An Integrative Review of the Structures and Processes Related to Nurse Supervisory Performance in Long‐Term Care
Bibliographic record
Abstract
BACKGROUND: Understanding the structures and processes related to the supervisor performance of regulated nurses (registered nurses [RN] and registered practical nurses [RPN]) is critical in order to discern how administrators of long-term care (LTC) homes can facilitate and better support nurses given their important contribution to nurse assistants' job satisfaction and resident outcomes. AIMS: The aim of this integrative review is to identify the structures and processes related to supervisory performance of regulated nurses in LTC. METHODS: An electronic search of six databases for studies published in English between 2000 and September 2015 was conducted by a librarian. The inclusion criteria were studies focused on RN or RPN supervisory performance in LTC, which included a structure or process related to supervisory performance of the nurse. Screening, quality assessment using the Mixed Methods Assessment Tool, and data extraction for the included studies were conducted independently by two reviewers. RESULTS: A total of 22 studies were included in the review. Six nurse structures (e.g., nurses' "perceptions of their supervisory role and authority" as well as their "personal qualities"), and eight organizational structures (e.g., "organizational support (culture) for supervisory and management practices" and "staffing levels") were identified. Six processes of effective supervisory performance were identified, such as "being flexible, understanding, considerate listeners and encourage staff input" as well as "respect, value, recognize, acknowledge and motivate" nursing assistants they supervise. LINKING EVIDENCE TO ACTION: The results highlight the nuanced and complex nature of nurses' supervisory performance and the multifaceted approach required to support effective nurse supervisors in LTC. Future research should examine how resident-related structures, as well as other moderators and mediators, may influence supervisory performance. Developing detailed models of effective supervision can inform future interventions targeting modifiable processes related to supervisory performance to thereby change practice and optimize supervisory performance in LTC.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".