Emotional burnout,job satisfaction,and intention to leave among pre-hospital emergency healthcare workers during the COVID-19 pandemic

Abstract

BACKGROUND:

With the onset of the COVID-19 pandemic, pre-hospital emergency healthcare workers (PHEHW) assumed critical responsibilities in controlling and preventing the spread of the virus.

OBJECTIVE:

This descriptive study aimed to explore the emotional burnout, job satisfaction, and intention to leave among PHEHW during the COVID-19 pandemic.

METHODS:

The study was conducted with 401 emergency medical technicians and paramedics. The Sociodemographic Data Form, the Emotional Burnout Scale, the Job Satisfaction Scale, the Intention to Leave the Profession Scale were used to collect data. The findings were assessed with a significance level set at p < 0.05 and a 95% confidence interval.

RESULTS:

The participants demonstrated moderate scores in emotional burnout, job satisfaction, and intention to leave the profession. The analysis revealed a negative correlation, indicating that as emotional burnout increased, job satisfaction decreased, and the intention to leave the profession heightened. Notably, the participants who had 6–9 years of service, lacked knowledge about COVID-19, had no COVID-19 training, underwent COVID-19 testing, and experienced the loss of a healthcare worker due to COVID-19 exhibited higher levels of burnout. Furthermore, those who had 6–9 years of service, lacked knowledge about COVID-19, had no COVID-19 training, and lost a healthcare worker due to COVID-19 reported lower levels of job satisfaction. Additionally, participants who had 6-9 years of service, lacked knowledge about COVID-19, had no COVID-19 training, and experienced the loss of a healthcare worker due to COVID-19 displayed a greater intention to leave the profession.

CONCLUSIONS:

It is important to implement improvement initiatives that will increase the motivation and job satisfaction of PHEHW. These include the regulation of working hours and shifts, augmenting staff numbers, enhancing working conditions, improving salaries, and implementing strategies aimed at fostering motivation and job satisfaction.

Keywords

Pandemic COVID-19 pre-hospital emergency healthcare workers emotional burnout job satisfaction intention to leave the profession

1 Introduction

In December 2019, a novel and unidentified pneumonia outbreak emerged in Wuhan City, Hubei Province, China. The virus causing this outbreak, known as COVID-19, was considered a relative of the Middle East respiratory syndrome (MERS) and the severe acute respiratory syndrome (SARS) pathogens. Due to its ease of transmission through droplets and close contact from person to person, COVID-19 rapidly spread worldwide within approximately three months and was declared a pandemic by the World Health Organization (WHO) on March 11, 2020 [1]. According to the WHO’s situation reports as of February 5, 2022, there have been 386,548,962 COVID-19 cases and 5,705,754 deaths reported globally. In Turkey, the total number of cases was 11,939,804, with a total of 88,064 deaths [2].

With the onset of the COVID-19 pandemic, healthcare workers assumed critical responsibilities in controlling and preventing the spread of the virus, as well as in providing patient care and treatment [3, 4]. One of the professional groups in the healthcare sector adversely affected by the COVID-19 outbreak was the pre-hospital emergency healthcare (PHEH) workers, who provide services 24/7 and are required to deliver rapid and effective care in risky and unpredictable conditions during life-and-death situations. Ambulances used in PHEH have limited and confined spaces, and the PHEH workers have to intervene with patients under challenging working conditions, which significantly increases the risk of being contaminated with infectious agents, even with the necessary precautions taken [5]. Furthermore, certain resuscitation interventions such as manual ventilation before intubation, non-invasive ventilation, and tracheal intubation can lead to substantial contamination with the COVID-19 virus [6].

PHEH workers are already at a high risk of experiencing burnout and reduced job satisfaction due to issues such as overutilization of PHEH services, working in a shift-based system, low wages, challenging working conditions, exposure to traumatic events experienced by people continuously, and serving in non-secure environments similar to other healthcare institutions [7]. During the COVID-19 pandemic, these healthcare workers faced numerous additional problems, including an increase in workload, the risk of infection, uncertainty about the disease and its treatment, compliance with new protocols and rules, inadequate materials and equipment, difficulties of working with personal protective equipment during long working hours, the possibility of transmitting the virus to their families or others, excessive workload, long working hours, lack of leave rights, communication issues within the team, and lack of support from supervisors [8]. These factors have further worsened the working environment for PHEH workers, reduced their job satisfaction, led to burnout, and increased their desire to leave the profession.

Although studies have explored the effects of the COVID-19 pandemic on healthcare workers, limited research has specifically focused on PHEH workers. In a study conducted with 335 Emergency Medical Technicians (EMTs) working in pre-hospital emergency healthcare services in Iran, the relationship between the risk of exposure to COVID-19 and burnout in EMTs was assessed. According to the results, 41.9% of the personnel were at risk of burnout, while 32.7% had experienced burnout. The study determined that pre-hospital emergency service personnel with a high occupational exposure risk to COVID-19 also had a high risk of burnout [9]. Mousavi and colleagues examined the ethical work environment and intention to leave among 315 EMTs during the COVID-19 pandemic. The participants in their study rated their intention to leave the job at a moderate level with an average score of 12.54 (±4.52) [10]. Another study involving 134 participants, including EMTs and paramedics, examined moral distress, burnout, and job satisfaction during the COVID-19 pandemic. The mean job satisfaction score was 3.63±1.07, and the mean burnout score was 35.45±5.04. It was found that burnout and job satisfaction were significantly related [11]. A study conducted in Slovenia examined sleep deprivation and burnout syndrome among pre-hospital emergency healthcare workers. The study revealed that 17.6% of the participants experienced high levels of burnout, 32.8% exhibited high levels of depersonalization, and 9.3% showed low levels of personal accomplishment [12]. As observed, studies have investigated the relationship between various variables and burnout, job satisfaction, and intention to leave the profession among pre-hospital emergency healthcare service (PHEH) workers. However, a study specifically exploring the relationship among these three variables in PHEH workers has not been encountered. Therefore, this study aimed to examine the emotional burnout and job satisfaction levels, and intention to leave the profession among PHEH workers during the COVID-19 pandemic, as well as the factors influencing these aspects.

Occupational satisfaction, burnout and intention to leave the profession are very important concepts in terms of patient care quality and patient safety. [13]. These outcomes are interconnected and can influence each other, while being influenced by various factors [13]. Ensuring job satisfaction among PHEH workers is of great importance for delivering high-quality emergency medical services to patients [3].

1.1 Research questions

The study addressed the following research questions:

Did the COVID-19 pandemic affect the emotional burnout, job satisfaction, and intention to leave the profession among PHEH workers?

Is there a relationship between emotional burnout, job satisfaction, and intention to leave the profession among PHEH workers during the COVID-19 pandemic and their sociodemographic characteristics?

Materials and methods

2.1 Design

The data for this cross-sectional and descriptive study were collected between February and April 2022 from active paramedics and emergency medical technicians (EMTs) who were working in the field of PHEH and who were the members of the Association of All Emergency Medical Technicians and Paramedics (TAPDER).

2.2 Research population

The research population consisted of active paramedics and emergency medical technicians (EMTs) who were the members of the Association of All Emergency Medical Technicians and Paramedics (TAPDER) and working in the field of PHEH (n = 2500). The sample size was determined using the openepi program, considering the population size (n = 2500), a 5% margin of error, a 95% confidence level, and a 50% prevalence rate, and it was found that a minimum of 334 participants must be reached. Invitations to participate in the study were sent to the entire population via TAPDER, and the final sample included individuals who voluntarily agreed to participate, resulting in a sample size of 401.

2.3 Dependent and independent variables

2.3.1 Dependent variables

The emotional burnout, job satisfaction, and intention to leave the profession scale scores of the PHEH workers were used.

2.3.2 Independent variables

The sociodemographic characteristics were included in the Sociodemographic Data Form.

