Serving Families of Those Who Serve: An Exploration of the Psychosocial Experience and Psychosocial Support Needs of Defence and Public Safety Families in Canada
Bibliographic record
Abstract
Background. A considerable body of research demonstrates a significant link between family and work life; the connection between family and work life may be especially salient for the families of defence and public safety (DPS) personnel, who carry a significant risk of injury, illness and/or death through their occupational duties. When tragedy strikes and serving personnel are injured and/or killed in the line of duty, this can have significant impacts on the mental health and psychosocial wellbeing of families of serving personnel. In addition to these risks, DPS families are linked by shared adversity and challenges unique to this population, and often form a tight-knit community, meaning that tragedies ripple through the community. Though serving personnel may receive support by their organizations following tragedy, family members are often left without comparable supports. There remains little research on how to support families following tragedy. Purpose. To develop preliminary recommendations for psychosocial support for DPS families following tragedy, this thesis had two main purposes: (1) to identify and describe existing psychosocial support in disaster-impacted populations that may aid in the development of tailored psychosocial support programs for DPS families following tragedy; and (2) to explore the psychosocial experiences of DPS families following a tragedy within their occupational communities. Methods. A two-phase parallel, convergent multiple methods study was used. A scoping review was conducted to meet the first purpose, and an interpretative phenomenological analysis was used to meet the second. Findings. The integrated findings of this thesis were used to develop preliminary recommendations for psychosocial support to be provided by DPS organizations, including specific program components, incorporation of peer support, facilitation of social networks, a stepped care model, culturally competent care, and internet-based delivery to allow for flexibility. Conclusion. This thesis drew on existing literature in disaster mental health and the lived experiences of DPS family members to create a series of preliminary recommendations for psychosocial support following tragedy within the occupational communities. More research is needed within the Canadian context to best support DPS families following tragedy.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.020 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".