THE PREVALENCE AND PREDICTORS OF DEPRESSION AND ANXIETY AMONG EMERGENCY MEDICAL SERVICES PERSONNEL

H JADOON; ES SIDDIQUI; R MOHSIN; A BATOOL; N JABEEN; F MUH

doi:10.54112/bcsrj.v2023i1.334

Authors

H JADOON Department of Obstetrics and Gynae, Ayub Teaching Hospital Abbottabad, Pakistan
ES SIDDIQUI Department of Obstetrics and Gynae Civil Hospital, Liaquat University of Medical & Health Sciences (LUMHS), Pakistan
R MOHSIN Department of Obstetrics and Gynae, Pak Emirates Military Hospital Rawalpindi (PEMH), Pakistan
A BATOOL Department of Obstetrics and Gynae, Family and Children Hospital Lodhran, Pakistan
N JABEEN Department of Gynae, Rawal Institute Of Health Sciences, Islamabad, Pakistan
F MUH Department of medicine, Indus Medical College & Hospital Tando Muhammad Khan, Pakistan

DOI:

https://doi.org/10.54112/bcsrj.v2023i1.334

Keywords:

Emergency Department, Beck Anxiety Inventory (BAI), Anxiety, Depression Beck Depression Inventory (BDI)

Abstract

This study aimed to determine the prevalence and predictors of depression and anxiety among emergency medical services personnel at the Liaquat University of Medical & Health Sciences (LUMHS). The study was conducted over the course of one year, from December 2021 to December 2022, and involved a sample size of 120 participants. The study used a cross-sectional design, and data was collected using a self-administered questionnaire that assessed depression and anxiety symptoms, as well as demographic and job-related factors. The questionnaire was distributed to all emergency medical services personnel working in LUMHS, and participation in the study was voluntary. Data collected was analyzed using descriptive statistics to determine the prevalence of depression and anxiety among emergency medical services personnel in LUMHS. Logistic regression analysis was used to identify predictors of depression and anxiety, including demographic and job-related factors such as age, gender, years of service, and job stressors. The results showed that the prevalence of depression and anxiety among emergency medical services personnel in LUMHS was 45% and 50%, respectively. Logistic regression analysis revealed that older age, female gender, long years of service, and higher job stressors were significant predictors of depression and anxiety. These findings provided valuable information about the mental health status of emergency medical services personnel in LUMHS, highlighting the need for interventions and support services to address the high prevalence of depression and anxiety in this population. The study contributed to the growing body of research on mental health in the workplace, particularly in high-stress occupations such as emergency medical services and underscored the importance of addressing the mental health needs of this vulnerable population.

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