ORGANIZATIONAL CULTURE AND WORKFORCE CONTRIBUTIONS TO QUALITY IN LONG-TERM CARE
Bibliographic record
Abstract
There is increasing demand for quality residential care services in the face of constrained resources. In previous work, we developed an intervention comprising external facilitation of change cycles (‘TOrCCh’: Towards Organisational Culture Change), implemented by staff work teams. This study was undertaken to develop, and evaluate a toolkit and training resource to support sustainable culture change in residential aged care facilities (RACF), eventually with minimal external facilitation. Eight RACFs across two Australian States participated. A toolkit was drafted iteratively engaging participating sites and a reference group. Participating facilities undertook one change cycle with some external facilitation by research staff. The toolkit was then refined, and a second change cycle was undertaken using the toolkit, with minimal external facilitation. Qualitative data were collected from project sponsors and/or managers, work teams, and other care staff. Participants perceived benefits including staff development, increased communication, teamwork and leadership. The intervention was perceived to provide a generic approach which could be applied to solve agreed challenges in the work place (“Let’s TOrCCh it!”), generating useful outcomes. The role of a project sponsor, and organisational support, were perceived as important for sustainability. Challenges were the complexity and application of the toolkit resource and management of work place constraints. Final products for the TOrCCh Project comprised Workteam Members and Leaders Guides as well as additional tools and resources accessible from https://www.perkins.org.au/wacha/torcch/. Our findings demonstrate that staff teams can work together to achieve change when provided with a toolkit and process.
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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 | 0.023 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".