Volume 15, Issue 4 (Vol.15, No.4 2020)
irje 2020, 15(4): 352-361 |
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Hasanzadeh S, Sadeghi Bazargani H, Hashemiparast M, Asghari Jafarabadi M. Assessing Partial Least Squares-Structural Eqation Modeling for the Predictors of Injuries Resulting in Hospitalization in Motorcyclists: A Case-Control Study. irje 2020; 15 (4) :352-361
URL: http://irje.tums.ac.ir/article-1-6425-en.html
URL: http://irje.tums.ac.ir/article-1-6425-en.html
1- MSc of biostatistics, Department of Statistics and Epidemiology, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran
2- Associate Professor of Epidemiology, Road Traffic Injury Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
3- Assistant Professor of Health Education and Promotion, Department of Public, Maragheh University of Medical Sciences, Maragheh, Iran
4- Professor of Biostatistics, Department of Statistics and Epidemiology, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran , asghari862@gmail.com
2- Associate Professor of Epidemiology, Road Traffic Injury Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
3- Assistant Professor of Health Education and Promotion, Department of Public, Maragheh University of Medical Sciences, Maragheh, Iran
4- Professor of Biostatistics, Department of Statistics and Epidemiology, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran , asghari862@gmail.com
Abstract: (2892 Views)
Background and Objectives: The aim of this study was to determine the predictability of the PLS-SEM model for injuries resulting in hospitalization in motorcyclists using a mediator variable in a case-control study.
Methods: In this case-control study, 300 cases and 156 controls were randomly selected from 150 clusters using random cluster sampling. The data were collected using the motorcycle riding behavior (MRB) questionnaire, adult attention deficit hyperactivity disorder (ADHD) questionnaire (subscales) and a checklist containing motorcycle related variables.
Results: The motorcycle riding behavior, adult ADHD, motorcycling related variables and some demographic variables were found to be the predictors of injury. There were significant positive relationships between injury and motorcycling related variables (B=0.20, P=0.001) and ADHD (B=0.33, P=0.001), between MRB and motorcycling related variables (B=0.51, P=0.001) and ADHD (B=0.52, P=0.001), and between ADHD and motorcycling related variables (B=0.39, P=0.001).
Conclusion: Considering the more accurate results of PLS-SEM, the intervention programs should especially address those who have hyperactive children, those who use the cellphone while riding, and those who ride in dark hours of the night.
Methods: In this case-control study, 300 cases and 156 controls were randomly selected from 150 clusters using random cluster sampling. The data were collected using the motorcycle riding behavior (MRB) questionnaire, adult attention deficit hyperactivity disorder (ADHD) questionnaire (subscales) and a checklist containing motorcycle related variables.
Results: The motorcycle riding behavior, adult ADHD, motorcycling related variables and some demographic variables were found to be the predictors of injury. There were significant positive relationships between injury and motorcycling related variables (B=0.20, P=0.001) and ADHD (B=0.33, P=0.001), between MRB and motorcycling related variables (B=0.51, P=0.001) and ADHD (B=0.52, P=0.001), and between ADHD and motorcycling related variables (B=0.39, P=0.001).
Conclusion: Considering the more accurate results of PLS-SEM, the intervention programs should especially address those who have hyperactive children, those who use the cellphone while riding, and those who ride in dark hours of the night.
Keywords: Partial least squares, Traffic, Injury, Motorcycle riding behavior, Adult hyperactivity disorder
Type of Study: Research |
Subject:
Epidemiology
Received: 2020/01/28 | Accepted: 2020/01/28 | Published: 2020/01/28
Received: 2020/01/28 | Accepted: 2020/01/28 | Published: 2020/01/28
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