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Modeling the behavior of motorcyclist with Millon and ADHD: regression modeling
BACKGROUND: Road traffic accidents are one of the serious public health problems in the world and human factors can be effective. This study was carried on modeling of the relationship between MRBQ with Millon and ADHD. METHODS: In this case-control study, 300 cases and 156 controls were selected us...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Kermanshah University of Medical Sciences
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7187124/ |
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author | Hasanzadeh, Shila Asghari Jafarabadi, Mohammad Sadeghi-Bazargani, Homyoun |
author_facet | Hasanzadeh, Shila Asghari Jafarabadi, Mohammad Sadeghi-Bazargani, Homyoun |
author_sort | Hasanzadeh, Shila |
collection | PubMed |
description | BACKGROUND: Road traffic accidents are one of the serious public health problems in the world and human factors can be effective. This study was carried on modeling of the relationship between MRBQ with Millon and ADHD. METHODS: In this case-control study, 300 cases and 156 controls were selected using a cluster random sampling in Tabriz, Iran. Regression modeling to investigate the relationship between MRBQ with Millon and ADHD was studied with SPSS25 software. RESULTS: Due to the R Square was predictable for the overall model approximately 30%, case group models 35% and for the control group was approximately 18% of MRBQ by Millon and ADHD. The standard coefficients (confidence interval) and the probable significance of the relationship between MRBQ with Millon and ADHD were obtained as follows. In generally: Millon (B= 0.17 (CI (0.95) 0.06, 0.17), P<0.001) ADHD (B= 0.48 (CI (0.95) 0.80, 1.15), P<0.001) In Case group: Millon (B= 0.20 (CI (0.95) 0.06, 0.18), P<0.001) ADHD (B= 0.50 (CI (0.95) 0.82, 1.15), P<0.001) In Control group: Millon (B= 0.10 (CI (0.95) -0.04, 0.20), P=0.204) ADHD (B= 0.39 (CI (0.95) 0.44, 1.07), P<0.001). CONCLUSIONS: The results showed, that the behavior of the people who accident (case group), There was a stronger relationship with Millon and ADHD. Therefore, planning appropriate and fits with the conditions of individuals it is necessary to accident avoidance and improved their quality of life. KEYWORDS: MRBQ, ADHD, Linear regression, Millon |
format | Online Article Text |
id | pubmed-7187124 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Kermanshah University of Medical Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-71871242020-05-01 Modeling the behavior of motorcyclist with Millon and ADHD: regression modeling Hasanzadeh, Shila Asghari Jafarabadi, Mohammad Sadeghi-Bazargani, Homyoun J Inj Violence Res Poster Presentation BACKGROUND: Road traffic accidents are one of the serious public health problems in the world and human factors can be effective. This study was carried on modeling of the relationship between MRBQ with Millon and ADHD. METHODS: In this case-control study, 300 cases and 156 controls were selected using a cluster random sampling in Tabriz, Iran. Regression modeling to investigate the relationship between MRBQ with Millon and ADHD was studied with SPSS25 software. RESULTS: Due to the R Square was predictable for the overall model approximately 30%, case group models 35% and for the control group was approximately 18% of MRBQ by Millon and ADHD. The standard coefficients (confidence interval) and the probable significance of the relationship between MRBQ with Millon and ADHD were obtained as follows. In generally: Millon (B= 0.17 (CI (0.95) 0.06, 0.17), P<0.001) ADHD (B= 0.48 (CI (0.95) 0.80, 1.15), P<0.001) In Case group: Millon (B= 0.20 (CI (0.95) 0.06, 0.18), P<0.001) ADHD (B= 0.50 (CI (0.95) 0.82, 1.15), P<0.001) In Control group: Millon (B= 0.10 (CI (0.95) -0.04, 0.20), P=0.204) ADHD (B= 0.39 (CI (0.95) 0.44, 1.07), P<0.001). CONCLUSIONS: The results showed, that the behavior of the people who accident (case group), There was a stronger relationship with Millon and ADHD. Therefore, planning appropriate and fits with the conditions of individuals it is necessary to accident avoidance and improved their quality of life. KEYWORDS: MRBQ, ADHD, Linear regression, Millon Kermanshah University of Medical Sciences 2019-08 /pmc/articles/PMC7187124/ Text en Copyright © 2019, KUMS http://creativecommons.org/licenses/by/3/ This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Poster Presentation Hasanzadeh, Shila Asghari Jafarabadi, Mohammad Sadeghi-Bazargani, Homyoun Modeling the behavior of motorcyclist with Millon and ADHD: regression modeling |
title | Modeling the behavior of motorcyclist with Millon and ADHD: regression modeling |
title_full | Modeling the behavior of motorcyclist with Millon and ADHD: regression modeling |
title_fullStr | Modeling the behavior of motorcyclist with Millon and ADHD: regression modeling |
title_full_unstemmed | Modeling the behavior of motorcyclist with Millon and ADHD: regression modeling |
title_short | Modeling the behavior of motorcyclist with Millon and ADHD: regression modeling |
title_sort | modeling the behavior of motorcyclist with millon and adhd: regression modeling |
topic | Poster Presentation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7187124/ |
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