Dog Therapy for Staff in a Pediatric Emergency Department: A Quality Improvement Project
Bibliographic record
Abstract
AbstractBackground: Recent surveys of our pediatric emergency department staff showed a decrease in staff morale related to increased stress, indicating the need for intervention. Animal-assisted therapy has been shown to have multiple other positive effects in various populations including decreased stress and anxiety reduction. Our existing dog therapy program was unpredictable and inconsistent, resulting in limited staff involvement. Objectives: The purposes of this project were to determine whether a consistently offered dog therapy program in our pediatric emergency department would be utilized by staff and to elicit staff feedback on the program.Methods: A therapy dog was scheduled for one hour twice weekly for staff to visit when they were available. All staff in the ED were encouraged to attend these sessions.Results: Staff responses were collected via pre- and post-intervention questionnaires. The percentage of staff who were not able to visit the dogs pre-intervention was 33%, decreasing to 15% post-intervention. Prior to project initiation, 60% of staff indicated that dog therapy was not offered enough, compared to only 37% after project completion. Staff reported the program was a morale booster and added positivity to the unit. Barriers to participation and suggested improvements were identified.Conclusions: Staff were able to participate in dog therapy more often during the project than prior to project implementation, meeting the overall goal of providing more accessible dog therapy to staff. The program was well-received and has now become a standard offering for our emergency department staff.Keywords: animal assisted therapy, professional burnout, emergency departments, job-related stress, complementary therapy, compassion fatigue
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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 | 0.018 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".