From Lyme disease emergence to endemicity: a cross sectional comparative study of risk perceptions in different populations
Notice bibliographique
Résumé
BACKGROUND: Lyme disease (LD) is a tick-borne emerging disease in Canada that has been endemic in many temperate countries for decades. Currently, one of the main approaches for LD prevention is the promotion of individual-level preventive behaviors against ticks. Health behaviors are influenced by individual and social factors, one important of which is risk perception. This study aims to describe and compare risk perception of LD, within and between general populations and experts living in two different regions: the Neuchâtel canton in Switzerland, where LD is endemic, and the Montérégie region in Québec (Canada), where LD is emerging. METHOD: A web-based survey was conducted in both study regions (814 respondents) in 2012, and a questionnaire was administered to 16 experts. Comparative analyses of knowledge, risk exposure and different components of LD risk perception were performed. Multivariate analyses were used to calculate a global risk perception score and to identify determinants of risk perception in both regions. RESULTS: In Montérégie, only 15% of the survey respondents had a good level of knowledge of LD compared to Neuchâtel where 51% of survey respondents had good levels of knowledge. In Montérégie, 24% of respondents perceived themselves as being at high or very high risk of contracting LD vs 54% in Neuchâtel; however, a higher percentage of respondents from this region believed that personal protection was simple to carry out (73% vs 58% in Montérégie). Based on the population surveys, almost all of the identified determinants of risk perception were different between both populations except for gender. A good level of knowledge, living in the risk zone and knowing someone who has had LD increased risk perception, while a high level of education and being 18-34 years of age decreased this perception. The majority of the studied components of risk perception were different between populations and their regional experts. CONCLUSION: This study suggests that risk perception of LD differs between populations and regional experts living in different epidemiological situations. Monitoring of knowledge and risk perception in local populations may help to better target LD communication efforts in accordance with population specific attributes thereby enhancing prevention efficacy.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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 | 0,000 |
| 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 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 ».