Occupational safety perceptions of prehospital emergency health services employees: A sample of Sivas central district

Abstract

BACKGROUND:

Prehospital emergency health services ambulance workers are in the risky class in terms of occupational health and safety, and they are faced with more risks due to the fact that they are the first responders to the events, especially regarding COVID-19.

OBJECTIVE:

The aim of the present study is to determine the occupational risk perceptions of health care workers and their relations with demographic variables.

METHODS:

A literature review was performed to develop a questionnaire. This questionnaire was used in a survey with 250 respondents. The collected data was analysed through factor analysis. Cronbach’s Alpha was calculated to verify the reliability of the data.

RESULTS:

The risk perceptions of the employees (Factor 1 and Factor 3) differ significantly according to gender. Another important point is that 60.3% of the participants stated that they “agree” with the statement that health workers “experience violence” during work.

CONCLUSION:

The risk perception of women was found to be higher, and the reason for this is that women are less physically strong than men along with social gender roles and gender discrimination.

Keywords

EMS paramedic ambulance services risk perception questionnaire

1 Introduction

Prehospital emergency health workers (emergency medical technicians, paramedics such as doctors, nurses) respond to automobile accidents, gunshot wounds, medical emergencies, hazardous material incidents, and disasters. Therefore, emergency health care workers face a wide variety of occupational hazards. Verbal and physical attacks, infectious diseases, exposure to dangerous substances such as biological, chemical and nuclear agents, stress, long working hours, ambulance accidents and secondary accidents such as falls, and electric shock are among some of the occupational hazards [1].

When the literature on occupational risks faced by emergency health services employees is examined, it is seen that various studies have been carried out based on certain risks. In addition, there are also studies in which meta-analyses are made based on the studies in this field. In these studies, risk issues such as emotional distress, violence, stress, depression, and burnout [2–20], occupational accidents and death [1, 21, 22], patient safety and safety culture (climate) [23–32] were addressed. In the studies carried out, the problems that arise related to the risks in the field of emergency health services were discussed and the reasons for them were emphasized. Just as important as these issues is the perceptions of employees regarding risk.

Our study was carried out in a time period when the COVID-19 pandemic was intensely experienced all over the world and various protective measures were applied. Especially during the pandemic process, healthcare workers are at serious risk. It is easier for them to become infected when necessary and sufficient precautions are not taken at the individual and institutional level. Again in this process, deaths due to infection among employees, the uncertainties caused by the process and the resulting fear have increased the risk perception and absenteeism of the employees, while reducing their ability to provide services [33].

It has been determined that my uncertainty caused by the pandemic process causes serious wear, stress and depression in healthcare workers, and causes them to feel insecure and exhausted [34]. In the literature, there are many studies on healthcare workers during the COVID-19 pandemic. Some of these studies include: topics such as violence [35], burnout (stress, anxiety, depression) [36–39], use of personal protective equipment [40, 41], life quality [42]. It has been determined that the uncertainty caused by the pandemic process causes serious burn out, stress and depression in healthcare workers, and causes them to feel insecure and exhausted [43].

Considering the background presented in the literature, this study aims to measure the risk perceptions of pre-hospital emergency health services ambulance employees.

2 Methods

This study was carried out in Sivas, Turkey in 2021. In order to measure the risk perception levels of the employees, data were collected through face-to-face survey application. It has been determined that 400 professionals work in 25,911 emergency stations in the province.

The survey study lasted 4 months on the web and 7 months actively in the field, and the total data collection process took 11 months. In order to identify the professionals, the stations where they work with an active search were visited every 3 weeks and feedback was received.

