Notice bibliographique
Résumé
Abstract Vaccination is one of the greatest public health successes. With sanitation and clean water, vaccines are estimated to have saved more lives over the past 100 years than any other health intervention. Vaccination not only protects the individual, but also, in many instances, provides community protection against vaccine-preventable diseases through herd immunity. To reduce the risk of vaccine-preventable diseases, vaccination programs rely upon reaching and sustaining high coverage rates, but paradoxically, because of the success of vaccination, new generations are often unaware of the risks of these serious diseases and their concerns now concentrate on the perceived risk of individual vaccines. Over the past decades, several vaccine controversies have occurred worldwide, generating concerns about vaccine adverse effects and eroding trust in health authorities, experts, and science. Gaps in vaccination coverage can, in part, be attributed to vaccine hesitancy and not just to “supply side issues” such as access to vaccination services and affordability. The concept of vaccine hesitancy is now commonly used in the discourse around vaccine acceptance. The World Health Organization defines vaccine hesitancy as “lack of acceptance of vaccines despite availability of vaccination services. Vaccine hesitancy is complex and context specific, varying across time, place and vaccines.” A vaccine-hesitant person can delay, be reluctant but still accept, or refuse one, some, or all vaccines. Technical, psychological, sociocultural, political, and economic factors can contribute to vaccine hesitancy. At the individual level, recent reviews have focused on factors associated with vaccination acceptance or refusal, identifying determinants such as fear of side effects, perceptions around health and prevention of disease and a preference for “natural” health, low perception of the efficacy and usefulness of vaccines, negative past experiences with vaccination services, and lack of awareness or knowledge about vaccination. Very few interventions have been shown to be effective in reducing vaccine hesitancy. Most of the studies have only focused on metrics of vaccine uptake and refusal to evaluate interventions aimed at enhancing vaccine acceptance, which makes it difficult to assess their potential effectiveness to address vaccine hesitancy. In addition, despite the complex nature of vaccination decision-making, the majority of public health interventions to promote vaccination are designed with the assumption that vaccine hesitancy is due to lack or inadequate knowledge about vaccines (the “knowledge-deficit” or “knowledge gap” approach). A key predictor of acceptance of a vaccine by a vaccine-hesitant person remains the recommendation for vaccination by a trusted healthcare provider. When providers communicate effectively about the value and need for vaccinations and vaccine safety, people are more confident in their decisions. However, to do this well, healthcare providers must be confident themselves about the safety, effectiveness, and importance of vaccination, and recent research has shown that a proportion of healthcare providers are vaccine-hesitant in their professional and personal lives. Effective strategies to address vaccine hesitancy among these hesitant providers have yet to be identified. A better understanding of the dynamics of the underlying determinants of vaccine hesitancy is critical for effective tailored interventions to be designed for both the public and healthcare providers.
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 | 0,011 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,004 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».