Schwartz Rounds for Staff in an Australian Tertiary Hospital: Protocol for a Pilot Uncontrolled Trial
Bibliographic record
Abstract
BACKGROUND: Schwartz Rounds are a unique, organization-wide interdisciplinary intervention aimed at enhancing staff well-being, compassionate care, teamwork, and organizational culture in health care settings. They provide a safe space wherein both clinical and nonclinical health staff can connect and share their experiences about the social and emotional aspects of health care. OBJECTIVE: Although Schwartz Rounds have been assessed and widely implemented in the United States and United Kingdom, they are yet to be formally evaluated in Australian health care settings. The purpose of this study is to evaluate the feasibility and impact of Schwartz Rounds on staff well-being, compassionate care, and organizational culture, in a tertiary metropolitan hospital in Brisbane, Australia. METHODS: This mixed methods repeated measures pilot study will recruit 24 participants in 2 groups from 2 departments, the intensive care unit and the gastroenterology department. Participants from each group will take part in 3 unit-based Schwartz Rounds. Primary outcomes will include the study and intervention feasibility measures, while secondary outcomes will include scores on the Maslach Burnout Inventory-Human Services Survey, the Schwartz Centre Compassionate Care Scale, and the Culture of Care Barometer. Primary and secondary outcomes will be collected at baseline, after the Rounds, and 3-month follow-up. Two focus groups will be held approximately 2 months after completion of the Schwartz Rounds. Descriptive statistics, paired t tests, chi-square tests, and analysis of variance will be used to compare quantitative data across time points and groups. Qualitative data from focus groups and free-text survey questions will be analyzed using an inductive thematic analysis approach. RESULTS: The study was approved by the Mater Hospital Human Research Ethics Committee (reference number: HREC/MML/71868) and recruitment commenced in July 2021; study completion is anticipated by May 2022. CONCLUSIONS: The study will contribute to the assessment of feasibility and preliminary efficacy of the Schwartz Rounds in a tertiary Australian hospital during the COVID-19 pandemic. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12621001473853; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=382769&isReview=true. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35083.
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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 | 0.063 | 0.045 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.066 | 0.013 |
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".