Electroconvulsive Therapy in Canada During the First Wave of COVID-19
Bibliographic record
Abstract
OBJECTIVES: The COVID-19 pandemic has disrupted the provision of essential and potentially life-saving procedural treatments such as electroconvulsive therapy (ECT). We surveyed ECT providers across Canada to understand how the first wave of the pandemic affected ECT delivery between mid-March 2020 and mid-May 2020. METHODS: The survey was administered to ECT team members and decision makers at 107 Canadian health care centers with a focus on 5 domains: operations, decision-making, hospital resources, ECT procedure, and patient impact. Responses were obtained from 72 institutions, and collected answers were used to derive representative responses reflecting the situation at each ECT center. For specific domains, responses were split into 2 databases representing the perspective of psychiatrists (n = 67 centers) and anesthesiologists (n = 24 centers). RESULTS: Provision of ECT decreased in 64% centers and was completely suspended in 27% of centers after the onset of the pandemic. Outpatient and maintenance ECT were more affected than inpatient and acute ECT. Programs reported a high level of collaboration between psychiatry and hospital leadership (59%) but a limited input from clinical ethicists (18%). Decisions were mostly made ad hoc leading to variability across institutions in adopted resource allocation, physical location of ECT delivery, and triaging frameworks. The majority of centers considered ECT to be aerosol-generating and incorporated changes to airway management. CONCLUSIONS: Electroconvulsive therapy services in Canada were markedly disrupted by the COVID-19 pandemic. The variability in decision-making across centers warrants the development of a rational approach toward offering ECT in pandemic contexts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".