Impact of Managers’ Coaching Conversations on Staff Knowledge Use and Performance in Long‐Term Care Settings
Bibliographic record
Abstract
BACKGROUND: Extended lifespans and complex resident care needs have amplified resource demands on nursing homes. Nurse managers play an important role in staff job satisfaction, research use, and resident outcomes. Coaching skills, developed through leadership skill-building, have been shown to be of value in nursing. AIMS: To test a theoretical model of nursing home staff perceptions of their work context, their managers' use of coaching conversations, and their use of instrumental, conceptual and persuasive research. METHODS: Using a two-group crossover design, 33 managers employed in seven Canadian nursing homes were invited to attend a 2-day coaching development workshop. Survey data were collected from managers and staff at three time points; we analyzed staff data (n = 333), collected after managers had completed the workshop. We used structural equation modeling to test our theoretical model of contextual characteristics as causal variables, managers' characteristics, and coaching behaviors as mediating variables and staff use of research, job satisfaction, and burnout as outcome variables. RESULTS: = 58, df = 43, p = .06) indicating no significant differences between data and model-implied matrices. Resonant leadership (a relational approach to influencing change) had the strongest significant relationship with manager support, which in turn influenced frequency of coaching conversations. Coaching conversations had a positive, non-significant relationship with staff persuasive use of research, which in turn significantly increased instrumental research use. Importantly, coaching conversations were significantly, negatively related to job satisfaction. LINKING EVIDENCE TO ACTION: Our findings add to growing research exploring the role of context and leadership in influencing job satisfaction and use of research by healthcare practitioners. One-on-one coaching conversations may be difficult for staff not used to participating in such conversations. Resonant leadership, as expected, has a significant impact on manager support and job satisfaction among nursing home staff.
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 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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".