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Prevention of occupational stress in health-care workers during COVID-19 pandemic

2020· article· en· W3089533017 on OpenAlex
Muhammad Irfan, Farooq Naeem, Muhammad Iqbal Afridi, Afzal Javed

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIndian Journal of Psychiatry · 2020
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsHealth carePandemicMental healthAnxietyPsychological resilienceOccupational stressSomatizationIsolation (microbiology)PsychologyMedicineNursingCoronavirus disease 2019 (COVID-19)PsychiatryClinical psychologyPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

In a humanitarian crisis, healthcare workers are on the frontline in providing their services. Despite being crisis management personnel, healthcare workers may get exposed to occupational stress due to unprecedented circumstances, challenges in delivery of high-quality care, lack of resources, and most importantly for being at high risk to suffer from the impact of the situation itself. Therefore, it is imperative to maintain the mental health of healthcare workers on a regular basis and more so during a pandemic like COVID-19. For addressing the occupational stress in healthcare workers, a Cognitive Behaviour Therapy (CBT) based intervention is suggested, also supported by a Cochrane review, which can build/ improve/ enhance resilience, needed to shield individuals against the development of psychopathology, at the public health level in humanitarian crises. In addition to developing resilience, which will be helpful in combating anxiety, depression, somatization, and incapacitation, CBT will also help in dealing with the social isolation which has been part and parcel of COVID-19 and similar pandemic situations.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.011
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

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

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 head0.077
GPT teacher head0.439
Teacher spread0.362 · 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