What is needed to effectively communicate risk during a health crisis? A qualitative study with international experts based on the COVID-19 pandemic
Bibliographic record
Abstract
OBJECTIVE: To identify a framework for risk communication during health crises by using the current pandemic as a case study. DESIGN: A qualitative study based on individual interviews. SETTING: Different countries with diverse levels of perceived success on risk communication during the COVID-19 health crisis. PARTICIPANTS: International experts with experience in health crisis management or risk communication. ANALYSIS: A thematic analysis was performed supported by Atlas.ti. RESULTS: Four men and six women took part in the study (three from Europe, two from Latin America, two from North America, one from Asia and two from Oceania). Three major themes emerged from the data: (1) institutionalising the communication strategy; (2) defining the problem that needs to be faced; (3) developing an effective communication strategy. CONCLUSION: Risk communication during a health crisis requires preparation of governments and of health teams in order to produce and deliver effective messages as well as to help communities to make informed and healthy decisions. This is particularly relevant for slow disasters, such as COVID-19, as the strategy must innovate to avoid information fatigue of the audience. The findings of this article could inform guidelines to best equip countries for a clear communication strategy for future crises. PROSPERO REGISTRATION NUMBER: CRD42021234443.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".