Abstract

Introduction

Recent research has shown increased rates of suicide and suicidal thoughts amongst emergency medical service professionals. This has brought more attention to the subject of burnout as a potential cause. A literature review demonstrated there was limited study of factors that may correlate with increased burnout. Our goal was to conduct a survey among a convenience sample of area emergency services providers to evaluate their rate of burnout in addition to identifying factors that may contribute to that rate.

Methods

A voluntary, anonymous paper survey was distributed among 152 participants at a regional EMS conference in Northwest Louisiana. The data recorded were age, type of EMS service, shift length, how many agencies employed at, non-EMS employment, level of EMS provider, call types, average transport time, shifts per month, how often greater than 24 hours shifts, average sleep per shift, position as a supervisor, years of EMS experience, years at current EMS provider level and level of burnout These participants represented paid and volunteer providers from a variety of systems to include; fire based, private, third city and air medical services. Data was analyzed utilizing descriptive statistics.

Results

A total of 90 surveys were received from the 152 participants for a response rate of 59.2%. Burnout level increased with number of years of EMS experience, increased years at current EMS provider level and more advanced levels of EMS provider. Shift length of 12-24 hours showed the highest level of burnout (2.8, range 2-4). Decreased amount of sleep correlated with increasing burnout levels. A supervisory position correlated with higher levels of burnout.

Related

• Burnout Among EMS Professionals: Incidence, Assessment and Management
• Stop the Burn and Churn of Turnover and Burnout Through Resiliency Science

Services that did transfers only showed the lowest burnout levels (1, range 0-2) and those who did scene calls with and without transfer and special events showed the highest levels of burnout (2.75 range 2-3.5). Burnout levels decreased with increasing numbers of agencies employed at. The lowest levels of burnout were reported in volunteer providers (0.5, range 0-1) and highest levels in third city service agencies (2.25, range 1-3). Burnout tended to increase with increasing age until age 45. Numbers of EMS agencies employed at, transport time and shifts/month showed no relation to reported burnout levels.

Conclusions

An increase in years of experience, years at current level of care and more advanced levels of EMS provider correlated with elevated burnout. Several other factors showed trends of increasing burnout. Further study is needed to look at specific factors and their correlation to burnout levels.

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Burnout is a term that first was used by a United States psychologist in the 1970s to describe symptoms seen in “helping professions.”¹ Burnout has been defined as a state of emotional, physical and mental exhaustion caused by excessive and prolonged stress. People who suffer from burnout tend to feel overwhelmed, emotionally drained, and unable to meet constant demands. In order to truly understand burnout, there has to be a more clear definition of what exactly burnout consists of and the factors that lead to this state.

Burnout in EMS is a worldwide problem. In Saudi Arabia, Nasser et al. looked at burnout and coping mechanisms. High levels of depersonalization (40%) and emotional exhaustion (63%) and low levels of personal achievement (42%) were seen.² A study in Poland looked at EMS providers, including paramedics, nurses and doctors, and found that 15.7% were at a high risk of occupational burnout.³ In Germany, Baier et al. showed burnout rates between 20 and 40%.⁴

The Ruderman White Paper published in April of 2018attempted to establish the prevalence of reported level of DSM-5 diagnosable mental disorders such as depression, anxiety, post-traumatic stress disorder (PTSD) and substance abuse and compare them to the general population. The findings showed an increased prevalence in mental health illness amongst firefighters with results ranging from poor work performance up to suicide.⁵ EMS however was not specifically looked at as they were grouped with firefighters. A study looking at EMS burnout as it relates to critical incidents showed paramedics had an 18% burnout rate and dispatchers had a 32% rate of burnout.⁶ The 2019 Eagles burnout survey had more than 60% of the 1547 survey responders agree or strongly agree they felt burned out.⁷

The purpose of this research was to identify key variables in the daily aspect of an EMS professionals workday and determine if there is correlation between these variables and burnout. Some of the variables studied included number of hours of sleep during a shift, time to eat proper meals, and number of jobs held by a firefighter. Other aspects were surveyed such as the number of years a respondent had been in the industry, a supervisory position and whether or not they were career staff or volunteer.

Materials and Methods

Study Design and Settings: A voluntary, anonymous survey was distributed among 152 participants at a regional EMS conference in Northwest Louisiana. Participants represented paid and volunteer providers from a variety of systems. The survey was designed by discussion with EMS subject matter experts to compile a list of factors that may influence burnout. A standard 0-5 Likert scale was used to rate self reported burnout. A standard Likert scale allows for degrees of burnout from none to complete to be expressed.

Measures

Data collected included age, type of EMS service, shift length, how many agencies employed at, non-EMS employment, level of EMS provider, call types, average transport time, shifts per month, how often greater than 24 hours shifts, average sleep per shift, position as a supervisor, years of EMS experience, years at current EMS provider level and level of burnout.

