Knowledge, Attitudes, and Practices Regarding Zika: Paper- and Internet-Based Survey in Zhejiang, China
Notice bibliographique
Résumé
Background: As public access to the Internet increases, many health workers prefer to carry out health education online, reducing the use of traditional community-based health education methods. Since March 2016, four Zika cases have been confirmed in Zhejiang, China. Rapid assessment of people’s knowledge, attitudes, and practices (KAP) regarding Zika is crucial to its prevention and control. Web-based surveys to assess public KAP may be a growing trend; however, we had little experience with this method. Objectives: The aim of this study was to explore KAP regarding Zika in residents of Zhejiang using both traditional paper- and innovative Internet-based investigations. Methods: A questionnaire was designed by Zhejiang Provincial Center for Disease Control and Prevention. A paper-based version of the survey was used in a cross-sectional community study following multistage cluster random sampling, and an Internet-based survey was promoted through a local health education site. Data were interpreted via univariate and multivariate analyses. Results: A total of 447 community residents participated in the paper-based survey, with a response rate of 89.4% (447/500), and 621 eligible Internet users participated in the Internet-based survey, with a response rate of 36.92% (621/1682). Age, education level, and occupation differed significantly between participants in the paper- and Internet-based surveys. Participants completing the Internet-based survey were much younger (χ22=144.7, P<.001) and had a higher level of education (χ22=423.5, P<.001) than those completing the paper-based survey. Among participants completing the paper-based survey, there were more farmers, housewives, and unemployed people (χ23=413.7, P<.001). Overall, 83.52% of participants (892/1068) knew the transmission route for Zika, 76.12% (813/1068) knew that pregnant women were at high risk of severe complications, 66.39% (709/1068) knew that contracting Zika during pregnancy could lead to newborn babies with microcephaly, and 98.88% (1056/1068) knew places where mosquitos could usually be found. After controlling for sociodemographic variables, participants completing the Internet-based survey were more likely to know the transmission route of Zika (odds ratio [OR]=5.0, 95% CI 3.0-8.0), the association between pregnant women with Zika and newborn babies with microcephaly (OR 2.1, 95% CI 1.4-3.0), and that pregnant women were at high risk for Zika (OR 5.5, 95% CI 3.5-8.4) than those completing the paper-based survey. They were less likely to worry about contracting Zika (OR 0.6, 95% CI 0.4-0.9) and more likely to actively seek information about Zika than participants completing the paper-based survey (OR 3.3, 95% CI 2.0-5.6). Conclusions: Participants completing the Internet-based survey had a higher level of basic knowledge and more positive attitudes and behaviors than participants completing the paper-based survey. In addition to providing Web-based health information, the government should ensure sufficient access to health information for the elderly and less educated people in the community to improve health equity.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 source (Gemma direct ou Codex distillé), 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 ».