External validation of the parental attitude about childhood vaccination scale

IntroductionInternal validation techniques alone do not guarantee the value of a model. This study aims to investigate the external validity of the Parental Attitude toward Childhood Vaccination (PACV) scale for assessing parents' attitude toward seasonal influenza vaccination.MethodsUsing a sn...

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Main Authors: Ramy Mohamed Ghazy (Author), Sally Waheed Elkhadry (Author), Suzan Abdel-Rahman (Author), Sarah Hamed N. Taha (Author), Naglaa Youssef (Author), Abdelhamid Elshabrawy (Author), Sarah Assem Ibrahim (Author), Salah Al Awaidy (Author), Tareq Al-Ahdal (Author), Bijaya Kumar Padhi (Author), Noha Fadl (Author)
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Published: Frontiers Media S.A., 2023-05-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Ramy Mohamed Ghazy  |e author 
700 1 0 |a Sally Waheed Elkhadry  |e author 
700 1 0 |a Suzan Abdel-Rahman  |e author 
700 1 0 |a Sarah Hamed N. Taha  |e author 
700 1 0 |a Naglaa Youssef  |e author 
700 1 0 |a Abdelhamid Elshabrawy  |e author 
700 1 0 |a Sarah Assem Ibrahim  |e author 
700 1 0 |a Salah Al Awaidy  |e author 
700 1 0 |a Tareq Al-Ahdal  |e author 
700 1 0 |a Bijaya Kumar Padhi  |e author 
700 1 0 |a Noha Fadl  |e author 
245 0 0 |a External validation of the parental attitude about childhood vaccination scale 
260 |b Frontiers Media S.A.,   |c 2023-05-01T00:00:00Z. 
500 |a 2296-2565 
500 |a 10.3389/fpubh.2023.1146792 
520 |a IntroductionInternal validation techniques alone do not guarantee the value of a model. This study aims to investigate the external validity of the Parental Attitude toward Childhood Vaccination (PACV) scale for assessing parents' attitude toward seasonal influenza vaccination.MethodsUsing a snowball sampling approach, an anonymous online questionnaire was distributed in two languages (English and Arabic) across seven countries. To assess the internal validity of the model, the machine learning technique of "resampling methods" was used to repeatedly select various samples collected from Egypt and refit the model for each sample. The binary logistic regression model was used to identify the main determinants of parental intention to vaccinate their children against seasonal influenza. We adopted the original model developed and used its predictors to determine parents' intention to vaccinate their children in Libya, Lebanon, Syria, Iraq, Palestine, and Sudan. The area under the curve (AUC) indicated the model's ability to distinguish events from non-events. We visually compared the observed and predicted probabilities of parents' intention to vaccinate their children using a calibration plot.ResultsA total of 430 parents were recruited from Egypt to internally validate the model, and responses from 2095 parents in the other six countries were used to externally validate the model. Multivariate regression analysis showed that the PACV score, child age (adolescence), and Coronavirus disease 2019 (COVID-19) vaccination in children were significantly associated with the intention to receive the vaccination. The AUC of the developed model was 0.845. Most of the predicted points were close to the diagonal line, demonstrating better calibration (the prediction error was 16.82%). The sensitivity and specificity of the externally validated model were 89.64 and 37.89%, respectively (AUC = 0.769).ConclusionThe PACV showed similar calibration and discrimination across the six countries. It is transportable and can be used to assess attitudes towards influenza vaccination among parents in different countries using either the Arabic or English version of the scale. 
546 |a EN 
690 |a external validation 
690 |a calibration 
690 |a discrimination 
690 |a parental attitude about childhood vaccination 
690 |a seasonal influenza vaccine 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n Frontiers in Public Health, Vol 11 (2023) 
787 0 |n https://www.frontiersin.org/articles/10.3389/fpubh.2023.1146792/full 
787 0 |n https://doaj.org/toc/2296-2565 
856 4 1 |u https://doaj.org/article/556dc2d1c88143f2844f54b85d30179f  |z Connect to this object online.