ArticlePDF AvailableLiterature Review

Abstract and Figures

Objective To examine the association of physician burnout with the career engagement and the quality of patient care globally. Design Systematic review and meta-analysis. Data sources Medline, PsycINFO, Embase, and CINAHL were searched from database inception until May 2021. Eligibility criteria for selecting studies Observational studies assessing the association of physician burnout (including a feeling of overwhelming emotional exhaustion, feelings of cynicism and detachment from job defined as depersonalisation, and a sense of ineffectiveness and little personal accomplishment) with career engagement (job satisfaction, career choice regret, turnover intention, career development, and productivity loss) and the quality of patient care (patient safety incidents, low professionalism, and patient satisfaction). Data were double extracted by independent reviewers and checked through contacting all authors, 84 (49%) of 170 of whom confirmed their data. Random-effect models were used to calculate the pooled odds ratio, prediction intervals expressed the amount of heterogeneity, and meta-regressions assessed for potential moderators with significance set using a conservative level of P<0.10. Results 4732 articles were identified, of which 170 observational studies of 239 246 physicians were included in the meta-analysis. Overall burnout in physicians was associated with an almost four times decrease in job satisfaction compared with increased job satisfaction (odds ratio 3.79, 95% confidence interval 3.24 to 4.43, I ² =97%, k=73 studies, n=146 980 physicians). Career choice regret increased by more than threefold compared with being satisfied with their career choice (3.49, 2.43 to 5.00, I ² =97%, k=16, n=33 871). Turnover intention also increased by more than threefold compared with retention (3.10, 2.30 to 4.17, I ² =97%, k=25, n=32 271). Productivity had a small but significant effect (1.82, 1.08 to 3.07, I ² =83%, k=7, n=9581) and burnout also affected career development from a pooled association of two studies (3.77, 2.77 to 5.14, I ² =0%, n=3411). Overall physician burnout doubled patient safety incidents compared with no patient safety incidents (2.04, 1.69 to 2.45, I ² =87%, k=35, n=41 059). Low professionalism was twice as likely compared with maintained professionalism (2.33, 1.96 to 2.70, I ² =96%, k=40, n=32 321), as was patient dissatisfaction compared with patient satisfaction (2.22, 1.38 to 3.57, I ² =75%, k=8, n=1002). Burnout and poorer job satisfaction was greatest in hospital settings (1.88, 0.91 to 3.86, P=0.09), physicians aged 31-50 years (2.41, 1.02 to 5.64, P=0.04), and working in emergency medicine and intensive care (2.16, 0.98 to 4.76, P=0.06); burnout was lowest in general practitioners (0.16, 0.03 to 0.88, P=0.04). However, these associations did not remain significant in the multivariable regressions. Burnout and patient safety incidents were greatest in physicians aged 20-30 years (1.88, 1.07 to 3.29, P=0.03), and people working in emergency medicine (2.10, 1.09 to 3.56, P=0.02). The association of burnout with low professionalism was smallest in physicians older than 50 years (0.36, 0.19 to 0.69, P=0.003) and greatest in physicians still in training or residency (2.27, 1.45 to 3.60, P=0.001), in those who worked in a hospital (2.16, 1.46 to 3.19, P<0.001), specifically in emergency medicine specialty (1.48, 1.01 to 2.34, P=0.042), or situated in a low to middle income country (1.68, 0.94 to 2.97, P=0.08). Conclusions This meta-analysis provides compelling evidence that physician burnout is associated with poor function and sustainability of healthcare organisations primarily by contributing to the career disengagement and turnover of physicians and secondarily by reducing the quality of patient care. Healthcare organisations should invest more time and effort in implementing evidence-based strategies to mitigate physician burnout across specialties, and particularly in emergency medicine and for physicians in training or residency. Systematic review registration PROSPERO number CRD42021249492.
Content may be subject to copyright.
RESEARCH
thebmj
BMJ
2022;378:e070442 | doi: 10.1136/bmj-2022-070442 1
Associations of physician burnout with career engagement and
quality of patient care: systematic review and meta-analysis
Alexander Hodkinson,1,9 Anli Zhou,1 Judith Johnson,2,3 Keith Geraghty,1 Ruth Riley,4
Andrew Zhou,5 Earis Panagopoulou,6 Carolyn A Chew-Graham,7 David Peters,8 Aneez Esmail,1
Maria Panagioti1.9
ABSTRACT
OBJECTIVE
To examine the association of physician burnout with
the career engagement and the quality of patient care
globally.
