Factors Predicting Death Depression of Emergency Medical Technicians in Iran

Shafaei, Mahya and Mafi, Mohamad Hossein and Dehghankar, Leila and Panahi, Rahman and Khorany, Hossein and Namdar, Peyman (2021) Factors Predicting Death Depression of Emergency Medical Technicians in Iran. The Journal of Qazvin University of Medical Sciences, 24 (5). pp. 422-433. ISSN 24235814

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Background Psychological problems such as death depression can have adverse effects on Emergency Medical Technicians (EMTs) including reduced quality of medical services, job dissatisfaction, feelings of incompetence, depression, and reduced job values. Objective This study aims to determine the factors predicting death depression of EMTs in Iran. Methods In this descriptive cross-sectional study conducted in 2019, participants were 125 eligible EMTs in hospitals affiliated to Qazvin University of Medical Sciences in Qazvin, Iran. Templer’s Death Depression Scale (DDS) and a demographic form were used to collect data. The collected data were analyzed using descriptive and inferential statistics. Findings The Mean±SD DDS score was reported 4.73±2.93. Most of subjects (n=79, 63.2%) had low death depression. According to the results of linear regression analysis, “number of resuscitation attempts in the last 3 months”, “organizational position” and “history of depression” were the predictors of death depression (P<0.05). In total, the regression model predicts 9% of the variance in death depression. Conclusion Death depression of EMTs in Iran is low. Due to the importance of mental health in medical staff in providing quality clinical services, it is recommended that further studies should be conducted in this area using a larger sample size.

Item Type: Article
Subjects: R Medicine > RP Paramedical > RP104 Medical emergencies
R Medicine > RT Nursing
Divisions: University Portal > vice chancellor > vcr
Depositing User: pr vcen research
Date Deposited: 29 May 2021 05:09
Last Modified: 29 May 2021 05:09
URI: http://eprints.qums.ac.ir/id/eprint/10795

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