Job burnout has been identified in many professions since its classification in the 1970s (Freudenberger, 1974). However, its prevalence in the health professions, and paramedicine in particular, has been consistently high (Hammer et al, 1986; Grigsby and McKnew, 1988; Murphy et al, 1994; Stassen et al, 2013).
What is burnout?
Job burnout has variously been described as having components of ‘emotional exhaustion, depersonalisation, and reduced personal accomplishment’ (Maslach et al, 2001), or ‘a state of physical, emotional and mental exhaustion that results from long-term involvement in work situations that are emotionally demanding’ (Schaufeli and Greenglass, 2001).
These definitions highlight the multicomponent nature of the issue. Burnout is linked to poor job retention, poor patient care and decreased emotional and physical wellbeing (Grevin, 1996; Maslach et al, 2001; Nirel et al, 2008). It has also been linked to other mental health disorders such as depression, anxiety and negative physical outcomes. There is still a lack of clarity around the interconnectedness of these domains that are further obviated dependent upon the tool used to measure burnout (Shirom, 2005).
There has been an increasing focus on mental health concerns related to paramedics (Ambulance Victoria, 2015). However, this emphasises aspects such as suicide (Milner et al, 2016), stressors, traumatic events (Halpern et al, 2012), fatigue and mental health (Courtney et al, 2010), experience and paramedic resilience (Gayton and Lovell, 2012), and rurality and stress (Pyper and Paterson, 2016)— but none specifically look at burnout.
International context
Recent South African research identified that up to 30% of paramedics suffer the effects of burnout (Stassen et al, 2013), while a Dutch study described the risk of burnout to ambulance personnel as greater than that found in the general population (van der Ploeg and Kleber, 2003). A Scottish study found that up to 36% of paramedics reported some component of burnout (Alexander and Klein, 2001). However, the multidimensional nature of burnout makes it difficult to compare these figures to the Australian paramedic population, which works across different healthcare systems, patient case-mixes, prehospital organisations or with different levels of education to their overseas counterparts (Grigsby and McKnew, 1988; Grevin, 1996; Alexander and Klein 2001; Alexander et al, 2009).
Current study
The current study describes the prevalence of total burnout in a sample of the Australian paramedic workforce and the prevalence of three subcategories of burnout:
Possible predictors of burnout are also presented.
Methods
Study design
The present study used a quantitative, cross-sectional online survey methodology to gather a national convenience sample over a period of 5 weeks in April–May 2015. The primary outcome for the study was prevalence of overall work burnout (%). Secondary outcomes were prevalence of subgroups of burnout (personal, work and patient), and factors predictive of these.
Participants
Participants were Australian paramedics currently employed by either an Australian state ambulance service or the Australian Defence Force (ADF). Australian paramedicine is predominantly a paramedic-led system, with physicians rarely working in frontline paramedic services. Most Australian ambulance services provide a two-tiered response system: (advanced life support (ALS)/qualified paramedics (QP) and intensive care paramedics (ICP)). ADF paramedicine includes medics, advanced medics and combat medics who have a combined nursing/paramedicine skill set.
Recruitment
Owing to the lack of a central register of paramedics in Australia, national recruitment was carried out via advertisements in paramedicine industry journals, social media platforms, and self-initiated participant snowballing. Various recruitment avenues directed participants to a secure online survey site (SurveyMonkey®, California USA) with information and participant consent fields that had to be completed prior to being able to access the survey itself. Privacy and confidentiality were guaranteed; while the survey tool linked each response to an internet protocol (IP) address, it was not capable of collecting individual login details.
Survey instrumentation
The Copenhagen Burnout Inventory (CBI) (Kristensen et al, 2005) is a 19-item validated survey used to determine the prevalence of burnout. The survey is divided into three subcategories:
Each subcategory is evaluated through a number of questions:
These questions have a 5-point Likert-type response of ‘always’ or ‘to a very high degree’ scoring 100, to ‘never/almost never’ or ‘to a very low degree’ scoring 0. This allows calculation of an average burnout score for each of the three subcategories, as well as a ‘total’ burnout score from all of the subcategories as described by Kirstensen et al (2005). A score of >50 is indicative of total burnout.
