The Power of Stories: The Experiences and Well-Being of Mental Health Providers Working in Northern Saskatchewan Communities
Bibliographic record
Abstract
THE POWER OF STORIES: THE EXPERIENCES AND WELL-BEING OF MENTAL HEALTH PROVIDERS WORKING IN NORTHERN SASKATCHEWAN COMMUNITIES \nWanda Seidlikoski Yurach, PhD Candidate, Health Sciences, College of Medicine, University of Saskatchewan \n\nThis study explores the experiences of outsider mental health providers (MHPs) and the impact of delivering trauma-informed care/counselling in northern Saskatchewan First Nations communities (NSFNCs). With limited information and increased demand for mental health supports in NSFNCs it is important to tap into MHPs’ experiences and insights. An Approval Certificate (Beh ID 851) was received from the University of Saskatchewan’s Behavioural Research Ethics Board prior to commencing this project. \nAn embedded mixed methods research design was utilized guided by participatory narrative inquiry to support participants to be involved in all aspect of this project. A sample of ten female MHPs (Health Canada approved social workers) that have travelled into NSFNCs to work were interviewed in three phases. Narrative interviews indicated working in NSFNCs was both inspiring and tragic revealing these major themes: work complexity; lack of safety; awakening/transformation; power of relationships; reconciliation; impact on well-being; lessons learned; and needed supports. Although MHPs’ love their work, clients and communities, many have discontinued northern trauma work due to the isolation, job demands, and lack of safety and well-being supports. Well-being was examined qualitatively through participants’ stories and described as balance or overall wellness within life and work. Well-being was also quantitatively assessed using the Professional Quality of Life Scale-5 (Pro-QOL-5), a self-administered questionnaire measuring compassion satisfaction and compassion fatigue (burnout/secondary trauma). ProQOL-5 results found 60% of participants had high levels of compassion satisfaction; 70% experienced low levels of burn out; and, 70% experienced moderate levels of secondary trauma. MHPs collectively made the following recommendations to protect their well-being and improve the quality of their work environments: adopt a team approach; address safety concerns; improve management/MHP relationships; develop a trauma-informed training curriculum, specific to NSFNC work; improve MHP approval and hiring guidelines; and, expand access to professional supports including a ‘community of practice’. By understanding NSFNC trauma work and its impact, MHPs are better able, to make evidence-informed recommendations to support their well-being, reduce isolation, and improve the quality of their work environments. This in turn, could help attract and retain experienced MHPs, thereby improving the quality of services to facilitate healing for and with NSFNCs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".