DESIGN
Systematic review and meta-analysis.
DATA SOURCES
Medline, PsycINFO, Embase, and CINAHL were
searched from database inception until May 2021.
ELIGIBILITY CRITERIA FOR SELECTING STUDIES
Observational studies assessing the association of
physician burnout (including a feeling of overwhelming
emotional exhaustion, feelings of cynicism and
detachment from job dened as depersonalisation,
and a sense of ineectiveness and little personal
accomplishment) with career engagement (job
satisfaction, career choice regret, turnover intention,
career development, and productivity loss) and the
quality of patient care (patient safety incidents, low
professionalism, and patient satisfaction). Data
were double extracted by independent reviewers and
checked through contacting all authors, 84 (49%) of
170 of whom conrmed their data. Random-eect
models were used to calculate the pooled odds
ratio, prediction intervals expressed the amount of
heterogeneity, and meta-regressions assessed for
potential moderators with signicance set using a
conservative level of P<0.10.
RESULTS
4732 articles were identied, of which 170
observational studies of 239 246 physicians were
included in the meta-analysis. Overall burnout in
physicians was associated with an almost four
times decrease in job satisfaction compared with
increased job satisfaction (odds ratio 3.79, 95%
condence interval 3.24 to 4.43, I2=97%, k=73
studies, n=146 980 physicians). In the presence of
increased burnout, career choice regret increased by
more than threefold compared with being satised
with career choice (3.49, 2.43 to 5.00, I2=97%, k=16,
n=33 871). Turnover intention also increased by more
than threefold compared with retention (3.10, 2.30
to 4.17, I2=97%, k=25, n=32 271). Productivity had a
small but signicant association with burnout (1.82,
1.08 to 3.07, I2=83%, k=7, n=9581) and burnout
also aected career development (3.77, 2.77 to 5.14,
I2=0%, n=3411). Overall physician burnout doubled
patient safety incidents compared with no patient
safety incidents (2.04, 1.69 to 2.45, I2=87%, k=35,
n=41 059). As burnout increased, low professionalism
was twice as likely compared with maintained
professionalism (2.33, 1.96 to 2.70, I2=96%, k=40,
n=32 321), as was patient dissatisfaction compared
with patient satisfaction (2.22, 1.38 to 3.57, I2=75%,
k=8, n=1002). Burnout and poorer job satisfaction
was greatest in hospital settings (1.88, 0.91 to 3.86,
P=0.09), physicians aged 31-50 years (2.41, 1.02 to
5.64, P=0.04), and working in emergency medicine
and intensive care (2.16, 0.98 to 4.76, P=0.06);
burnout was lowest in general practitioners (0.16,
0.03 to 0.88, P=0.04). However, these associations
did not remain signicant in the multivariable
regressions. The association between burnout and
patient safety incidents was greatest in physicians
aged 20-30 years (1.88, 1.07 to 3.29, P=0.03), and
people working in emergency medicine (2.10, 1.09
to 3.56, P=0.02). The association of burnout with
low professionalism was smallest in physicians older
than 50 years (0.36, 0.19 to 0.69, P=0.003) and
greatest in physicians still in training or residency
(2.27, 1.45 to 3.60, P=0.001), in those who worked in
a hospital (2.16, 1.46 to 3.19, P<0.001), specically
in emergency medicine specialty (1.48, 1.01 to 2.34,
P=0.042), or situated in a low to middle income
country (1.68, 0.94 to 2.97, P=0.08).
CONCLUSIONS
This meta-analysis provides compelling evidence that
physician burnout is associated with poor function
For numbered aliations see
end of the article
Correspondence to: A Hodkinson
alexander.hodkinson@
manchester.ac.uk
(or @drAlexHodkinson on Twitter:
ORCID 0000-0003-2063-0977)
Additional material is published
online only. To view please visit
the journal online.
