S Mehdipour, F Zolala, M Hoseinnejad, R Zahedi, E Najafi, M , N Farrokhnia, M Fathi,
Volume 14, Issue 2 (Vol.14, No.2, 2018)
Abstract
Background and Objectives: Evidence suggests that underlying diseases increase the severity of influenza and lead to hospitalization or death. This study was conducted to determine the risk factors associated with hospitalization of patients in Afzalipour Hospital, Kerman, Iran during an outbreak of H1N1 influenza in December 2015.
Methods: In this case-control study, the case group comprised 85 patients who were hospitalized for influenza and the control group included 51 patients who had influenza symptoms and were discharged after required evaluations and check-up. The data were collected from both groups on a daily basis for two weeks. For data analysis, descriptive analysis, logistic regression analysis, Lasso Regression, and likelihood ratio were used. Analysis was performed using the Stata version 12 and R software.
Results: Among the variables examined, after removal of additional variables, 12 variables were introduced into the multivariate regression. The history of pulmonary disease and diabetes increased the odds of hospitalization following influenza by more than 11 (OR = 11.6, P. value = 0.003) and 9 times (OR = 9, P. value = 0.01), respectively.
Conclusion: Underlying disease and factors play a major role in exacerbating the disease. Therefore, the health system should take the necessary preventive measures when outbreaks occur.
Alireza Didarloo, Behrouz Fathi, Raana Hosseini, Habibollah Pirnejad, Sima Ghorbanzadeh, Kajal Yasamani,
Volume 19, Issue 1 (Vol.19, No.1, Spring 2023)
Abstract
Background and Objectives: Vaccination stands as a paramount achievement in global public health and a key strategy to control COVID-19. Vaccine acceptance is a pivotal determinant of the success or failure of vaccination programs. Leveraging health education models and theories to predict behavioral intention, this study aimed to investigate the determinants of the intention to receive the COVID-19 vaccine among the general population of Urmia using the Health Belief Model (HBM).
Methods: This descriptive-analytical study employed a cross-sectional approach among 575 individuals aged over 18 residing in Urmia. Sampling was conducted through the snowball and convenience sampling methods. Data was collected using a valid and reliable electronic researcher-made questionnaire comprising four sections: demographic characteristics, knowledge, HBM constructs, and intention to receive the COVID-19 vaccine. Data were analyzed using descriptive and inferential statistics in SPSS version 16.
Results: The HBM effectively explained 67% of the variance in the intention to vaccinate against COVID-19. Within the model's constructs, individuals' perceived self-efficacy (β = 0.505, P = 0.001) emerged as the strongest predictor of the intention to receive the COVID-19 vaccination. Other influencing factors included perceived susceptibility (β = 0.158, P = 0.001) and perceived barriers (β = -0.109, P = 0.001).
Conclusion: Given the robust predictive ability of the HBM for the intention to vaccinate against COVID-19, this model can be utilized in educational and behavioral programs and interventions. Special emphasis should be placed on effective constructs, particularly self-efficacy, to enhance citizens' willingness to receive the COVID-19 vaccine.
