Position Statement for Mental Health Care in Long-Term Care During COVID-19
Bibliographic record
Abstract
COVID-19 has disproportionately impacted older adults in long-term care (LTC) facilities in Canada. There are opportunities to learn from this crisis and to improve systems of care in order to ensure that older adults in LTC enjoy their right to the highest attainable standard of health. Measures are needed to ensure the mental health of older adults in LTC during COVID-19. The Canadian Academy of Geriatric Psychiatry (CAGP) and Canadian Coalition for Seniors' Mental Health (CCSMH) have developed the following position statements to address the mental health needs of older adults in LTC facilities, their family members, and LTC staff. We outlined eight key considerations related to mental health care in LTC during COVID-19 to optimize the mental health of this vulnerable population during the pandemic.
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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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.069 | 0.057 |
| Insufficient payload (model declined to judge) | 0.017 | 0.013 |
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".