‘Communication, that is the key’: a qualitative investigation of how essential workers with COVID-19 responded to public health information
Bibliographic record
Abstract
OBJECTIVES: To understand how essential workers with confirmed infections responded to information on COVID-19. DESIGN: Qualitative analysis of semistructured interviews conducted in collaboration with the national contact tracing management programme in Ireland. SETTING: Semistructured interviews conducted via telephone and Zoom Meetings. PARTICIPANTS: 18 people in Ireland with laboratory confirmed SARS-CoV-2 infections using real-time PCR testing of oropharyngeal and nasopharyngeal swabs. All individuals were identified as part of workplace outbreaks defined as ≥2 individuals with epidemiologically linked infections. RESULTS: A total of four high-order themes were identified: (1) accessing essential information early, (2) responses to emerging 'infodemic', (3) barriers to ongoing engagement and (4) communication strategies. Thirteen lower order or subthemes were identified and agreed on by the researchers. CONCLUSIONS: Our findings provide insights into how people infected with COVID-19 sought and processed related health information throughout the pandemic. We describe strategies used to navigate excessive and incomplete information and how perceptions of information providers evolve overtime. These results can inform future communication strategies on COVID-19.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".