Beyond Spa Days and Self-Care: An Examination of Workplace Culture and Wellness in Child Protection Work
Notice bibliographique
Résumé
Social work practice in child welfare is widely acknowledged as a challenging field. Most social workers who choose to enter this field of practice do so with the knowledge that they will be exposed to difficult, at times traumatic, situations. They expect that the job will be stressful; that they will need to manage complex and challenging cases; and they will do so with few resources and often little public support. They also expect to be supported by their workplace in carrying out their mandated roles, however increasingly, a disconnect exists between those administer child welfare services and their understanding of front-line work (Herbert, 2007). Social workers’ wellbeing in child protection practice is directly affected by workplace culture; a subject that is often unexamined when addressing the high turnover of staff in the field. Instead, workers who leave child welfare practice – as well as though who stay while experiencing compassion fatigue or vicarious trauma - are viewed by administrators as being unsuitable for the work, a way of individualizing systemic issues (La Rose, 2009). This study sought to understand the ways that the culture of the workplace contributes to worker experiences of vicarious trauma, compassion fatigue and burnout. Survey research was conducted anonymously with child protection workers in Southern Ontario to understand the aspects of workplace culture that child welfare workers find helpful and supportive in managing the day-to-day of their work, as well as in addressing mental health in the workplace. From the seventy responses that were received, a number of themes emerged including Workplace Culture; Worker Well-being; Agency Support; Safety; Systemic Issues and Training. In this study, participants identified informal peer support and reflexive, supportive supervision as key areas that either sustained their practice or worsened their experiences. Workplace culture emerged as a significant factor in determining worker well-being and resiliency. Survey participants provided examples that illustrated clearly the ways in which neo-liberal policies and austerity measures have contributed to a workplace culture in which workers expressed feeling replaceable, devalued, and in precarious situations. Cutbacks to services and staffing, crushing workload and increasingly complex client situations contribute to the sense of being overwhelmed experienced by workers. Addressing experiences of compassion fatigue and vicarious trauma requires a paradigm shift from exclusively individual responsibility and towards an understanding of the broader systemic context and organizational responsibility (Antonopoulou, 2017; Mathieu, 2012; van Dernoot Lipsky, 2009). Organizational strategies to support worker wellbeing are shown to be significant factors in addressing and preventing compassion fatigue and vicarious trauma, ultimately preventing burnout and staff turnover.
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,006 | 0,005 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 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 ».