Improving Decision making On Location of Care with the frail Elderly and their caregivers (the DOLCE study): study protocol for a cluster randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: One of the toughest decisions faced by elderly people is whether to stay at home or move to a care facility. This study seeks to evaluate the impact of training interprofessional home-care teams in shared decision making combined with a decision aid on the proportion of elderly people who report being active in the decision-making process regarding whether to stay at home or move to a care facility. METHODS/DESIGN: We propose a multicenter cluster randomized trial conducted with home-care interprofessional teams in the Province of Quebec with 2 data collection phases: before and after the intervention. Units of randomization will be centers for primary healthcare and social services. We will enroll 16 of these and ask each to provide one home-care interprofessional team involved in decisions and care planning with eligible clients. Clients will be included if they i) are aged ≥65; ii) are receiving care from the participating home-care interprofessional team; iii) have faced the decision about staying at home or moving to a care facility in the past 3 to 6 months; iv) are able to read, understand and write French or English; and v) are able to give informed consent. If clients are unable to provide informed consent, their primary caregiver who was involved in the decision-making process will be eligible to participate. The intervention arm will receive training in shared decision making and use of a decision aid. The control arm will receive 'usual care'. The primary outcome of interest is the assumed role in the decision-making process as assessed in clients or caregivers with a modified version of the Control Preferences Scale. Multilevel modeling will be used to take the hierarchical structure of the data into account. The study has obtained full ethical approval. The trial will comply with CONSORT guidelines adapted for cluster randomized trials. DISCUSSION: Home care is a rapidly growing sector and this study will lay the foundations of a national strategy to ensure that IP home-care teams provide the highest quality of care for seriously ill elderly people and support for their families. TRIAL REGISTRATION: ClinicalTrials.gov NCT02244359 (registered 18 September 2014).
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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 | 0.045 | 0.044 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.062 | 0.008 |
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".