The CBI has good reliability and criterion-related validity when used in Australian samples (Winwood and Winefield, 2004) and has been used in recent international paramedic research (Stassen et al, 2013). Additionally, participants were asked to complete data relating to potential predictors of burnout including gender, age, marital status, years of employment, organisational role, level of education and location of work (all categorical; refer to Table 1 for categories of each variable).
| Characteristic | n (%) |
|---|---|
| Age | |
| 20–29 years | 219 (24.5) |
| 30–39 years | 323 (36.2) |
| 40–49 years | 233 (26.1) |
| 50+ years | 118 (13.2) |
| Marital status | |
| Single | 158 (17.7) |
| Married | 459 (51.4) |
| Separated | 25 (2.8) |
| Divorced | 36 (4.0) |
| De facto | 201 (22.5) |
| Other † | 14 (1.6) |
| Primary role | |
| Advanced life support paramedic | 559 (62.6) |
| Medic | 56 (6.3) |
| Intensive care paramedics | 140 (15.7) |
| Specialist paramedic | 43 (4.8) |
| Manager | 31 (3.5) |
| Student | 25 (2.8) |
| Other ‡ | 39 (4.4) |
| Education | |
| In-housing training | 22 (2.5) |
| Certificate | 6 (0.7) |
| Diploma | 276 (30.9) |
| Bachelor's degree | 446 (49.9) |
| Honours degree/graduate certificate/graduate diploma | 104 (11.6) |
| Masters and Doctor of Philosophy | 39 (4.4) |
- included widowed, same-sex partner, engaged
- includes differing terminology due to organisational variations
Ethical approval
Western Sydney University Human Research Ethics committee granted approval: H10916.
Data analysis
Data were downloaded from the survey and analysed using Stata® v.13 (StataCorp LP). Analysis was only conducted on complete sets of respondent data, hence management of missing data is not described.
Descriptive statistics were generated, with continuous variables described as mean with standard deviation (SD) or median with interquartile range (IQR) for normal and non-normally distributed data, respectively. Statistical significance for all descriptive tests was established when p<0.05. Initial descriptive analysis was undertaken to determine prevalence of the primary outcome of burnout, and the secondary outcomes of total burnout, personal burnout, work burnout and patient burnout as described by Kristensen et al (2005).
Categorical variables of gender, age, marital status, years of employment, organisational role, level of education, and location of work, identified a priori through existing literature and author consensus, were subjected to multivariable logistic regression to identify associations with the dichotomous outcome variable of ‘total burnout’ (yes or no).
In this exploratory analysis, each predictor variable underwent univariable logistic regression analysis, and those with significance of p<0.25 were included in a base multivariable regression model. A backward elimination approach was used to fit the final multivariable model, with the most non-significant variable removed at each step until only statistically significant variables (p<0.05) remained. Interactions between significant variables were assessed and retained in the regression model only if p<0.01; goodness of fit of any final model was tested using the Hosmer and Lemeshow test. Regression analysis results are expressed as odds ratios (OR) with 95% confidence intervals (CI).
Results
A total of 960 paramedics consented to participate in the survey. This represents an estimated response rate of 8.3% based on the probable number of paramedics reported in the 2011 census data (Paramedics Australasia, 2012). Of these, 67 provided incomplete data and were removed; there were 893 complete datasets used in the analysis.
Demographic data for participants are presented in Figures 1–3 and Table 1. Most respondents were male (54%) (Figure 1); married (52%); working as ALS paramedics (63%) in capital cities (66%) (Figure 3); and had completed at least a Bachelor's degree in paramedic education (50%). There was a spread of data for years of service with slightly more respondents having worked as a paramedic for 9 years or less (54%) (Figure 2).
Prevalence of burnout noted 55.9% of respondents were determined to have total burnout at the time of completing the survey, while 43.4% had patient-related burnout, 62.7% had work-related burnout and 69.1% had personal-related burnout.