As a result of the literature review on the subject, 100 items to be included in the questionnaire were determined as well as demographic variables. Questionnaire items were prepared in a five-point Likert type. In the first stage, the opinions of 24 experts were taken regarding the items, and the content validity was determined at a rate of 0.916 in the calculation made with Lawshe’s [44] formula. 17 items that were lower than the lowest content validity rate (0.417) were removed from the form. In the second stage, a pilot application was made on the web to 100 professionals working at the stations. In the third stage, data were obtained from 250 of the 400 employees who made up the universe by visiting the stations where the pre-hospital emergency health workers were located, and by making face-to-face interviews with non-random and purposeful sampling method. The questionnaires of 21 of them were excluded from the evaluation due to their deficiencies and analyses were made on the remaining 229 forms. This amount was considered sufficient as the sample size, since the sample size is calculated as 196 units with a 95% confidence level and a 5% margin of error for a population consisting of 400 units [45]. In addition, it is considered sufficient for the sample size to be over 200 in order to obtain reliable factors in exploratory factor analysis [46].

As a result of the reliability analysis of the data obtained, a total of 28 items with Corrected Item-Total Correlation ratios below 0.2 and with the same and similar expressions were excluded from the study. In addition, in the factor analysis made with these data, items with a Communalities/Extraction value of less than 0.3 and 30 items with a maximum value of less than 0.5 in the Component Matrix and Rotated Component Matrix tables were excluded from the evaluation [47].

As a result of factor analysis, Kaiser-Meyer-Olkin Sampling adequacy (Kaiser-Meyer-Olkin Measure of Sampling Adequac) was determined as 0.869, which indicates that the sample was sufficient for factor analysis. The result of Bartlett’s Test of Sphericity shows that Sig = 0.000 and the matrix formed by the relations between the variables is significant for factor analysis (p < 0.05) [48].

2.1 Reliability

In order to determine the normality distribution of the data, the Skewness (Skewness) and Kurtosis (Kurtosis) values were checked and since these values were between ±2.0, it was accepted that the data showed a normal distribution [49].

As a result of the analyses and evaluations, the Cronbach’s Alpha value of the questionnaire consisting of 25 items and 5 factors was determined at the level of 0.92, and this rate shows that the results of the questionnaire are very reliable. In addition, it was observed that the lowest Cronbach’s Alpha value of the factors was 0.879 and the reliability of the sub-factors was high.

3 Results

In the questionnaire used to measure the risk perceptions of pre-hospital health workers, the findings regarding the demographic characteristics of the professionals are given in detail in the table (Table 1). When we examine the highest values of the variables of the participants in this table, it is seen that 52.4% are male, 72% are married, 52.8% are between the ages of 26–33, 45% are associate degree graduates, 43% are paramedic, 73% are in the 4-A position and 49% have served between 6–11 years. As a result of the factor analysis, 5 risk perception factors were determined.