Data Analysis

The data contained both categorical and numerical data. Basic statistics were performed in three ways: by using the numeric data only, by using only the categorical data, and using the combination of both. For additional processing, burnout was treated as both a numeric and ordinal variable. Numeric data was evaluated by descriptive statistics and correlation coefficients were calculated using Pearson’s method. Categorical data was processed using counts for each class label and correlation coefficients were calculated using Spearman’s Rank-order correlation. The decision tree was created used a form of decision tree learning using Beth Atkinson’s “rpart” algorithm. This is an extension to the CART method to produce a binary tree which may be used to determine in what circumstances a given burnout level may apply.

Results

A total of 152 participants were present at the conference where the survey was distributed. We received 90 responses for a 59.2% response rate. The mean age was 35.74 (range 19-59, IQR 28-44 or std dev 10.30). More than 61% of the participants were employed by fired based EMS and over 24% were employed by prvate EMS agencies. Participant demographics of the cohort can be seen in Table 1. Of note, the percentage is greater than 100% as some participants were employed at several types of agencies. Thirty-seven participants (40.217%) were employed at more than one agency.

Demographics	% (n)
Employment Type
Fire based	61.1% (55)
Private EMS	24.4% (22)
Third City Service	8.9% (8)
Volunteer	6.7% (6)
Government/Parish	3.3% (3)
Flight Based	3.3% (3)
EMS Level
EMT	42.2% (38)
AEMT	8.88% (8)
Paramedic	47.4% (43)
Nurse	5.55% (5)
Shift Length
48-72 hours	1.1% (1)
48 hours	2.2% (2)
24 hours	68% (62)
12-24 hours	5.5% (5)
12 hours	2.2% (2)
10 hours	4.4% (4)
8 hours	7.7% (7)
Transport Type
Scene Calls with transport	80% (72)
Scene Calls without transport	51.1% (44)
Special Events	41.1% (37)
Standby Calls	36.7% (33)
Transfer Calls	34.4% (31)

The average and median years of EMS service was 12.11 and 9 years, respectively (range 0-35, IQR 4-19, std dev 9.46). Non-EMS employment was reported in 31.5%. Average shift length was 24 hours in 68% of participants. Average shifts per month were 7-14 in 55.5%, followed by 14-21 in 26.7% and 0-7 in 14.4%. Scene calls with transport were the most common call type at 80%. Average transport times were 18.9 minutes. Average amount of sleep was 3-6 hours in 44.4%, 6-9 hours in 28.9%, 0-3 hours in 15.6%, 9-12 hours in 2.2% of participants. Participants were able to eat during shifts 87.8% of the time. Correlation were only observed between age, years of experience, and years of experience at current provider level.

Variable	n	Range (min, max)	Median	Mean	SD (%)
Age	90	40 [19, 59]	35	35.744	10.295 (25.7%)
# Service Type	90	2 [0, 2]	1	1.078	0.343 (17.1%)
# Employment	90	4 [1, 5]	1	1.522	0.768 (19.2%)
# Provider Level	90	2 [0, 2]	1	1.044	0.256 (12.8%)
# Call Type	90	5 [0, 5]	2	2.444	1.622 (32.4%)
Avg. Transport Time (min)	87	75 [0, 75]	15	18.891	16.195 (21.6%)
Years EMS Experience	90	35 [0, 35]	9	12.111	9.464 (27.0%)
Years Exp. At Current Level	90	30 [0, 30]	5	7.666	7.065 (23.5%)
Level Burnout	90	5 [0, 5]	2	1.944	1.419 (28.4%)

	Age	# Svc. Type	#Empl	# Prov. Level	# Call Type	Avg. Xport Time	Years EMS Exp.	Exp. At Level	Burn-Out
Age	1	-0.052	-0.082	0.107	0.172	0.054	0.799	0.688	0.278
# Service Type	-0.052	1	0.100	-0.168	0.099	-0.021	-0.046	-0.103	0.021
# Employed	-0.082	0.100	1	-0.005	-0.017	-0.235	0.090	-0.128	-0.076
# Provider Level	0.107	-0.168	-0.005	1	0.196	0.038	0.058	0.052	0.069
# Call Type	0.172	0.099	-0.017	0.196	1	0.005	0.158	0.096	0.211
Average Transport Time	0.054	-0.021	-0.235	0.038	0.005	1	-0.050	-0.083	-0.012
Years EMS Experience	0.799	-0.046	0.090	0.058	0.158	-0.050	1	0.793	0.465
Years Experience At Current Level	0.688	-0.103	-0.128	0.052	0.096	-0.083	0.793	1	0.374
Level Personal Burnout	0.278	0.021	-0.076	0.069	0.211	-0.012	0.465	0.374	1

Non-supervisory positions were held by 81.1% of participants while 16.7% were supervisors and 1.1% reported occasional supervisory shifts. The two most common levels were EMT (42.2%) and paramedic (47.4%). (Table 1) years of experience at current EMS level 7.67 (range 0-30, IQR 2.5-10.0, std dev 7.06).

