Impact of COVID-19 on Canadian Medical Oncologists and Cancer Care: Canadian Association of Medical Oncologists Survey Report
Bibliographic record
Abstract
Background: The covid-19 pandemic has presented unprecedented professional and personal challenges for the oncology community. Under the auspices of the Canadian Association of Medical Oncologists, we conducted an online national survey to better understand the impact of the pandemic on the medical oncology community in Canada. Methods: An English-language multiple-choice survey, including questions about demographics, covid-19 risk, use of personal protective equipment (ppe), personal challenges, and chemotherapy management was distributed to Canadian medical oncologists. The survey was open from 30 March to 4 April 2020, and attracted 159 responses. Results: More than 70% of medical oncologists expressed moderate-to-extreme concern about personally contracting covid-19 and about family members or patients (or both) contracting covid-19 from them. Despite that high level of concern, considerable variability in the use of ppe in direct cancer care was reported at the time of this survey, with 33% of respondents indicating no routine ppe use at their institutions and 69% indicating uncertainty about access to adequate ppe. Of the respondents, 54% were experiencing feelings of nervousness or anxiety on most days, and 52% were having feelings of depression or hopelessness on at least some days. Concern about aging parents or family and individual wellness represented the top personal challenges identified. The management of cancer patients has been affected, with adoption of telemedicine reported by 82% of respondents, and cessation of clinical trial accrual reported by 54%. The 3 factors deemed most important for treatment decision-making were■ cancer prognosis and anticipated benefit from treatment,■ risk of treatment toxicity during scarce health care access, and■ patient risk of contracting covid-19. Conclusions: This report describes the results of the first national survey assessing the impact of the covid-19 on Canadian medical oncologists and how they deliver systemic anticancer therapies. We hope that these data will provide a framework to address the challenges identified.
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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 | 0.003 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".