Table 1
Demographic characteristics of the study participants

N % Total

Gender Male 120 52,4 52,4

Female 109 47,6 47,6

Total 229 100,0 100,0

Age 18–25 47 20,5 20,5

26–33 121 52,8 52,8

34–41 45 19,7 19,7

42–49 14 6,1 6,1

50–++ 2 0,9 0,9

Total 229 100,0 100,0

Marital status Single 64 27,9 27,9

Married 165 72,1 72,1

Total 229 100,0 100,0

Educational status High school 37 16,2 16,2

Associate degree 103 45,0 45,0

Undergraduate 72 31,4 31,4

Master’s degree 17 7,4 7,4

Total 229 100,0 100,0

Occupation EMT 83 36,2 36,2

Paramedic 99 43,2 43,2

Driver 30 13,1 13,1

Nurse 4 1,7 1,7

Doctor 13 5,7 5,7

Total 229 100,0 100,0

Employment status 4-A 168 73,4 73,4

4-B 29 12,7 12,7

4-C 19 8,3 8,3

4-D 13 5,7 5,7

Total 229 100,0 100,0

Work experience 0–5 years 59 25,8 25,8

6–11 years 113 49,3 49,3

12–17 years 38 16,6 16,6

18–23 years 17 7,4 7,4

24– ++years 2 0,9 0,9

Total 229 100,0 100,0

		N	%	Total
Gender	Male	120	52,4	52,4
Female	109	47,6	47,6
	Total	229	100,0	100,0
Age	18–25	47	20,5	20,5
	26–33	121	52,8	52,8
	34–41	45	19,7	19,7
	42–49	14	6,1	6,1
	50–++	2	0,9	0,9
	Total	229	100,0	100,0
Marital status	Single	64	27,9	27,9
Married	165	72,1	72,1
	Total	229	100,0	100,0
Educational status	High school	37	16,2	16,2
	Associate degree	103	45,0	45,0
	Undergraduate	72	31,4	31,4
	Master’s degree	17	7,4	7,4
	Total	229	100,0	100,0
Occupation	EMT	83	36,2	36,2
	Paramedic	99	43,2	43,2
	Driver	30	13,1	13,1
	Nurse	4	1,7	1,7
	Doctor	13	5,7	5,7
	Total	229	100,0	100,0
Employment status	4-A	168	73,4	73,4
	4-B	29	12,7	12,7
	4-C	19	8,3	8,3
	4-D	13	5,7	5,7
	Total	229	100,0	100,0
Work experience	0–5 years	59	25,8	25,8
	6–11 years	113	49,3	49,3
	12–17 years	38	16,6	16,6
	18–23 years	17	7,4	7,4
	24– ++years	2	0,9	0,9
	Total	229	100,0	100,0

In the study, the lowest factor load was found at the level of 0.611. This ratio indicates a successful factor separation. It was determined that 5 factors related to the risk perception of the professionals explained 73,786% of the total variance.

A statistical comparison of the total scores obtained from the survey questions and the sums of the factors separately according to the demographic variables was made. Independent t-test for two variables was used for pairwise comparisons, ANOVA for multiple comparisons, and Scheffe test for post-hoc test. In addition, the descriptive statistical values of the factor items were analyzed. In the study, the table of all the factors and the frequency tables of the sub-items were not included, the values were written as text.

As a result of the comparison of factor scores according to Age, Educational Status, Occupation, Staff, Status and Length of Service with ANOVA test (Table 2), no statistically significant difference was found in terms of total score (p > 0.05). It shows that these qualifications of the professionals do not have a decisive effect on their risk perceptions.

Table 2

Multiple comparisons

	Age		Educational status		Occupation		Employment status		Work experience
	F	p	F	p	F	p	F	p	F	p
Total	0,238	0,916	0,972	0,407	2,443	0,051	0,862	0,462	0,192	0,943
Factor_1	2,188	0,071	0,476	0,699	2,112	0,080	1,553	0,202	0,921	0,453
Factor_2	0,810	0,520	1,665	0,175	1,702	0,151	0,475	0,700	0,289	0,885
Factor_3	1,035	0,390	0,975	0,405	1,743	0,142	1,675	0,173	1,290	0,275
Factor_4	0,729	0,573	1,876	0,134	1,975	0,099	0,826	0,481	0,803	0,524
Factor_5	1,575	0,182	0,593	0,620	1,449	0,219	0,162	0,922	0,431	0.786

Six items under the sources of stress in the work environment factor (Table 3),

Six items under the factor of safety precautions in contact with the patient (Table 5),

Six items under the factor of patient intervention and intervention environment (Table 6),

Four items under personal precautions and training factor (Table 8),

Three items under the factor of tools and equipment used (Table 9).

Table 3

Sub-items for sources of stress in the work environment

	Due to intense and stressful working conditions (on duty, on-call work, time pressure, working in unusual situations, etc.) employees might experience …	Extraction	Rotation sums of squared loadings % of variance	Cronbach’s alpha
Items	1. Family problems	0,870	17,313	0,915
	2. Behavioral disturbances	0,842
	3. An increase in the use of cigarettes, alcohol and drugs	0,816
	4. Mood disorder	0,814
	5. Chronic insomnia problem	0,772
	6. Verbal/physical harassment and violence by patients and/or their relatives	0,668

Table 4

Factor 1 t table

	Gender	N	Mean	Std. deviation	df	t	p
Factor1	Male	120	24	5,21149	227	2,431	0,016*
	Female	109	25,7339	5,58212

