Impact of COVID-19 on the lives of people with severe mental illness—front-line community psychiatry workers observation from a provincial survey of assertive community treatment teams in Ontario, Canada
Bibliographic record
Abstract
Using an online survey distributed to members of the provincial organization that represents the 88 Assertive Community Treatment (ACT) and Flexible ACT teams in Ontario, Canada, this descriptive study relied on the unique vantage points and observations of the front-line community psychiatry workers who maintained contact with patients through outreach and telecommunication during the height of COVID-19. The patients who suffer from serious mental illness (SMI) were uniquely affected by COVID-19 due to the changes, reduction or shut down of many essential clinical and community support services. Thematic and quantitative analyses of the workers' observations highlighted 6 main areas of note, including significant social isolation and loneliness, clinical course deterioration and life disruption, increased hospital and ER use, police and legal contacts, and substance abuse and related deaths. There were also encouraging signs of positive adaptations in terms of independence and resilience. Reflections of these impacts and potential ameliorating approaches are further discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.003 |
| 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".