Transforming work place relationships through shared decision making
Bibliographic record
Abstract
AIM: Using Donabedian's Structure-Process-Outcomes (SPO) paradigm, this study explored the SPO linkages related to nurse-nurse leader shared decision making around workload issues, such as safe staffing assignments. BACKGROUND: Shared decision making represents nurses' control over practice, which is associated with positive nurse outcomes, such as job satisfaction. This study is based upon four project sites where nurse-led project teams addressed workload issues. METHODS: Participatory action research was used, with the authors acting as participant observers. Four sites were case ordered and analysed: least successful to most successful outcomes. Cross-case matrices were constructed to identify SPO linkages. Data included observation field notes, interviews and focus groups. RESULTS: Operations leaders with formal access to empowerment structures, such as information and resources, were the critical link to successful outcomes. Sites with conflict that blocked team-operations leader relationships were unable to engage in effective, sustainable decision making. CONCLUSIONS: Effective work relationships among teams consisting of staff and front-line leaders contributed to successful outcomes, but team-operations leader relationships made the biggest difference. IMPLICATIONS FOR NURSING MANAGEMENT: Formal access to power through leadership is critical for building and sustaining processes that promote and sustain nurses' control over practice.
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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 | 0.027 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".