Table 5

Sub-items for safety precautions in contact with the patient

	Component 2 (F2): Safety precautions in contact with the patient	Extraction	Rotation sums of squared loadings % of variance	Cronbach’s alpha
Items	1. Measures are taken to ensure the safety of patients and employees during transport.	0,863	17,091	0,905
	2. There is necessary equipment to ensure the safety of patients and employees during transport.	0,858
	3. Necessary treatment and care opportunities are provided for employees who are found to be negative as a result of health screenings.	0,731
	4. There is appropriate personal protective equipment in the ambulance in order to prevent the employees from coming into contact with a chemical, biological, radioactive and nuclear agent.	0,717
	5. Training is given on precautions and practices that will ensure the safety of patients and employees during transport.	0,668
	6. There is appropriate personal protective equipment in the ambulance in order to protect employees from diseases that may occur as a result of contact with blood, body fluids and respiratory tract.	0,626

Table 6

(Factor 3) sub-items of patient intervention and intervention environment

	Component 3 (F3): Patient intervention and intervention environment	Extraction	Rotation sums of squared loadings % of variance	Cronbach’s alpha
Items	1. Secondary accidents occur in employees as a result of falling, slipping, burning, electric shock, etc.	0,838	15,712	0,879
	2. Hepatitis B, Hepatitis C, AIDS, CCHF, etc. diseases are seen in the employees as a result of the injury of the employee by the cutting tools during the intervention to the patient.	0,833
	3. Diseases such as Hepatitis B, Hepatitis C, AIDS, CCHF etc. are seen in employees due to the open wound in the patient or the blood and body fluids of the patient splashed into the eye.	0,822
	4. Diseases such as cold, flu (influenza), SARS, MERS, Coronavirus, etc. are seen in employees as a result of inhalation of droplets belonging to the patient.	0,719
	5. Ambulances are involved in traffic accidents due to heavy traffic, traffic rules and other vehicle drivers who do not act in accordance with traffic rules, etc.	0,667
	6. In ambulances, situations such as disability, injury, etc. emerges as a result of accidents.	0,611

Table 7

Factor 3 table

	Gender	N	Mean	Std. deviation	df	t	p
Factor 3	Male	120	23,0833	5,93605	227	2,043	0,042*
	Female	109	24,5688	4,96724

Table 8

Personal precautions and training

	Component 4 (F4): Personal precautions and training	Extraction	Rotation sums of squared loadings % of variance	Cronbach’s alpha
Items	1. Employees are given training on waste management.	0,855	13,308	0,905
	2. Personal protective equipment is used by the employees.	0,824
	3. Employees are trained in the prevention of infections.	0,815
	4. There are necessary materials to ensure hand hygiene of the employees in the ambulance.	0,766

Table 9

Sub-items of tools and equipment used

	Component 5 (F5): Tools and equipment used	Extraction	Rotation sums of squared loadings % of variance	Cronbach’s alpha
Items	1. Vehicle inspections and maintenance of ambulances are carried out regularly.	0,762	10,363	0,915
	2. Regular maintenance, approval, calibration, sterilization, disinfection, etc. of all electrical, electronic and other devices and equipment in ambulances are carried out.	0,728
	3. All devices in ambulances are used according to the safety rules.	0,695

The comparison of factor scores according to the variables of gender and marital status was made with the t test. As a result of the analyses, it was determined that the risk perceptions of the participants regarding Work Environment Stress Sources (Factor 1) and Patient Intervention and Intervention Environment (Factor 3) differ according to gender (Tables 4 and 7). However, it was determined that there was no statistical difference between the total and all other factor scores of the marital status variable (p > 0.05).

3.1 Sources of stress in the work environment (Factor 1)

Component 1 (F1), which consists of 6 items measuring the risk perception of work environment stress sources, explains 17.31% of the risk perceptions of the employees, and the Cronbach’s Alpha value is 0.915 (Table 3). Working conditions (such as shifts, time pressure, working in unusual situations) cause problems such as family problems, behavioral disorders, increased use of cigarettes, alcohol and drugs, and insomnia.

