Awareness, knowledge, attitudes, and behaviors related to COVID-19 in Libya: a nation-wide online survey.
Bibliographic record
Abstract
INTRODUCTION: the World Health Organization declared the COVID-19 outbreak to be a global pandemic in March 2020. However, the pandemic cannot be ended overnight and more social distancing and other self-care measures are needed to protect our communities. Therefore, people´s awareness, knowledge, attitudes, and appropriate behaviors are instrumental to containing the pandemic. The aim of this study was to determine COVID-19 awareness, knowledge, attitudes, and related behaviors in Libya. METHODS: , 2020 in 24 cities in Libya. The participants were non-medical professionals who were living in Libya for at least 2 years and were at least 18 years old. RESULTS: a total of 1018 participants completed the questionnaire, with ages ranging from 18-74 years (Mean ± SD = 33.49±13.24); nearly two-thirds were < 40, and 68.2% were females. Almost half of the participants considered the potential threat of COVID-19 to be low, and one in five reported that they were "Not worried at all" about getting COVID-19. In multivariate analyses, participants who were 40-49 years old, had master´s degrees or higher, and worked in the private sector reflected high mean scores for both knowledge and attitudes, while those who lived in the Eastern or Southern regions had lower mean attitude scores. CONCLUSION: the low levels of awareness as well as the attitudes and behaviors among the public in Libya are worrisome. This study highlighted profound gaps that may put Libyan communities at high risk of a COVID-19 explosion. Therefore, immediate action is needed to address public awareness and attitudes and to improve COVID-19 related behaviors among the Libyan public.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".