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Record W2131841402 · doi:10.1177/070674370404900609

Psychological Effects of the SARS Outbreak in Hong Kong on High-Risk Health Care Workers

2004· article· en· W2131841402 on OpenAlexvenueno aff
Siew E. Chua, Vinci Cheung, Charlton Cheung, Gráinne McAlonan, Josephine WS Wong, Erik P.T. Cheung, Marco T. Y. Chan, Michael MC Wong, Siu Wa Tang, Khai M Choy, Meng K Wong, Chung‐Ming Chu, Kenneth WT Tsang

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2004
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
FundersQueen Mary University of London
KeywordsMedicineInfection controlHealth careOutbreakPopulationPsychological stressPsychiatryGerontologyEnvironmental healthClinical psychologyIntensive care medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To quantify stress and the psychological impact of severe acute respiratory syndrome (SARS) on high-risk health care workers (HCWs). METHOD: We evaluated 271 HCWs from SARS units and 342 healthy control subjects, using the Perceived Stress Scale (PSS) to assess stress levels and a structured list of putative psychological effects of SARS to assess its psychological effects. Healthy control subjects were balanced for age, sex, education, parenthood, living circumstances, and lack of health care experience. RESULTS: Stress levels were raised in both groups (PSS = 18) but were not relatively increased in the HCWs. HCWs reported significantly more positive (94%, n = 256) and more negative psychological effects (89%, n = 241) from SARS than did control subjects. HCWs declared confidence in infection-control measures. CONCLUSIONS: In HCWs, adaptive responses to stress and the positive effects of infection control training may be protective in future outbreaks. Elevated stress in the population may be an important indicator of future psychiatric morbidity.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.020
GPT teacher head0.344
Teacher spread0.324 · 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

Citations484
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of PsychiatrySame topicCOVID-19 and Mental HealthFrench-language works237,207