Evaluating the capabilities model of dementia care: a non-randomized controlled trial exploring resident quality of life and care staff attitudes and experiences
Bibliographic record
Abstract
BACKGROUND: This 12 month, Australian study sought to compare the Capabilities Model of Dementia Care (CMDC) with usual long-term care (LTC), in terms of (1) the effectiveness of the CMDC in assisting care staff to improve Quality Of Life (QOL) for older people with dementia; and (2) whether implementation of the CMDC improved staff attitudes towards, and experiences of working and caring for the person with dementia. METHODS: A single blind, non-randomized controlled trial design, involving CMDC intervention group (three facilities) and a comparison usual LTC practice control group (one facility), was conducted from August 2010 to September 2011. Eighty-one staff members and 48 family members of a person with dementia were recruited from these four LTC facilities. At baseline, 6 and 12 months, staff completed a modified Staff Experiences of Working with Demented Residents questionnaire (SEWDR), and families completed the Quality of Life - Alzheimer's Disease questionnaire (QOL-AD). RESULTS: LTC staff in the usual care group reported significantly lower SEWDR scores (i.e. less work satisfaction) than those in the CMDC intervention group at 12 months (p = 0.005). Similarly, family members in the comparison group reported significantly lower levels of perceived QOL for their relative with dementia (QOL-AD scores) than their counterparts in the CMDC intervention group at 12 months (p = 0.012). CONCLUSIONS: Although the study has a number of limitations the CMDC appears to be an effective model of dementia care - more so than usual LTC practice. The CMDC requires further evaluation with participants from a diverse range of LTC facilities and stages of cognitive impairment.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".