Univariable regression for total burnout is shown in Table 2, and the multivariable regression in Table 3. Location, gender and years of employment were all seen to be predictors of total burnout. The multivariable logistic regression showed that male paramedics had 33% less odds of suffering burnout (OR=0.67, 95% CI 0.5–0.9, p<0.001) while those working in capital cities (OR=3.0, 95% CI 1.6–5.7, p=0.001) and who had been working between 15 and 19 years (OR=3.7, 95% CI 2.3–6.1, p<0.001) had increased odds of suffering burnout. The final multivariable model has a good strength of fit, Hosmer-Lemeshow χ2 (df=8) of 7.77 p=0.46. Location and gender also interacted statistically, and indicate that the different effects of total burnout between the genders are greatest in the capital city and have almost no effect in those paramedics working in a remote setting.
| Characteristic | Burnout n (%) † | No burnout n (%) † | Unadjusted OR (95% CI) ‡ | P | |
|---|---|---|---|---|---|
| Gender | Female | 242 (59.3) | 166 (40.7) | 1 | 0.06 |
| Male | 257 (53.0) | 228 (47.0) | 0.8 (0.6–1.0) | ||
| Age | 20–29 years | 108 (49.3) | 111 (50.7) | 1 | 0.12 |
| 30–39 years | 186 (57.6) | 137 (42.4) | 1.4 (1.0–2.0) | ||
| 40–49 years | 140 (60.0) | 93 (40.0) | 1.5 (1.1–2.2) | ||
| 50+ years | 65 (55.0) | 53 (45.0) | 1.3(0.8–2.0) | ||
| Marital status | Single | 87 (55.1) | 71 (44.9) | 1 | 0.81 |
| Married | 264 (57.5) | 195 (42.5) | 1.1 (0.8–1.6) | ||
| Separated | 13 (52.0) | 12 (48.0) | 0.9 (0.4–2.1) | ||
| Divorced | 21 (58.3) | 15 (41.7) | 1.1 (0.5–2.4) | ||
| De facto | 105 (52.2) | 96 (47.8) | 0.9 (0.6–1.4) | ||
| Other (widowed, same-sex, engaged) | 9 (64.3) | 5 (35.7) | 1.5 (0.5–4.6) | ||
| Years as a paramedic | <5 years | 92 (41.4) | 130 (58.6) | 1 | <0.001 |
| 5–9 years | 159 (61.9) | 98 (38.1) | 2.3 (1.6–3.3) | ||
| 10–14 years | 100 (58.5) | 71 (41.5) | 2.0 (1.3–3.0) | ||
| 15–19 years | 82 (68.9) | 37 (31.1) | 3.1 (2.0–5.0) | ||
| 20+ years | 66 (53.2) | 58 (46.8) | 1.6 (1.0–2.5) | ||
| Primary role | ALS paramedic | 321 (57.4) | 238 (42.6) | 1 | 0.08 |
| Medic | 31 (55.4) | 25 (44.6) | 0.9 (0.5-1.6) | ||
| Intensive care paramedics | 79 (56.4) | 61 (43.6) | 1.0 (0.7–1.4) | ||
| Specialist paramedic | 20 (46.5) | 23 (53.5) | 0.6 (0.3–1.2) | ||
| Manager | 16 (51.6) | 15 (48.4) | 0.8 (0.4–1.6) | ||
| Student | 7 (28.0) | 18 (72.0) | 0.3 (0.1–0.7) | ||
| Other | 25 (64.1) | 14 (35.9) | 1.3 (0.7–2.6) | ||
| Education | Bachelor's degree | 240 (53.8) | 206 (46.2) | 1 | 0.09 |
| In-housing training | 18 (81.8) | 4 (18.2) | 3.9 (1.3–11.6) | ||
| Certificate | 3 (50.0) | 3 (50.0) | 0.9 (0.2–4.3) | ||
| Diploma | 163 (59.1) | 113 (40.9) | 1.2 (0.9–1.7) | ||
| Honours degree/graduate certificate/graduate diploma | 52 (50.0) | 52 (50.0) | 0.9 (0.6–1.3) | ||
| Masters and Doctor of Philosophy | 23 (59.0) | 16 (41.0) | 1.2 (0.6–2.4) | ||
| Location of work | Remote (<5000) | 16 (34.8) | 30 (65.2) | 1 | 0.03 |
| Rural (5000–24999) | 66 (55.1) | 53 (44.9) | 2.3 (1.1–4.7) | ||
| Large rural centre (<25000) | 77 (57.9) | 56 (42.1) | 2.6 (1.3–5.2) | ||
| Capital city | 341 (57.2) | 255 (42.8) | 2.5 (1.3–4.7) |
- Percentages do not always add to 100 due to rounding;
- OR = Odds Ratio; CI = confidence interval § - includes differing terminology due to organisational variations
| Factor | Adjusted OR (95% CI) † | P | |
|---|---|---|---|
| Years employed | 0–4 (referent) | 1 | <0.001 |
| 5–9 | 2.5 (1.7–3.6) | ||
| 10–14 | 2.2 (1.4–3.3) | ||
| 15–19 | 3.7 (2.3–6.1) | ||
| 20+ | 2.0 (1.2–3.1) | ||
| Location | Remote population <5000 (referent) | 1 | 0.008 |
| Small rural (5000–24 999) | 2.6 (1.2–5.3) | ||
| Large rural (population <25 000) | 3.0 (1.5–6.1) | ||
| Capital city | 3.0 (1.6–5.7) | ||
| Gender | Female (referent) | 1 | 0.005 |
| Male | 0.7 (0.5–0.6) |
Abbreviations: † - OR = odds ratio; CI = confidence interval
Discussion
