Abstract
Background
Medical trainees’ work schedule is designed to cover duties without consideration of differences in circadian rhythms during a 24-hour period (chronotype).
Objective
To explore chronotype variation among medical trainees and understand its association with burn-out and schedule satisfaction.
Methods
In a multicentre observational study, we conducted two surveys between 1 October 2018 and 1 April 2019. Trainees from nine centres across the USA participated. We measured burn-out using Maslach Burnout Inventory (MBI), and trainee chronotype using the Morningness-Eveningness Questionnaire (MEQ).
Results
324 (32%) out of 1012 responded to our survey. Participants were 51% female and had a mean age of 30.8 years. Most participants had an intermediate MEQ type (65%). A large proportion of participants had burn-out on at least one of three tested MBI scales (62%); 5% of participants had burn-out on all three MBI scales. More participants with evening MEQ type had burn-out (66%) compared with morning MEQ type (55%), however, the results were not statically significant (p=0.294). Overall satisfaction with work shifts was 6.5 (95% CI 6.3 to 6.7), with higher satisfaction with day shift 7.7 (95% CI 7.5 to 7.9) and lowest satisfaction with overnight 24-hour call 3.5 (95% CI 3.2 to 3.9). Satisfaction was lower in trainees with burn-out 6.0 (95% CI 5.7 to 6.4), (p<0.001). In the follow-up survey, burn-out was present in at least one scale in 64% compared with 60% of respondents in the initial survey.
Conclusion
Burn-out is prevalent among medical trainees. Improving alignment between trainee preferences may improve performance, reduce human errors and burn-out.
INTRODUCTION
Chronotype is a measure referring to the individual differences in personal perception of the optimal time for wakefulness activities and sleep during a 24-hour period.1 Individuals can be classified to morning types, intermediate type or evening types based on their chronotype. The diurnal peak in physiologic function occurs earlier in morning types and later in evening types while the intermediate types are in between the other two groups.1 2 Over the last two decades, resident schedules have been extensively redesigned to meet work hour restrictions since the first implementation by the Accreditation Council for Graduate Medical Education in 2003.3–5 Work hour restrictions have contributed to decreases in longer overnight call shifts, but have increased the use of evening and night shifts. Little is known of how residents prefer to modify their schedules to align better with their chronotype, and whether such misalignment affects their perception of satisfaction with their work.
Misalignment between an individual’s chronotype and their job requirements may lead to adverse consequences such as tardiness, difficulty in waking, sleep-onset insomnia, sleep insufficiency and excessive daytime sleepiness.5–7 In addition, working evening or night shifts can lead to a misalignment between a person’s biological ability to sleep (usually during the night) and available time to sleep (during the day when working nightshift). This ultimately leads to sleep insufficiency, the main pathophysiology underlying shift-work sleep disorder. Shift-work sleep disorder is associated with cognitive impairment, an increased incidence of car accidents and medical errors.8 Long-term health consequences of shift-work disorder may include an increased risk of myocardial infarction, stroke, and, in some series, breast cancer.8 9
Our primary objective was to explore the variation in chronotype among medical trainees and understand its association with burn-out and work schedule satisfaction. We hypothesised that satisfaction with shift timing and resident burn-out would vary across chronotypes.
METHODS
Study design
In a multicentre observational study, we conducted a survey at two time points 6 months apart. The surveys explored the variation in chronotype among trainee physicians, evaluated their satisfaction with their schedule and assessed correlation between burn-out and chronotype. This study was carried out at nine medical centres across the USA after obtaining ethics approval at each individual institution including: Children’s Mercy Kansas City, Cleveland Clinic Florida, Kansas University Medical Center, Mayo Clinics Florida, Mercy Hospital St Louis, Oregon Health and Science, St Louis University, University of Missouri Kansas City and Yale University School of Medicine.
Survey participants and survey development
We developed and piloted a survey in Qualtrics (Qualtrics, Provo, Utah, USA) which included open-ended questions, multiple choice questions and a 10-point Likert-type scale response option (see online supplemental content). Initially, the investigators collected feedback on readability, potential sources of confusion, and any missing questions. Following revision, between 1 October 2018 and 31 December 2018, participants completed the survey anonymously after its distribution electronically across sites. Each participant was assigned a code which was used to match first and subsequent responses. Only one investigator (AAG) had access to the codes, while the rest of the investigators and research coordinators were all blinded to the code. At the end of the survey, trainees were provided information for local and national resources for burn-out relief, employee assistance programmes and suicide hotlines. We collected data on demographics, age, gender, site, area of study, postgraduate year (PGY), number of night shifts and shift distribution in the last month and satisfaction with shifts. The survey was repeated 6 months later in respondents to the initial survey between 1 April 2019 and 30 June 2019.
Chronotype assessment was done using the Morningness-Eveningness Questionnaire (MEQ), used with permission. MEQ classifies people into five categories based on their sleep pattern, (definite morning, moderate morning, intermediate, moderate evening and definite evening).1 MEQ was originally validated for students aged 18–32 years. Burn-out assessment was completed using the Maslach Burn-out Inventory-Human Services Survey (MBI-HSS),10 used with permission. Response options used a seven-point Likert scale ranging from 0 to 6. The survey was designed to measure three subscales of burn-out: emotional exhaustion (EE), depersonalisation (DP) and personal accomplishment (PA). Total scores on each of the three subscales were stratified into high, moderate or low tertiles. The cutoffs for each tertile of burn-out were determined based on previously validated normative MBI-HSS data for healthcare workers (low EE ≤18, moderate EE 19–26, high EE ≥27; low DP ≤5, moderate DP 6–9, high DP ≥10; low PA ≥34, moderate PA 29–33, high PA ≤28).10 We defined the outcome of ‘burn-out’ as reporting a high level of burn-out on one or more subscales, that is, in the third tertile of EE or DP or the first tertile of PA. We repeated the burn-out portion of the survey at 6 months.
Statistical analyses
We analysed the data using standard descriptive statistics, using means and SD for continuous variables, and frequencies for categorical variables. We studied associations between categorical variables and burn-out using χ2 tests and used one-way analysis of variance to measure between-groups differences for age, number of shifts (day, evening, night, overnight call) and satisfaction with shifts (overall, day, evening, night, overnight call) by overall burn-out (yes vs no) and by burn-out tertiles on each subscale. A p<0.05 was considered statistically significant. Statistical analyses were performed using SPSS V.23.0 (IBM).
RESULTS
Participants’ characteristics
Three hundred and twenty-four trainee physicians (86% residents and 14% fellows) from nine medical centres participated in the study, 51% were females and had average age of 30 years. Most respondents were internal medicine residents/fellows (71%), followed by paediatrics (15%), surgery (7%), and obstetrics and emergency medicine (7%). Most respondents were born in North America (73%) (online supplemental content). Survey design and participants’ characteristics are illustrated in figure 1.
Figure 1.
Survey design and participants’ characteristics.
Chronotype
The participants had mostly an Intermediate MEQ type (65%), 24% were of morning type (definite and moderate morning) and 12% were of evening type (definite and moderate evening).
Burn-out
A large proportion of participants had burn-out on at least one scale of the MBI (62%) with 21% with burn-out on one scale, 36% on two scales and 5% with burn-out on all three tested scales (figure 2). When burn-out on least one scale was correlated with other variables, 65% of female respondents had burn-out compared with 59% of males. Burn-out levels decreased with higher PGY levels, with >60% of PGY 1–4 with burn-out, compared with 50% of PGY 5–8 with burn-out. More participants born in North America had burn-out (69%) compared with participants born elsewhere (p=0.002). Also, more participants with evening MEQ type had burn-out (66%) compared with morning MEQ type participants (55%), however, results were not statically significant (p=0.294) (table 1).
Figure 2.
Results of baseline Maslach Burnout Inventory among survey participants.
Table 1.
Association between burn-out level among medical trainees and categorical variables
| Burn-out on any subscale? N (%) | ||||
|---|---|---|---|---|
| Variable | Total, n (%) | No (n=123) | Yes (n=201) | P value |
| Gender | ||||
| Female | 166 (51.2) | 59 (35.5) | 107 (64.5) | 0.290 |
| Male | 155 (47.8) | 64 (41.3) | 91 (58.7) | |
| Position | ||||
| Resident | 280 (86.4) | 104 (37.1) | 201 (62.9) | 0.505 |
| Fellow | 44 (13.6) | 19 (43.2) | 25 (56.8) | |
| Programme | ||||
| Internal medicine | 231 (71.3) | 90 (39.0) | 141 (61.0) | 0.141 |
| Emergency Medicine and Obstetrics and Gynaecology | 21 (6.5) | 3 (14.3) | 18 (85.7) | |
| Paediatrics | 48 (14.8) | 19 (39.6) | 29 (60.4) | |
| Surgery | 23 (7.1) | 10 (43.5) | 13 (56.5) | |
| Years of clinical training (PGY) | ||||
| 1 | 98 (30.2) | 39 (39.8) | 59 (60.2) | 0.852 |
| 2 | 79 (24.4) | 26 (32.9) | 53 (67.1) | |
| 3 | 92 (28.4) | 34 (37) | 58 (63) | |
| 4 | 25 (7.7) | 9 (36) | 16 (64) | |
| 5–8 | 30 (9.3) | 15 (50) | 15 (50) | |
| Season of birth | ||||
| Fall | 74 (22.8) | 30 (40.5) | 44 (59.5) | 0.589 |
| Spring | 78 (24.1) | 33 (42.3) | 45 (57.7) | |
| Summer | 103 (31.8) | 34 (33) | 69 (67) | |
| Winter | 67 (20.7) | 25 (37.3) | 42 (62.7) | |
| Place of birth | ||||
| Africa | 5 (1.5) | 4 (80) | 1 (20) | 0.002 |
| Asia | 50 (15.4) | 25 (50) | 25 (50) | |
| Australia | 2 (0.6) | 2 (100) | 0 (0) | |
| Europe | 9 (2.8) | 6 (66.7) | 3 (33.3) | |
| North America | 235 (72.5) | 74 (31.5) | 161 (68.5) | |
| Other | 15 (4.6) | 6 (40) | 9 (60) | |
| South America | 7 (2.2) | 5 (71.4) | 2 (28.6) | |
| MEQ type | ||||
| Morning | 77 (23.8) | 35 (45.5) | 42 (54.5) | 0.294 |
| Intermediate | 209 (64.5) | 75 (35.9) | 134 (64.1) | |
| Evening | 38 (11.7) | 13 (34.2) | 25 (65.8) | |
MEQ, Morningness-Eveningness Questionnaire; PGY, postgraduate year.
Using a logistic regression with Burn-out on any scale as the dependent variable, we calculated the OR for different chronotype types while adjusting for age, sex, PGY level, position and programme. The results showed that there is no statistically significant association between burn-out on any scale and chronotype types, with the results of the logistic regression below:
When Morning MEQ type was considered as the reference, the OR to have burn-out on one scale for the Evening MEQ type was 1.25 (95% CI (0.51 to 3.07)), and the OR to have burn-out on one scale for the Intermediate MEQ type was 1.64 (95% CI (0.91 to 2.92)).
When Evening MEQ type was considered as the reference, the OR to have burn-out on one scale for the Morning MEQ type was 0.80 (95% CI (0.33 to 1.96)), and the OR to have burn-out on one scale for the Intermediate MEQ type was 1.31 (95% CI (0.51 to 2.92)).
When Intermediate MEQ type was considered as the reference, the OR to have burn-out on one scale for the Morning MEQ type was 0.61 (95% CI (0.34 to 1.09)), and the OR to have burn-out on one scale for the Evening MEQ type was 0.77 (95% CI (0.34 to 2.72)).
Satisfaction with work shifts
Overall satisfaction with work shifts was 6.5 (95% CI 6.3 to 6.7) on a Likert scale of 1–10 with higher satisfaction with day shift 7.7 (95% CI 7.5 to 7.9) and lower with evening shifts 5.7 (95% CI 5.4 to 6.0) and night shifts 4.7 (95% CI 4.3 to 5.0) and lowest with overnight 24-hour call 3.5 (95% CI 3.2 to 3.9) (p<0.001) (online supplemental content). Satisfaction with day shifts was significantly higher in morning types trainee 8.2 (95% CI 7.8 to 8.6) compared with evening type trainee 6.9 (95% CI 6.3 to 7.5) (p<0.001), while all other shifts had no statistically significant difference between the chronotype groups. Satisfaction was lower in general in trainee with burn-out 6.0 (95% CI 5.7 to 6.4) compared with trainee without burn-out 7.3 (95% CI 7.0 to 7.6) (p<0.001) (table 2).
Table 2.
Association between burn-out level among medical trainees with continuous variables
| Total, mean (95% CI) n=324 | No burn-out, mean (95% CI) n=123 | Burn-out, mean (95% CI) n=201 | P value | |
|---|---|---|---|---|
| Age | 30.81 (28.29 to 33.33) | 29.74 (29.02 to 30.46) | 31.46 (27.43 to 35.49) | 0.516 |
| Day shifts (n/month) | 19.03 (19.28 to 19.77) | 19.61 (18.36 to 20.85) | 18.66 (17.72 to 19.6) | 0.227 |
| Evening shifts (n/month) | 2.88 (2.27 to 3.50) | 2.6 (1.56 to 3.64) | 3.06 (2.3 to 3.82) | 0.469 |
| Night shifts (n/month) | 3.04 (2.52 to 3.57) | 3.03 (2.09 to 3.98) | 3.05 (2.43 to 3.68) | 0.973 |
| Overnight call shifts (n/month) | 1.35 (1.10 to 1.60) | 1.52 (1.09 to 1.96) | 1.24 (0.94 to 1.55) | 0.280 |
| Overall satisfaction with shifts | 6.49 (6.28 to 6.71) | 7.25 (6.95 to 7.56) | 6.02 (5.74 to 6.29) | 0.000 |
| Satisfaction with day shifts | 7.69 (7.50 to 7.87) | 8.23 (7.98 to 8.48) | 7.35 (7.1 to 7.59) | 0.000 |
| Satisfaction with evening shifts | 5.69 (5.39 to 5.99) | 6.25 (5.73 to 6.77) | 5.35 (4.99 to 5.71) | 0.004 |
| Satisfaction with night shifts | 4.65 (4.34 to 4.96) | 4.67 (4.18 to 5.17) | 4.63 (4.24 to 5.03) | 0.902 |
| Satisfaction with overnight call shifts | 3.51 (3.15 to 3.87) | 4.16 (3.55 to 4.76) | 3.04 (2.6 to 3.47) | 0.002 |
Follow-up survey
From the original 324 trainee who responded to the first survey, 140 responded to the follow-up (43%) (tables 3–4). As in the first survey, follow-up survey participants were mostly intermediate MEQ type (65%); 25% were morning type and 10% were evening type. Notably, 64% of participants demonstrated burn-out on at least 1 scale of the MBI (table 3). Satisfaction with all shifts increased from a mean of 6.6 (95% CI 6.2 to 6.9) to 7.0 (95% CI 7.7 to 7.3) with continued higher satisfaction with day shift 8.6 (95% CI 8.2 to 9.0) and lower with evening shifts 6,3 (95% CI 5.4 to 6.2) and night shifts 5.6 (95% CI 4.7 to 6.5). The lowest satisfaction was again found with overnight 24-hour call 4.0 (95% CI 2.9 to 5.2) (p=0.00). Overall satisfaction and satisfaction with day and evening shifts continued to be lower in trainees with burn-out compared with trainees without burn-out. Additional analysis summarising the results of the follow-up survey is presented in online supplemental content.
Table 3.
Burn-out levels for the participants who took the follow-up survey
| Initial survey, n (%) | Follow up survey, n (%) | ||
|---|---|---|---|
| No burn-out | 56 (40) | 51 (36) | |
| Burn-out on | ≥1 scale | 84 (60) | 89 (64) |
| ≥2 scales | 54 (39) | 50 (36) | |
| 3 scales | 5 (4) | 1 (1) |
Table 4.
Burn-out levels for the participants who repeated the survey in correlation with different categorical variables MEQ, Morningness-Eveningness Questionnaire; PGY, postgraduate year.
| Burn-out on any subscale, n (%) | |||
|---|---|---|---|
| Total, 140 (100) | Before, 84 (60) | After, 89 (64) | |
| Gender | |||
| Female | 73 (52.1) | 45 (61.6) | 47 (64.4) |
| Male | 67 (47.9) | 39 (58.2) | 42 (62.7) |
| Position | |||
| Resident | 127 (90.7) | 75 (59.1) | 82 (64.6) |
| Fellow | 13 (9.3) | 9 (69.2) | 7 (53.8) |
| Programme | |||
| Internal Medicine | 93 (66.4) | 53 (57) | 56 (60.2) |
| Emergency Medicine Obstetrics and Gynaecology | 10 (7.1) | 9 (90) | 8 (80) |
| Paediatrics | 23 (16.4) | 14 (60.9) | 16 (69.6) |
| Surgery | 13 (9.3) | 8 (61.5) | 9 (69.2) |
| Years of clinical training (PGY) | |||
| 1 | 47 (33.6) | 25 (53.2) | 27 (57.4) |
| 2 | 37 (26.4) | 23 (62.2) | 26 (70.3) |
| 3 | 33 (23.6) | 21 (63.6) | 22 (66.7) |
| 4 | 11 (7.9) | 8 (72.7) | 8 (72.7) |
| 5 | 8 (5.7) | 4 (50) | 4 (50) |
| 6 | 3 (2.1) | 2 (66.7) | 1 (33.3) |
| 7 | 0 (0.0) | 0 (0.0) | 0 (0.0) |
| 8 | 1 (0.7) | 1 (100) | 1 (100) |
| Season of birth | |||
| Fall | 29 (20.7) | 18 (62.1) | 23 (79.3) |
| Spring | 39 (27.9) | 23 (59) | 20 (51.3) |
| Summer | 44 (31.4) | 29 (65.9) | 31 (70.5) |
| Winter | 28 (20) | 14 (50) | 15 (53.6) |
| Place of birth | |||
| Africa | 2 (1.4) | 1 (50) | 1 (50) |
| Asia | 25 (17.9) | 11 (44) | 17 (68) |
| Europe | 3 (2.1) | 2 (66.7) | 2 (66.7) |
| North America | 106 (75.7) | 69 (65.1) | 68 (64.2) |
| Other | 3 (2.1) | 1 (33.3) | 1 (33.3) |
| South America | 1 (0.7) | 0 (0) | 0 (0) |
| MEQ type | |||
| Morning | 35 (25) | 18 (51.4) | 8 (57.1) |
| Intermediate | 91 (65) | 59 (64.8) | 61 (67) |
| Evening | 14 (10) | 7 (50) | 20 (57.1) |
DISCUSSION
Individual preference for sleep and awake time can affect medical trainee burn-out, performance and potentially lead to patient harm. We surveyed 324 medical trainees from nine sites across the USA and found that 64.5% of the participants had an intermediate MEQ type, 23.8% morning and 11.7% evening type, respectively. While participants overall satisfaction with the shifts was 6.5 on a Likert scale of 1–10, they had highest satisfaction with day shift 7.7, with decline from evening shifts 5.7 to night shifts 4.7 and lowest with overnight 24-hour call 3.5.
Medical trainee burn-out correlates to workload and lack of perceived control of their work.11 A recent meta-analysis showed that work demands, concerns about patient care, work environment, work–life balance, financial worries and low self-efficacy were the main factors that increased the odds of burn-out and work stress.12 Correlation of chronotype and burn-out was explored in few studies, and showed certain chronotypes are more susceptible to burn-out than others.10 13 14
Satisfaction with dayshift was significantly higher in morning chronotype compared with evening chronotypes, with drop in satisfaction for evening shift and further decline for night and long shift with overnight stay. The evening chronotype had no difference in satisfaction between morning and evening shifts. Similar to other studies, burn-out was present in majority of participants on at least one scale of MBI.15 Study participants with evening chronotype had a higher level of burn-out compared with participants with morning chronotype. Our data are in line with a study from Finland that showed that eveningness correlated to increased burn-out in a large group of young adults.10 Similarly when chronotype was examined in patients with chronic insomnia, eveningness correlated to greater anxiety.14
One factor that could have increased the burn-out in the evening chronotype is the less satisfaction with the day shift compared with the morning chronotype trainee. Satisfaction with day shifts was significantly higher in morning types trainee compared with evening type trainee. Although there was decline in satisfaction in the evening chronotype between shifts from morning to evening to night shift, the decline was less prominent than the morning chronotype.
One factor that may have affected the satisfaction is the classification we suggested for the three shifts (7:00–15:00, 15:00–23:00 and 23:00–7:00 hours). Trainees may come in the morning before 7:00 and finish after 15:00 hours especially if on inpatient service. Evening type trainee may have shown less satisfaction with the morning shift if it started before 7:00 hours which may happen in at least some rotations. Although satisfaction of the evening and night shifts were not statistically significant between the two groups, satisfaction with evening and night shifts were higher in the evening chronotype for evening shift and for night shift compared with the morning chronotype for the evening shift and for the night shift.
While all trainees had similar schedule, overall satisfaction with work schedule as well as morning and evening shifts were significantly lower in trainees with burn-out compared with trainee without burn-out. Satisfaction scores with night shift were very low in all chronotype groups, which likely explains the lack of difference among groups. We are not certain if the lower satisfaction increased burn-out, or the increased burn-out led to lower satisfaction. These two effects are likely interrelated. Ozyurt et al showed that job satisfaction was inversely correlated with EE and DP, and positively correlated with PA.16 Similarly Gan et al showed that general practitioners with lower levels of job satisfaction, experienced higher levels of burn-out and interventions aimed at increasing job satisfaction may be promising strategies to reduce burn-out among general practitioners.17
The evening chronotype had more burn-out than the morning chronotype. We expect that the most likely chronotype types to be affected are the extremes, the morning and the evening chronotypes rather than the intermediate type. Work satisfaction was significantly higher in the morning chronotype with the day shift compared with the night shift and we expect them to perform better in the day shift compared with night shift.
Our study has several strengths. We incorporated data from programmes across the whole country and included individuals at level of training from PGY 1 through PGY 8, both genders, a wide range of age groups and specialties which increases the generalisability of our findings. We included both large and small academic centres in different geographical areas hence this should allow for a good sampling. We also tried to use methodological rigour in the development of the survey which may allow comparison with other groups and easy replication of our data. Our study is also unique in exploring trainee chronotype and relation to burn-out and work satisfaction.
Our study has several limitations. This was an online voluntary survey with the participants self-selected and it is possible that individuals with the highest level of burn-out did not participate in the study due to being burnt out which could limit our findings. Our response rate to the initial survey was at 32% which is nearly similar to other surveys done by Dyrbye et al who had survey response rates of 22.5% for residents/fellows.18
Our response to the follow-up survey at 6 months was only 43% of the initial responders, making it difficult to interpret the changes over time with progression of training. While we confirmed that schedules across all the institutions and training programmes were similar, it is possible that small changes in the schedule could have led to some of the differences. While we had a diverse group of medical trainees that can make the results of our study generalisable, the majority of participants were from North America which could have skewed the results, hence affecting its’ generalisability.
The performance peak for different chronotypes is different. The physical performance was studied using the BLEEP (20m multistage fitness test) test for athletes and found that the earlier circadian phenotype had their highest performance at noon, the intermediate circadian phenotypes had their highest performance 16:00 hours, while the late circadian phenotypes had their highest performance at 19:30 hours.19 If the residents chronotype is well known before the schedule of the work is done, we can benefit in many aspects: In the ED, the morning chronotype will perform better in day shifts and may prefer to take more day shifts and less night shifts, while the evening chronotype may prefer to get more evening shifts. Also, on inpatient rotations if there are two teams, it is possible to have two residents with two different chronotypes, morning and evening. The morning trainee can come earlier and leave earlier while the evening chronotype can come little later and leave later. The attending can round first with the morning chronotype then the evening chronotype. Trainees may prefer to have more shifts that aligns with their chronotype and this may improve performance and may reduce errors.
CONCLUSIONS
Chronotype’s have not been well studied, nor considered in training or workforce schedules and our study stands out as one of the few to assess the variation in chronotype among medical trainees, evaluate their satisfaction with their schedule in terms of sleep-wake cycle and to assess correlation between burn-out and chronotype. We found that medical trainees continue to have high levels of burn-out and a propensity for eveningness further increases the risk of burn-out. Consideration of trainee chronotype in arranging graduate medical education schedules could help decrease burn-out. Future research on medical trainee schedules should include chronotype as an adjustable variable and assess the effect of chronotype on burn-out to help improve trainee and patient outcomes.
Supplementary Material
Main messages
Chronotype’s have not been well studied, nor considered in training or workforce schedules.
Medical trainees continue to have high levels of burn-out and a propensity for eveningness further increases the risk of burn-out.
Consideration of trainee chronotype in arranging graduate medical education schedules could help decrease burn-out.
What is already known on the subject
Over the last two decades, resident schedules have been extensively redesigned to meet work hour restrictions since the first implementation by the Accreditation Council for Graduate Medical Education in 2003. Little is known of how residents prefer to modify their schedules to align better with their chronotype, and whether such misalignment affects their perception of satisfaction with their work.
