Pandemic and Protective Health Behaviour: How do Brussels citizens view the Covid pandemic and Future pandemics? A Qualitative study.
Bibliographic record
Abstract
Introduction: SARS-CoV-2 crisis is an opportunity to be better prepared for similar episodes. Considering them from a behaviour perspective might be relevant. Indeed, difficulties arose in „translating” measures into behaviours. The research is part of a prospective participative study funded by Innoviris that aims to elaborate scenarios of a new pandemic in Brussels, focusing on behaviours. This part tackles the following questions: (1) What were the factors blocking/encouraging protective behaviour (i.e., compliance with government rules, vaccination, or self-behaviour) during the Covid episode? (2) What roles should citizens, government or other bodies play in maintaining “a good health”? Material and Methods: A qualitative study, using semi-structured interviews, was carried out with Brussels citizens. Citizens’ groups were interviewed twice by a pair of researchers with different backgrounds: once about the Covid-19 crisis, and once about future pandemics. A thematic analysis was conducted, associating the Canadian model of health determinants and emerging categories. Results: Fifty-one citizens took part in seven „double” focus groups and three individual interviews between March and July 2022. Surprisingly, the visions of the future mainly consist of a transfer of the participants, with the same age, into the future. While citizens did stress the need for better preparedness by drawing up plans, they also emphasized the difficulty of being ready and the possible need to learn anew, or even integrate the concept of ‚risk’ inherent to life. Different views of what a good crisis management should be were highlighted: specific at-risk groups versus “for everyone” management; renewed confidence in a democratically elected government versus new forms of participation governance to ensure trust in the decision; partly overlapping with convince versus coerce, spheres of influence on health (taking care of oneself, one’s entourage, „personified” strangers, the common good or the environment) matching with “appropriated” health education for the first four. The relevance of these choices is sometimes modulated by the “pathogen”. Conclusions: The visions cover a broad spectrum which, alongside other sources (literature review, databases), provides interesting material for scenarios that depend on the choices made by both politicians and citizens, before and during the pandemic.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".