2.4 Data collection tools

The Sociodemographic Data Form, the Emotional Burnout Scale, the Job Satisfaction Scale, and the Intention to Leave the Profession Scale were used to collect data.

2.4.1 Sociodemographic data form

The form was prepared by the researchers based on the literature. It consists of 13 questions related to age, gender, education level, income status, job title, total years of service in the profession, working shift, and other sociodemographic characteristics.

2.4.2 Emotional burnout scale (EBS)

The emotional burnout subscale of the Maslach Burnout Inventory was utilized [14]. Adaptation of the scale to Turkish was conducted by Ergin [15]. The scale comprises 9 items on a five-point Likert scale, with response options ranging from “Strongly Disagree = 1” to “Strongly Agree = 5”. Higher scores indicate a higher level of emotional burnout. In Ergin’s study, the scale demonstrated a Cronbach’s alpha internal consistency value of 0.83 [15]. In this study, the Cronbach’s alpha of the scale was found to be.71.

2.4.3 Job satisfaction scale (JSS)

The scale was developed by Özer and colleagues to assess employees’ level of job satisfaction [16]. The validity and reliability study of the scale was also conducted by Özer and colleagues [16]. It consists of 6 items on a five-point Likert scale, with response options ranging from “Strongly Disagree = 1” to “Strongly Agree = 5”. Higher scores indicate a higher level of job satisfaction. In the study by Özer et al., the Cronbach’s alpha of the scale was found to be.79 [16]. In this study, the Cronbach’s alpha was found to be.80.

2.4.4 Intention to leave the profession scale (ILPS)

The validity and reliability study of the scale, which was conducted by Özer and colleagues, measures employees’ intention to leave the profession [16]. The scale consists of 9 items on a five-point Likert scale, with response options ranging from “Strongly Disagree = 1” to “Strongly Agree = 5”. Higher scores indicate a higher intention to leave the profession [16]. In the study by Özer and colleagues, the Cronbach’s alpha was found to be.92 [16]. In this study, the Cronbach’s alpha was found to be .95.

2.5 Data collection process

The data collection instruments of the study were sent to the active email addresses currently used by the paramedics and emergency medical technicians (EMTs) from a pre-established reliable email address. The email sent to the participants included a voluntary informed consent form explaining the data collection tools and the purpose and scope of the research. Those who agreed to participate in the study clicked the “I agree to participate in the study” button before filling out the scales, allowing them to proceed with the study. In this way, digital consent was obtained. The paramedics and EMTs who volunteered to take part in the study completed the data collection instruments online. The survey was administered with certain measures to prevent multiple responses by implementing address blocking. The maximum time allowed for completing the data collection instruments was set to be 10–15 minutes.

2.6 Statistical analysis

The data were analyzed using the SPSS 24 software package. Descriptive statistics such as frequency, percentage, mean, and standard deviation was used for data analysis. The normality of the data was tested using Kolmogorov-Smirnov and Shapiro-Wilk tests. For variables that exhibited a normal distribution, One-Way Analysis of Variance (ANOVA) tests and t-tests were conducted. Spearman’s correlation analysis was applied to examine the relationships between the scales. The reliability of the scales was determined using Cronbach’s alpha reliability analysis. Ordinal Logistic Regression analysis was performed to determine the cause-effect relationship between dependent variables and independent variables. The results were evaluated at a 95% confidence interval with a significance level of p < 0.05.

2.6.1 Ethical considerations

The study was conducted following the principles of the Helsinki Declaration. Prior to the study, approval was obtained from the University’s Medical Research Ethics Committee. Written permission was also obtained from the Turkish Ministry of Health and the Association of All Emergency Medical Technicians and Paramedics (TAPDER) to conduct the study. The principles of confidentiality and voluntariness were clearly explained to all the participants, and informed consent was obtained from each participant before data collection.

3 Results

3.1 Distribution of the sociodemographic characteristics of the participants

A total of 401 PHEH workers participated in the study. Among the participants, 53% were female, 32% were in the age group of 25–29, 58% were married, 51% had children, 53% had the professional title of Emergency Medical Technician (EMT), 32% had a service period of 2–5 years, 83.5% worked exclusively on a shift basis, and 32% had a working time of 180–200 hours a month (Table 1).

Table 1
Distribution of some sociodemographic characteristics of the participants

Variable n %

Gender

Male 188 46.8

Female 213 53.2

Age group

19–24 91 22.4

25–29 129 32.3

30–34 74 18.5

35–39 79 19.8

40 and above 28 7.0

Marital status

Married 234 58.4

Single 167 41.6

Status of having a child

Yes 203 50.6

No 198 49.4

Professional title

Emergency medical technician 212 52.9

Paramedic 189 47.1

Total years of service in the profession

2–5 131 32.5

6–9 83 20.8

10–14 108 26.9

15 years and above 79 19.8

Working shift

Full-time day shift 21 5.3

Full-time night shift 5 1.2

Night/day shift rotation 32 8.0

Full-time day shift and occasional night shifts 8 2.0

On-call/standby only 335 83.5

Average monthly total working hours during the pandemic (hours)

160–180 107 26.7

180–200 127 31.7

200–220 45 11.2

220–240 67 16.7

240–280 43 10.7

280 hours and above 12 3.0

Total 401 100

Variable	n	%
Gender
Male	188	46.8
Female	213	53.2
Age group
19–24	91	22.4
25–29	129	32.3
30–34	74	18.5
35–39	79	19.8
40 and above	28	7.0
Marital status
Married	234	58.4
Single	167	41.6
Status of having a child
Yes	203	50.6
No	198	49.4
Professional title
Emergency medical technician	212	52.9
Paramedic	189	47.1
Total years of service in the profession
2–5	131	32.5
6–9	83	20.8
10–14	108	26.9
15 years and above	79	19.8
Working shift
Full-time day shift	21	5.3
Full-time night shift	5	1.2
Night/day shift rotation	32	8.0
Full-time day shift and occasional night shifts	8	2.0
On-call/standby only	335	83.5
Average monthly total working hours during the pandemic (hours)
160–180	107	26.7
180–200	127	31.7
200–220	45	11.2
220–240	67	16.7
240–280	43	10.7
280 hours and above	12	3.0
Total	401	100

As far as COVID-19 is concerned, 35% stated that they had a good level of knowledge about COVID-19, 78% received COVID-19 related training, 83% got tested for COVID-19, and 46% reported that they lost an acquaintance due to COVID-19 (Table 3).

3.2 The EBS, JSS and ILPS mean scores of the participants and the relationship between these mean scores

The mean scores of the participants on the EBS was 3.18±0.60 (min = 1 –max = 5). Their mean scores on the JSS and ILPS were 3.02±0.85 (min = 1 –max = 5) and 3.24±1.08 (min = 1 –max = 5), respectively (Table 2).

Table 2
The participants’ mean scores obtained from the EBS, JSS, and ILPS and the relationship between the means (n = 401)

X±SD Min - Max EBS JSS ILPS

r p r p r p

EBS 3.18±.60 1–5 –

JSS 3.02±.85 1–5 –0.562 0.000^* –

ILPS 3.24±1.08 1–5 0.687 0.000^* –0.694 0.000^* –

	X±SD	Min - Max	EBS	JSS	ILPS
EBS	3.18±.60	1–5	–
JSS	3.02±.85	1–5	–0.562	0.000^*	–
ILPS	3.24±1.08	1–5	0.687	0.000^*	–0.694	0.000^*	–

^*p < 0.05. r = Spearman correlation analysis.

A statistically significant moderate negative relationship was found between the participants’ mean scores on the EBS and the JSS (r = –0.562; p = 0.000). As the level of emotional burnout increased, the level of job satisfaction decreased (Table 2).

