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Exploring the acceptance of <scp>COVID</scp>‐19 vaccine among healthcare workers and general population using health belief model
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Abstract<sec><title>Rationale, aims and objectives

Little is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.

Methods

This was a cross‐sectional study based on electronic survey data that was collected in Iraq during December first‐19th, 2020. The electronic survey was designed using Qualtrics. HBM was followed to develop the survey items. A regression analysis was used to identify factors influencing people accepting vaccination. Thematic analysis for participant comments to an open‐ended question.

Results

A total of 1680 completed surveys were received. The mean age of 31.2 ± 9.9 years, 53.0% were female and 47.0% were male. The largest group was HCWs (45.7%), followed by general population (37.5%) and health college students (16.8%). Our findings expressed some hesitancy to receive the COVID‐19 vaccine with the acceptance rate of 61.7%. The HCWs perceived significantly higher susceptibility and severity of the COVID‐19 infection compared to the general population. The HCWs were significantly more likely than the general population to receive COVID‐19 vaccine. Concerns with proper storage was the biggest barrier to vaccine receipt. The regression analysis indicated eight factors that were significantly associated with the willingness to receive COVID‐19 vaccine: Preventive measures, perceived benefit, perceived barriers, cue to action, subjective norm, supportive of vaccination in general and having received a flu vaccine before.

Conclusions

Awareness campaign can focus on enhancing the vaccine perceived benefit, debunking misconceptions, and increasing the disease perceived severity. Additionally, the public health leaders need to minimize the perceived barriers by providing the vaccines and appeasing people concerns about their storage, effectiveness, and adverse events.

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Sat Aug 31 2024
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International Journal Of Intelligent Engineering And Systems
Credit Card Fraud Detection Using an Autoencoder Model with New Loss Function
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Publication Date
Sun Feb 24 2019
Journal Name
Iraqi Journal Of Physics
High spatial resolution digital elevation model (DEM) production using different interpolations techniques
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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Solving Time-Cost Tradeoff Problem with Resource Constraint Using Fuzzy Mathematical Model
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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using jack knife to estimation logistic regression model for Breast cancer disease
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Crossref
Publication Date
Wed Sep 30 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Impact of Earnings Quality using the Sustainability model (Persistence) and predictability in the Continuity of the Banks: بحث تطبيقي في عينة من المصارف التجارية المدرجة في سوق العراق للاوراق المالية
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The research aims to measure the extent of the impact of Earnings quality in the continuity of the company for a sample of private commercial banks listed on the Iraq Stock Exchange. The research sample included (15) of the listed commercial banks that continue to issue their financial statements for the period from (2009-2018).The research relied on three main models of measurement and on four steps. The first step is to measure the Persistence (Earnings Quality) by Depending the sustainability model. While the second step included measuring the Predictability of accounting profits by deriving the square root of the disparity of the estimation error from the first model Persistence (Earnings Quality), and the third step included

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Publication Date
Sat May 01 2021
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Investigating of Charge Transfer in Cu/F8 Using Donor-Acceptor Model due Quantum Transition
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in this paper, we study and investigate a simple donor-acceptor model for charge transfer formation using a quantum transition theory. The transfer parameters which enhanced the charge transfer and the rate of the charge transfer have been calculated. Then, we study the net charge transfer through interface of Cu/F8 contact devices and evaluate all transfer coefficients. The charge transfer rate of transfer processes is found to be dominated in the low orientation free energy and increased a little in decreased potential at interface comparison to the high potential at interface. The increased transition energy results in increasing the orientation of Cu to F8. The transfer in the system was more active when the system has large driving for

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Publication Date
Wed Mar 10 2021
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Mathematical model of optical amplifier using nonlinear stimulated Brillouin scattering (SBS) in optical fiber
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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

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Publication Date
Fri Sep 30 2022
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Distinguishing Shapes of Breast Cancer Masses in Ultrasound Images by Using Logistic Regression Model
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The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

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Crossref
Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

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