Patterns of long-term care utilization during the last five years of life among Swedish older adults with and without dementia
Bibliographic record
Abstract
AIMS: The aims of this study were to compare the patterns of long-term care (LTC) use (no care, homecare, residential care) among people with and without dementia aged 70+ in Sweden during their last five years of life and its association with sociodemographic factors (age, gender, education, cohabitation status) and time with a dementia diagnosis. METHODS: This retrospective cohort study included all people who died in November 2019 aged 70 years and older (n = 6294) derived from several national registers. A multinomial logistic regression was conducted to identify which sociodemographic factors predicted the patterns of LTC use. RESULTS: Results showed that the time with a dementia diagnosis and cohabitation status were important predictors that influence the patterns of LTC use during the last five years of life. Nearly three-quarters of people living with dementia (PlwD) used residential care during the last five years of life. PlwD were more likely to reside in residential care close to death. Women who lived alone, with or without dementia, used residential care to a higher degree compared to married or cohabiting women. CONCLUSIONS: Among people without a dementia diagnosis, as well as those who were newly diagnosed, it was common to have no LTC at all, or use LTC only for a brief period close to death. During the last five years of life, PlwD and those living alone more often entered LTC early and used residential care for a longer time compared to people without dementia and people living alone, respectively.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".