First-line managers' views of the long-term effects of clinical supervision: how does clinical supervision support and develop leadership in health care?
Bibliographic record
Abstract
There have recently been several organizational changes that have challenged nursing managers in the Finnish health care system. First-line managers need support in their work because of organizational changes and scarce economic resources. One of these supportive measures is clinical supervision. A group of first-line managers in a Finnish University hospital participated in a 2-year clinical supervision intervention in 1999-2000. The managers' perceptions of the clinical supervision were followed up twice during the intervention and 1 year after (2001). The aim of this study is to describe how the first-line managers saw the future effects of the clinical supervision intervention 1 year after its termination. At the beginning of the intervention, the number of participating nursing managers was 32. The number of respondents in this study 1 year (2001) after the clinical supervision was 11. Data was collected using empathy-based stories, which involved writing short essays. The respondents received orientation and a script to assist them in the writing of essays. The stories were analysed qualitatively by categorizing the responses by themes. The managers deemed that clinical supervision had, in the 3-year time frame, positive long-term effects on their leadership and communication skills, the desire for self-development, self-knowledge and coping. Managers believed that in the long run, clinical supervision would provide them with a broader perspective on work and would enhance the use of clinical supervision as a supportive measure among co-workers. First-line managers expect clinical supervision to have long-term positive effects on their work and coping. Empathy-based stories, as a method, were found suited to studies, which aim to obtaining future-oriented knowledge.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".