may be representative of the veterinarians throughout a large geographic area in Canada, it may not represent the work arrangements of veterinarians in other countries. CONCLUSIONS: The significance of these findings is that they may shift research attention from focusing on the harmful, demanding aspects of veterinary work to better understanding the deeply meaningful aspects that improve veterinarians' well-being. In addition, the results may stimulate consideration of strategies that move beyond individual-level interventions that focus on veterinarians adopting better coping strategies and becoming more resilient. This may lead to adopting organisational and occupational-level strategies that can involve promoting more positive and supportive workplace cultures and developing more professional resources for promoting wellness and meaning in the profession of veterinary medicine.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,039
Score d'incertitude au seuil0,692

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,169
Tête enseignante GPT0,433
Écart entre enseignants0,263 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle