Abstract
Background
Burnout is prevalent in doctors and can impact on job dissatisfaction and patient care. In medical students, burnout is associated with poorer self-rated health; however, it is unclear what factors influence its development. This study investigated whether health behaviours predict burnout in medical students.
Methods
Medical students (n=356) at the Universities of St Andrews and Manchester completed an online questionnaire assessing: emotional exhaustion (EE), depersonalisation (DP), personal accomplishment (PA), alcohol use, physical activity, diet, and smoking.
Results
Approximately 55% (54.8%) of students reported high levels of EE, 34% reported high levels of DP, and 46.6% reported low levels of PA. Linear regression analysis revealed that year of study, physical activity, and smoking status significantly predicted EE whilst gender, year of study, and institution significantly predicted DP. PA was significantly predicted by alcohol binge score, year of study, gender, and physical activity.
Conclusions
Burnout is present in undergraduate medical students in the United Kingdom, and health behaviours, particularly physical activity, predict components of burnout. Gender, year of study, and institution also appear to influence the prevalence of burnout. Encouraging medical students to make healthier lifestyle choices early in their medical training may reduce the likelihood of the development of burnout.
Keywords: burnout, medical students, diet, physical activity, alcohol, lifestyle
Burnout is a measure of physical and psychological exhaustion and mental distress catalysed primarily by occupational and professional demands. It is characterised by heightened levels of emotional exhaustion (EE) and depersonalisation (DP) (described as emotional indifference and the dehumanisation of the client or patient), and a decreased perception of personal accomplishment (PA) (1). Burnout is commonly found in individuals working within human services and recent studies estimate the prevalence of burnout in American doctors to be around 40% (2, 3), although some have found it to be as high as 76% in internal medicine residents (4). The cause of burnout is complex and unclear; however, it is becoming increasingly evident that many students begin to experience burnout in medical school, with prevalence rates of around 49% in medical students in the USA and 28–61% in Australia (5).
Burnout and stress are symptomatically similar, with burnout attributed specifically to occupational stressors (6). McManus and colleagues (7) proposed that there is a cyclical relationship between stress and EE, suggesting that heightened levels of stress and poor coping strategies may be key contributors in the development of burnout. Medical school is challenging and previous work suggests that a number of factors, from academic pressures and educational debt, to personal life events, gender, learning environment and exposure to human suffering, contribute to heightened levels of stress and poor mental health in medical students, including burnout 8–11) . Additional research has also shown that maladaptive lifestyle and health behaviours as a means of coping with stress are prevalent among young people and university students, with studies suggesting associations between stress, alcohol consumption (12, 13), unhealthy diets (14, 15), and reduced physical activity (16).
Generally, it has been shown that health beliefs and behaviours are sub-optimal in European university students (17). In addition, alcohol consumption has been found to be higher in medical students than in age-matched samples in the general population (18, 19) and increased alcohol intake has also been associated with higher levels of distress, anxiety, and exam and work pressures in medical students (20, 21). Other studies have found physical inactivity, unhealthy diets, and smoking to be an issue in university and medical student samples 22–25).
Research has identified associations between burnout and lifestyle health behaviours. Gorter and colleagues (26) noted that Dutch dentists who reported high levels of burnout consumed more alcohol and had less healthy diets than those reporting lower levels of burnout. More recently, Gerber and colleagues (27) proposed that interventions to increase physical activity can help to improve the symptoms of burnout.
Poor lifestyle, poor health behaviours, and high levels of burnout have been reported in medical students; however, few studies have directly investigated the relationship between burnout, lifestyle, and health behaviours in a medical student population, with most work focusing on trainee doctors (28, 29). This study investigates the prevalence of burnout and potential association of burnout with habitual diet, physical activity, alcohol consumption, and smoking in medical students from two medical schools (St Andrews & Manchester) in the United Kingdom. More specifically this study asks:
Is burnout prevalent in a sample of medical students from two UK medical schools?
Does the prevalence of burnout vary with age, gender, year of study, and institution attended?
Do medical students’ lifestyle and health behaviours vary by gender, year of study, and institution?
Do medical students’ lifestyle and health behaviours (alcohol consumption, physical activity, diet, and smoking) predict burnout component scores?
Methods
Participants
All undergraduate medical students at both St Andrews and Manchester Universities were invited to participate in the study. St Andrews Medical School offers a 3-year BSc medicine degree, after which students typically move to a guaranteed place at another medical school (including the Manchester Medical School or one of the other medical schools in Scotland) to complete their medical studies. Manchester Medical School offers a 5-year MBChB degree course.
Data collection
Consenting participants were surveyed electronically from March to May 2012. The survey consisted of four separate and validated tools used to assess burnout (30) alcohol consumption (31), physical activity levels (32), and eating habits (33). Demographic data were also collected, including age, gender, year of study, and institution. Smoking status was also recorded.
Maslach Burnout Inventory
The Maslach Burnout Inventory (MBI) is a standard measure of burnout (30), commonly used in medical student populations (10, 35, 36). It contains 22 questions asking the participant to rate how often they experience various feelings. Each question has a seven-point response scale (1: never, 2: a few times a year or less, 3: once a month or less, 4: a few times a month, 5: once a week, 6: a few times a week, 7: everyday), and is designed to measure three components of burnout; EE, DP, and PA. EE are characterised by feelings of emotional overextension as a result of one's work. DP is characterised by emotional indifference and the dehumanisation of the recipients of one's services. Low PA is characterised by feelings of occupational stagnation, incompetence and underachievement (1). Scores in each of the three subscales were categorised into high, average or low scores according to ‘medicine’ cut-offs detailed in the MBI manual (6). High EE was defined as scoring ≥27, high DP≥10, and low PA≤33. Participants were identified as having burnout if they scored high in EE (≥27) and DP (≥10).
Alcohol Use Questionnaire
The Alcohol Use Questionnaire (AUQ) measures alcohol consumption (31, 36) and has been used previously in university student and young adult populations 37–39). The 12-item questionnaire assesses the frequency and quantity of alcohol consumption within the last six months. Alcohol intake and binge scores were calculated from this data (31).
International Physical Activity Questionnaire
The International Physical Activity Questionnaire (IPAQ) has been recognised as a reliable tool for providing estimates of an individual's general level of physical activity (32). It has been validated internationally and in university student populations (40, 41). This study used the short-form IPAQ which asked participants to estimate how often they had taken part in vigorous and moderate exercise as well as how much time they had spent walking and sitting over the last 7 days. The questionnaire provides information with regards to exercise frequency (times per week and duration of time spent) and intensity (low, moderate, high). Metabolic equivalents (METs/week) were also calculated from responses, giving a single quantifiable score that represented each participant's level of physical activity and each participant was categorised as having a high, moderate, or low level of physical activity using the IPAQ scoring protocol (42).
Food Frequency Questionnaire
The Food Frequency Questionnaire (FFQ) was used to assess how often participants typically ate listed foods, allowing their habitual dietary behaviour to be examined. It was developed as a means of replacing the time-consuming diet diary method and has proven itself as a reliable alternative (33) and variations have been used in populations of young people and health professionals (43, 44). Using a short-form version of the FFQ (33), participants estimated how often they consumed each of 36 different food options on a six-point scale, ranging from ‘two or more times daily’ to ‘rarely/never’. Seven food groups of interest were constructed from these options: Fruit, Vegetables, Fruit & Vegetables, High Calorie Drinks, Sweet Foods (foods high in fat and sugar, e.g., chocolate, cakes, sweets, and candies), Savoury Foods (foods high in fat, e.g., fried foods, cheese-based foods, butter, margarines, and oils), and Savoury Snacks (crisps and similar foods, high in fat and salt). Total scores were calculated for each food group to identify frequency of consumption.
Ethics
This study was reviewed and approved by the University of St Andrews and University of Manchester research ethics committees.
Analysis
Descriptive summary statistics were conducted to estimate the prevalence of burnout in the student sample and to assess alcohol intake, levels of physical activity, and food frequency. Analysis of variance (ANOVA) was used to examine differences in burnout, alcohol intake, physical activity, food frequency and smoking between student genders, and year of study. Backward multiple linear regression analysis was conducted for each of the three MBI component scores to examine the relationship between burnout and lifestyle behaviours. All predictors were entered into the model initially and successively removed if p≥0.10 until a final model was produced. All analysis was conducted using SPSS 19. Statistical significance was set at p≤0.05.
Results
Participation and sample
A total of 2,647 students were invited to take part via an advert on their virtual learning environments, 471 medical students at the University of St Andrews and 2,176 medical students at the University of Manchester. Four hundred and seven participants were recruited and submitted an online questionnaire. Fifty-one questionnaires were removed from the analysis because of incomplete MBI questionnaires leaving 356 questionnaires. The usable data response rate from St Andrews students was 27.2% (n=128), whilst for Manchester students it was 10.5% (n=228) of the possible sample.
Participant demographic information is shown in Table 1. More female medical students (65.8%, n=232) than males (34.8%, n=124) participated. The majority of participants (90.2%, n=321) were between the ages of 18 and 23, and 79.7% (n=284) of participants were in the first, second, or third year of their medical studies.
Table 1.
Participant demographics
| Variable | n | % of respondents |
|---|---|---|
| Institution | ||
| St Andrews only | 128 | 36 |
| Manchester only | 195 | 54.8 |
| St Andrews then Manchester | 27 | 7.6 |
| Other University then Manchester | 6 | 1.7 |
| Gender | ||
| Male | 124 | 34.8 |
| Female | 232 | 65.2 |
| Age group | ||
| 18–23 | 321 | 90.2 |
| 24–29 | 30 | 8.4 |
| ≥30 | 5 | 1.4 |
| Year of study | ||
| First | 141 | 39.6 |
| Second | 77 | 21.6 |
| Third | 66 | 18.5 |
| Fourth | 47 | 13.2 |
| Fifth | 25 | 7 |
Burnout prevalence
More than half of the participants (54.8%) reported experiencing high levels of EE, 34% reported high levels of DP and 46.6% reported low levels of PA (Table 2). Overall, 26.7% of participants met the criteria to be considered ‘burned out’.
Table 2.
MBI scoring for components of burnout and burned out prevalence by institution(s) attended, gender and year of study
| Emotional exhaustion (EE) | Depersonalisation (DP) | Personal accomplishment (PA) | |||||
|---|---|---|---|---|---|---|---|
|
|
|
|
|||||
| Mean (SD) | n (%) high EE score | Mean (SD) | n (%) high DP score | Mean (SD) | n (%) low PA score | Burned out n (%) | |
| All participants (n=356) | 28.26 (10.08) | 195 (54.8) | 9.08 (4.30) | 121 (34) | 38.07 (9.39) | 166 (46.6) | 95 (26.7) |
| Institution | |||||||
| St Andrews (n=128) | 28.59 (10.39) | 70 (54.7) | 9.26 (4.47) | 50 (39.1) | 38.16 (9.72) | 60 (46.9) | 39 (30.5) |
| Manchester (n=195) | 28.15 (10.13) | 106 (54.4) | 8.76 (4.15) | 56 (28.7) | 37.31 (9.36) | 84 (43.1) | 45 (23.1) |
| St Andrews then Manchester (n=27) | 27.96 (9.02) | 16 (59.3) | 10.22 (4.33) | 12 (44.4) | 42.37 (7.46) | 18 (66.7) | 9 (33.3) |
| Other than Manchester (n=6) | 26 (7.77) | 3 (50) | 10.83 (4.92) | 3 (50) | 41.67 (5.32) | 4 (66.7) | 2 (33.3) |
| p | ns | ns | 0.049 | ns | |||
| Gender | |||||||
| Male (n=124) | 27.68 (11.01) | 65 (52.4) | 9.85 (4.86) | 50 (40.3) | 36.28 (10.16) | 52 (31.3) | 38 (30.6) |
| Female (n=232) | 28.57 (9.56) | 130 (56) | 8.68 (3.68) | 71 (30.6) | 39.03 (8.83) | 114 (68.7) | 57 (24.6) |
| p | ns | 0.014 | 0.008 | ns | |||
| Year of study | |||||||
| 1 (n=141) | 28.67 (10.36) | 79 (56) | 8.68 (4.30) | 42 (29.8) | 35.98 (10.14) | 52 (31.3) | 35 (24.8) |
| 2 (n=77) | 29.42 (9.72) | 46 (59.7) | 9.05 (4.11) | 27 (35.1) | 37.25 (9.78) | 35 (21.1) | 21 (27.3) |
| 3 (n=66) | 26.33 (9.69) | 34 (51.5) | 8.85 (4.08) | 20 (30.3) | 39.56 (7.84) | 38 (22.9) | 16 (24.2) |
| 4 (n=47) | 26.74 (10.08) | 21 (44.7) | 9.62 (4.18) | 19 (40.4) | 40.13 (7.60) | 22 (13.3) | 13 (27.7) |
| 5 (n=25) | 30.32 (10.29) | 15 (60) | 11.08 (5.28) | 13 (52) | 44.64 (6.02) | 19 (11.4) | 10 (40) |
| p | ns | ns | <0.001 | ns | |||
SD=standard deviation.
MBI cut-offs: high EE≥27; high DP≥10; low PA≤33; burned out if high in EE and DP; ns=not significance.
Prevalence of burnout by age, gender, year of study, and institution
Chi-square analysis showed no significant impact of participant gender (χ 2 (1)=1.53, p=0.217), year of study (χ 2 (4)=2.75, p=0.600), or institution (χ 2 (3)=2.98, p=0.395) on the global prevalence of burnout in the sample. However, analysis of variance revealed that there were significant effects of participant gender, year of study, or institution on scores for the three components of burnout (EE, DP, and PA). The small number of participants who were in the St Andrews then Manchester cohort had significantly higher PA than those in the Manchester only cohort (F (3)=2.65, p=0.049). Males reported significantly higher levels of DP (F (1)=6.06, p=0.014) and significantly lower levels of PA than females (F (1)=7.04, p=0.008). PA scores increased with each year of study (F (4)=6.29, p≤0.001) (Table 2).
Lifestyle and health behaviours by gender, year of study, and institution
Alcohol use
There were no gender differences in alcohol consumption. Mean alcohol intake scores were significantly higher in first year (46.86±13.92) than second year (40.46±9.98), (F (4)=4.48, p=0.002). Alcohol binge scores were also significantly higher in first year (38.47±11.41) when compared with second-year (32.44±8.68) and fourth-year scores (32.65±7.75), whilst third-year binge scores (37.45±11.97) were significantly higher than second-year scores (32.44±8.68), (F (4)=6.30, p<0.001). Alcohol consumption did not significantly differ between institutions.
Physical activity
Chi-square analysis indicated that there was a significant association between physical activity intensity (low, moderate, and high) and gender (χ 2 (2, n=325)=11.76, p=0.003), with a greater proportion of male students (n=59, 54.1% of males) in the high intensity physical activity group than female students (n=76, 35.2% of females). There was no significant relationship between physical activity intensity and year of study or institution. Physical activity levels differed by gender with males reporting higher weekly METs (2773.72±1708.57) than females (2214.12±1810.65), (F (1)=7.18, p=0.008). Reported weekly METs were significantly higher in fifth-year students (3500.46±2868.50) than in first (2138.96±1567.30) or second year (2331.78±1409.44), (F (4)=3.12, p=0.015). Physical activity levels did not significantly differ between institutions.
Diet
Gender impacted intake of several food groups. Female students reported lower FFQ savoury food consumption scores (13.85±9.23) than male students (18.33±11.31), (F (1)=16.22, p<0.001). Female students also had higher vegetable consumption scores (18.08±10.59) than male students (14.27±10.01), (F (1)=9.92, p=0.002). Vegetable consumption scores systematically increased with each successive year of study (F (4)=2.72, p=0.029) whilst sweet food consumption scores were significantly higher in third year (15.49±15.11) than in second year (10.01±8.03), (F (4)=2, 12, p=0.048). St Andrews only participants were found to have a significantly higher combined fruit and vegetable consumption scores (30.78±17.46) than Manchester only participants (24.83±14.96), (F (3)=4.78, p=0.003).
Smoking
Three hundred and sixteen (88.8%) participants reported that they did not smoke currently and had never smoked, 22 (6.2%) participants reported that they were ex-smokers, and 18 (5.1%) reported being current smokers. Chi-square analysis indicated that there was no significant difference between smoking status and gender, year of study, or institution.
Relationship between burnout components, demographics, lifestyle, and health behaviours
Backward stepwise multiple regression analysis was used to test whether the demography, lifestyle and health behaviours of the students predicted levels of the three components of burnout (EE, DP, and PA).
The results of an 18-step regression using EE scores as the dependant variable (Table 3) indicate that four predictors explained 6.4% of the variance (R 2=.064, F (4,317)=5.36, p<.001). It was found that being in third year in comparison to first year (β=−0.13, p=0.020) significantly predicted lower EE scores. It was also found that having low levels of physical activity in comparison to high levels (β=0.15, p=0.005) and being an ex-smoker in comparison to having never smoked (β=0.14, p=0.012) significantly predicted higher EE scores. Sweet food consumption scores were important for the overall model but were not found to be a significant predictor of EE scores (β=0.09, p=0.081).
Table 3.
Final model in an 18-step backward stepwise regression analysis predicting MBI emotional exhaustion (EE) scores
| Variable (variable type/reference category) | B (SE) | 95% CI | β | p |
|---|---|---|---|---|
| Constant | 27.16 (0.87) | 25.45; 28.87 | ||
| Year of study (categorical) | ||||
| Third year (reference: first year) | −3.36 (1.43) | −6.17; −0.54 | −0.13* | 0.020* |
| Level of physical activity (categorical) | ||||
| Low level (reference: high level) | 5.62 (1.99) | 1.69; 9.55 | 0.15 | 0.005** |
| FFQ Sweet Foods Score (continuous) | 0.09 (0.05) | −0.01; 0.18 | 0.09 | 0.081 |
| Smoking status (categorical) | ||||
| Ex-smoker (reference: never smoked) | 5.81 (2.29) | 1.29; 10.33 | 0.14 | 0.012* |
R 2 for step 1=0.096, ΔR 2 for final step=−0.005 (final model p<0.001).
p<0.05
p<0.01.
A 17-step regression using DP scores as the dependant variable (Table 4) identified that four predictors explained 6.7% of the variance (R 2=0.067, F (5, 317)=4.51, p=0.001). It was found that attending St Andrews University only in comparison to attending Manchester University only (β=0.15, p=0.014), being male (β=0.12, p=0.041) and being in fifth year in comparison to first year (β=0.19, p=0.001) were significant predictors of higher DP scores. Being in fourth year (β=0.11, p=0.064) and savoury foods consumption (β=0.10, p=0.066) were important for the overall model but were not found to be significant predictors of DP.
Table 4.
Final model in a 17-step backward stepwise regression analysis predicting MBI depersonalisation (DP) scores
| Variable (variable type/reference category) | B (SE) | 95% CI | β | p |
|---|---|---|---|---|
| Constant | 7.17 (0.51) | 6.17; 8.16 | ||
| Institution (categorical) | ||||
| St Andrews only (reference: Manchester only) | 1.32 (0.53) | 0.27; 2.36 | 0.15 | 0.014* |
| Gender (categorical) | ||||
| Male (reference: female) | 1.05 (0.51) | 0.04; 2.06 | 0.12 | 0.041* |
| Year of study (categorical) | ||||
| Fourth year (reference first year) | 1.35 (0.73) | −0.08; 2.78 | 0.11 | 0.064 |
| Fifth year of study (reference: first year) | 3.06 (0.91) | 1.27; 4.86 | 0.19 | 0.001** |
| FFQ Savoury Foods Scores (continuous) | 0.04 (0.02) | −0.003; 0.09 | 0.10 | 0.066 |
R 2 for step 1=0.096, ΔR 2 for final step=−0.004 (final model p=0.001).
p<0.05
p<0.01.
A 15-step regression using PA scores as the dependant variable (Table 5) identified that four predictors explained 14.5% of the variance (R 2=0.145, F (7,317)=7.52, p<0.001). Being male (β=−0.14, p=0.009) was significantly predictive of lower PA scores. Being in third (β=0.13, p=0.020), fourth (β=0.14, p=0.010) or fifth year (β=0.24, p<0.001) in comparison to first year was significantly predictive of higher PA scores and the significance of the prediction increased with each successive year. Higher alcohol binge scores were significantly associated with higher PA scores (β=0.15, p=0.005). Having moderate (β=−0.12, p=0.027) or low levels (β=−0.17, p=0.002) of physical activity in comparison to high levels were significant predictors of lower PA score.
Table 5.
Final model in a 15-step backward stepwise regression analysis predicting MBI personal accomplishment (PA) scores
| Variable (variable type/reference category) | B (SE) | 95% CI | β | p |
|---|---|---|---|---|
| Constant | 33.99 (2.05) | 29.95; 38.04 | ||
| Gender (categorical) | ||||
| Male (reference: female) | −2.92 (1.11) | −5.09; −0.74 | −0.14 | 0.009** |
| Year of study (categorical) | ||||
| Third year (reference: first year) | 3.13 (1.34) | 0.50; 5.76 | 0.13 | 0.020* |
| Fourth year (reference first year) | 3.99 (1.54) | 0.96; 7.03 | 0.14 | 0.010* |
| Fifth year (reference: first year) | 8.69 (1.95) | 4.85; 12.54 | 0.24 | <0.001*** |
| AUQ binge score (continuous) | 0.14 (0.05) | 0.04; 0.23 | 0.15 | 0.005** |
| Level of physical activity (categorical) | ||||
| Moderate level (reference: high level) | −2.37 (1.07) | −4.48; −0.27 | −0.12 | 0.027* |
| Low level (reference: high level) | −5.97 (1.91) | −9.73; −2.19 | −0.17 | 0.002** |
R 2 for step 1=0.162, ΔR 2 for final step=−0.005 (final model p<0.001).
p<0.05
p<0.01
p<0.001.
Discussion
This study investigated the prevalence of burnout in UK medical students and explored the association between burnout and health related behaviours. Our findings indicate that burnout was present in this undergraduate medical student sample, with one in four participants being categorised as burned-out according to the appropriate cut-offs in the MBI (30). In addition, this study has indicated that specific demographic, lifestyle, and behavioural factors, including physical activity, sweet or savoury food consumption, alcohol bingeing, gender, year, and institution of study may predict medical student's experience of burnout components.
The results of this study show that burnout exists in this undergraduate medical student sample (26.7%), with a substantial number of participants reporting high levels of EE (54.8%) and DP (34%), and low levels of PA (46.6%). These results are consistent with a recent systematic review on burnout in medical students (5), and suggest that many medical students are at risk of, or are already suffering from, burnout well before they qualify as medical doctors. In comparison to dental students, where 10–22% report high EE (45, 46), 17% low PA and 28% high DP (45), the percentage of medical students in this sample experiencing high EE or DP and low PA are concerning.
In addition, a number of demographic factors were shown to predict participant's experience of burnout, including gender, institution, and year of study. Institution was found to have an impact on both DP and PA. Although institution did not significantly impact on DP scores when examined via ANOVA, regression analysis suggested that participants who attended St Andrews University (St Andrews only cohort: Years 1–3) were significantly more likely to have higher DP than Manchester University participants (Manchester only cohort: Years 1–5). Additionally, analysis of variance found that mean PA was significantly higher for participants who had progressed from St Andrews to Manchester (Years 3–5) than for those in the Manchester only cohort (Years 1–5). Associations have previously been found between differing learning environments and burnout in American medical students (10). There are differences in the learning approach adopted by the two institutions in this study which may influence the student experience, and therefore potential for development of burnout. However, it is also possible that students who select to apply for either course may vary prior to entry, and thus we cannot determine from our data whether this result is influenced by differences in student cohort per se.
Male participants reported higher levels of DP and lower levels of PA than females suggesting that, in this sample, males may be at greater risk of burnout than females. These findings are partially supported by a recent meta-analysis of multiple professions conducted by Purvanova and Muros (11) who rebutted the belief that burnout is more commonly experienced by female employees and that males appear more susceptible to DP. Work examining the gender differences in burnout prevalence within medical student samples is limited and inconclusive (5). Further study is therefore required to clarify the relationship between gender and burnout in the medical student population.
This study revealed that DP and PA were positively associated with year of study. These findings are supported by previous research. Dyrbye et al. found that DP and PA increased with year of study in American medical schools (35). This increase in DP as medical students progress through their training has potential implications for communication with patients (47) and patient outcomes (48). There was a negative trend between EE and year of study in the current study with EE decreasing from first to third year, although scores still remained relatively high. These findings are contrary to Guthrie et al. who identified a modest increase in EE scores with year of study in a sample of medical students from the University of Manchester, UK (49). Perhaps the most striking finding, however, was that over 50% of first-year students reported high levels of EE and over 40% reported low levels of PA. This suggests that a very large proportion of students are at high risk of developing burnout very early in their medical training and that there may be scope for a preventative intervention before burnout becomes established.
Previous studies in medical student samples have noted a change in the components of burnout with year of study and others have identified gender differences, however this study furthers our understanding of burnout by identifying a potential relationship between medical students’ lifestyle and health behaviours and the components of burnout. Interestingly, physical activity predicted lower EE and higher PA, while alcohol binge scores were predictive of higher PA. This previously unreported finding related to alcohol suggests that the relationship between alcohol consumption and psychological distress in not unidirectional (19, 21). There is some evidence that alcohol may be used as a coping strategy for stress in certain individuals (50, 51), however this is unlikely to result in the perceptions of high PA in this sample. Szmigin et al. (52) conducted interviews with young adults in the United Kingdom and proposed that young drinkers have a ‘hedonistic’ approach to binge drinking, suggesting that medical students may be drinking for pleasure rather than as a coping mechanism of stress and burnout.
Physical activity was the most predictive of all the lifestyle and health behaviour variables and was associated with higher PA and lower EE. This finding agrees with recent research suggesting that physical activity may be associated with a reduction in the experience of burnout in male workers (27) and in trainee doctors (28). Physical activity has been shown to be beneficial for mental health 53–57). Salmon (56) postulated that many aspects of physical activity, including an improved sense of self-control and greater social interaction, may have positive implications for mental health. The results of this study suggest that the active promotion of physical activity within medical student populations may help to protect students from the effects burnout.
Although not statistically significant predictors, sweet and savoury food scores were retained in the final regression models for EE and DP respectively. This suggests that there may be a relationship between diet and the components of burnout. Torres and Nowson (58) reviewed the literature exploring eating behaviour and stress and concluded that chronic stress may increase the consumption of such high-energy foods. Devine et al. (59) examined working conditions and dietary choices in working parents and found that long and busy working hours were associated with poorer dietary choices and missed meals. It is possible that participants in the current study who were experiencing higher levels of EE and DP were making poorer dietary choices as a maladaptation to their busy schedules and as a coping mechanism for their increased feelings of mental distress. As this study only collected self-report data the actual intake of the food groups cannot be confirmed, further study may clarify the specific relationship between burnout and diet choice.
In this sample, being an ex-smoker was significantly predictive of higher EE scores. There is little research examining the relationship between burnout and smoking; however, links have been suggested between occupational stress and smoking (60). A recent study has also highlighted that stress increases cigarette cravings (61). These results suggest that there is potentially a link between smoking behaviour and burnout. However, the number of smokers and ex-smokers in this study was low in comparison to non-smokers and therefore it is difficult to meaningfully interpret this finding; further study is required to fully understand this link.
There are limitations to this study. The response rate in this study was relatively low; this may in part be due to the timing of the data collection which was conducted during the pre-exam period. This low response rate must be taken into account when considering these findings, although it is possible that those students who were experiencing high burnout may have been less likely to complete the survey. In addition, the response rate was unequal between years and female students were over-represented in the sample. The population of medical students at the Universities of St Andrews and Manchester at the time of this study was 57% female. This slight over-representation of female medical students in our sample may have impacted upon the results and the unequal response rate between years of study reduced the scope for cross-year analysis. The number of students was greatest in first year where the prevalence of burnout was comparably lower than other years and this may have underestimated levels of burnout in this medical student sample. Although there were differences between the institutions in the burnout reported by participants, differences in course structure and content may influence the characteristics of the students who apply to and study at a particular institution, therefore caution must be taken when attempting to generalise these results to all medical schools.
Conclusion
This study highlights the risk of burnout within all years of this medical student sample as well as the importance of understanding the various lifestyle and health behaviour factors that predict burnout in medical students. Although the amount of variance in burnout predicted by these health behaviours is small, this study suggests that they do play a role and that medical students should consider making healthier lifestyle choices early in their medical training, within their first year of study, to help prevent burnout becoming established. Particular attention should be paid to increasing physical activity, improving dietary choices and encouraging male medical students to engage in healthy behaviours. Future research should incorporate health behaviour choices within models of burnout in medical students to aid with the development of preventive interventions.
Acknowledgements
We wish to thank MSc student Ashley Rae who assisted in the data collection for this project.
Conflict of interest and funding
The authors report no conflict of interest.
References
- 1.Maslach C, Schaufeli WB, Leiter MP. Job burnout. Ann Rev Psychol. 2001;52:397–422. doi: 10.1146/annurev.psych.52.1.397. [DOI] [PubMed] [Google Scholar]
- 2.Linzer M, Manwell LB, Williams ES, Bobula JA, Brown RL, Varkey AB, et al. Working conditions in primary care: physician reactions and care quality. Ann Intern Med. 2009;151:28–36. doi: 10.7326/0003-4819-151-1-200907070-00006. [DOI] [PubMed] [Google Scholar]
- 3.Shanafelt TD, Boone S, Tan L, Dyrbye LN, Sotile W, Satele D, et al. Burnout and satisfaction with work–life balance among US physicians relative to the general US population. Arch Intern Med. 2012;172:1377–85. doi: 10.1001/archinternmed.2012.3199. [DOI] [PubMed] [Google Scholar]
- 4.Shanafelt TD, Bradley KA, Wipf JE, Back AL. Burnout and self-reported patient care in an internal medicine residency program. Ann Intern Med. 2002;136:358–67. doi: 10.7326/0003-4819-136-5-200203050-00008. [DOI] [PubMed] [Google Scholar]
- 5.IsHak W, Nikravesh R, Lederer S, Perry R, Ogunyemi D, Bernstein C. Burnout in medical students: a systematic review. Clin Teach. 2013;10:242–5. doi: 10.1111/tct.12014. [DOI] [PubMed] [Google Scholar]
- 6.Maslach C, Jackson SE, Leiter MP. The Maslach Burnout Inventory. 3rd Ed. Palo Alto, CA: Consulting Psychologists Press; 1996. [Google Scholar]
- 7.McManus IC, Keeling A, Paice E. Stress, burnout and doctors’ attitudes to work are determined by personality and learning style: a twelve year longitudinal study of UK medical graduates. BMC Med. 2004;2:1–12. doi: 10.1186/1741-7015-2-29. English. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Dahlin M, Joneborg N, Runeson B. Stress and depression among medical students: a cross-sectional study. Med Educ. 2005;39:594–604. doi: 10.1111/j.1365-2929.2005.02176.x. [DOI] [PubMed] [Google Scholar]
- 9.Dyrbye LN, Thomas MR, Shanafelt TD, editors. Medical student distress: causes, consequences, and proposed solutions. Mayo Clinic Proc. 2005;80:1613–22. doi: 10.4065/80.12.1613. [DOI] [PubMed] [Google Scholar]
- 10.Dyrbye LN, Thomas MR, Harper W, Massie F, Power DV, Eacker A, et al. The learning environment and medical student burnout: a multicentre study. Med Educ. 2009;43:274–82. doi: 10.1111/j.1365-2923.2008.03282.x. [DOI] [PubMed] [Google Scholar]
- 11.Purvanova RK, Muros JP. Gender differences in burnout: a meta-analysis. J Vocat Behav. 2010;77:168–85. [Google Scholar]
- 12.Kuntsche E, Knibbe R, Gmel G, Engels R. Why do young people drink? A review of drinking motives. Clin Psychol Rev. 2005;25:841–61. doi: 10.1016/j.cpr.2005.06.002. [DOI] [PubMed] [Google Scholar]
- 13.Park CL, Armeli S, Tennen H. The daily stress and coping process and alcohol use among college students. J Stud Alcohol Drugs. 2004;65:126. doi: 10.15288/jsa.2004.65.126. [DOI] [PubMed] [Google Scholar]
- 14.Liu C, Xie B, Chou C-P, Koprowski C, Zhou D, Palmer P, et al. Perceived stress, depression and food consumption frequency in the college students of China seven cities. Physiol Behav. 2007;92:748–54. doi: 10.1016/j.physbeh.2007.05.068. [DOI] [PubMed] [Google Scholar]
- 15.Mikolajczyk RT, El Ansari W, Maxwell AE. Food consumption frequency and perceived stress and depressive symptoms among students in three European countries. Nutr J. 2009;8:31. doi: 10.1186/1475-2891-8-31. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Nguyen-Michel ST, Unger JB, Hamilton J, Spruijt-Metz D. Associations between physical activity and perceived stress/hassles in college students. Stress Health. 2006;22:179–88. [Google Scholar]
- 17.Steptoe A, Wardle J, Cui W, Bellisle F, Zotti A-M, Baranyai R, et al. Trends in smoking, diet, physical exercise, and attitudes toward health in European university students from 13 countries, 1990–2000. Prev Med. 2002;35:97–104. doi: 10.1006/pmed.2002.1048. [DOI] [PubMed] [Google Scholar]
- 18.Newbury-Birch D, White M, Kamali F. Factors influencing alcohol and illicit drug use amongst medical students. Drug Alcohol Depend. 2000;59:125–30. doi: 10.1016/s0376-8716(99)00108-8. [DOI] [PubMed] [Google Scholar]
- 19.Pickard M, Bates L, Dorian M, Greig H, Saint D. Alcohol and drug use in second-year medical students at the University of Leeds. Med Educ. 2000;34:148–50. doi: 10.1046/j.1365-2923.2000.00491.x. [DOI] [PubMed] [Google Scholar]
- 20.Firth J. Levels and sources of stress in medical students. Br Med J (Clinical Research Edition) 1986;292:1177–80. doi: 10.1136/bmj.292.6529.1177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Newbury-Birch D, Walshaw D, Kamali F. Drink and drugs: from medical students to doctors. Drug Alcohol Depend. 2001;64:265–70. doi: 10.1016/s0376-8716(01)00128-4. [DOI] [PubMed] [Google Scholar]
- 22.Glore SR, Walker C, Chandler A. Brief communication: dietary habits of first-year medical students as determined by computer software analysis of three-day food records. J Am Coll Nutr. 1993;12:517–20. doi: 10.1080/07315724.1993.10718345. [DOI] [PubMed] [Google Scholar]
- 23.Soriano JM, Moltó JC, Mañes J. Dietary intake and food pattern among university students. Nutr Res. 2000;20:1249–58. [Google Scholar]
- 24.Troyer D, Ullrich IH, Yeater RA, Hopewell R. Physical activity and condition, dietary habits, and serum lipids in second-year medical students. J Am Coll Nutr. 1990;9:303–7. doi: 10.1080/07315724.1990.10720384. [DOI] [PubMed] [Google Scholar]
- 25.Smith DR, Leggat PA. An international review of tobacco smoking among medical students. J Postgrad Med. 2007;53:55–62. doi: 10.4103/0022-3859.30333. [DOI] [PubMed] [Google Scholar]
- 26.Gorter RC, Eijkman MAJ, Hoogstraten J. Burnout and health among Dutch dentists. Eur J Oral Sci. 2000;108:261–7. doi: 10.1034/j.1600-0722.2000.108004261.x. [DOI] [PubMed] [Google Scholar]
- 27.Gerber M, Brand S, Elliot C, Holsboer-Trachsler E, Puhse U, Beck J. Aerobic exercise training and burnout: a pilot study with male participants suffering from burnout. BMC Res Notes. 2013;6:78. doi: 10.1186/1756-0500-6-78. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Weight CJ, Sellon JL, Lessard-Anderson CR, Shanafelt TD, Olsen KD, Laskowski ER. Physical activity, quality of life, and burnout among physician trainees: the effect of a team-based, incentivized exercise program. Mayo Clin Proc. 2013;88:1435–42. doi: 10.1016/j.mayocp.2013.09.010. [DOI] [PubMed] [Google Scholar]
- 29.Oakley SH, Estanol MV, Westermann LB, Crisp CC, Kleeman SD, Pauls RN. Resident burnout after the 2011 accreditation council for graduate medical education duty-hour restrictions: a cross-sectional survey study. Obstet Gynecol. 2014;123(Suppl 1):117S–8. [Google Scholar]
- 30.Maslach C, Jackson SE. The measurement of experienced burnout. J Organ Behav. 1981;2:99–113. [Google Scholar]
- 31.Townshend J, Duka T. Patterns of alcohol drinking in a population of young social drinkers: a comparison of questionnaire and diary measures. Alcohol Alcohol. 2002;37:187–92. doi: 10.1093/alcalc/37.2.187. [DOI] [PubMed] [Google Scholar]
- 32.Booth ML, Ainsworth BE, Pratt M, Ekelund U, Yngve A, Sallis JF, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;195:3508–1381. doi: 10.1249/01.MSS.0000078924.61453.FB. [DOI] [PubMed] [Google Scholar]
- 33.Margetts BM, Cade JE, Osmond C. Comparison of a food frequency questionnaire with a diet record. Int J Epidemiol. 1989;18:868–73. doi: 10.1093/ije/18.4.868. [DOI] [PubMed] [Google Scholar]
- 34.Brazeau CM, Schroeder R, Rovi S, Boyd L. Relationships between medical student burnout, empathy, and professionalism climate. Acad Med. 2010;85:S33–6. doi: 10.1097/ACM.0b013e3181ed4c47. [DOI] [PubMed] [Google Scholar]
- 35.Dyrbye LN, Thomas MR, Huntington JL, Lawson KL, Novotny PJ, Sloan JA, et al. Personal life events and medical student burnout: a multicenter study. Acad Med. 2006;81:374–84. doi: 10.1097/00001888-200604000-00010. [DOI] [PubMed] [Google Scholar]
- 36.Mehrabian A, Russell JA. A questionnaire measure of habitual alcohol use. Psychol Rep. 1978;43:803–6. doi: 10.2466/pr0.1978.43.3.803. [DOI] [PubMed] [Google Scholar]
- 37.Hartley DE, Elsabagh S, File SE. Binge drinking and sex: effects on mood and cognitive function in healthy young volunteers. Pharmacol Biochem Behav. 2004;78:611–19. doi: 10.1016/j.pbb.2004.04.027. [DOI] [PubMed] [Google Scholar]
- 38.Higgs S, Stafford LD, Attwood AS, Walker SC, Terry P. Cues that signal the alcohol content of a beverage and their effectiveness at altering drinking rates in young social drinkers. Alcohol Alcohol. 2008;43:630–5. doi: 10.1093/alcalc/agn053. [DOI] [PubMed] [Google Scholar]
- 39.Townshend JM, Duka T. Binge drinking, cognitive performance and mood in a population of young social drinkers. Alcohol Clin Exp Res. 2005;29:317–25. doi: 10.1097/01.alc.0000156453.05028.f5. [DOI] [PubMed] [Google Scholar]
- 40.Ballard M, Gray M, Reilly J, Noggle M. Correlates of video game screen time among males: body mass, physical activity, and other media use. Eat Behav. 2009;10:161–7. doi: 10.1016/j.eatbeh.2009.05.001. [DOI] [PubMed] [Google Scholar]
- 41.Papathanasiou G, Georgoudis G, Papandreou M, Spyropoulos P, Georgakopoulos D, Kalfakakou V, et al. Reliability measures of the short International Physical Activity Questionnaire (IPAQ) in Greek young adults. Hellenic J Cardiol. 2009;50:283–94. [PubMed] [Google Scholar]
- 42.IPAQ. Guidelines for data processing and analysis of the International Physical Activity Questionnaire (IPAQ) Stockholm, Sweden: Karolinska Institute; 2005. [Google Scholar]
- 43.Rimm EB, Giovannucci EL, Stampfer MJ, Colditz GA, Litin LB, Willett WC. Reproducibility and validity of an expanded self-administered semiquantitative food frequency questionnaire among male health professionals. Am J Epidemiol. 1992;135:1114–26. doi: 10.1093/oxfordjournals.aje.a116211. [DOI] [PubMed] [Google Scholar]
- 44.Rockett HRH, Breitenbach M, Frazier AL, Witschi J, Wolf AM, Field AE, et al. Validation of a youth/adolescent food frequency questionnaire. Prev Med. 1997;26:808–16. doi: 10.1006/pmed.1997.0200. [DOI] [PubMed] [Google Scholar]
- 45.Pöhlmann K, Jonas I, Ruf S, Harzer W. Stress, burnout and health in the clinical period of dental education. Eur J Dent Educ. 2005;9:78–84. doi: 10.1111/j.1600-0579.2004.00359.x. [DOI] [PubMed] [Google Scholar]
- 46.Humphris G, Blinkhorn A, Freeman R, Gorter R, Hoad-Reddick G, Murtomaa H, et al. Psychological stress in undergraduate dental students: baseline results from seven European dental schools. Eur J Dent Educ. 2002;6:22–9. doi: 10.1034/j.1600-0579.2002.060105.x. [DOI] [PubMed] [Google Scholar]
- 47.Brown R, Dunn S, Byrnes K, Morris R, Heinrich P, Shaw J. Doctors’ stress responses and poor communication performance in simulated bad-news consultations. Acad Med. 2009;84:1595–602. doi: 10.1097/ACM.0b013e3181baf537. [DOI] [PubMed] [Google Scholar]
- 48.Halbesleben JR, Rathert C. Linking physician burnout and patient outcomes: exploring the dyadic relationship between physicians and patients. Health Care Manage Rev. 2008;33:29–39. doi: 10.1097/01.HMR.0000304493.87898.72. [DOI] [PubMed] [Google Scholar]
- 49.Guthrie E, Campbell M, Black D, Creed F, Bagalkote H, Shaw C. Psychological stress and burnout in medical students: a five-year prospective longitudinal study. J Roy Soc Med. 1998;91:237–43. doi: 10.1177/014107689809100502. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Williams A, Clark D. Alcohol consumption in university students: the role of reasons for drinking, coping strategies, expectancies, and personality traits. Addict Behav. 1998;23:371–8. doi: 10.1016/s0306-4603(97)80066-4. [DOI] [PubMed] [Google Scholar]
- 51.Cooper ML, Russell M, Skinner JB, Frone MR, Mudar P. Stress and alcohol use: moderating effects of gender, coping, and alcohol expectancies. J Abnorm Psychol. 1992;101:139–52. doi: 10.1037//0021-843x.101.1.139. [DOI] [PubMed] [Google Scholar]
- 52.Szmigin I, Griffin C, Mistral W, Bengry-Howell A, Weale L, Hackley C. Re-framing ‘binge drinking’ as calculated hedonism: empirical evidence from the UK. Int J Drug Policy. 2008;19:359–66. doi: 10.1016/j.drugpo.2007.08.009. [DOI] [PubMed] [Google Scholar]
- 53.Puterman E, Lin J, Blackburn E, O'Donovan A, Adler N, Epel E. The power of exercise: buffering the effect of chronic stress on telomere length. PLoS One. 2010;5:e10837. doi: 10.1371/journal.pone.0010837. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Norris R, Carroll D, Cochrane R. The effects of physical activity and exercise training on psychological stress and well-being in an adolescent population. J Psychosom Res. 1992;36:55–65. doi: 10.1016/0022-3999(92)90114-h. [DOI] [PubMed] [Google Scholar]
- 55.Paluska S, Schwenk T. Physical activity and mental health. Sports Med. 2000;29:167–80. doi: 10.2165/00007256-200029030-00003. English. [DOI] [PubMed] [Google Scholar]
- 56.Salmon P. Effects of physical exercise on anxiety, depression, and sensitivity to stress: a unifying theory. Clin Psychol Rev. 2001;21:33–61. doi: 10.1016/s0272-7358(99)00032-x. [DOI] [PubMed] [Google Scholar]
- 57.Hassmén P, Koivula N, Uutela A. Physical exercise and psychological well-being: a population study in Finland. Prev Med. 2000;30:17–25. doi: 10.1006/pmed.1999.0597. [DOI] [PubMed] [Google Scholar]
- 58.Torres SJ, Nowson CA. Relationship between stress, eating behavior, and obesity. Nutrition. 2007;23:887–94. doi: 10.1016/j.nut.2007.08.008. [DOI] [PubMed] [Google Scholar]
- 59.Devine CM, Farrell TJ, Blake CE, Jastran M, Wethington E, Bisogni CA. Work Conditions and the food choice coping strategies of employed parents. J Nutr Educ Behav. 2009;41:365–70. doi: 10.1016/j.jneb.2009.01.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Kouvonen A, Kivimäki M, Virtanen M, Pentti J, Vahtera J. Work stress, smoking status, and smoking intensity: an observational study of 46,190 employees. J Epidemiol Community Health. 2005;59:63–9. doi: 10.1136/jech.2004.019752. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Childs E, de Wit H. Effects of acute psychosocial stress on cigarette craving and smoking. Nicotine Tob Res. 2010;12:449–53. doi: 10.1093/ntr/ntp214. [DOI] [PMC free article] [PubMed] [Google Scholar]