Unmet care needs are common among community-dwelling older people with memory problems in Finland
Bibliographic record
Abstract
Aims: Ageing in place has become a policy priority. Consequently, residential care has been reduced, and more older people with multiple care needs reside at home with the help of informal care and home care services. An increasing share of these people has memory disorders. We examined the extent to which memory problems, in addition to other individual characteristics, are associated with unmet care needs among community-dwelling older people. Methods: The study employed cross-sectional survey data from community-dwelling people aged 75+ collected in 2010 and 2015, analysed using binary logistic regression analysis. The study population consisted of people who had long-term illnesses or disabilities that limited their everyday activities ( N = 1928). Nine per cent reported substantial memory problems. Of these, 35.7% had a proxy respondent. Results: People with memory problems have more care needs than those with other types of disability or illness. They receive more care but still have more unmet needs than others. About a quarter of people with memory problems reported that they did not receive enough help. This result did not change significantly when the proxy responses were excluded. Even a combination of informal and formal home care was insufficient to meet their needs. Conclusions: Insufficient care for people with memory problems implies a serious demand for further development of home care services. The care needs of this population are often complex. Unmet needs represent a serious risk to the well-being of people with memory disorders, and may also create an extensive burden on their informal caregivers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".