As communication and interaction with service users increase in working life, demands and expectations from service providers also increase. These expectations are the source of excessive and long-term stress in healthcare professionals. Freudenberger [50] conceptualized burnout as the negative effects and reductions of this stress on the energy and resources of the employee. Maslach [51], on the other hand, defines burnout as the individual’s alienation from the purpose of his profession and not being able to deal with service recipients as they should.

Burnout syndrome, which occurs as a result of organizational and individual reasons, manifests itself in various physical and behavioral problems [50]. These problems include muscle and joint pain, psychosomatic problems such as eating and sleeping disorders, emotional problems such as anger, anger, impatience and guilt, behavioral problems such as absenteeism or late departure from work [52]. Burnout consists of certain stages. The individuals first experience emotional exhaustion related to their job, and then experiences depersonalization towards their work and service recipients. In the final stage, they develop a general belief of inadequacy in their sense of accomplishment [51].

Environmental and personal factors affect the individual’s feeling of burnout. Among the environmental factors, there are also organizational factors. Among the important ones, authoritarian management and excessive control policies in the workplace, conflicts between employees, inability to participate in the decisions taken and the practices to be made, excessive and intense interaction with the patient and their relatives, insufficient organizational support, job insecurity and role ambiguity, role confusion, workload shift work, insufficient wages, career development barriers can be counted [53]. Individual factors include personality traits, age, gender, education, and ability to cope with stress [52].

In studies conducted on healthcare workers, symptoms of post-traumatic stress disorder were also observed in workers who were exposed to extreme stress [54]. Pre-hospital emergency health workers face more traumatized patients than other workers. This situation may cause a secondary trauma similar to that experienced by the patient in the employee. The consequences of secondary traumatic stress can be observed at the personal, interpersonal, or organizational level [55].

According to the results of the Independent Sample t test, whether the risk perception regarding the sources of stress in the working environment differs significantly according to the gender, the opinions of the professionals regarding the risk perceptions differ significantly (t₍₂₂₇₎ = 2,431; p < 0,05). According to the sources of stress in the working environment, the average of risk perceptions of female employees (Mean = 104,798; S.S = 25,733) was found to be higher than the average of male employees (Mean = 24,000).

In the study, some data of the frequency tables obtained by using Likert-type scaling for the items were expressed as text.

Factor 1 consists of items related to the problems experienced by professionals due to stress sources in the working environment (Table 3) given as text in the study. “Family problems are seen in employees due to intense and stressful working conditions (on duty, on-call work, time pressure, working in unusual situations, etc.).” While 44.5% of the participants stated that they “strongly agree” with the statement, only 4.8% stated that they “disagree". While the total rate of those who answered “strongly agree” that stressful working conditions cause behavioral problems in employees was 39.7%, it was determined that the rate of “strongly disagree” remained at the level of 3.9%. Again, 50.7% of the respondents said “strongly agree” to the statement that stressful working conditions cause mood disorders in employees, while 56.3% said that they “strongly agree” that they have chronic insomnia. The rate of “participants” was determined at the level of 43.2%. In addition, the rate of those who “absolutely agree” to the verbal and physical violence exposure of the patients and/or their relatives was determined as 60.3%.

3.2 Patient contact safety precautions (Factor 2)

Factor 2 consists of items related to the safety precautions of professionals in contact with the patient. Component 2 (F2), which consists of 6 items measuring the risk perception regarding safety precautions in contact with the patient, explains 17.09% of the risk perceptions of the employees, and the Cronbach’s Alpha value was found to be 0.905 (Table 5).

As a result of the Independent Sample t test and ANOVA tests performed for the analysis of the relationship between Factor 2 regarding safety measures in contact with the patient and demographic variables, no significant relationship was found between the variables (p > 0.05).

