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Record W6886100475 · doi:10.14288/1.0400139

Impact of COVID-19 on Canadian medical oncologists and cancer care : Canadian Association of Medical Oncologists survey report

2021· article· en· W6886100475 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Collections · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsnot available
Fundersnot available
KeywordsFeelingAnxietyPandemicCancerPersonal protective equipmentDepression (economics)AccrualMEDLINEMedical care

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score0.231

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.008
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.109
GPT teacher head0.491
Teacher spread0.381 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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