Relation of corona-specific health literacy to use of and trust in information sources during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: COVID-19 has developed into a worldwide pandemic which was accompanied by an «infodemic» consisting of much false and misleading information. To cope with these new challenges, health literacy plays an essential role. The aim of this paper is to present the findings of a trend study in Switzerland on corona-specific health literacy, the use of and trust in information sources during the COVID-19 pandemic, and their relationships. METHODS: Three online surveys each with approximately 1'020 individuals living in the German-speaking part of Switzerland (age ≥ 18 years) were conducted at different timepoints during the COVID-19 pandemic, namely spring, fall and winter 2020. For the assessment of corona-specific health literacy, a specifically developed instrument (HLS-COVID-Q22) was used. Descriptive, bivariate, and multivariate data analyses have been conducted. RESULTS: In general, a majority of the Swiss-German population reported sufficient corona-specific health literacy levels which increased during the pandemic: 54.6% participants in spring, 62.4% in fall and 63.3% in winter 2020 had sufficient corona-specific health literacy. Greatest difficulties concerned the appraisal of health information on the coronavirus. The most used information sources were television (used by 73.3% in spring, 70% in fall and 72.3% in winter) and the internet (used by 64.1, 64.8 and 66.5%). Although health professionals, health authorities and the info-hotline were rarely mentioned as sources for information on the coronavirus, respondents had greatest trust in them. On the other hand, social media were considered as the least trustworthy information sources. Respondents generally reporting more trust in the various information sources, tended to have higher corona-specific health literacy levels. CONCLUSIONS: Sufficient health literacy is an essential prerequisite for finding, understanding, appraising, and applying health recommendations, particularly in a situation where there is a rapid spread of a huge amount of information. The population should be supported in their capability in appraising the received information and in assessing the trustworthiness of different information sources.
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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 | 0.013 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| 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".