A mixed-methods examination of an on-campus canine-assisted intervention by gender: Women, men, and gender-diverse individuals’ self-reports of stress-reduction and well-being
Bibliographic record
Abstract
Abstract On-campus canine-assisted interventions (CAIs) provide opportunities for college students to interact with therapy dog-handler teams and are considered a low-cost and low-barrier way for students to reduce their stress and bolster their well-being. Across studies, we see participant samples comprised predominantly of women participants. The aim of this study was to assess the effects of a 20-min CAI on the well-being of women ( n = 80), men ( n = 54), and gender-diverse ( n = 28; i.e., non-binary, genderfluid, and two-spirit) participants. Across all gender conditions, significant pre-to-post increases in well-being (i.e., campus connectedness, happiness, positive affect, or optimism) and decreases in ill-being (i.e., homesickness, loneliness, negative affect, anxiety, or stress) were found. Controlling for pre-test scores, there was no significant effect of gender on any of the well-being or ill-being. Findings corroborate previous research attesting to the efficacy of CAIs in enhancing the social and emotional well-being of students and suggest that CAIs are equally effective across participants of varied genders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".