Pan‐Canadian estimates of the prevalence and risks associated with critical wandering among home care clients
Bibliographic record
Abstract
INTRODUCTION: We used clinical assessment records to provide pan-Canadian estimates of the prevalence and risks associated with recent (within the last 3 days) critical wandering among home care clients, with and without dementia. METHODS: The data source is interRAI Home Care (interRAI HC) assessments. The population was all long-stay home care clients assessed between 2004 and 2021 in seven Canadian provinces and territories (N = 1,598,191). We tested associations between wandering and cognition and dementia diagnoses using chi-square tests and logistic regression. RESULTS: Approximately 84% of the sample was over the age of 65. The overall rate of recent wandering was 3.0%. Dementia diagnosis was strongly associated with two to four times higher rates in the prevalence of recent critical wandering. DISCUSSION: InterRAI HC offers insights into the wandering risk of home care clients. This information should be used to manage risks in the community and could be shared with first responders. HIGHLIGHTS: In all the study regions combined, the rate of recent wandering is 3.0%. Dementia was associated with 18 times greater prevalence of recent critical wandering. Home care clients at risk of wandering have complex clinical profiles that pose important risks for their health and well-being. Collaboration and information sharing between search and rescue and health professions is essential for managing risks related to critical wandering.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 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".