There was a statistically significant moderate positive relationship between the participants’ mean scores on the EBS and the ILPS (r = .687; p = .000). As the level of emotional burnout increased, the level of intention to leave the profession also increased (Table 2).

A statistically significant moderate negative relationship was observed between the participants’ mean scores on the ILPS and the JSS (r = –0.694; p = 0.000). As the level of intention to leave the profession increased, the level of job satisfaction decreased (Table 2).

3.3 The distribution of the mean scores on the EBS, JSS, and ILPS according to the participants’ sociodemographic characteristics and other variables

No statistically significant difference was found between the participants’ gender, marital status, status of having a child, professional titles, working shift, average monthly total working hours during the pandemic period, and EBS mean scores (p > 0.05). There was a statistically significant difference between the participants’ age groups, total years of service in the profession, levels of knowledge about COVID-19, COVID-19 related training received, COVID-19 testing status, COVID-19 related loss of an acquaintance, and their EBS mean score (p < 0.05). The participants who had 6–9 years of experience in the profession, had no knowledge about COVID-19, did not receive COVID-19 training, underwent COVID-19 testing, and lost a healthcare worker due to COVID-19 were found to have higher EBS scores (Table 3).

There was no statistically significant difference between the participants’ gender, marital status, status of having a child, professional titles, working shift, average monthly total working hours during the pandemic period, COVID-19 test status, and JSS mean scores (p > 0.05). A statistically significant difference was found between the participants’ age groups, total years of service in the profession, levels of knowledge about COVID-19, COVID-19 related training received, COVID-19 related loss of an acquaintance, and their JSS mean score (p < 0.05). Those who were in the 19–24 age group, had 6–9 years of experience in the profession, had no knowledge about COVID-19, had no COVID-19 training, and lost a healthcare worker due to COVID-19 were found to have lower levels of job satisfaction (Table 3).

Table 3
The distribution of participants’ o EBS, JSS, and ILPS mean scores according to certain variables (n = 401)

Descriptive characteristics n % EBS JSS ILPS

$\bar{X}$ ±SD Test $\bar{X}$ ±SD Test $\bar{X}$ ±SD Test

Gender

Male 188 46.8 3.18±.63 t = –0.800 2.97±.84 t = –0.810 3.31±1.08 t = –0.983

Female 213 53.2 3.18±.58 p = 0.936 3.04±.85 p = 0.418 3.20±1.08 p = 0.326

Age group

19–24 91 22.4 3.13±.59 2.80±.85 3.02±1.09

25–29 129 32.3 3.28±.62 3.25±.84 3.41±1.16

30–34 74 18.5 3.29±.56 F = 3.853 2.92±.83 F = 4.785 3.35±1.09 F = 2.294

35–39 79 19.8 3.08±.57 p = 0.004^* 3.12±.80 p = 0.001* 3.22±.93 p = 0.600

40 and above 28 7.0 2.89±.64 3.20±.83 2.98±.96

Marital status

Married 234 58.4 3.19±.58 t = 0.132 3.05±.84 t = 0.912 3.24±1.07 t = –0.013

Single 167 41.6 3.18±.64 p = 0.895 2.97±.86 p = 0.363 3.24±1.11 p = 0.990

Status of having a child

Yes 203 50.6 3.17±.59 t = 0.180 3.02±.86 t = 0.210 3.27±1.05 t = 0.523

No 198 49.4 3.19±.61 p = 0.671 3.00±.85 p = 0.834 3.22±1.12 p = 0.602

Professional title

Emergency medical technician 212 52.9 3.20±.58 t = 0.538 3.02±.85 t = 0.285 3.17±1.12 t = –1.483

Paramedic 189 47.1 3.16±.63 p = 0.591 3.00±.85 p = 0.776 3.33±1.04 p = 0.139

Total years of service in the profession

2–5 131 32.5 3.08±.61 3.20±.83 2.97±1.12

6–9 83 20.8 3.38±.56 F = 6.609 2.73±.85 F = 5.849 3.47±1.08 F = 4.928

10–14 108 26.9 3.27±.59 p = 0.000* 2.95±.81 p = 0.001* 3.41±1.07 p = 0.002*

15 years and above 79 19.8 3.05±.59 3.09±.86 3.22±.94

Working shift

Full-time day shift 21 5.3 2.78±.58 3.21±.89 3.23±1.32

Full-time night shift 5 1.2 3.31±.93 F = 1.505 3.20±.94 F = 0.585 3.31±1.60 F = 0.828

Night/day shift rotation 32 8.0 3.40±.58 p = 0.200 3.01±.95 p = 0.674 3.23±1.12 p = 0.508

Full-time day shift and occasional night shifts 8 2.0 3.18±.31 2.73±.62 3.93±.93

On-call/standby only 335 83.5 3.04±.60 3.00±.84 3.23±1.06

Average monthly total working hours during the pandemic (hours)

160–180 107 26.7 3.17±.59 3.13±.83 3.13±1.04

180–200 127 31.7 3.17±.60 3.00±.86 3.31±1.02

200–220 45 11.2 3.16±.68 F = 0.153 2.86±.83 F = 0.839 3.48±.94 F = 0.995

220–240 67 16.7 3.20±.61 p = 0.979 3.02±1.01 p = 0.523 3.27±1.21 p = 0.420

240–280 43 10.7 3.22±.57 2.91±.65 3.07±1.18

280 hours and above 12 3.0 3.29±.52 2.96±.73 3.20±1.39

Knowledge about COVID-19

None 42 10.5 3.43±.60 2.57±.57 3.67±.92

Little 53 13.2 3.33±.48 F = 3.803 2.67±.72 F = 10.412 3.53±.96 F = 3.685

Moderate 70 17.5 3.15±.55 p = 0.005^* 2.92±.68 p = 0.000^* 3.25±.94 p = 0.006^*

Good 139 34.7 3.11±.57 3.08±.87 3.11±1.06

Very good 97 24.1 3.13.70 3.36±.93 3.09±1.27

Having received training on COVID-19

Yes 314 78.2 3.11±.61 t = –5.222 3.09±.85 t = 3.722 3.13±1.09 t = –4.327

No 87 21.8 3.44±.50 p = 0.000^* 2.71±.78 p = 0.000^* 3.65±.96 p = 0.000^*

COVID-19 test status

Yes 332 82.8 3.21±.60 t = 2.231 2.99±.86 t = –1.107 3.27±1.10 t = 0.851

No 69 17.2 3.04±.62 p = 0.026^* 3.12±.79 p = 0.269 3.14±1.01 p = 0.395

Loss of someone known due to COVID-19

A family member 51 12.7 2.97±.77 3.28±.93 3.03±1.23

A colleague from the same team 4 1.0 2.78±.65 F = 7.432 2.83±1.31 F = 3.745 3.00±.40 F = 5.706

A healthcare worker I know 37 9.2 3.59±.45 p = 0.000^* 2.59±.68 p = 0.005^* 3.96±.85 p = 0.000^*

