MétaCan
Menu
Back to cohort
Record W3093329438 · doi:10.1177/0963662520963365

Knowledge, (mis-)conceptions, risk perception, and behavior change during pandemics: A scoping review of 149 studies

2020· review· en· W3093329438 on OpenAlex

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

VenuePublic Understanding of Science · 2020
Typereview
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsMaRSWestern UniversityUniversity of Toronto
Fundersnot available
KeywordsPandemicContext (archaeology)DiseaseMiddle East respiratory syndromeOutbreakRisk perceptionSocial distancePerceptionHygieneEnvironmental healthInfectious disease (medical specialty)PsychologyMedicineCoronavirus disease 2019 (COVID-19)GeographyVirology

Abstract

fetched live from OpenAlex

The severe acute respiratory syndrome-coronavirus-2 pandemic has spread rapidly and has a growing impact on individuals, communities, and healthcare systems worldwide. At the core of any pandemic response is the ability of authorities and other stakeholders to react appropriately by promoting hygiene and social distancing behaviors. Successfully reaching this goal requires both individual and collective efforts to drastically modify daily routines and activities. There is a need to clarify how knowledge and awareness of disease influence risk perception, and subsequent behavior in the context of pandemics and global outbreaks. We conducted a scoping review of 149 studies spanning different regions and populations to examine the relationships between knowledge, risk perceptions, and behavior change. We analyzed studies on five major pandemics or outbreaks in the twenty-first century: severe acute respiratory syndrome, influenza A/H1N1, Middle East respiratory syndrome, Ebola virus disease, and coronavirus disease 2019.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.628
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.005
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.471
GPT teacher head0.492
Teacher spread0.020 · 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