Cite this as: BMJ ;:e
http://dx.doi.org/10.1136/
bmj-2022-070442
Accepted: 03 July 2022
WHAT IS ALREADY KNOWN ON THIS TOPIC
Burnout is reaching global epidemic levels among physicians and many
physicians advocate that the capacity in the eld of medicine is almost reaching
crisis point
A better understanding of the association of burnout with the career engagement
of physicians is urgently needed now more than ever as health and care systems
across the globe are facing a critical workforce crisis
No meta-analysis to date has examined the association of burnout with the
career engagement of physicians, nor have they presented this relationship in
parallel with the potential impacts on the quality of patient care
WHAT THIS STUDY ADDS
The largest and most comprehensive systematic review and meta-analysis
assessing the association of burnout with the career engagement of physicians
and the quality of patient care, summarising results from 170 observational
studies with 239 246 physicians
Physicians with burnout are up to four times more likely to be dissatised with
their job and more than three times as likely to have thoughts or intentions to
leave their job (turnover) or to regret their career choice
Physicians with burnout are twice as likely to be involved in patient safety
incidents and show low professionalism, and over twice as likely to receive low
satisfaction ratings from patients
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
2 doi: 10.1136/bmj-2022-070442 |
BMJ
2022;378:e070442 | thebmj
and sustainability of healthcare organisations
primarily by contributing to the career disengagement
and turnover of physicians and secondarily by
reducing the quality of patient care. Healthcare
organisations should invest more time and eort in
implementing evidence-based strategies to mitigate
physician burnout across specialties, and particularly
in emergency medicine and for physicians in training
or residency.
SYSTEMATIC REVIEW REGISTRATION
PROSPERO number CRD42021249492.
Introduction
Burnout is defined as a syndrome related to work
that involves three key dimensions. Firstly, emotional
exhaustion, which represents the basic individual
stress dimension of burnout and refers to feelings of
being overextended and depleted of emotional and
physical resources. Secondly, depersonalisation,
which is the cynicism component and represents a
motivational, interpersonal distancing dimension of
burnout and refers to a negative, callous, or excessively
detached response to various aspects of the job.
Finally, a sense of reduced personal accomplishment,
which represents the self-evaluation dimension of
burnout and refers to feelings of incompetence and
inadequate achievement and productivity at work.1
Burnout is rampant and reaching global levels among
physicians.2 In the US, four in 10 physicians report at
least one symptom of burnout,3 and in the UK, a third
of trainee doctors report that they experience burnout
to a high or very high degree.4 In a recent review of low
and middle income countries the overall single-point
prevalence of burnout ranged from 2.5% to 87.9%
among 43 studies.5 Moreover, the covid-19 pandemic
has created new causes for stress with unsafe working
conditions and higher workloads, which have further
exacerbated burnout in physicians.6 7
Physicians with burnout often report poor work-
life balance and career dissatisfaction.8 9 However,
previous systematic reviews that focused on the
potential eects of physician burnout on healthcare
eciency have overlooked the association of burnout
with career engagement of physicians. Healthcare
provider burnout was associated with lower quality
patient care in a recent systematic review.10 However,
no pooled estimates of these associations were
provided due to high heterogeneity, which was partly
caused by analysing mixed samples of healthcare
providers and studies with little to no flexibility of the
quality metrics used for patient outcome subgroups.
A joint synthesis of the links of physician burnout with
the career engagement of physicians and the quality of
care provided to patients is important because these
aspects are complementary of the overall eciency
of healthcare organisations according to existing
theoretical frameworks and research evidence.11-13
These reciprocal relations should be made available
to governments and policy organisations to encourage
financial investments and policies to mitigate physician
burnout internationally. No previous systematic
reviews has taken this approach.14-16 For instance,
a meta-analysis published in 2022 that assessed
the association of burnout with only self-reported
medical errors among physicians found an increased
risk of self-reported errors.16 Two further systematic
reviews,14 15 which assessed the association between
physician or healthcare professionals’ wellbeing and
burnout with patient safety, did so through a narrative
review approach due to large heterogeneity.
Therefore, we aimed to add value through a larger
and more robust meta-analysis that controlled for
heterogeneity and other possible biases in career
engagement (which is currently unknown at the
systematic review level) and quality-of-care outcomes.
In this systematic review and meta-analysis, we
examined the association of physician burnout with
the career engagement of physicians focusing on job
satisfaction, career choice regret, career development,
productivity loss and turnover intention; and
the quality of patient care focusing on patient
safety incidents, low professionalism, and patient
satisfaction. Based on existing frameworks that have
studied the relation between occupational distress and
impairment related to sleep deprivation in physicians
and unsolicited patient complains,13 a flow diagram
of the anticipated associations is presented in figure
1. We also conducted meta-regressions to uncover
important moderators of these associations.
Methods
This systematic review followed a registered
(PROSPERO CRD42021249492) protocol17 and is
reported in accordance with the Reporting Checklist
for Meta-analyses of Observational Studies (MOOSE)18
and Preferred Reporting Items for Systematic Reviews
and Meta-Analyses (PRISMA) guidance.19 A protocol
amendment was made in November 2021 to exclude
grey literature from this review. The completed
checklists are available in appendix 1.
