Knowledge, attitude, practice and fear of COVID-19: A cross-cultural study
Notice bibliographique
Résumé
Abstract Background Knowledge, Attitude and Practice (KAP), and Fear toward COVID-19 are an important issue when designing public health approaches to control the spread of this highly contagious disease like COVID-19 during the global pandemic period. Studies with KAP and fear measures are limited only regional or country level, not yet with global or cross-cultural populations. The study is aimed to measure KAP and fear level towards COVID-19 and explore its cross-cultural variances in knowledge by socio-demographic factors among the general population of 8 different countries over 5 continents. Method A cross-sectional online survey was conducted in April 2020 among 1296 participants using the Google form platform. Considering the social distancing formula and pandemic situation, we collect data using popular social media networks. Univariate and bivariate analyses were used to explore the collected data on KAP, fear, and sociodemographic factors. Result Overall knowledge score was 9.7 (out of 12) and gender differences (female vs male: 9.8 vs 9.5) were significant (p=0.008) in the bivariate analysis. Knowledge score variances found significant in some regions by gender, marital status and education qualification. The highest and lowest mean knowledge scores were recorded in the Middle East (10.0) and Europe (9.3). Despite having a high fear score (22.5 out of 35), 78.35% of respondents were in a positive attitude and 81.7% in good practice level. Fear score rankings: Middle East (1st; 23.8), Europe (2nd; 23.2); Africa (3rd; 22.7); South Asia (4th; 22.1); Oceania (5th; 21.9); and North America (6th; 21.7). We didn’t find a correlation between fear and knowledge. Limitation Due to the nature of the online survey, aged and rural populations are under-representing (e.g. more than half of the responders are 16-29 age group). Conclusion KAP and fear variation exist among geographical regions. Gender, marital status and education qualification are factors in knowledge variances for some regions. KAP and fear measures can assist health education programs considering some sociodemographic factors and regions during an outbreak of highly contagious disease and, which can uplift a positive attitude and good practice. Highlights Cross-cultural KAP and fear toward COVID-19 are evaluated Respondents from Europe scored less knowledge on COVID 19 but had more good knowledge level About 80% participants had positive attitude and good practice behavior. Interestingly, Participants in Oceania avoided more crowded places whereas, in Europe worn more masks during outing as a measure of prevention Participants in Middle East had the highest score in fear, and fear was independent of knowledge
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».