Development of a “Changes Toolkit” for Rural Older Palliative Patients and Their Family Caregivers
Bibliographic record
Abstract
A Changes Toolkit was developed to help rural older palliative care patients and their caregivers deal with multiple concurrent transitions that cause disruption in their lives. The purpose of this article is to describe the development of the Changes Toolkit to support rural palliative patients and their families with transitions using the Medical Research Council (UK) guidelines for complex intervention development The first step was to develop a theoretical understanding of the likely process of change, by drawing on existing evidence and theory, supplemented by new primary research. The intervention was then developed based on this first step by multidisciplinary experts (step 2), followed by conceptual mapping of the critical inputs of the intervention with the theoretical understanding (step 3). Then an assessment of the feasibility of the intervention was completed (step 4). The preliminary findings of a feasibility pilot study of this toolkit were positive with the majority of participants describing it as acceptable, easy to use, and having potential to help deal with transitions.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".