Search strategy and study eligibility
We included quantitative observational studies
involving physicians working in any healthcare
setting. We reported comparative data on the
association between burnout and career engagement
of physicians (ie, job satisfaction, career choice regret,
turnover intention, reduced productivity indicated by
presenteeism or absenteeism, and career development)
and quality of patient care outcomes (ie, patient safety
incidents including medication errors, suboptimal
patient care due to low professionalism based on an
established definition,20 and patient satisfaction).
Definitions for each of the outcomes are provided in
appendix 2. Studies that did not report their sample
had this missing information confirmed by contacting
authors. Randomised controlled trials were excluded
because our study focus is on associations and not
interventions, qualitative studies and quantitative
studies involving fewer than 70% of responses from
physicians were also excluded. This 70% threshold
is an arbitrary criterion that we have used in previous
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
thebmj
BMJ
2022;378:e070442 | doi: 10.1136/bmj-2022-070442 3
reviews in this area.21 The reason we adopted this
criterion is because we did not want to exclude relevant
studies that included only a small number of other
health professionals in addition to physicians.
We searched Medline, PsycINFO, Embase, and
CINAHL from database inception to May 2021
for citations in English. The searches included
combinations of key blocks of terms involving Medical
Subject Headings terms and text words. The full search
strategies are detailed in the appendix 3. The reference
lists of relevant systematic reviews and eligible
studies were manually searched to identify additional
literature.
Two independent reviewers (AH and AZ or MP and
AZ) rated the eligibility of each of the abstracts and
full texts in Covidence.22 Disagreements were resolved
by consensus, and we measured inter-rater agreement
with the κ statistic.
Data extraction and quality assessment
Using a standardised form that was pilot tested, we
extracted data for study characteristics (country,
recruitment, healthcare setting, and design), physician
characteristics (sample size, mean age, sex (percentage
of men), specialty, and work experience), burnout
(measure characteristics) and the outcome measures
including the method of reporting. The outcomes of
interest were each assessed against overall burnout
and any of the three subscales of burnout including
emotional exhaustion, depersonalisation, and
personal accomplishment. Where all three subscales
were reported and the overall burnout score was not,
we calculated burnout by pooling across the three
subscale scores. We tr ansformed extr acted quantitative
data to the uniform log scale and standardised
mean dierence using the statistical software
Comprehensive Meta-Analysis.23 The formulae for
these transformations are provided in appendix 4.
One of six reviewers (AH, MP, JJ, KG, RR, and AZ)
completed data extractions and double checked with
any disagreements being resolved by consensus.
We emailed all the study authors to confirm the
accuracy and validity of their data and to obtain any
missing data. 84 (49%) of 170 of the study authors
confirmed their data and our extractions were found
to be accurate in 96% of these studies (appendix 5).
The Newcastle Ottawa critical appraisal tool was
used to assess the quality of the studies.24 Pairs of
reviewers in three groups (AH and AZ, MP and KG,
or JJ and RR) appraised the fundamental criteria:
(1) representativeness of the sample, (2) sample
size, (3) non-respondents, (4) ascertainment of the
exposure, (5) controlled for confounding factors, (6)
assessment of outcome, and (7) adequate statistical
tests. Explanations of how each variable was coded
is detailed in the appendix. The total maximum score
was 7, and we classified overall scores of 0-2 as high
risk, 3-5 as medium risk, and 6-7 as low risk.
