Caregivers' decision‐making for health service utilisation across the Alzheimer's disease trajectory
Bibliographic record
Abstract
Health and social care services can enhance the community experiences of people with Alzheimer's disease and their caregivers but making decisions about service use is complex. Using a grounded theory methodology, we explored service use decision-making in 40 spousal and adult children caregivers for people with Alzheimer's disease across the caregiving and disease trajectory. Participants' perception of their initial service interactions influenced their decision-making process and use of services. Difficulties navigating the healthcare system and finding available services also influenced decision-making. Caregivers make decisions to sustain care in the community that change throughout the caregiving and disease trajectory. Two key factors influence service use (a) the goals of caregiving and (b) the practicalities of accessing services. Both factors change across caregiving phases. By expanding our understanding of how caregivers make service use decisions, we can augment future practice to help caregivers access services that can better support them across the disease trajectory.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".