Dementia Care Partner Preparedness and Desire to Seek Long-Term Care at Hospital Discharge: Mediating Roles of Care Receiver Clinical Factors
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to explore the mediating roles of care receiver clinical factors on the relationship between care partner preparedness and care partner desire to seek long-term care admission for persons living with dementia at hospital discharge. METHODS: This study analyzed data from the Family centered Function-focused Care (Fam-FFC), which included 424 care receiver and care partner dyads. A multiple mediation model examined the indirect effects of care partner preparedness on the desire to seek long-term care through care receiver clinical factors (behavioral and psychological symptoms of dementia [BPSD], comorbidities, delirium severity, physical function, and cognition). RESULTS: Delirium severity and physical function partially mediated the relationship between care partner preparedness and care partner desire to seek long-term care admission (B = -.011; 95% CI = -.019, -.003, and B = -.013; 95% CI = -.027, -.001, respectively). CONCLUSIONS: Interventions should enhance care partner preparedness and address delirium severity and physical function in hospitalized persons with dementia to prevent unwanted nursing home placement at hospital discharge. CLINICAL IMPLICATIONS: Integrating care partner preparedness and care receiver clinical factors (delirium severity and physical function) into discharge planning may minimize care partner desire to seek long-term care.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".