Acknowledgements
The authors would like to acknowledge Dr Razan Mansour (Outcomes and Implementation Research Unit, University of Kansas Medical Center), who provided administrative support and helped with the final submission of the manuscript.
Funding
The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Footnotes
Additional supplemental material is published online only. To view, please visit the journal online (https://dx.doi.org/10.1136/postgradmedj-2021-140975).
Competing interests None declared.
Ethics approval Informed consent was obtained as part of the survey questionnaire that we emailed to study participants. We structured the consenting process in plain language with a statement documenting that survey participation is voluntary and that study participants are not obligated to complete the survey once they had started it. The University of Missouri in Kansas City Institutional Review Board (IRB), in collaboration with all other study sites IRB, reviewed the study protocol and approved it.
Data availability statement
Data are available in a public, open access repository. Data are available upon request.
REFERENCES
- 1.Horne JA, Ostberg O. A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. Int J Chronobiol 1976;4:97–110. [PubMed] [Google Scholar]
- 2.Duffy JF, Dijk DJ, Hall EF, et al. Relationship of endogenous circadian melatonin and temperature rhythms to self-reported preference for morning or evening activity in young and older people. J Investig Med 1999;47:141–50. [PMC free article] [PubMed] [Google Scholar]
- 3.Philibert I, Friedmann P, Williams WT, et al. New requirements for resident duty hours. JAMA 2002;288:1112–4. [DOI] [PubMed] [Google Scholar]
- 4.Nasca TJ, Day SH, Amis ES, et al. The new recommendations on duty hours from the ACGME Task force. N Engl J Med 2010;363:e3. [DOI] [PubMed] [Google Scholar]
- 5.Bordley J, Agustin AG, Ahmed MA, et al. Restoration of resident sleep and wellness with block scheduling. Med Educ 2017;51:1241–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Vetter C. Circadian disruption: what do we actually mean? Eur J Neurosci 2020;51:531–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Morgenthaler TI, Lee-Chiong T, Alessi C, et al. Practice parameters for the clinical evaluation and treatment of circadian rhythm sleep disorders. An American Academy of sleep medicine report. Sleep 2007;30:1445–59. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Lockley SW, Landrigan CP, Barger LK, et al. When policy meets physiology: the challenge of reducing resident work hours. Clin Orthop Relat Res 2006;449:116–27. [DOI] [PubMed] [Google Scholar]
- 9.Megdal SP, Kroenke CH, Laden F, et al. Night work and breast cancer risk: a systematic review and meta-analysis. Eur J Cancer 2005;41:2023–32. [DOI] [PubMed] [Google Scholar]
- 10.Maslach C, Leiter MP. Understanding the burnout experience: recent research and its implications for psychiatry. World Psychiatry 2016;15:103–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Mata DA, Ramos MA, Bansal N, et al. Prevalence of depression and depressive symptoms among resident physicians: a systematic review and meta-analysis. JAMA 2015;314:2373–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Zhou AY, Panagioti M, Esmail A, et al. Factors associated with burnout and stress in trainee physicians: a systematic review and meta-analysis. JAMA Netw Open 2020;3:e2013761. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Elmore LC, Jeffe DB, Jin L, et al. National survey of burnout among US general surgery residents. J Am Coll Surg 2016;223:440–51. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Passos GS, Santana MG, Poyares D, et al. Chronotype and anxiety are associated in patients with chronic primary insomnia. Braz J Psychiatry 2017;39:183–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Ishak WW, Lederer S, Mandili C, et al. Burnout during residency training: a literature review. J Grad Med Educ 2009;1:236–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Ozyurt A, Hayran O, Sur H. Predictors of burnout and job satisfaction among Turkish physicians. QJM 2006;99:161–9. [DOI] [PubMed] [Google Scholar]
- 17.Gan Y, Jiang H, Li L, et al. Prevalence of burnout and associated factors among general practitioners in Hubei, China: a cross-sectional study. BMC Public Health 2019;19:1607. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Dyrbye LN, West CP, Satele D, et al. Burnout among U.S. medical students, residents, and early career physicians relative to the general U.S. population. Acad Med 2014;89:443–51. [DOI] [PubMed] [Google Scholar]
- 19.Facer-Childs E, Brandstaetter R. The impact of circadian phenotype and time since awakening on diurnal performance in athletes. Curr Biol 2015;25:518–22. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data are available in a public, open access repository. Data are available upon request.