An acquaintance 183 45.6 3.22±.54 3.00±.82 3.28±1.02

I haven’t experienced any loss 126 31.4 3.11±.60 3.05±.85 3.08±1.10

Descriptive characteristics	n	%	EBS	JSS	ILPS
Gender
Male	188	46.8	3.18±.63	t = –0.800	2.97±.84	t = –0.810	3.31±1.08	t = –0.983
Female	213	53.2	3.18±.58	p = 0.936	3.04±.85	p = 0.418	3.20±1.08	p = 0.326
Age group
19–24	91	22.4	3.13±.59		2.80±.85		3.02±1.09
25–29	129	32.3	3.28±.62		3.25±.84		3.41±1.16
30–34	74	18.5	3.29±.56	F = 3.853	2.92±.83	F = 4.785	3.35±1.09	F = 2.294
35–39	79	19.8	3.08±.57	p = 0.004^*	3.12±.80	p = 0.001*	3.22±.93	p = 0.600
40 and above	28	7.0	2.89±.64		3.20±.83		2.98±.96
Marital status
Married	234	58.4	3.19±.58	t = 0.132	3.05±.84	t = 0.912	3.24±1.07	t = –0.013
Single	167	41.6	3.18±.64	p = 0.895	2.97±.86	p = 0.363	3.24±1.11	p = 0.990
Status of having a child
Yes	203	50.6	3.17±.59	t = 0.180	3.02±.86	t = 0.210	3.27±1.05	t = 0.523
No	198	49.4	3.19±.61	p = 0.671	3.00±.85	p = 0.834	3.22±1.12	p = 0.602
Professional title
Emergency medical technician	212	52.9	3.20±.58	t = 0.538	3.02±.85	t = 0.285	3.17±1.12	t = –1.483
Paramedic	189	47.1	3.16±.63	p = 0.591	3.00±.85	p = 0.776	3.33±1.04	p = 0.139
Total years of service in the profession
2–5	131	32.5	3.08±.61		3.20±.83		2.97±1.12
6–9	83	20.8	3.38±.56	F = 6.609	2.73±.85	F = 5.849	3.47±1.08	F = 4.928
10–14	108	26.9	3.27±.59	p = 0.000*	2.95±.81	p = 0.001*	3.41±1.07	p = 0.002*
15 years and above	79	19.8	3.05±.59		3.09±.86		3.22±.94
Working shift
Full-time day shift	21	5.3	2.78±.58		3.21±.89		3.23±1.32
Full-time night shift	5	1.2	3.31±.93	F = 1.505	3.20±.94	F = 0.585	3.31±1.60	F = 0.828
Night/day shift rotation	32	8.0	3.40±.58	p = 0.200	3.01±.95	p = 0.674	3.23±1.12	p = 0.508
Full-time day shift and occasional night shifts	8	2.0	3.18±.31		2.73±.62		3.93±.93
On-call/standby only	335	83.5	3.04±.60		3.00±.84		3.23±1.06
Average monthly total working hours during the pandemic (hours)
160–180	107	26.7	3.17±.59		3.13±.83		3.13±1.04
180–200	127	31.7	3.17±.60		3.00±.86		3.31±1.02
200–220	45	11.2	3.16±.68	F = 0.153	2.86±.83	F = 0.839	3.48±.94	F = 0.995
220–240	67	16.7	3.20±.61	p = 0.979	3.02±1.01	p = 0.523	3.27±1.21	p = 0.420
240–280	43	10.7	3.22±.57		2.91±.65		3.07±1.18
280 hours and above	12	3.0	3.29±.52		2.96±.73		3.20±1.39
Knowledge about COVID-19
None	42	10.5	3.43±.60		2.57±.57		3.67±.92
Little	53	13.2	3.33±.48	F = 3.803	2.67±.72	F = 10.412	3.53±.96	F = 3.685
Moderate	70	17.5	3.15±.55	p = 0.005^*	2.92±.68	p = 0.000^*	3.25±.94	p = 0.006^*
Good	139	34.7	3.11±.57		3.08±.87		3.11±1.06
Very good	97	24.1	3.13.70		3.36±.93		3.09±1.27
Having received training on COVID-19
Yes	314	78.2	3.11±.61	t = –5.222	3.09±.85	t = 3.722	3.13±1.09	t = –4.327
No	87	21.8	3.44±.50	p = 0.000^*	2.71±.78	p = 0.000^*	3.65±.96	p = 0.000^*
COVID-19 test status
Yes	332	82.8	3.21±.60	t = 2.231	2.99±.86	t = –1.107	3.27±1.10	t = 0.851
No	69	17.2	3.04±.62	p = 0.026^*	3.12±.79	p = 0.269	3.14±1.01	p = 0.395
Loss of someone known due to COVID-19
A family member	51	12.7	2.97±.77		3.28±.93		3.03±1.23
A colleague from the same team	4	1.0	2.78±.65	F = 7.432	2.83±1.31	F = 3.745	3.00±.40	F = 5.706
A healthcare worker I know	37	9.2	3.59±.45	p = 0.000^*	2.59±.68	p = 0.005^*	3.96±.85	p = 0.000^*
An acquaintance	183	45.6	3.22±.54		3.00±.82		3.28±1.02
I haven’t experienced any loss	126	31.4	3.11±.60		3.05±.85		3.08±1.10

^*p < 0,05. t = t test F = One way ANOVA test.

There was no statistically significant difference between the participants’ gender, age group, marital status, status of having a child, professional titles, working shift, average monthly total working hours during the pandemic period, COVID-19 test status, and ILPS mean scores (p > 0.05). A statistically significant difference was found between the participants’ total years of service in the profession, levels of knowledge about COVID-19, COVID-19 related training received, COVID-19 related loss of an acquaintance, and their ILPS mean score (p < 0.05). The participants who had 6–9 years of service in the profession, had no knowledge about COVID-19, had no COVID-19 training, and lost a healthcare worker due to COVID-19 were found to have higher intention to leave the profession (Table 3).

3.4 Ordinal logistic regression analysis of the EBS, JSS and ILPS mean scores with independent variables

The relationship between the mean EBS, JSS and ILPS scores and the independent variables was examined with the ordinal logistic regression analysis (Table 4).

Table 4
Ordinal logistic regression analysis of the EBS, JSS, and ILPS mean scores with independent variables

Variables ß Standard error Wald e^ß p

EBS

Age group 19–24 (1) 1.334 0.572 5.443 3.796 0.020^*

25–29 (2) 0.861 0.506 2.902 2.366 0.088

30–34 (3) 0.867 0.449 3.730 2.381 0.053

35–39 (4) 0.410 0.395 1.078 1.506 0.299

40 and above (5) 0^a – – – –

Having received Yes (1) –0.501 0.225 4.973 0.606 0.026^*

training on COVID-19 No (2) 0^a – – – –

COVID-19 test status Yes (1) 0.558 0.237 5.520 1.747 0.019^*

No (2) 0^a – – – –

JSS

Knowledge about COVID-19 None (1) –1.190 0.346 11.834 0.304 0.001^*

Little (2) –1.100 0.314 12.297 0.332 0.000^*

Moderate (3) –0.728 0.287 6.410 0.483 0.011^*

Good (4) –0.454 0.241 3.542 0.635 0.060

Very good (5) 0^a

ILPS

Loss of someone known due to COVID-19 A family member (1) 0.707 0.300 5.564 2.027 0.018^*

A colleague from the same team (2) 0.138 0.890 0.024 1.148 0.877

A healthcare worker I know (3) 0.979 0.355 7.631 2.662 0.006^*

An acquaintance (4) 0.374 0.205 3.337 1.453 0.068

I haven’t experienced any loss (5) 0^a

Variables		ß	Standard error	Wald	e^ß	p
	EBS
Age group	19–24 (1)	1.334	0.572	5.443	3.796	0.020^*
	25–29 (2)	0.861	0.506	2.902	2.366	0.088
	30–34 (3)	0.867	0.449	3.730	2.381	0.053
	35–39 (4)	0.410	0.395	1.078	1.506	0.299
	40 and above (5)	0^a	–	–	–	–
Having received	Yes (1)	–0.501	0.225	4.973	0.606	0.026^*
training on COVID-19	No (2)	0^a	–	–	–	–
COVID-19 test status	Yes (1)	0.558	0.237	5.520	1.747	0.019^*
	No (2)	0^a	–	–	–	–
		JSS
Knowledge about COVID-19	None (1)	–1.190	0.346	11.834	0.304	0.001^*
	Little (2)	–1.100	0.314	12.297	0.332	0.000^*
	Moderate (3)	–0.728	0.287	6.410	0.483	0.011^*
	Good (4)	–0.454	0.241	3.542	0.635	0.060
	Very good (5)	0^a
		ILPS
Loss of someone known due to COVID-19	A family member (1)	0.707	0.300	5.564	2.027	0.018^*
	A colleague from the same team (2)	0.138	0.890	0.024	1.148	0.877
	A healthcare worker I know (3)	0.979	0.355	7.631	2.662	0.006^*
	An acquaintance (4)	0.374	0.205	3.337	1.453	0.068
	I haven’t experienced any loss (5)	0^a

Note: ^*p < 0,05. ß= estimate, e^ß = odds ratio.

