An evaluation of a person-centred care programme for long-term care facilities
Bibliographic record
Abstract
ABSTRACT Person-centred approaches in long-term care focus on providing holistic care to residents in order to improve quality of life, enhance resident wellbeing and autonomy, and mitigate behavioural and/or other symptoms. The results of research on person-centred approaches to care are mixed, with very few high-quality empirical studies examining resident outcomes specifically. The purpose of this investigation was to examine a person-centred care programme implemented in three Canadian long-term care facilities to determine its effect on resident outcomes, approach to care and maintenance of the programme three years after implementation. Using the Resident Assessment Instrument Minimum Data Set (RAI-MDS) scale scores and quality indicators, we retrospectively examined resident outcomes before, after and six months following the initiation of the programme using three additional facilities as control. We did not find any effects on resident outcomes. Focus group interviews with facility staff revealed no systematic differences between the programme and control facilities in their approach to care. All facilities supported aspects of a person-centred philosophy. Focus group interview data from the programme facilities indicated partial maintenance in two facilities and more complete maintenance in one facility. Although staff members supported the programme, implementation and maintenance proved difficult and effectiveness on resident outcomes was not indicated in this research. Additional controlled studies are needed.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".