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Record W4308045438 · doi:10.17269/s41997-022-00702-z

Public health communication in Canada during the COVID-19 pandemic

2022· article· en· W4308045438 on OpenAlexafffundvenueabout
Maya Lowe, Shawn Harmon, Ksenia Kholina, Rachel Parker, Janice Graham

Bibliographic record

VenueCanadian Journal of Public Health · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health Research
KeywordsPublic healthTransparency (behavior)Health communicationPublic relationsThematic analysisCLARITYPandemicPublic engagementPolitical scienceQualitative researchPsychologyMedicineSociologyCoronavirus disease 2019 (COVID-19)NursingInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

OBJECTIVES: Communication is central to the implementation and effectiveness of public health measures. Informed by theories of good governance, COVID-19 pandemic public health messaging in 3 Canadian provinces is assessed for its potential to encourage or undermine public trust and adherence. METHODS: This study employed a mixed-methods constant comparative approach to triangulate epidemiological COVID-19 data and qualitative data from news releases, press briefings, and key informant interviews. Communications were analyzed from January 2020 to October 2021 in Nova Scotia, Ontario, and Alberta. Interview data came from 34 semi-structured key informant interviews with public health actors across Canada. Team-based coding and thematic analysis were conducted to analyze communications and interview transcripts. RESULTS: Four main themes emerged as integral to good communication: transparency, promptness, clarity, and engagement of diverse communities. Our data indicate that a lack of transparency surrounding evidence and public health decision-making, delays in public health communications, unclear and inconsistent terminology and activities within and across jurisdictions, and communications that did not consider or engage diverse communities' perspectives may have decreased the effectiveness of public health communications and adherence to public health measures throughout the COVID-19 pandemic. CONCLUSION: This study suggests that increased federal guidance with wider jurisdictional collaboration backed by transparent evidence could improve the effectiveness of communication practices by instilling public trust and adherence with public health measures. Effective communication should be transparent, supported by reliable evidence, prompt, clear, consistent, and sensitive to diverse values. Improved communication training, established engagement infrastructure, and increased collaborations and diversity of decision-makers and communicators are recommended.

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)0.010
metaresearch head score (Gemma)0.031
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.916

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.031
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0230.005
Scholarly communication0.0070.002
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.166
GPT teacher head0.345
Teacher spread0.179 · 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

Citations37
Published2022
Admission routes4
Has abstractyes

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