An exploratory investigation of psychosocial effects of service dogs on veterans’ families from the perspective of family members
Bibliographic record
Abstract
Research on the psychosocial effects of service dogs (SDogs) on veterans’ family members is relatively limited and often centers veterans’ perspectives rather than those of the family. This exploratory study aimed to examine how Canadian veterans’ family members perceive veterans’ SDog and how they affect different psychosocial outcomes, specifically family quality of life and caregiving. A mixed-methods design utilizing an online questionnaire and follow-up interviews was employed. A non-probability sample of veterans’ family members (i.e., spouses, parents, siblings, friends) were recruited via convenience and snowball sampling methods. Participants (N = 35) completed an online questionnaire containing scales measuring their perceptions of and bond with the SDogs, their experience of caregiving, and overall family quality of life. Interviews with veterans’ spouses (N = 7) expanded on these topics. We analyzed quantitative data with descriptive and inferential statistics and qualitative data with content analysis. Overall, family members had positive perceptions of and felt bonded to the SDogs. Caregiver scores were relatively high suggesting risk of burnout. Interviewed participants reported no change in their caregiving duties, but they worried less about the veterans because of the SDog. Family quality of life scores were relatively high and SDogs were generally well-integrated into the family, but families seemed to need some support concerning their own emotional well-being. Findings from this study highlight some of the psycho-social benefits of SDogs for veterans’ families from their perspectives. Optimizing these benefits may require awareness of and managing drawbacks related to SDogs, acknowledging limits of the SDog role, and that SDogs’ role can overlap with that of family pets.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".