Handwashing Adherence and the Trajectory of COVID-19 Pandemic: Findings from 14 Countries
Bibliographic record
Abstract
Abstract Background: The COVID-19 pandemic has affected people's engagement in health behaviors, especially those that protect individuals from SARS-CoV-2 transmission, such as handwashing/sanitizing. Associations between the pandemic's trajectory and engagement in the protective behavior of handwashing are unclear. This study investigated whether adherence to the World Health Organization's (WHO) handwashing guidelines is associated with (i) total cases of COVID-19 morbidity/mortality accumulated since the onset of the pandemic, (ii) recent cases (country-level COVID-19 morbidity/mortality in the 14 days prior to data collection), (iii) increases/acceleration in recent cases (country-level COVID-19 morbidity/mortality in the previous 14 days minus cases recorded 14-28 days earlier), and (iv) stringency of the national containment-and-health policies (in the 7 days prior to data collection). Methods : The observational study (#NCT04367337) enrolled 6,064 adults residing in Australia, Canada, China, France, Gambia, Germany, Israel, Italy, Malaysia, Poland, Portugal, Romania, Singapore, and Switzerland. Data on cross-situational handwashing adherence were collected via an online survey (March–July 2020). Individual data were matched with the WHO daily reports of COVID-19 and indices of containment-and-health policies. Country-level human development index and sociodemographic variables were controlled. Results: Multilevel regression models indicated that as the total cases of COVID-19 morbidity and mortality grew higher, handwashing adherence decreased. As increases in recent cases of COVID-19 morbidity and mortality occurred, handwashing adherence increased. Higher levels of containment-and-health policy index were associated with lower handwashing. Conclusions : Research investigating protective behaviors should account for indicators of fluctuations of COVID-19 morbidity/mortality, besides accounting for time since the beginning of the pandemic. Trial Registration: Clinical Trials.Gov, #NCT04367337, first registration date: 29/04/2020
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".