Table 4 shows that the reference categories for the variables are the last categories. Therefore, interpretations of the results have been made with respect to each variable, taking the reference categories and the odds ratio (e^ß) into account.

The relationship between the emotional exhaustion variable and the variables of the 19–24 age group (p = 0.020), having received training on COVID-19 (p = 0.026), and COVID-19 test status (p = 0.019) is statistically significant due to the p-values being less than 0.05 (Table 4). The odds ratio was found to be 3.796 for the 19–24 age group variable. Since the β#x03B2; coefficient for the 19–24 age group variable is positive, the odds ratio is greater than 1. When interpreting this variable, it is necessary to consider the odds ratio (eß). According to the analysis results, the likelihood of experiencing emotional exhaustion for participants in the 19–24 age group is 3.80 times higher than for participants aged 40 and above (Table 4).

The relationship between having received training on COVID-19 variable and the emotional exhaustion variable is statistically significant (p = .026). The odds ratio for the having received training on COVID-19 variable was found to be 0.606. Since the β#x03B2; coefficient for this variable is negative, the odds ratio is less than 1. When interpreting this variable, it is necessary to divide 1 by the odds ratio. According to the analysis results, the likelihood of experiencing burnout for participants who did not receive training on COVID-19 is 1.65 times higher than for participants who received training (1/e^ß = 1/0.606) (Table 4).

The likelihood of experiencing burnout for participants who underwent a COVID-19 test was found to be 1.75 times higher than for participants who did not undergo the test (e^ß = 1.747) (Table 4).

The relationship between the variables of having no knowledge about COVID-19 (p = .001), having little knowledge (p = .000), having moderate knowledge (p = .011), and the variable of professional satisfaction is statistically significant due to the p-values being less than 0.05 (Table 4). For participants who had very good knowledge about COVID-19, the likelihood of being satisfied with their profession was found to be 3.29 times higher than the likelihood for those who had no knowledge about COVID-19 (1/e^ß = 1/0.304). Similarly, for participants who had very good knowledge about COVID-19, the likelihood of being satisfied with their profession was found to be 3.01 times higher than the likelihood for those who had little knowledge (1/e^ß = 1/0.332). Additionally, for participants who had very good knowledge about COVID-19, the likelihood of being satisfied with their profession was 2.07 times higher than the likelihood for those who had moderate knowledge (1/ e^ß = 1/0.483) (Table 4).

The relationship between the variables of losing a family member due to COVID-19 (p = .018) and losing an acquaintance who is a healthcare worker due to COVID-19 (p = .006), and the variable of intention to leave the profession is statistically significant as the p-values are less than 0.05 (Table 4). For participants who lost a family member due to COVID-19, the likelihood of leaving the profession was 2.03 times higher than the likelihood for participants who did not lose a family member due to COVID-19 (e^ß = 2.027). Similarly, for participants who lost an acquaintance who is a healthcare worker due to COVID-19, the likelihood of leaving the profession was found to be 2.66 times higher than the likelihood for participants who did not lose an acquaintance due to COVID-19 (e^ß = 2.662).

4 Discussion

This study was conducted to investigate the PHEH workers’ emotional burnout, job satisfaction, and intention to leave the profession during the COVID-19 pandemic.

This study revealed that the participants exhibited emotional burnout scores at a moderate level. A similar finding was reported in a study conducted in Taiwan, where the emotional burnout levels of PHEH workers were found to be at a moderate level [17]. In a comparison study conducted by Petrie and colleagues in Australia, it was found that paramedics had higher emotional burnout scores compared to other healthcare workers [18]. The existing literature [19, 20] has consistently highlighted the heightened emotional burnout experienced by healthcare workers during the COVID-19 pandemic. The findings of our study align with this trend, indicating that pre-hospital emergency healthcare (PHEH) workers, who already operated in an environment prone to burnout outside the pandemic, became even more susceptible to burnout during the COVID-19 crisis. Various factors, such as the significant number of fatalities, uncertainties surrounding COVID-19, extended working hours, a continuously rising influx of patients, perpetual vigilance against disease transmission, physical constraints due to protective gear, and the loss of spontaneity and autonomy, contributed to this heightened vulnerability [21, 22]. The evident conclusion is that measures should be implemented to bolster the psychological resilience of all healthcare workers, with a particular focus on PHEH workers, especially in challenging working conditions like those presented during the pandemic.

The current study found that the participants demonstrated job satisfaction scores at a moderate level. Previous studies have also found a decrease in the job satisfaction of healthcare workers during the COVID-19 pandemic [3 , 24]. The dissatisfaction with the work and lack of enthusiasm, leading to a lack of mental well-being, can create serious issues for the PHEH workers, resulting in improper practices and unsuccessful interventions [23]. The satisfaction of the PHEH workers with their work may enhance the success and quality of healthcare services provided during critical stages that are vital for the patients. Based on our study’s findings, it is deemed crucial to prioritize the creation of conducive working conditions and job satisfaction for pre-hospital emergency healthcare (PHEH) workers, given the critical nature of their profession, involving a constant struggle between life and death.

The intention to leave the job refers to employees’ behavioral attitude of wanting to leave the organization where they work. The intention to leave the job arises as a result of employees’ dissatisfaction with the job and working conditions provided by the organization. As stated in the literature, healthcare workers have been under immense pressure during the COVID-19 pandemic, to the extent that many individuals have started to feel concerned about their jobs and even considered leaving their positions [25]. Similarly, this study found that the participants exhibited intention to leave the job scores at a moderate level. The departure of high-performing healthcare workers can also impact the motivation and productivity of other staff members. Until a replacement is found for the vacant position, the remaining employees within the organization have to work harder to fill the gap. This can lead to an increase in the workload and a decrease in the motivation of the remaining PHEH workers who continue to work, thus affecting their efficiency.

The experience of burnout among the PHEH workers and their low level of job satisfaction can lead to an increased intention to leave the job. In this study, it was found that as participants’ emotional burnout levels increased, their job satisfaction decreased, and their intention to leave the job heightened. It has been revealed in studies in the literature that the constant exposure of health workers to stress during the COVID-19 pandemic reduced their professional efficiency, created a sense of burnout in employees, and caused a desire in them to leave the job. In a study conducted in the Netherlands, a negative relationship was found between emotional burnout and job commitment [26]. In another study, it was observed that healthcare workers who were satisfied with their jobs had higher levels of positive emotions, while those who were dissatisfied with their jobs had higher levels of overall burnout [27]. The existing literature also indicates that individuals experiencing emotional burnout tend to distance themselves from the job that is overwhelming them [28].

During the COVID-19 pandemic, it was crucial for healthcare workers to feel satisfied with their current jobs and lives without having the intention to leave their positions. A study conducted in Turkey revealed that nurses providing care to COVID-19 patients had low levels of job satisfaction, which had an impact on their intention to leave their jobs [29]. Similarly, in this study, it was found that as participants’ intention to leave their job increased, their job satisfaction level decreased, which aligns with the existing literature. The increased workload, decreased work performance, inability to fully meet the demands of their job and profession, fear of contracting the COVID-19 virus and transmitting it to their families, and feelings of emotional vulnerability presented challenges to the PHEH workers during the pandemic, posing a social problem. As a result, they questioned their profession, leading to a decrease in job satisfaction.