Burnout was reported on a 0-5 Likert scale, with 0 being no burnout and level 5 being exhaustion of physical or emotional strength or motivation. Level 0 and 1 burnout was 43.18% of all participants. Level 2 burnout was 17.05%. Level 3 burnout was 23.86%. Level 4 burnout was 14.77%. Level 5 burnout was only 1.14%. Mean level of burnout was 1.94 (range 0-5, IQR 1-3, std dev 1.42). The decision tree showed some interesting factors associated with increased levels of burnout. More than 20.5 years of EMS experience was associated with burnout level of four where as no reported burnout was more related to shifts per month, sleep on shift and being an EMT. The amount of burnout did seem to increase directly with number of years experience with a slight U shaped curve below 20 years.

Discussion

EMS burnout has been recognized as a significant problem in EMS. This study showed correlation of burnout with age, years of experience as well as years of experience at current provider level. Burnout does directly increase with numbers of years of experience. Differences in levels of burnout were associated with number of shifts per month and sleep on shift, although they did not show correlation.

One of the factors we found associated with increased levels of self-reported burnout was increased amount of time in both EMS and at the current EMS level. In our cohort, we found more than 20.5 years in EMS was associated with increased burnout. Below 20 years of experience, there was a slight U-shaped curve seen in burnout. When a nationwide assessment of depression, anxiety and stress in EMS was performed in 2009, they found that those with more than 16 years of experience had an increased likelihood of depression.⁸ When looking at a cohort of volunteer EMS personnel, it was found that those who had more than six years of service were likely to have more risk-taking behavior and not talk about their thoughts or feelings.⁹ Crowe did a study of over 21,000 EMT and paramedics which showed increased levels of burnout at the paramedic level and having between 5-15 years of ems service.¹⁰

The increased burnout at the paramedic level may be secondary increased responsibility but it also may be directly related to the increased number of years in EMS at the paramedic level. However, in a South African study they found increased levels of burnout but no association with years of experience.¹¹ Current EMS levels showed some small effect on the burnout level. Duli showed correlations between years of experience, emotional exhaustion and depersonalization. This study also found that years of experience better predicted depersonalization and emotional exhaustion than proactive coping.¹²

Some of the other factors that differentiated levels of burnout in our study were numbers of shifts per month and sleep during shift. Our study showed decreased levels of burnout in those working six or less shifts and more than 14 shifts and increased levels of burnout at 7-13 shifts a month. The low burnout with 14 or more shifts is likely a function of those who are not burnt out and seek out extra work. Increased burnout with 7-13 shifts a month is less easily explained. It is possible these are people who are feeling burnt out and choose to work minimal amounts of shifts because of this.

This is an interesting finding as Rickard et al. found that those who were more financially dependent on extra work, and therefore working more shifts than average, had higher intention of leaving EMS at one year and lower job satisfaction which are factors that can lead to burnout.¹³

Our study showed sleep on shift for all EMS levels showed a low level of burnout if they got 0-2 hours or 6-8 hours of sleep. The 6-8 hours is a normal or near normal amount of sleep but the 0-2 hours is less understandable. Those who slept 3-5 hours or 9-11hours and had more than 3.5 years of EMS experience had a burnout level of three, but with the same ranges of sleep if they had less than 3.5 years EMS experience they reported a burnout level of one. This is also an unexplained observation as previous studies show that sleep disturbances may promote the onset of burnout.

Problems Caused

Burnout is a critical problem among medical providers which translates into poorer health outcomes for patients and leads providers to drop out of their profession and increases their risk of suicidality.^{15, 16} Provider drop out adds increased strain on existing EMS resources which, in turn, further exacerbates the problem of burnout itself. EMS providers, first responders in particular, have demonstrated high rates of burnout leading to increased lifetime suicide risk.¹⁷ Safety compromising behavior, injury, error and adverse events were found to be significantly associated with higher levels of burnout.⁴ Increased use of sick days was found in those who reported burn out symptoms.¹⁰ From the physiologic standpoint it was found paramedics in Houston had statistically significant higher levels of cortisol, epinephrine and norepinephrine in comparison to the firemen.¹⁸

Solutions

Burnout and overall mental health in EMS have to be addressed from both the critical incident and the daily cumulative incident standpoints. These solutions must be multifactorial and personalized. Halpern et al. looked at characteristics of potential critical incidents that were troubling to EMS providers. Personal characteristics such as being surprised and feeling helpless were most strongly associated with these incidents. Situational characteristics such as factors being beyond their control or difficult relatives were also highly prevalent in these incidents. Systemic characteristics however seemed to much less prevalent in these incidents. They also found these critical incidents to have nonsignificant relationships to current symptoms of depression and burnout.¹⁹

Another study also found career exposure to critical incidents was not associated with burnout.¹⁷ A period of downtime after a critical incident was associated with lower depression symptoms but no effect on burnout or PTSD symptoms.¹⁸ Studies have shown conflicting data about the association between critical incidents and burnout or PTSD. This is likely secondary to individual characteristics of each person and therefore individualized personal response to troubling incidents should be made.

