Knowledge, Attitude, Awareness, and Barriers Toward Influenza Vaccination Among Medical Doctors at Tertiary Care Health Settings in Peshawar, Pakistan–A Cross-Sectional Study
Notice bibliographique
Résumé
Objective: This study aimed to investigate the knowledge, attitude and awareness of medical doctors towards influenza vaccination and the reasons for not getting vaccinated. Methods: A cross-sectional study was carried out among medical doctors in three major tertiary care hospitals in Peshawar, Khyber Pakhtunkhwa (KP), Pakistan. A web-based, pre-tested questionnaire was used for data collection. Results: A total of (n=300) medical doctors were invited, however only (n=215) participated in the study with a response rate of 71.7%. Among the participants, 95.3% (n=205) were males with a mean age of 28.67±3.89 years. By designation, 121(56.3%) were trainee medical officers and 40 (18.6%) were house officers. The majority had a job experience of 1-2 years (n=102, 60.6%). Of the total sample, 38 (17.7%) doctors reported having received some kind of vaccination, whereas only 19 (8.84%) were vaccinated against influenza. The results identified that the major barriers towards influenza vaccinations included (1) a general perception among the health-care professionals that influenza is not a serious condition and therefore not worth vaccinating against (relative importance index RII=0.775), (2) the non-compulsory requirement for vaccination (RII=0.756), (3) fear of needles (RII=0.713) and (4) the associated side-effects or safety concerns (RII=0.681). Additionally, 156(72.6%) of doctors were not aware of the influenza immunization guidelines published by the Advisory Committee on Immunization Practices (ACIP) and Centre for Disease Control (CDC). Physicians obtained a high score (8.27 ± 1.61) of knowledge and understanding regarding influenza and its vaccination followed by medical officers (8.06 ±1.37). Regression analysis revealed that gender was significantly associated with the knowledge score with males having a higher score (8.0+1.39) than females (6.80+1.61). Conclusion: A very low proportion of doctors were vaccinated against influenza, despite the published guidelines and recommendations. Strategies that address multiple aspects like increasing awareness and the importance of the influenza vaccine, the international recommendations and enhancing access and availability of the vaccine are needed to improve its coverage and health outcomes.
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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 | 0,006 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».