Attitudes towards vaccines and intention to vaccinate against COVID-19: Implications for public health communications in Australia
Notice bibliographique
Résumé
Abstract Objective To examine SARS-CoV-2 vaccine confidence, attitudes and intentions in Australian adults. Methods Nationwide survey in February-March 2021 of adults representative across sex, age and location. Vaccine uptake and a range of putative drivers of uptake, including vaccine confidence, socioeconomic status, and sources of trust, were examined using logistic and Bayesian regressions for vaccines generally and for SARS-CoV-2 vaccines. Results Overall 1,166 surveys were collected from participants aged 18-90 years (mean 52, SD of 19). Seventy-eight percent reported being likely to receive a vaccine against COVID-19. Higher SARS-CoV-2 vaccine intentions were associated with: increasing age (OR: 1.04 95%CI [1.03-1.044]), being male (OR: 1.37, 95% CI [1.08 – 1.72]), residing in the least disadvantaged area quintile (OR: 2.27 95%CI [1.53 – 3.37]) and a self-perceived high risk of getting COVID-19 (OR: 1.52 95% CI [1.08 – 2.14]). However, 72% of participants did not believe that they were at a high risk of getting COVID-19. Findings regarding vaccines in general were similar except there were no sex differences. For both the SARS-CoV-2 vaccine and vaccines in general, there were no differences in intentions to vaccinate as a function of education level, perceived income level, and rurality. Knowing that the vaccine is safe and effective, and that getting vaccinated will protect others, trusting the company that made it and getting vaccination recommended by a doctor were reported to influence a large proportion of the study cohort to uptake the SARS-CoV-2 vaccine. Seventy-eight percent reported the intent to continue engaging in virus-protecting behaviours (mask wearing, social distancing etc.) post-vaccine. Conclusions Seventy-eight percent of Australians are likely to receive a SARS-CoV-2 vaccine. Key influencing factors identified in this study (e.g. knowing that the vaccine is safe and effective, getting a doctor’s recommendation to get vaccinated) can be used to inform public health messaging to enhance vaccination rates. Strengths and limitations of this study This research captured a large, representative sample of the adult Australian population across age, sex, location, and socioeconomic status. We have self-reported Australian uptake intentions and attitudes on general vaccines and COVID-19 vaccine, and intent to continue engaging in virus-protecting behaviours (mask wearing, social distancing etc.) post SARS-CoV-2 vaccine. We examine a range of drivers and factors that may influence intent to get the SARS-CoV-2 vaccine uptake, including vaccine confidence, demographics and socioeconomic status. The survey is based on established behavioural theories, and is the Australian arm of the international iCARE survey which to date has collected global comparative information from over 90,000 respondents in 140 countries. Our survey was only available in English, which may have led to an underrepresentation of ethnic groups, and participation was voluntary, so our sample may be prone to selection bias from those with more interest or engagement in COVID-19.
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 | 0,003 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».