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Predictors of Post-Traumatic Stress Disorder among Victims of Serious Motor Vehicle Accidents

BACKGROUND: Compelling evidence has shown that motor vehicle accidents have an enormous impact on mental health. Post-traumatic Stress Disorder (PTSD) is one of the most common psychological consequences in adult survivors of accidents, so it is important to understand the prevalence and predictors...

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Autores principales: Khodadadi-Hassankiadeh, Naema, Dehghan Nayeri, Nahid, Shahsavari, Hooman, Yousefzadeh-Chabok, Shahrokh, Haghani, Hamid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Shiraz University of Medical Sciences 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635555/
https://www.ncbi.nlm.nih.gov/pubmed/29043281
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author Khodadadi-Hassankiadeh, Naema
Dehghan Nayeri, Nahid
Shahsavari, Hooman
Yousefzadeh-Chabok, Shahrokh
Haghani, Hamid
author_facet Khodadadi-Hassankiadeh, Naema
Dehghan Nayeri, Nahid
Shahsavari, Hooman
Yousefzadeh-Chabok, Shahrokh
Haghani, Hamid
author_sort Khodadadi-Hassankiadeh, Naema
collection PubMed
description BACKGROUND: Compelling evidence has shown that motor vehicle accidents have an enormous impact on mental health. Post-traumatic Stress Disorder (PTSD) is one of the most common psychological consequences in adult survivors of accidents, so it is important to understand the prevalence and predictors of this issue since delay causes damage to crucial daily functioning. This study aimed at investigating the prevalence and predictors of PTSD after motor vehicle accident. METHODS: This cross-sectional study was conducted on 528 injured patients six weeks to six months after motor vehicle accident in Imam Reza Clinic of Poursina hospital, Rasht in 2015. Data collection tools were three questionnaires including post-traumatic stress-self report (PSS), Beck Depression Inventory (BDI-II), and the Numeric Rating Scale (NRS) for pain. The data were analyzed in SPSS (Version 19) using Chi-square, Fischer’s exact test and multivariate logistic regression. Significance level was considered P≤0.05. RESULTS: The prevalence of PTSD and depression was 30.49% and 19.89% in participants, respectively. Chi-square test indicated a significant relationship among age (P=0.02), sex (P<0.001), education level (P<0.001), work status (P<0.001) and PTSD. Participants who reported pain (P<0.001) and depression (P<0.001) were more likely to have high score of PTSD than the others. Multivariate logistic regression showed this significance in sex, depression, age, educational status and pain, as constant risk factors in developing PTSD after accident. CONCLUSION: This study suggests that primary care setting should be readily prompted for diagnosis of these disorders in non-treatment seeking individuals in the community.
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spelling pubmed-56355552017-10-17 Predictors of Post-Traumatic Stress Disorder among Victims of Serious Motor Vehicle Accidents Khodadadi-Hassankiadeh, Naema Dehghan Nayeri, Nahid Shahsavari, Hooman Yousefzadeh-Chabok, Shahrokh Haghani, Hamid Int J Community Based Nurs Midwifery Original Article BACKGROUND: Compelling evidence has shown that motor vehicle accidents have an enormous impact on mental health. Post-traumatic Stress Disorder (PTSD) is one of the most common psychological consequences in adult survivors of accidents, so it is important to understand the prevalence and predictors of this issue since delay causes damage to crucial daily functioning. This study aimed at investigating the prevalence and predictors of PTSD after motor vehicle accident. METHODS: This cross-sectional study was conducted on 528 injured patients six weeks to six months after motor vehicle accident in Imam Reza Clinic of Poursina hospital, Rasht in 2015. Data collection tools were three questionnaires including post-traumatic stress-self report (PSS), Beck Depression Inventory (BDI-II), and the Numeric Rating Scale (NRS) for pain. The data were analyzed in SPSS (Version 19) using Chi-square, Fischer’s exact test and multivariate logistic regression. Significance level was considered P≤0.05. RESULTS: The prevalence of PTSD and depression was 30.49% and 19.89% in participants, respectively. Chi-square test indicated a significant relationship among age (P=0.02), sex (P<0.001), education level (P<0.001), work status (P<0.001) and PTSD. Participants who reported pain (P<0.001) and depression (P<0.001) were more likely to have high score of PTSD than the others. Multivariate logistic regression showed this significance in sex, depression, age, educational status and pain, as constant risk factors in developing PTSD after accident. CONCLUSION: This study suggests that primary care setting should be readily prompted for diagnosis of these disorders in non-treatment seeking individuals in the community. Shiraz University of Medical Sciences 2017-10 /pmc/articles/PMC5635555/ /pubmed/29043281 Text en Copyright: © Shiraz University of Medical Sciences http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Khodadadi-Hassankiadeh, Naema
Dehghan Nayeri, Nahid
Shahsavari, Hooman
Yousefzadeh-Chabok, Shahrokh
Haghani, Hamid
Predictors of Post-Traumatic Stress Disorder among Victims of Serious Motor Vehicle Accidents
title Predictors of Post-Traumatic Stress Disorder among Victims of Serious Motor Vehicle Accidents
title_full Predictors of Post-Traumatic Stress Disorder among Victims of Serious Motor Vehicle Accidents
title_fullStr Predictors of Post-Traumatic Stress Disorder among Victims of Serious Motor Vehicle Accidents
title_full_unstemmed Predictors of Post-Traumatic Stress Disorder among Victims of Serious Motor Vehicle Accidents
title_short Predictors of Post-Traumatic Stress Disorder among Victims of Serious Motor Vehicle Accidents
title_sort predictors of post-traumatic stress disorder among victims of serious motor vehicle accidents
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635555/
https://www.ncbi.nlm.nih.gov/pubmed/29043281
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