Healthcare workers have experienced constant fear of infection due to the contagious nature of the virus, unknown transmission routes, close contact with patients, and colleagues getting sick [30]. Existing literature shows that there are many factors that contribute to burnout and intention to leave the profession among healthcare workers, leading to a decrease in job satisfaction. Some of these reasons are shown as sociodemographic characteristics. Therefore, in our study, we also examined whether there was a relationship between the sociodemographic characteristics of the participants and the dependent variables of the study.

According to the analysis results, the likelihood of experiencing emotional exhaustion for participants in the 19–24 age group is 3.80 times higher than for participants aged 40 and above. As age decreases, emotional exhaustion levels tend to increase, and professional satisfaction tends to decrease. Consistent with this study, similar findings in the literature describe younger workers as having a higher likelihood of experiencing emotional exhaustion compared to older individuals [14]. A large-scale study with nurses in China also identified a tendency for younger healthcare professionals to exhibit higher levels of burnout [31]. Older employees are generally more experienced, and as a result, they may develop more effective coping mechanisms for potential traumatic stressors. It is speculated that the study’s outcome may be attributed to this factor.

In this study, it was found that the participants who did not receive any COVID-19 training or have no knowledge about the disease had higher levels of emotional burnout and intention to leave their profession, and their job satisfaction level was lower compared to other groups. A study conducted in Wuhan, China reported a significant decrease in concerns about the disease among healthcare professionals who received COVID-19 training compared to those who did not receive such training [32]. Another study revealed that in-service training during the COVID-19 period positively affected the emotional state of healthcare workers [33]. De Los Santos and Labrague (2021) attributed the high level of COVID-19 fear among nurses to lack of COVID-19 training [3]. Another study found that keeping healthcare workers informed with the latest information reduced the fear of uncertainty and negative emotions associated with the virus [34].

Many EMTs and paramedics who provided initial treatment and transportation for the COVID-19 diagnosed patients in the back cabin of ambulances tested positive for the virus, and some of them even lost their lives [35]. This study revealed that individuals who underwent COVID-19 testing had higher levels of emotional burnout and intention to leave their profession compared to those who did not get tested, and their job satisfaction level was lower. As stated in the literature, healthcare workers who were aware of their contact with COVID-19 positive patients had higher stress levels compared to those who were not aware, and stress on its own can adversely affect a person’s health and increase the likelihood of experiencing burnout [36]. In the COVID-19 pandemic strategy, until a safe vaccine was found, detecting and reducing its transmission was crucial through measures such as social distancing, isolation, and testing [37]. Undergoing a COVID-19 test implies direct exposure to the disease. Given the initial scarcity of personal protective equipment and vaccination for pre-hospital emergency healthcare (PHEH) workers during the early stages of the pandemic, it can be anticipated that they encountered elevated levels of fear, stress, and burnout through patient interactions. Consequently, this heightened exposure contributed to a decline in job satisfaction and an increased inclination to consider leaving the profession among PHEH workers.

The findings of this study indicate that individuals who experienced the loss of a healthcare worker they knew due to COVID-19 exhibited elevated levels of emotional burnout and a heightened intention to leave the profession. In addition, their level of job satisfaction was observed to be lower. Throughout the pandemic, healthcare workers, including EMTs and paramedics, confronted the necessity of isolating themselves from their own families due to the apprehension of transmitting the virus to their loved ones [38]. In addition to enduring mental health challenges such as the fear of infection, insufficient social support, a demanding workload, shortages of personal protective equipment, and the illness or demise of their colleagues, these professionals experienced burnout, a decline in job satisfaction, and an inclination to leave the profession [39]. Despite the escalating number of healthcare workers contracting the virus and losing their lives, coupled with the ongoing fear of transmitting the virus to their colleagues, families, and friends, both they and pre-hospital emergency healthcare workers persisted in the frontline battle to fulfill their duties.

5 Conclusions

In the current study, pre-hospital emergency healthcare (PHEH) workers exhibited moderate levels of emotional burnout, job satisfaction, and intention to leave the profession. Furthermore, a discernible pattern emerged, indicating that heightened emotional burnout was associated with decreased job satisfaction and an increased intention to leave the profession. Additionally, the study revealed an inverse relationship as the intention to leave the profession increased, job satisfaction concurrently decreased. The PHEH workers who had no knowledge about COVID-19, did not receive any COVID-19 related training, underwent a COVID-19 test, and knew a healthcare worker who lost their life due to COVID-19 were found to have higher levels of emotional burnout and intention to leave the profession, and lower job satisfaction scores. In the battle against COVID-19, maintaining the presence of PHEH workers is imperative for delivering high-quality and secure healthcare services. To mitigate burnout among PHEH workers and retain them in the profession and workplace, a range of measures should be adopted. These include the regulation of working hours and shifts, augmenting staff numbers, enhancing working conditions, improving salaries, and implementing strategies aimed at fostering motivation and job satisfaction.

5.1 Limitations

This study is subject to certain limitations. The data analyzed were collected from paramedics and emergency medical technicians (PHEH workers), relying on self-reported information from these participants. Consequently, the outcomes derived from the analysis of data from 401 participants may not be universally applicable to all PHEH workers. Additionally, the data were gathered within a specific timeframe, and changes in economic, social, and cultural contexts over time could potentially impact the generalizability of the study’s findings. Another limitation is that the study exclusively focused on healthcare workers who volunteered to participate, which may introduce selection bias. The results are confined to the participants’ responses to the scale questions, and there is the possibility that participants intentionally provided misleading answers. Furthermore, as the data collection occurred online, potential drawbacks related to electronic security concerns, respondents’ uncertainties, access issues to survey questions, misinterpretation of research sensitivity, and difficulties accessing the webpage may have influenced the study’s outcomes.

Ethical approval

Approval for the study was obtained from the University’s Medical Research Ethics Committee (Decision No. 49/14 dated 07.12.2021).

Informed consent

The principles of confidentiality and voluntariness were clearly explained to all participants, and informed consent was obtained from each participant before data collection.

Conflict of interest

The authors declare no conflict of interest.

Footnotes

Acknowledgments

We would like to thank all pre-hospital emergency healthcare personnel who voluntarily participated and supported the study.

Funding

None.

References

Sohrabi

, Alsafi

, O’Neill

, Khan

, Kerwan

, Al-Jabir

, Iosifidis

, Agha

. World Health Organization declares global emergency: A review of the novel coronavirus (COVID-19), Int J Surg. 2020;76:71–76. https://doi.org/10.1016/j.ijsu.2020.02.034.

WHO. World Health Organization (WHO), Corona Virus Disease (Covid-19). Date of access: 16.07.2023 https://covid19.who.int/region/euro/country/tr

Labrague

, de Los Santos

JAA

. Fear of COVID-19, psychological distress, work satisfaction and turnover intention among frontline nurses, J Nurs Manag. 2021;29(3):395–403. https://doi.org/10.1111/jonm.13168.

Manzano García

, Ayala Calvo

. The threat of COVID-19 and its influence on nursing staff burnout, J Adv Nurs. 2021;77(2):832–844. https://doi.org/10.1111/jan.14642.

Sönmez

, şahin

, Sucu çakmak

N C

. Determination of depression, anxiety, and stress levels of paramedics and emergency medical technicians in the covid-19 pandemic, Journal of Pre-Hospital. 2022;7(2):219–235

Yang

, Hou

, Lee

, Chiang

, Chien

, Chen

, Ma

. Taipei Azalea - Supraglottic airways (SGA) preassembled with high-efficiency particulate air (HEPA) filters to simplify prehospital airway management for patients with out-of-hospital cardiac arrests (OHCA) during Coronavirus Disease (COVID-19) pandemic, Resuscitation. 2020;151:3–5. https://doi.org/10.1016/j.resuscitation.2020.03.021.