Personal characteristics including means of coping have been linked to burnout. “Talking with colleagues” and “thinking about the positive benefits of work” have been found to be helpful or very helpful and lack of social support, coping strategies such as self-blame and food/substance use were associated with increased burnout. Significant differences in gender were found for coping mechanisms.^{2, 6, 9} Another technique found to have statistically significant decreases in burnout for EMS providers was a mindfulness intervention.¹⁹ The positive benefits of social support on burnout have been clearly shown. Peer discussion of perceived problems should be undertaken within the agency. An intensive mindfulness program may be outside time constraints, but periodic shorter mindfulness sessions should be considered.

Systemic characteristics have been shown to have some effect on provider burnout. Fatigue, insomnia and low sleep quality were found to be associated with depression in Australian paramedics.²⁰ Shift length can also have effect on provider burnout. A 2018 systematic review found little literature on the subject but did suggest that shifts of less than 24 hours were favorable for outcomes that the EMS personnel considered important such as sleep and sleep quality, fatigue and burnout/stress.²¹ Another study in rural EMS personnel found some burnout syndrome factors to be lack of control over workload, poor value alignment with employer, and lack of efficient teamwork.²²

EMS workers in both public and private sector companies cited factors such as wages, work locations and commute, vocational training and organizational support as having significant effect on their perceptions of self-wellness.²³ All of these factors can be addressed to mitigate provider burnout. Matching shifts to the providers natural sleep pattern can help. Shortening shifts to less than 24 hours may also have some effect. Open communication between employers and providers can help mitigate the provider feelings of lack of control and poor value alignment with the employer. Team trainings build efficient teamwork. Working with the providers on selection of work area should be undertaken to try and mitigate commute and unfavorable work location stress. Innovative ways of increasing wages should be sought.

Conclusions

Our study aimed to identify burnout rates and contributing factors among a regional EMS workforce. Results of this study provide no statistically significant data toward recognizing factors of burnout however does highlight associations and correlations. Analysis of the responses determined an association between burnout and years of EMS service, years at current level of care, and more advanced EMS provider levels. Recognizing and accounting for limitations of this study may yield higher resolution of burnout precipitating factors in future studies, perhaps even establishing factors temporally along a burnout continuum.

Limitations

A primary limitation of this study is the power, with a sample size of 92 respondents yielding a response rate of 60.5%. The response rate raises concerns of both selection and reporting bias as those providers who may be on the higher end of the burnout spectrum are less likely both to attend non-compulsory professional development activities and to complete the survey. Of the responses received, reporting bias may also present confounding of the results as the survey used was not blinded to the fact that its primary focus was burnout. The survey has “burnout” in the title and asks participants to self-identify their level of burnout on a Likert scale, rather than utilizing surrogate markers of burnout.

This direct nature of the survey affords respondents the opportunity to embellish or obscure burnout respectively due to extraneous factors such as transient dissatisfaction or shame associated with the stigma of burnout. Additional factors that were not considered include information regarding wages and benefits, including vacation time; the quality, upkeep, and regularity of replacement of equipment regularly used by EMS personnel; as well as what methods and software are used for charting. 

Future Research

This study provides opportunities to refine further investigation into burnout among EMS providers. Through continued utilization of a Likert scale for respondents to self-ascribe their level of burnout, burnout may be evaluated as a spectrum with temporal stratification of factors that lead to its progression. Other potential methodologies include: obtaining responses through a multi-agency survey rather than a convenience sample to achieve data that more accurately reflect the true population, and qualitative interviewing to further elucidate the complex adaptive system in which burnout occurs among EMS providers.

Use of qualitative methods for data collection and evaluation may provide opportunity to construct a more cohesive theory of burnout and provide for targeted interventions to prevent it. A technique such as grounded theory methodology, which seeks to extract, codify, and classify qualitative information into a working theory may prove beneficial for this purpose. Future research should also consider whether combinations of factors, rather than each factor individually, significantly contribute to the development of burnout. 

Acknowledgments

Clarence Reese, Shreveport Fire Department

Cody Daniels, Signal 51 Group

Shreveport Fire Department

Declaration of interest statement: the authors declare to have no declarations of interest.

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