What contributes to a decline in cognitive performance among home care clients? Analysis of interRAI data from across Canada
Bibliographic record
Abstract
BACKGROUND: The current study examined potential risk factors for experiencing a decline on the interRAI Cognitive Performance Scale (CPS). METHODS: This was a retrospective cohort study using secondary data collected with the Resident Assessment Instrument for Home Care (RAI-HC) for all assessments completed in Canada between 2001 and 2020. Eligible home care clients included individuals 65+, with at least two assessments completed within 12 months, and who had a CPS score of zero at baseline (n = 146,187). A decline on the CPS was defined as any increase (i.e., worsening) on the CPS score between the two assessments. RESULTS: The mean age of the sample was 80.6 years (standard deviation = 7.7), 67.9% were female and 44.5% were widowed. At the time of the second assessment, 25.2% experienced a decline on their CPS score. In the final multivariate model, age, having a diagnosis of Alzheimer's dementia/other type of dementia, physical inactivity, and having a caregiver at risk of experiencing burden were the most significant predictors of experiencing the outcome. CONCLUSIONS: Roughly one-quarter of Canadian home care clients experienced a cognitive decline, over an average of seven months. Since there are some modifiable risk factors for this outcome, it is important to identify and flag these factors as early as possible. Early identification of modifiable risk factors allows clinicians to create care plans that can optimize the well-being of the client and their family.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 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".