This cross-sectional survey of a national population of paramedics represents the first such study in the Australasian context, and has identified a prevalence of total burnout of ~56%. High levels of burnout are consistent with international paramedic burnout studies in the United States (Hammer et al, 1986; Grigsby and McKnew, 1988; Murphy et al, 1994; Grevin, 1996; Essex and Scott, 2008); Canada (Regehr and Millar, 2007); Israel (Schaufeli and Greenglass, 2001); South Africa (Stassen et al, 2013); the Netherlands (van der Ploeg and Kleber, 2003); and Scotland (Alexander and Klein, 2001) over the last 30 years.
The current study also presents the largest sample the authors could locate of paramedic burnout, with many other studies sampling less than 250 respondents. This was often as a result of small workforce populations, but given the diverse work environments of Australian paramedics, the larger sample provides a sound base for further research into this area. Indeed, the authors found three factors which had an impact upon the likelihood of experiencing total burnout when controlled for other factors: gender; location; and years of service.
Gender
The present study identified women to be almost one-third more likely to experience total burnout than male colleagues, adjusted for location and length of employment. Reasons underpinning such a result are unclear, although possible suggestions include disproportionate childcare and family responsibilities. Previous studies present contradictory results in terms of gender and burnout, and have offered suggestions of occupational bias, gender norms, and caring responsibilities (Schaufeli and Greenglass, 2001).
Maslach et al (2001) found some indication that males are more prone to cynicism and females to emotional exhaustion, but questioned whether this was a function of the skewed gender sample in some occupations rather than attributable to gender itself. Conversely, Bekker et al (2005) noted that male, rather than female, nurses were more likely to experience emotional exhaustion, while Nirel et al (2008) found no influence of gender.
Perhaps because of its larger sample, the present study exhibited a gender balance rarely seen in other studies (Hammer et al, 1986; Murphy et al, 1994). Gender imbalance is expected in earlier studies, reflective of a male-dominated workforce, but even more recent studies (Pyper and Paterson, 2016) don't reflect increasing feminisation of the Australian paramedic workforce (females represented 26% of the paramedic workforce in the 2006 census compared with 32% in 2011) (Paramedics Australasia, 2012).
Gender-associated flexible working patterns and increasing feminisation are important to gain an accurate understanding of the role played by gender in burnout. When gender responses are not skewed, other studies have noted differences in coping mechanisms to stress in relation to males and females, indicating that interventions may need to be different in order to be most effective for each gender (Essex and Scott, 2008).
Location
Work location proved to be a powerful predictor of burnout. Adjusting for gender and years of service, working in a metropolitan location was associated with 2.7 times greater odds of total burnout compared with non-metropolitan locations. This contrasts with the results of Courtney et al (2010) who found no significant difference in the mental health of rural paramedics compared with their metropolitan counterparts, although both suffered poorer mental health than non-paramedic participants. Paramedics who work in capital cities suffering greater burnout could be simplistically linked to higher clinical workload; however, the concept of burnout is more complex. Possible positive influences in rural locations such as increased quality of life away from work and sense of community need to be balanced with negatives of decreased support and resources.
Length of employment
Length of employment as a paramedic was found in this population to be associated with burnout. Paramedics suffering the greatest burnout after 15–19 years supports the supposition that burnout is cumulative, taking years to manifest. It also highlights the importance of longitudinal studies to best describe the chronic nature of burnout (Shirom, 2005).
