Facilitating Change Among Nursing Assistants in Long Term Care
Bibliographic record
Abstract
In this article, the authors consider the implementation of change in long term care organizations (LTCOs) and present their study describing the process by which new nursing assistants are informally integrated into LTCOs in Quebec, Canada. The study method included 23 in-depth interviews with nursing assistants in two long term care centres. The findings enabled the authors to describe the informal process by which new nursing assistants are integrated into LTCOs and the manner in which informal work strategies enhance the work of nursing care, thus enabling the nursing assistants to manage heavy workloads. The authors discuss whether this teamwork is a deterrent to change or a lever for change and address issues regarding the collective structure of nursing assistant teams. Implications for practice include a Five-Step Innovation Plan. In conclusion, the authors propose that organizational change among nursing assistants in a LTCO is best accomplished when the leaders consider the nursing assistants' strong sense of community to be a change engine rather than a change obstacle.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".