Children’s pictures of COVID-19 and measures to mitigate its spread: an international qualitative study
Bibliographic record
Abstract
Objectives: To gain insight into children’s health-related knowledge and understanding of SARS-CoV2 and measures adopted to mitigate transmission. \nDesign: A child-centred qualitative creative element, embedded in an online mixed method survey of children aged 7-12 years. \nSetting: Children participated in the study in six countries - the UK, Australia, Sweden, Brazil, Spain and Canada. \nMethod: A qualitative creative component, embedded in an online survey, prompted children to draw and label a picture. Children were recruited via their parents using the researchers’ professional social media accounts, through known contacts, media and websites from health organisations within each country. Analysis of the form and content of the children’s pictures took place. \nResults: 128 children (mean age 9.2 years) submitted either a hand-drawn (n=111) or digitally created (n=17) picture. Four main themes identified related to children’s health-related knowledge of (1) COVID-19 and how it is transmitted; (2) measures and actions to mitigate transmission; (3) places of safety during the pandemic; and (4) children’s role in mitigating COVID-19 transmission. \nConclusion: Children’s pictures indicated a good understanding of the virus, how it spreads and how to mitigate transmission. Children depicted their actions during the pandemic as protecting themselves, their families and wider society.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".