Exploring the role of service dogs for Canadian military Veterans experiencing suicidality
Bibliographic record
Abstract
Abstract Despite ample anecdotal evidence, there are limited meaningful studies speaking to the important role of the human-animal bond (HAB) in reducing suicidality. However, research is increasingly showing the viability of service dogs (SDs) as a complementary approach for military Veterans suffering from post-traumatic stress disorder (PTSD) and substance use harms – two of the strongest indicators of suicidality across any population. An original, exploratory study completed in 2020 focused on how SDs supported Canadian Veterans living with PTSD and substance use concerns. From this work, a secondary analysis was then undertaken: 28 transcripts were examined through thematic analysis to explore the experiences of the Veterans who were identified as being at high risk for suicide to better understand how SDs may assist with their suicidality. Our methodological approach for the secondary analysis employed affective coding to discover how the social support system enabled by the SDs reduced experiences of loneliness and hopelessness, as well as symptoms of PTSD, depression, and substance use concerns that are commonly associated with suicidality. The SDs were reported by the Veterans as being a catalyst in reducing self-harm and suicidality, as the HAB provided a unique and necessary form of social support for Veterans that was distinct from what other human-human interactions could provide. While acknowledgement of how context specificity and the lived experience of each individual remains crucial for making sense of suicidality, the significant finding from this research has been the identification of the critical impact that SDs have in the lives of Veterans when it comes to preventing suicide. The SD has been explained as a bridge to improve Veterans’ overall quality of life and reduce markers commonly recognized as precursors to suicide – a finding that may be critical in helping reduce future suicide risk among military Veterans, and warrants further investigation.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".