When we examine the frequency values of the factor items, 43% of the professionals agree with the statement “Measures are applied to ensure the safety of patients and employees during transport", while the rate of those who agree with the statement “There are necessary equipment to ensure the safety of patients and employees during transport” is at the level of 30.6%. In addition, when we look at the ratios of those who answered “I agree” to other items; “Necessary treatment and care opportunities are provided for employees who are found to be negative as a result of health screenings” 27.5%, “There are appropriate personal protective equipment in the ambulance in order to prevent the employees from contacting a chemical, biological, radioactive and nuclear agent” 30.6%, “Patients are and trainings are provided on measures and practices that will ensure the safety of employees during transport” 34.5%, “There are appropriate personal protective equipment in the ambulance in order to protect employees from diseases that may occur as a result of contact with blood, body fluids and respiratory tract” was found to be at the level of 27.5%.

3.3 Patient intervention and intervention environment (Factor 3)

Factor 3 consists of items related to patient intervention and the problems experienced by professionals in the intervention environment. Component 3 (F3), which consists of 6 items measuring the risk perception of the patient and the intervention environment, explains 15.71% of the risk perceptions of the employees, and the Cronbach’s Alpha value is 0.879 (Table 6).

In the environments where patient intervention is provided, professional personnel are exposed to electric shock, traffic accident and resulting injury or disability, Hepatitis B, Hepatitis C, AIDS, CCHF, SARS, MERS, Coronavirus, etc. It causes them to experience problems such as being exposed to virus infection.

According to the results of the Independent Sample t-test, which was performed to determine whether the risk perception regarding the intervention and the intervention environment differed significantly by gender, it was determined that the opinions of the professionals regarding the risk perceptions differed significantly (t(227) = 2.043; p < 0.05). It was found that the average of female employees’ risk perceptions regarding patient intervention and intervention environment (Mean = 24,568; SD = 4.967) was higher than the average of male employees (Mean = 23,083; SD = 5.936) (Table 7).

When the proportions of those who say “I agree” in the frequency values of Factor 3 items are examined, “Falls, slips, burns, electric shocks, etc. As a result, secondary accidents occur” at the level of 31.0%,

“As a result of the injury of the employee by the cutting tools during the intervention to the patient, Hepatitis B, Hepatitis C, AIDS, CCHF, etc. in the employees. diseases are seen” at the level of 22.3%,

“Hepatitis B, Hepatitis C, AIDS, CCHF, etc. in employees due to the open wound of the patient or the blood and body fluids of the patient splashed into the eyes. diseases are seen” at the level of 22.7%,

“As a result of inhalation of droplets belonging to the patient, cold, flu (influenza), SARS, MERS, Coronavirus, etc. in employees. diseases are seen” at the level of 27.1%,

“Ambulances are in heavy traffic, traffic rules and other vehicle drivers who do not act in accordance with traffic rules, etc. traffic accidents occur due to reasons” at the level of 26.2%,

“As a result of accidents in ambulances, disability, injury, etc. situations happen” was determined to be at the level of 29.3%.

3.4 Personal precautions and training (Factor 4)

Factor 4 consists of items related to Personal Precautions and Training of members of the profession. Component 4 (F4), which consists of 4 items measuring risk perception regarding personal measures and training, explains 13,308% of employees’ risk perceptions and the Cronbach’s Alpha value was found to be 0.905 (Table 8).

As a result of the Independent Sample t test and ANOVA tests performed for the analysis of the relationship between Personal Measures and Educational Factor 4 and demographic variables, no significant relationship was found between the variables (p > 0.05).

When the proportions of those who gave the answer “I agree” to the items of the Personal Precautions and Training factor (F4) were examined;

“Employees are given training on waste management” was found at the level of 35.4%,

“Personal protective equipment is used by the employees” was at 30.1%,

“Employees are trained on preventing infections” was at 32.8%,

“There are necessary materials to ensure hand hygiene of the employees in the ambulance” was at 31.9%.

3.5 Sub-items of tools and equipment used (Factor 5)

Factor 5 consists of questions to determine the risk perceptions of members of the profession regarding Tools and Equipment Used. Component 5 (F5), which consists of 3 items measuring the perception of occupational safety regarding Tools and Equipment Used, explains 10,363% of employees’ perceptions of safety and its Cronbach’s Alpha value is at the level of 0.915 (Table 9).

