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Record W4311888120 · doi:10.1136/jme-2022-108369

Ethical uncertainty and COVID-19: exploring the lived experiences of senior physicians at a major medical centre

2022· article· en· W4311888120 on OpenAlexaff
Ruaim Muaygil, Raniah N. Aldekhyyel, Lemmese Alwatban, Lyan Almana, Rana F Almana, Mazin Barry

Bibliographic record

VenueJournal of Medical Ethics · 2022
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMoral obligationMoral dilemmaAction (physics)PandemicPsychological interventionCoronavirus disease 2019 (COVID-19)Health careObligationQualitative researchPublic relationsPsychologyEngineering ethicsMedicineNursingMedical educationSociologyPolitical scienceSocial psychologyLawSocial science

Abstract

fetched live from OpenAlex

Given the wide-reaching and detrimental impact of COVID-19, its strain on healthcare resources, and the urgent need for-sometimes forced-public health interventions, thorough examination of the ethical issues brought to light by the pandemic is especially warranted. This paper aims to identify some of the complex moral dilemmas faced by senior physicians at a major medical centre in Saudi Arabia, in an effort to gain a better understanding of how they navigated ethical uncertainty during a time of crisis. This qualitative study uses a semistructured interview approach and reports the findings of 16 interviews. The study finds that participants were motivated by a profession-based moral obligation to provide care during the toughest and most uncertain times of the pandemic. Although participants described significant moral dilemmas during their practice, very few identified challenges as ethical in nature, and in turn, none sought formal ethics support. Rather, participants took on the burden of resolving ethical challenges themselves-whenever possible-rationalising oft fraught decisions by likening their experiences to wartime action or by minimising attention to the moral. In capturing these accounts, this paper ultimately contemplates what moral lessons can, and must be, learnt from this experience.

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)0.021
metaresearch head score (Gemma)0.025
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.009
Insufficient payload (model declined to judge)0.0060.000

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 head0.172
GPT teacher head0.473
Teacher spread0.301 · 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 designQualitative
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

Citations4
Published2022
Admission routes1
Has abstractyes

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