Canine-Assisted Intervention Effects on the Well-Being of Health Science Graduate Students: A Randomized Controlled Trial
Bibliographic record
Abstract
IMPORTANCE: The mental health crisis among college graduate students requires cost-effective interventions to support the increasing number of students experiencing negative mental health symptoms. OBJECTIVE: To assess the effects of a canine-assisted intervention (CAI) on student well-being, including quality of life (QOL), stress, anxiety, occupational performance, and adjustment to the graduate college student role. DESIGN: Random assignment to a treatment or control group. SETTING: College campus. PARTICIPANTS: A total of 104 college student participants were randomly assigned to either the treatment (n = 53) or control (n = 51) condition. INTERVENTION: Treatment consisted of 35-min weekly sessions over 6 wk. OUTCOMES AND MEASURES: QOL, stress, anxiety, and occupational role. RESULTS: An analysis of covariance revealed that, compared with participants in the control condition, participants who interacted with therapy dogs had significantly higher self-reports of QOL (p < .001) and decreased anxiety scores (p < .045). Within-subject paired t tests confirmed significant stress reductions for participants in the treatment condition (p < .000). No significant differences in self-reports of occupational performance or in adjustment to the graduate college student role were found. CONCLUSIONS AND RELEVANCE: These findings add to the body of literature attesting to the efficacy of CAIs in supporting student well-being and optimizing learning conditions. Moreover, this study demonstrated that graduate students in a professional program responded favorably to spending time with therapy dogs. Implications for CAIs and university mental health programming are discussed. What This Article Adds: A CAI may be a valuable tool for students and young adults experiencing mental health challenges, such as stress, anxiety, and decreased QOL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".