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Record W1990042623 · doi:10.1080/17441690802063304

Coping and health behaviours in times of global health crises: Lessons from SARS and West Nile

2009· article· en· W1990042623 on OpenAlexafffund
Eli Puterman, Anita DeLongis, Dayna Lee‐Baggley, Esther R. Greenglass

Bibliographic record

VenueGlobal Public Health · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsYork UniversityUniversity of British Columbia
FundersMichael Smith Health Research BC
KeywordsWishful thinkingCoping (psychology)MedicinePsychologyEnvironmental healthClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

We examined perceived threats of Severe Acute Respiratory Syndrome and West Nile Virus using an Internet-based questionnaire. Higher levels of perceived threats of diseases were associated with increases in a variety of ways of coping, including empathic responding and wishful thinking. In turn, we examined how coping with the perceived health threat was related to two specific health related behaviours: taking recommended precautions, and avoiding people in an attempt to avoid disease. The findings from linear regression indicated that empathic responding, in response to the threat of a virulent agent, was related to taking recommended and effective health precautions. On the other hand, wishful thinking was associated with those behaviours that may potentially lead to economic hardship in afflicted areas, such as avoiding people perceived to be at risk for an infectious agent. Implications for health promotion are discussed.

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)0.006
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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.111
GPT teacher head0.377
Teacher spread0.265 · 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

Citations62
Published2009
Admission routes2
Has abstractyes

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