As a result of the Independent Sample t test and ANOVA tests performed for the analysis of the relationship between Factor 5 related to Tools and Equipment Used and demographic variables, no significant relationship was found between the variables (p > 0.05).

When the proportions of those who answered “I agree” to Factor 5 items were examined;

“Vehicle inspections and maintenance of ambulances are carried out regularly” was found at the level 22.7%,

“Regular maintenance, approval, calibration, sterilization, disinfection, etc. of all electrical, electronic and other devices and equipment in ambulances are carried out” was at 28.4%,

“All devices in ambulances are used according to the safety rules” was at 27.5%.

4 Discussion

Rue et al. [56] evaluated the military, police, fire department, and emergency health services in occupational groups that require physical strength in his study and measured the physical activities and needs of ambulance workers during the tasks given in different scenarios.

Gender comes first among the demographic variables that cause the risk perceptions of prehospital healthcare professionals to differ. It has been determined by many studies in the field that women have a higher risk perception than men. These studies show several reasons for women’s high-risk perception:

Since men are physically stronger than women in terms of muscle mass and strength, women are exposed to more risk such as strain and fatigue in the same work and conditions [57–61].

Women are more exposed to sexist stress and gender discrimination [7, 58, 62–66].

Along with housework and childcare, work life [58, 67, 68] imposes more responsibilities on women than men. As a result, women experience more stress. Stress from all these sources causes dissatisfaction, burnout and depression in the work and private life of the female employee [52]. At this point, it can be said that our study is compatible with the studies on the subject.

Another source of stress that affects employees’ risk perceptions is the violence they are exposed to by others. In the studies examined, the rate of employees exposed to violence was reported as 67.5 % by Deniz et al. [9], 65.2 % by Bernardo-De-Quiro [5], 75 % by Bigham et al. [6], 88 % by Furin et al. [13], 41 % by Duchateau et al. [12] and 66 % by Petzall et al. [16], 33,5 % by Ferrara et al. [35].

In this study, 60.3% of the pre-hospital emergency health workers gave the answer “I strongly agree” to the statement “Verbal/physical harassment and violence is applied to the employees by the patient and/or patient relatives", one of the Factor 1 items. In addition, the risk perceptions of female employees in the case of patient intervention and intervention (F3) were found to be significantly higher (Table 7).

The results of the studies in the literature are in agreement with the results we found. On the other hand, in some of the studies examined, all kinds of violence that employees are exposed to are considered as a part of the employees’ burnout problem, while in some studies, workplace stress factors are the source of burnout in employees. In this study, items indicating the stages of burnout syndrome [51] were included under the title of Stress Factors (Factor 1).

Abareshi et al. [36] found a statistically significant difference in terms of burnout in different education levels and occupations of emergency health personnel. Sagaltici et al. [39] reported that the level of burnout was different according to occupation. In the present study, however, a significant difference was observed according to gender. Ebrahimi et al. [42] reported that unusual workload caused increased stress and burnout in nurses in their study on the quality of life of nurses during the pandemic process.

Demir et al. [37] reported in their study that there was an increase in the rate of drug use by healthcare professionals to sleep properly during the pandemic process. Their findings are consistent with the increase in drug use, which is one of the sub-items of F1 in the present study.

Dogru-Huzmeli et al. In their study in [38], the response rate of “strongly agree” that the familial problems of healthcare professionals increased during the COVID-19 process was 56.1%, while this rate was 44.5% in this study, and the results are consistent.

de Oliveira e Silva et al. [40] examined the quality of face shields of healthcare workers during the pandemic process and reported that the use of other personal protective equipment (PPE) together with face shields is more effective in protecting healthcare workers from disease. Dogan et al. [41] reported that long-term use of PPE during the pandemic had negative effects on the health of nurses. In the present study, it was determined that PPEs are suitable for use and the response rate of “strongly agree” to their use by healthcare professionals was 55% and 57.2%.

