HCA PIECES <sup>TM</sup> Care Coach Program: Peer-to-peer approach to promote person-centred care in long-term care
Bibliographic record
Abstract
In Long-Term Care (LTC) settings, the potentially inappropriate use of antipsychotics for behavioural and psychological symptoms of dementia is a persistent issue, with high rates despite limited benefit and serious risk. Best practice is a non-pharmacological, person-centred approach to care, though this can be challenging in LTC settings. To help address this gap, we developed the PIECES TM HCA Care Coach Program and described its implementation and outcomes observed at 13 LTC homes. This program empowers healthcare aides with training, tools, and processes to practice the principles of person-centred care and provide peer mentorship to the care team. After one year, we found declining antipsychotics use (by 4.4%) and positive indicators of improved staff experience and improved resident quality of life. The Care Coach Program can be adapted and spread to a variety of LTC settings to help reduce potentially inappropriate antipsychotic use and better support people living with dementia.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".