Demirbilek

, Uzman

. Compassion fatigue, compassion satisfaction and burnout among 112 emergency health workers –The case of province of Kayseri, Gümüşhane University Journal of Health Sciences. 2021;10(1):56–69

Duan

, Zhu

. Psychological interventions for people affected by the COVID-19 epidemic, Lancet Psychiatry. 2020;7(4):300–302. https://doi.org/10.1016/S2215-0366(20)30073-0.

Javanmardi

, Gilani

, Ghafourifard

, Dadashzadeh

, Dehghannejad

, Feyzollahzade

. The Relationship between COVID-19 exposure risk and burnout in prehospital emergency medical technicians, J Caring Sci. 2023;12(2):123–128. https://doi.org/10.34172/jcs.2023.31742.

10.

Mousavi

, Kamali

, Bahrami Eyvanaki

. Ethical work climate and the intention to leave the service in emergency medical technicians during the COVID-19 pandemic, J Med Ethics Hist Med. 2022;15, 9.

11.

Nassehi

, Jafari

, Jafari-Oori

, Jafari

. Moral distress, burnout, and job satisfaction in emergency medical technicians during the COVID-19 pandemic, Nurs Midwifery Stud. 2023;12, 48–54.

12.

Kren

, Vladič

. Sleep deprivation and burnout syndrome among pre-hospital emergency medical service employees in Slovenia: A cross-sectional study, Obzornik zdravstvene nege. 2021;55(4):243–252. https://doi.org/10.14528/snr.2021.55.4.3052.

13.

Nantsupawat

, Kunaviktikul

, Nantsupawat

, Wichaikhum

, Thienthong

, Poghosyan

. Effects of nurse work environment on job dissatisfaction, burnout, intention to leave, Int Nurs Rev. 2017;64(1):91–98. https://doi.org/10.1111/inr.12342.

14.

Maslach

, Jackson

, The measurement of experienced burnout, Journal of Occupational Behavior. 1981;2, 99–113.

15.

Ergin

. Doktor ve Hemşirelerde Tükenmişlik ve Maslach Tükenmişlik Ölçeğin Uyarlanması, VII, Ulusal Psikoloji Kongresi Bilimsel çalışmaları El Kitabı. 1992:143–154.

16.

Özer

, Günlük

, Yüksel

. The mediator effect of professional satisfaction between accountants’ emotional exhaustion and professional turnover intention relationship UIİİD-IJEAS, International Journal of Economics and Administrative Studies. 2018(21):203–226. https://doi.org/10.18092/ulikidince.395178

17.

Chang

, Hu

. Burnout and health issues among prehospital workers in taiwan fire departments during a sudden spike in community COVID-19 cases: A Cross-sectional study. Int. J. Environ. Res. Public Health. 2022;19,22–57. https://doi.org/10.3390/ijerph19042257

18.

Petrie

, Smallwood

, Pascoe

, Willis

. Mental health symptoms and workplace challenges among Australian paramedics during the COVID-19 pandemic, Int. J. Environ. Res. Public Health. 2022;19:1004. https://doi.org/10.3390/ijerph19021004

19.

Leskovic

, Erjavec

, Leskovar

, Vukovič

. Burnout and job satisfaction of healthcare workers in Slovenian nursing homes in rural areas during the COVID-19 pandemic. Ann Agric Environ Med. 2020;664–671.

20.

Jalili

, Niroomand

, Hadavand

, Zeinali

, Fotouhi

. Burnout among healthcare professionals during COVID-19 pandemic: a cross-sectional study. Int Arch Occup Environ Health. 2021;1–8.

21.

ALmutairi

, El Mahalli

. Burnout and coping methods among emergency medical services professionals, J Multidiscip Healthc. 2020;16(13):271–279. https://doi.org/10.2147/JMDH.S244303.

22.

Barello

, Palamenghi

, Graffigna

. Burnout and somatic symptoms among frontline healthcare professionals at the peak of the Italian COVID-19 pandemic, Psychiatry Res. 2020;290:113–129. https://doi.org/10.1016/j.psychres.2020.113129.

23.

Lavoie-Tremblay

, Gélinas

, Aubé

, Tchouaket

, Tremblay

, Gagnon

, Côté

. Influence of caring for COVID-19 patients on nurse’s turnover, work satisfaction and quality of care, J Nurs Manag. 2022;30(1):33–43. https://doi.org/10.1111/jonm.13462.

24.

Said

, El-Shafei

. Occupational stress, job satisfaction, and intent to leave: nurses working on front lines during COVID-19 pandemic in Zagazig City, Egypt, Environ Sci Pollut Res Int. 2021;28(7):8791–8801. https://doi.org/10.1007/s11356-020-11235-8.

25.

İşsever

, Bektas

, Effects of learned resourcefulness, work-life quality, and burnout on pediatric nurses‘ intention to leave job., Perspect Psychiatr Care. 2021;57(1):263–271. https://doi.org/10.1111/ppc.12557.

26.

Tijdink

, Vergouwen

, Smulders

. Emotional exhaustion and burnout among medical professors; A nationwide survey, BMC Medical Education. 2014;14:183. https://doi.org/10.1186/1472-6920-14-183

27.

Akalın

, Modanlıoğglu

. Professionals working in intensive care in the covid-19 process, Acıbadem University Journal of Health Sciences. 2021;12(2):346–352. https://doi.org/10.31067/acusaglik.850978

28.

Shah

SHA

, Haider

, Jindong

, Mumtaz

, Rafiq

. The impact of job stress and state anger on turnover intention among nurses during COVID-19: The mediating role of emotional exhaustion, Front Psychol. 2022;9(12):810378. https://doi.org/10.3389/fpsyg.2021.810378.

29.

Bayer

, Golbasi

, Uzuntarla

, Akarsu

. Job satisfaction, burnout and turnover intention of nurses working in hospital during the pandemic COVID-19 in Turkey, J Clin Med Kaz. 2021;18(6):69–75. https://doi.org/10.23950/jcmk/11347

30.

Moazzami

, Razavi-Khorasani

, Dooghaie Moghadam

, Farokhi

, Rezaei

. COVID-19 and telemedicine: Immediate action required for maintaining healthcare providers well-being, J Clin Virol. 2020;126:104345. https://doi.org/10.1016/j.jcv.2020.104345.

31.

Zhang

, Chen

, Afshar Jahanshahi

, Alvarez-Risco

, Dai

, Li

, Patty-Tito

. Succumbing to the COVID-19 Pandemic-Healthcare Workers Not Satisfied and Intend to Leave Their Jobs, Int J Ment Health Addict. 2022;20(2):956–965. doi:10.1007/s11469-020-00418-6.

32.

, Wang

, Luo

, Hu

, Lin

, Anderson

, Bruera

, Yang

, Wei

, Qian

. A comparison of burnout frequency among oncology physicians and nurses working on the frontline and usual wards during the COVID-19 epidemic in Wuhan, China, J Pain Symptom Manage. 2020;60(1):e60–e65. https://doi.org/10.1016/j.jpainsymman.2020.04.008.

33.

Akalın

, Modanlıoğlu

. Professionals working in intensive care in the covid-19 process, Acıbadem University Journal of Health Sciences. 2021;12(2):346–352. https://doi.org/10.31067/acusaglik.850978

34.

, Wang

, Xue

, Zhao

, Zhu

. The impact of COVID-19 epidemic declaration on psychological consequences: A study on active weibo users, Int. J. Environ. Res Public Health. 2032;17:2032. https://doi.org/10.3390/ijerph17062032

35.

Pala

Sç

, Metintaş

. Healthcare professionals in the covid-19 pandemic, ESTUDAM Public Health Journal. 2020;5(COVID-19 Special Issue):156–68.

36.

Howarth

, Zimmerman

, van de Mortel

, Barr

. Barriers to, and enablers of, paramedics responding to suspected or confirmed COVID-19 cases: An integrative review, Australas Emerg Care. 2023;26(1):66–74. https://doi.org/10.1016/j.auec.2022.08.001.