Data synthesis
We used DerSimonian-Laird random eects while
pooling the log odds,25 then exponentiated these
results to odds ratio and presented the data in forest
plots. A fixed eect method of pooling was considered
in meta-analysis with fewer than five studies and varied
sample and eect sizes. Heterogeneity in the meta-
analysis was quantified using the I2 statistic with its
95% confidence intervals.26 Because of the high level
of heterogeneity, Hartung-Knapp method of pooling
and estimating 95% confidence intervals were used
to account for uncertainty in the variance estimate.27
Overall burnout and its three subscales (emotional
exhaustion, depersonalisation, and personal
accomplishment) were synthesised individually and
presented as so within the forest plots. In total, 32
possible meta-analysis comparisons were found. A
Physician turnover
Career disengagement
Poor quality patient care
Patient safety incidents
Job dissatisfaction
Poor career development
Career choice regrets Productivity loss
Physician burnoutHealthcare inefficiency
Unprofessional care Patient dissatisfaction
Fig | Flow diagram of examined associations of physician burnout with career engagement and quality of patient care. Outcomes assessed in the
analysis are in yellow or red. Outcomes in red emphasise the potential heightened risk of the outcome compared with the outcomes in yellow (which
could be less serious to the physician and healthcare system
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
4 doi: 10.1136/bmj-2022-070442 |
BMJ
2022;378:e070442 | thebmj
subgroup meta-analysis was performed to assess for
dierences between the four burnout measures (full
22-item Maslach Burnout Inventory, abbreviated
(shortened) version of the Maslach Burnout Inventory,
Copenhagen burnout inventory, and use of another
inventory). Dierences between these groups were
assessed using the statistic ratio of odds ratio.28
In a meta-analysis involving 10 or more studies,
funnel plots and Egger’s test were used to assess for
publication bias,29 and prediction intervals were
calculated to express the amount of heterogeneity.30
We used univariable and multivariable meta-
regressions using the following variables: region
(US, UK/European Union, Commonwealth, South
East Asia/other); setting (primary care, hospital,
mixed); design (cross sectional, prospective cohort
or longitudinal); age (≤30, 31-50, and ≥51 years);
sex (female, male, mixed); specialty or position of
profession ((1) physician or internal medicine, (2)
general practitioners (GPs), (3) surgery including
neurosurgery, (4) emergency medicine and intensive
care, (5) cancer or oncology, (6) intern or resident, (7)
paediatrics, (8) psychiatry, (9) mixed, (10) neurology,
and (11) other); work experience (experienced with
over 6 years, less experienced intern/resident ≤6
years, mixture of experience), and burnout measure
(Maslach Burnout Inventory, any iteration,31 or other
classified burnout inventory v mixed and other32).
Variables from the univariable regressions with a more
conservative level of significance of P<0.10 rather
than p<0.05 were used in the multivariable model.33
The variables were added by using forward selection
process.34 Sensitivity analyses for risk of bias was done
based on the three categories for the total score of
the Newcastle Ottawa assessment (low, medium, and
high). All meta-analyses were conducted in R version
4.0.5 (R Foundation for Statistical Computing)35 using
the meta36 and metafor37 packages.
Patient and public involvement
We consulted five GPs in the Greater Manchester region
who were members of an established patient and
public involvement group about the appropriateness
of our research questions and classification of
outcomes and appropriateness of wellbeing measures
used. These GPs also advised on the interpretation
of our findings and will help with the dissemination
strategy.
Additional records identified through other sources
Full text articles excluded
Not burnout and patient or career outcome association
Non-amenable data for meta-analysis*
Randomised controlled trial design
Not physicians
Fewer than 70% were physicians
Not in English
Response letter
Conference abstract
Dissertation
Systematic or literature review or meta-analysis
361
49
35
34
16
11
4
2
1
1
Total records identified
Records identified through database searching
Duplicates removed
Records screened
Studies included in systematic review and meta-analysis
514
10 554
170
38
4732
Full text articles assessed for eligibility
5822
Records excluded at abstract and title level
4048
10 516
684
Fig | Study selection. *See references in appendix 
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
thebmj
BMJ
2022;378:e070442 | doi: 10.1136/bmj-2022-070442 5
Results
Our search strategy identified 4732 articles, of which
684 met the criteria for full text review (fig 2). A total
of 170 studies involving 239 246 physicians (150
cross sectional studies including 231 964 physicians
and 20 prospective or longitudinal studies including
7282 physicians) met the eligibility criteria. The
characteristics of the included studies are summarised
in appendix 6, and citations are provided in appendix
7. Agreement between reviewers for study inclusion
was high (κ 0.89, 95% confidence interval 0.81 to
0.96).