The factor items and findings of the scale of Eliseo et al. [26] applied by the emergency health care workers in their study on the safety climate are similar to the factor items of the questionnaire we applied in this study and are compatible with our findings.

Moreover, in their study, Milner et al. [69] investigated the problems that cause suicide in all emergency and preventive service professionals. It has been determined that problems such as work stress, bullying and emotional exhaustion affect the ambulance service employees more and lead them to suicidal thoughts.

In our study, these problems were detected at high levels. The employees stated that they “strongly agree” with the sub-items of Factor 1 (Table 3), “behavioral disturbances", “mood disturbances are observed” and “employees are exposed to verbal/physical violence” by rates of 39,7%, 50,7% and 60,3%, respectively.

4.1 Limitations

57.25 % of the sample could be reached not only due to the busy workload of the pre-hospital emergency ambulance health employees under normal conditions but also due to the extra workload resulting from the COVID-19 pandemic. In addition, it was observed that the pre-hospital ambulance employees avoided and had difficulty in conducting the survey due to the excessive workload, their long stay in the field and their long shifts.

5 Conclusions

In today’s world, where the population and technology are constantly increasing, pre-hospital emergency health services and employees are gaining more importance day by day. When the studies on the subject in different countries and cultures are examined, it is understood that the dangers and risks that pre-hospital emergency health employees are exposed to are similar.

In our study, it was observed that pre-hospital emergency health employees faced significant risks and dangers in their work life. Among the possible reasons for this;

The environment where emergency health employees intervene in the patient is generally open to the public, and the intervention should be done as soon as possible and fast transportation should be provided,

Presence of relatives of patients in the intervention environment and their attempts to intervene in the event as a result of their anxiety and panic about the event,

In some cases (psychiatric etc.) in which healthcare professionals intervene, physical and psychological violence may be shown by the patients and their relatives.

Because of the fact that women are weaker in physical strength than men, they are more exposed to gender discrimination and the responsibilities in their home life (housework, childcare, etc.) are more burdened by the societies, they see the situations they encounter in work life as more difficult and dangerous and increase their risk perception. It can be said that it is high.

Based on the results of this study, it is recommended that states, governments and decision makers take necessary legal measures to protect and increase the welfare of workers in high-risk occupations, improve working conditions, and encourage psycho-social training and awareness-raising activities for service recipients.

With the awareness that especially female employees are among the priority group of workers that should be protected in business life, they should be privileged in terms of working conditions. In this context, instead of the work that requires physically very demanding actions, it can be suggested that women should be given priority duties in organizations where mental power is used more, such as conducting tasks that require less power, facilitating the work ergonomically (for example, “using the stretcher strap while carrying the patient” [70]), and the management of the work.

It is possible to provide vocational trainings to reduce the risk perceptions of female employees and to ensure the continuity of the trainings.

The dissemination of programs and practices that will improve social awareness towards changing discriminatory perceptions of women regarding the social status, gender and roles of women will contribute to the solution of the problem.

It can be said that making arrangements and practices (reducing the duration and days of guard duty, giving equal opportunities with men in career development, improving their salaries and directing them to social activity groups, etc.; for female employees to balance their work and private life) will have a reducing effect on the risk perceptions of female employees.

Although it is seen that there are various studies on pre-hospital emergency health services in the literature, further studies on the relationship between risk perceptions and different variables will make the subject more understandable. Thus, the types of hazards and risks faced by pre-hospital health workers will be determined. In this way, we think that the exposure of the professionals working in the emergency health sector to the specified dangers and risks will be prevented and reduced.

Footnotes

Ethical approval

Ethics committee approval was obtained from Sivas Cumhuriyet University (date 02.04.2021, number 29111) and a work permit document was obtained from Sivas Provincial Health Directorate (date 09.06.2021, number 8060103).

Informed consent

Not applicable.

Conflict of interest

The authors declare that they have no conflict of interest.

Acknowledgments

Not applicable.

Funding

Not applicable.

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