Why this 15 to 19-year employment bracket experiences a peak in burnout compared with brackets before and after is unclear. A possible explanation might lie in this time period corresponding with the emergence of life and career challenges often experienced around middle age, with total burnout being a manifestation of broader stressors away from work.
The lower burnout in the most advanced career stages demonstrated in the current study has also been seen in other health professions such as emergency medicine and nursing (Howlett et al, 2015). Reasons for this fall may relate to positive coping strategies of these particular individuals.
Other predictors of burnout
A number of potential predictors such as genetic predisposition of the individual (Middeldorp et al, 2005); personality type (Grevin, 1996); protective influence of partners (Maslach et al, 2001); organisational culture and other work-related factors (Schaufeli and Enzmann, 1998) were expected to impact burnout based on existing literature and discussion with paramedics, but the analysis in the present study did not support these.
Education has previously been shown to have a negative correlation to burnout, with higher levels of education being associated with higher levels of burnout (Maslach et al, 2001) and lower levels of organisational commitment (Alexander et al, 2009). Anecdotally, paramedics suggested that the move to university pre-employment paramedic training, with greater focus on resilience and reflection, may have been protective towards burnout. This is not supported in the current analysis, and recent research by Gayton and Lovell (2012) indicates there is still insufficient training in this area.
Gayton and Lovell (20102) noted that some programmes provided less than 5 hours (out of a possible 350 hours) of resilience training, which suggests there may be a minimum amount of training and knowledge required for this to be protective. Re-examination of the relationship between pre-employment education and burnout should be considered further as resilience and wellness become integral parts of the profession (Porter and Johnson, 2008). A recent South African study, involving paramedic students, showed higher levels of burnout when compared with students in nursing and medical programmes, and similar levels of burnout when compared with already practising paramedics (Stein and Sibanda, 2016). This finding requires further exploration, as a newly graduated paramedic who experiences burnout upon entering a service may be problematic. The individual's wellness and resilience may already be compromised, leading to greater risk of occupational harm from sustained exposure to the clinical environment, as well as the operational and organisational pressures associated with it. There may be opportunities for university programmes to integrate wellness and resilience training more actively into undergraduate curricula during these formative years of study and preparation.
The findings presented here represent the first of their kind in Australian paramedicine, and lend weight to concerns surrounding this issue. These data will be beneficial for initiating a national dialogue on the issue of burnout in paramedicine and emergency medical services more broadly. That dialogue should focus on expanding the quantitative data presented herein, exploring strategies to support younger paramedics, and ensuring that support for paramedics is tailored with regard to individual circumstances and characteristics throughout their careers.
Limitations
There are a number of limitations in light of which these results should be considered. The response rate of 8% is low, and may affect the representativeness of these findings. However, web-based surveys are known to have significantly lower response rates and the lack of a defined population compounded this. The sample of almost 900 paramedics does represent one of the largest explorations of paramedic burnout and therefore makes a meaningful contribution to the existing body of knowledge in this area.
As with many other burnout studies, there is a concern with positive selection bias. However, others have suggested balancing these concerns with the effects of burnout, including apathy, which may predispose paramedics suffering from burnout to be less likely to respond (Grigsby and McKnew, 1988).
Finally, the study of burnout is compounded by the use of multiple assessment tools, impacting the comparability of studies. Both the CBI and the Maslach Burnout Inventory (MBI) are validated, reliable instruments, with cases being made by previous authors (Kristensen et al, 2005) for the preferred use of one over the other. Irrespective of the tool used, however, surveys frequently focus on the individual, thereby limiting results that address administrative or organisational stressors that may impact burnout.
Future qualitative research is recommended to enable a deeper understanding of such stressors, but this was beyond the scope of the current study. With the rapidly changing nature of Australian paramedicine, situational factors such as role clarity, registration and autonomy may have increasing impacts on burnout, and could be considered in future research (Maslach et al, 2001).
Conclusion
The present study suggests that the prevalence of total burnout is high in the Australian paramedic population and that, of the specific categories of burnout described in the CBI, personal burnout was most common. Females, metropolitan work location, and having worked 15–19 years as a paramedic were all predictive of burnout. Although there is some international research in this area, the unique situation of Australian paramedicine means that these new data can be used to inform the development of tailored preventative and recovery strategies for those with burnout or who are at risk.