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Record W3047751316 · doi:10.36834/cmej.70493

Resident physicians’ mental health during COVID-19: Advocating for supports during and post pandemic

2020· article· en· W3047751316 on OpenAlexaffvenueabout
Emma Gregory

Bibliographic record

VenueCanadian Medical Education Journal · 2020
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMental healthStressorPandemicCoronavirus disease 2019 (COVID-19)MedicineHealth carePublic healthDistressNursingPsychiatryPsychologyFamily medicineDiseaseInfectious disease (medical specialty)Political scienceClinical psychology

Abstract

fetched live from OpenAlex

There is already considerable evidence of how this novel corona virus (COVID-19) has had a major impact on our mental health and wellbeing. We are reminded of the mental health consequences of previous infectious disease outbreaks, not only for the public, but for frontline healthcare workers. Yet the lived experiences of resident physicians are missing from this discussion despite them being essential to the COVID-19 response and continuing to provide care during this time. The author asserts that considering what is known about the mental health effects of frontline healthcare work during previous outbreaks, residents are at risk given their role as physicians. In addition to baseline systemic stressors that put residents at risk of mental distress, they also face COVID-19 related stressors that exacerbate the risk given their role as trainees too. The author acknowledges and welcomes several rapid responses to residents' developing mental health needs from medical leaders across Canadian hospitals, programs, and resident bodies. Ultimately, however, medical leaders need to advocate for and implement changes that will support residents' mental health now and in the long-term well after COVID-19 has left its mark.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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.

Opus teacher head0.035
GPT teacher head0.411
Teacher spread0.376 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations6
Published2020
Admission routes3
Has abstractyes

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