Unmet needs of family caregivers of hospitalized older adults preparing for discharge home
Bibliographic record
Abstract
Objectives To describe unmet needs of caregivers of hospitalized older adults during the transition from hospital back home, and identify subgroups with different needs. Methods Patients and family caregivers were recruited from an acute care hospital in Montreal, Canada. Measures included Instrumental Activities of Daily Living (IADL), Hospital Anxiety and Depression Scale (HADS), Zarit burden scale, and Family Inventory of Needs. Dimensions of unmet needs were explored with principal component analysis; regression tree models were used to identify subgroups with different unmet needs. Results A total of 146 patient-caregiver dyads were recruited. Three categories of caregiver unmet needs were identified: patient medical information; role clarity and support; and reassurance. Caregiver subgroups with highest unmet needs were those with high burden of care plus depressive symptoms ( n = 46) and those caring for patients with low IADL scores ( n = 10). Discussion Caregivers with high burden and depression are those with the greatest unmet needs during the care transition.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".