The impact of the mySupport advance care planning intervention on family caregivers’ perceptions of decision-making and care for nursing home residents with dementia: pretest–posttest study in six countries
Bibliographic record
Abstract
BACKGROUND: the mySupport advance care planning intervention was originally developed and evaluated in Northern Ireland (UK). Family caregivers of nursing home residents with dementia received an educational booklet and a family care conference with a trained facilitator to discuss their relative's future care. OBJECTIVES: to investigate whether upscaling the intervention adapted to local context and complemented by a question prompt list impacts family caregivers' uncertainty in decision-making and their satisfaction with care across six countries. Second, to investigate whether mySupport affects residents' hospitalisations and documented advance decisions. DESIGN: a pretest-posttest design. SETTING: in Canada, the Czech Republic, Ireland, Italy, the Netherlands and the UK, two nursing homes participated. PARTICIPANTS: in total, 88 family caregivers completed baseline, intervention and follow-up assessments. METHODS: family caregivers' scores on the Decisional Conflict Scale and Family Perceptions of Care Scale before and after the intervention were compared with linear mixed models. The number of documented advance decisions and residents' hospitalisations was obtained via chart review or reported by nursing home staff and compared between baseline and follow-up with McNemar tests. RESULTS: family caregivers reported less decision-making uncertainty (-9.6, 95% confidence interval: -13.3, -6.0, P < 0.001) and more positive perceptions of care (+11.4, 95% confidence interval: 7.8, 15.0; P < 0.001) after the intervention. The number of advance decisions to refuse treatment was significantly higher after the intervention (21 vs 16); the number of other advance decisions or hospitalisations was unchanged. CONCLUSIONS: the mySupport intervention may be impactful in countries beyond the original setting.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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) | 0.002 | 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".