Caring Ahead: Preparing for End-of-Life with Dementia
Bibliographic record
Abstract
Family/friend caregivers of persons with dementia often do not feel prepared for end-of-life, which contributes to high rates of complicated grief, depression and anxiety in bereavement. This mixed methods study used an exploratory sequential design to explore the core concepts and indicators of preparedness, develop and evaluate a multidimensional questionnaire aimed at measuring caregiver preparedness for end-of-life for persons with dementia. In Phase 1, a qualitative study with an interpretive descriptive design was used to explore the core concepts and indicators of preparedness with 16 bereaved family caregivers recruited from six long-term care homes located in Ontario, Canada. In Phase 2, a quantitative, cross-sectional Delphi-survey was conducted with 5 caregivers and 12 diverse professional experts to select preparedness indicators/items and develop the Caring Ahead questionnaire. Lastly in Phase 3, the self-report, paper format questionnaire was evaluated for evidence of validity and reliability using a quantitative cross-sectional design. In this final phase, the questionnaire was completed through the postal mail by 134 caregivers from over 50 long-term care homes/residential care facilities, primarily in Ontario, Canada. Evidence for internal structure and concurrent validity was generated along with reliability coefficients suggesting internal consistency and stability in a test-retest. Findings from this study contributed to the conceptualization and operationalization of preparedness and produced the new, multidimensional questionnaire titled Caring Ahead: Preparing for End-of-Life with Dementia with preliminary evidence for validity and reliability. This questionnaire aims to fill an existing gap expressed by researchers who aim to design and evaluate interventions promoting preparedness through a palliative approach. In addition, policy-makers should benefit from introduction of the Caring Ahead questionnaire as an outcome measure to monitor and evaluate the effectiveness of policies surrounding a palliative approach.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".