Examining Supportive Strategies for the Director of Nursing Role in Ontario Long-Term Care Homes
Bibliographic record
Abstract
Aim: There are supportive strategies from the literature that may enhance the Director of Nursing (DON)’s ability to perform in their role and, in turn, may influence their intent to stay. The aims of this study were to 1) examine the perceived relevance of these supportive strategies, and 2) explore the contextual factors in Ontario long-term care (LTC) homes that influence their implementation from the viewpoints of LTC leaders. The seven supportive strategies included nursing home administrator (NHA) mentoring, a clear job description, shared leadership responsibility, competitive salary for role responsibilities, participating in continued education, maintaining professional networks, and orientation. Method and Analysis: A qualitative descriptive approach grounded in naturalistic inquiry was utilized. The Consolidated Framework for Implementation Research (CFIR) was applied to explore the contextual factors by assessing the barriers to and facilitators of implementation across the Outer Setting Domain, Inner Setting Domain, and Individuals Domain. Seventeen semi-structured interviews were completed with participants representing three levels of leadership in LTC homes. The sample included seven DONs, five NHAs, and five senior executive leaders. Results: The three strategies perceived to be relevant to all the participant groups were shared leadership responsibility, professional networking, and participation in continued education. The remaining four strategies – NHA mentoring, a clear job description, competitive salary for the role, and orientation to the role – did not hold equal relevance for all participating groups. When examining all supportive strategies, the most commonly occurring barriers to and facilitators of implementation within the outer setting domain were financing, policies and laws, and local attitudes. Within the inner setting domain, the most commonly occurring barriers to and facilitators of implementation included structural characteristics, culture, relative priority, relational connections, and available resources. Lastly, considering the individuals domain, barriers to and facilitators of implementation involved innovation recipients and innovation deliverers. Significance: The findings of this study lay the foundation for proposed actions that can be taken by leaders across home, sectoral, and Ministry levels, which will bolster implementation of the supportive strategies. This, in turn, may impact the retention of DONs and lessen the turnover in this critical nursing leadership role.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.017 |
| 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 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".