Caregivers’ Concerns About Assisted Living Residents’ Mental Health During the COVID-19 Pandemic: A Cross-Sectional Survey Study
Bibliographic record
Abstract
Family or friend caregivers' concerns about assisted living (AL) residents' mental health are reflective of poor resident and caregiver mental health. COVID-19-related visiting restrictions increased caregiver concerns, but research on these issues in AL is limited. Using web-based surveys with 673 caregivers of AL residents in Western Canada, we assessed the prevalence and correlates of moderate to severe caregiver concerns about residents' depressed mood, loneliness, and anxiety in the 3 months before and after the start of the COVID-19 pandemic. Caregiver concerns doubled after the start of the pandemic (resident depressed mood: 23%-50%, loneliness: 29%-62%, anxiety: 24%-47%). Generalized linear mixed models identified various modifiable risk factors for caregiver concerns (e.g., caregivers' perception that residents lacked access to counseling services or not feeling well informed about and involved in resident care). These modifiable factors can be targeted in efforts to prevent or mitigate caregiver concerns and resident mental health issues.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".