37.

Salathé

, Althaus

, Neher

et al. COVID-19 epidemic in Switzerland: on the importance of testing, contact tracing and isolation, Swiss Med Wkly. 2022;150:w20225. https://doi.org/10.4414/smw.2020.20225

38.

Lai

, Ma

, Wang

, Cai

, Hu

, Wei

, Wu

, Du

, Chen

, Li

, Tan

, Kang

, Yao

, Huang

, Wang

, Liu

, Hu

. Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019, JAMA Netw Open. 2020;3(3):e203976. https://doi.org/10.1001/jamanetworkopen.2020.3976.

39.

Jiang

, Zhou

, Rakofsky

, Hu

, Liu

, Wu

, Liu

, Tang

. Intention to leave and associated factors among psychiatric nurses in China: A nationwide cross-sectional study, Int J Nurs Stud. 2019;94:159–165. https://doi.org/10.1016/j.ijnurstu.2019.03.013.

Descriptive characteristics	n	%	EBS		JSS		ILPS
			$\bar{X}$ ±SD	Test	$\bar{X}$ ±SD	Test	$\bar{X}$ ±SD	Test
Gender
Male	188	46.8	3.18±.63	t = –0.800	2.97±.84	t = –0.810	3.31±1.08	t = –0.983
Female	213	53.2	3.18±.58	p = 0.936	3.04±.85	p = 0.418	3.20±1.08	p = 0.326
Age group
19–24	91	22.4	3.13±.59		2.80±.85		3.02±1.09
25–29	129	32.3	3.28±.62		3.25±.84		3.41±1.16
30–34	74	18.5	3.29±.56	F = 3.853	2.92±.83	F = 4.785	3.35±1.09	F = 2.294
35–39	79	19.8	3.08±.57	p = 0.004^*	3.12±.80	p = 0.001*	3.22±.93	p = 0.600
40 and above	28	7.0	2.89±.64		3.20±.83		2.98±.96
Marital status
Married	234	58.4	3.19±.58	t = 0.132	3.05±.84	t = 0.912	3.24±1.07	t = –0.013
Single	167	41.6	3.18±.64	p = 0.895	2.97±.86	p = 0.363	3.24±1.11	p = 0.990
Status of having a child
Yes	203	50.6	3.17±.59	t = 0.180	3.02±.86	t = 0.210	3.27±1.05	t = 0.523
No	198	49.4	3.19±.61	p = 0.671	3.00±.85	p = 0.834	3.22±1.12	p = 0.602
Professional title
Emergency medical technician	212	52.9	3.20±.58	t = 0.538	3.02±.85	t = 0.285	3.17±1.12	t = –1.483
Paramedic	189	47.1	3.16±.63	p = 0.591	3.00±.85	p = 0.776	3.33±1.04	p = 0.139
Total years of service in the profession
2–5	131	32.5	3.08±.61		3.20±.83		2.97±1.12
6–9	83	20.8	3.38±.56	F = 6.609	2.73±.85	F = 5.849	3.47±1.08	F = 4.928
10–14	108	26.9	3.27±.59	p = 0.000*	2.95±.81	p = 0.001*	3.41±1.07	p = 0.002*
15 years and above	79	19.8	3.05±.59		3.09±.86		3.22±.94
Working shift
Full-time day shift	21	5.3	2.78±.58		3.21±.89		3.23±1.32
Full-time night shift	5	1.2	3.31±.93	F = 1.505	3.20±.94	F = 0.585	3.31±1.60	F = 0.828
Night/day shift rotation	32	8.0	3.40±.58	p = 0.200	3.01±.95	p = 0.674	3.23±1.12	p = 0.508
Full-time day shift and occasional night shifts	8	2.0	3.18±.31		2.73±.62		3.93±.93
On-call/standby only	335	83.5	3.04±.60		3.00±.84		3.23±1.06
Average monthly total working hours during the pandemic (hours)
160–180	107	26.7	3.17±.59		3.13±.83		3.13±1.04
180–200	127	31.7	3.17±.60		3.00±.86		3.31±1.02
200–220	45	11.2	3.16±.68	F = 0.153	2.86±.83	F = 0.839	3.48±.94	F = 0.995
220–240	67	16.7	3.20±.61	p = 0.979	3.02±1.01	p = 0.523	3.27±1.21	p = 0.420
240–280	43	10.7	3.22±.57		2.91±.65		3.07±1.18
280 hours and above	12	3.0	3.29±.52		2.96±.73		3.20±1.39
Knowledge about COVID-19
None	42	10.5	3.43±.60		2.57±.57		3.67±.92
Little	53	13.2	3.33±.48	F = 3.803	2.67±.72	F = 10.412	3.53±.96	F = 3.685
Moderate	70	17.5	3.15±.55	p = 0.005^*	2.92±.68	p = 0.000^*	3.25±.94	p = 0.006^*
Good	139	34.7	3.11±.57		3.08±.87		3.11±1.06
Very good	97	24.1	3.13.70		3.36±.93		3.09±1.27
Having received training on COVID-19
Yes	314	78.2	3.11±.61	t = –5.222	3.09±.85	t = 3.722	3.13±1.09	t = –4.327
No	87	21.8	3.44±.50	p = 0.000^*	2.71±.78	p = 0.000^*	3.65±.96	p = 0.000^*
COVID-19 test status
Yes	332	82.8	3.21±.60	t = 2.231	2.99±.86	t = –1.107	3.27±1.10	t = 0.851
No	69	17.2	3.04±.62	p = 0.026^*	3.12±.79	p = 0.269	3.14±1.01	p = 0.395
Loss of someone known due to COVID-19
A family member	51	12.7	2.97±.77		3.28±.93		3.03±1.23
A colleague from the same team	4	1.0	2.78±.65	F = 7.432	2.83±1.31	F = 3.745	3.00±.40	F = 5.706
A healthcare worker I know	37	9.2	3.59±.45	p = 0.000^*	2.59±.68	p = 0.005^*	3.96±.85	p = 0.000^*
An acquaintance	183	45.6	3.22±.54		3.00±.82		3.28±1.02
I haven’t experienced any loss	126	31.4	3.11±.60		3.05±.85		3.08±1.10

Emotional burnout,job satisfaction,and intention to leave among pre-hospital emergency healthcare workers during the COVID-19 pandemic

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1 Introduction

1.1 Research questions

Materials and methods

2.1 Design

2.2 Research population

2.3 Dependent and independent variables

2.3.1 Dependent variables

2.3.2 Independent variables

2.4 Data collection tools

2.4.1 Sociodemographic data form

2.4.2 Emotional burnout scale (EBS)

2.4.3 Job satisfaction scale (JSS)

2.4.4 Intention to leave the profession scale (ILPS)

2.5 Data collection process

2.6 Statistical analysis

2.6.1 Ethical considerations

3 Results

3.1 Distribution of the sociodemographic characteristics of the participants

Table 2 The participants’ mean scores obtained from the EBS, JSS, and ILPS and the relationship between the means (n = 401) X±SD Min - Max EBS JSS ILPS r p r p r p EBS 3.18±.60 1–5 – JSS 3.02±.85 1–5 –0.562 0.000 * – ILPS 3.24±1.08 1–5 0.687 0.000 * –0.694 0.000 * –

5 Conclusions

5.1 Limitations

Ethical approval

Informed consent

Conflict of interest

Footnotes

Acknowledgments

Funding

References

Table 2
The participants’ mean scores obtained from the EBS, JSS, and ILPS and the relationship between the means (n = 401)

X±SD Min - Max EBS JSS ILPS

r p r p r p

EBS 3.18±.60 1–5 –

JSS 3.02±.85 1–5 –0.562 0.000^* –

ILPS 3.24±1.08 1–5 0.687 0.000^* –0.694 0.000^* –