THE IMPACT OF LEADERSHIP AND CULTURE ON SUSTAINABILITY OF A DEMENTIA TRAINING PROGRAM IN LONG-TERM CARE
Bibliographic record
Abstract
Leadership has been shown to have a positive influence on the sustainability of programs and innovations in long-term care (LTC) homes. This research focused on the relationship between leadership and the sustainability of a dementia-specific behavioural training program (Gentle Persuasive Approaches Program or GPA) for staff in LTC homes. Four focus groups with nursing aides (NAs) and 17 semi-structured interviews were completed with Directors of Care, Administrators, Registered Nurses, GPA Coaches, and a Clinical Nurse Leader were completed in a retrospective study in five rural LTC homes. Document reviews, direct observations, and 15 semi-structured interviews were completed with staff from all departments in two rural LTC homes prospectively over 15 months. Leadership was influential in the sustainability of the GPA program in the seven LTC homes. In low sustainability homes, GPA was not regarded as a priority by the formal leaders. They did not attend the training and it was viewed as “just another program” to complete. Staff were afraid of retribution by co-workers and leaders if they practiced GPA. In the medium sustainability homes, leaders verbally supported the GPA program and attended the training but the home’s culture was institutional. Leaders were seldom on the floor to role model or coach staff in using the GPA skills. Leaders in the high sustainability homes created a culture that was person-centred and where practice change was a top priority. Formal leaders in these homes displayed more advanced facilitation and leadership skills than leaders in the medium and low sustainability homes.
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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 | 0.005 | 0.018 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".