Evaluating the effectiveness of the abilities‐focused approach to morning care of people with dementia
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The abilities-focused approach demonstrated efficacy in promoting engagement of residents with dementia in care. The extent to which these resident outcomes can be replicated when the abilities-focused approach is implemented by nursing staff under the conditions of day-to-day practice was investigated in this study. The aim was to examine changes in resident outcomes before and after nursing staff' implementation of the abilities-focused approach and the contribution of this approach to resident outcomes. METHODS: A one-group pretest-post-test design was used. Observational data were obtained from 65 residents with dementia. The data pertained to the implementation of abilities-focused strategies during episodes of morning care and residents' level of agitation, participation in morning care and physical and psychosocial functioning. RESULTS: The number of abilities-focused strategies used during morning care increased at post-test. No clinically important changes in resident outcomes were observed over time. However, the implementation of some strategies was associated with residents' participation in care and functioning at post-test. The results provided preliminary evidence of the effectiveness of the abilities-focused approach in maintaining functioning in people with dementia. Additional research is needed to understand the mechanism underlying the effects of this person-centred approach to care on resident outcomes. IMPLICATIONS FOR PRACTICE: Implementation of the abilities-focused approach assists people with dementia to participate in morning care.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".