Table | Meta-analysis of the association of burnout with outcomes based on the career engagement of physicians and quality of patient care
Burnout and submeasure
No of studies (No of
physicians) Direction of association
Odds ratio (% CI);
(% PI) I (% CI) Publication bias†
Career engagement of physicians
Career choice regret:
Burnout 16 (33 871) Favours career choice regret compared
with being satised with their career
choice
3.49 (2.43 to 5.00);
(0.90 to 13.49)
97 (96 to 98) P=0.004
Emotional exhaustion* 4 (2014) 4.16 (3.34 to 5.19) 90 (77 to 95) NA
Depersonalisation* 2 (274) 1.54 (0.97 to 2.45) 65 (0 to 92) NA
Personal accomplishment* 1 (147) 1.12 (0.36 to 3.48) NA NA
Career development:
Burnout* 2 (3411) Favours negative career development
compared with positive career
development
3.77 (2.77 to 5.14) 0NA
Emotional exhaustion* 1 (593) 1.08 (0.80 to 1.44) NA NA
Depersonalisation* 1 (593) 1.12 (0.83 to 1.49) NA NA
Personal accomplishment No data No data No data NA
Job satisfaction:
Burnout 73 (146 980) Favours decreased job satisfaction
compared with increased job satisfaction
3.79 (3.24 to 4.43);
(1.13 to 12.77)
97 (96.6 to 98) P=0.002
Emotional exhaustion 33 (22 699) 4.81 (3.67 to 6.30);
(1.11 to 20.93)
98 (97 to 98.3) P=0.04
Depersonalisation 30 (22 002) 2.89 (2.37 to 3.53);
(1.07 to 7.82)
92 (90 to 94) P=0.98
Personal accomplishment 32 (27 374) 2.88 (2.28 to 3.63);
(0.86 to 9.66)
93 (91 to 95) P=0.83
Productivity loss:
Burnout 7 (9581) Favours increase in productivity loss
compared with sustained productivity
1.82 (1.08 to 3.07) 83 (66 to 91) NA
Emotional exhaustion* 4 (3421) 1.06 (1.00 to 1.12) 90 (77 to 96) NA
Depersonalisation* 3 (2969) 1.23 (1.18 to 1.28) 96 (92 to 98) NA
Personal accomplishment* 3 (2969) 1.53 (1.43 to 1.63) 97 (94 to 99) NA
Turnover intention:
Burnout 25 (32 271) Favours turnover intention compared with
retention
3.10 (2.30 to 4.17);
(0.71 to 13.56)
97 (96 to 97.3) P<0.001
Emotional exhaustion 16 (23 625) 2.81 (1.80 to 4.40);
(0.46 to 17.11)
99 (98.8 to 99.2) P=0.001
Depersonalisation 11 (23 257) 1.82 (1.26 to 2.62);
(0.53, 6.26)
99 (98.7 to 99.2) P=0.03
Personal accomplishment 5 (11 028) 1.28 (0.98 to 1.68) 86 (70 to 94) NA
Quality of patient care
Professionalism:
Burnout 40 (32 321) Favours low professionalism compared
with maintained professionalism
2.33 (1.96 to 2.70);
(0.88 to 6.16)
96 (95.5 to 97.4) P<0.001
Emotional exhaustion 16 (11 861) 2.45 (1.71 to 3.53);
(0.63 to 9.62)
94 (91.8 to 95.6) P<0.001
Depersonalisation 12 (10 488) 2.93 (1.93 to 4.46);
(0.72 to 11.94)
93 (89.9 to 95.1) P=0.03
Personal accomplishment 9 (2992) 2.17 (1.36 to 3.46) 92 (87 to 95) NA
Patient safety incidents:
Burnout 35 (41 059) Favours patient safety incidents compared
with no patient safety incidents
2.04 (1.69 to 2.45);
(0.71 to 5.81)
87 (84 to 90) P=0.04
Emotional exhaustion 17 (20 213) 2.15 (1.82 to 2.53);
(1.19 to 3.86)
73 (56 to 83) P<0.001
Depersonalisation 14 (19 616) 2.44 (1.84 to 3.23);
(0.92 to 6.44)
90 (85 to 94) P<0.001
Personal accomplishment 14 (19 616) 1.47 (1.20 to 1.80);
(0.78 to 2.76)
87 (79 to 91) P<0.001
Patient satisfaction:
Burnout 8 (1,002) Favours lower patient satisfaction
compared with them being satised
2.22 (1.38 to 3.57) 75 (53.4 to 86.6) NA
Emotional exhaustion 5 (527) 2.79 (0.75 to 10.42) 77 (44.2 to 90.5) NA
Depersonalisation 6 (571) 3.82 (1.57 to 9.29) 81 (60 to 91) NA
Personal accomplishment 5 (527) 1.79 (1.14 to 2.81) 5 (0 to 80) NA
Results pooled using the standardised mean dierence are provided in appendix 11. No changes in signicance were found when pooling using standardised mean dierence. CI=condence
interval; PI=prediction intervals were calculated only for meta-analysis involving 10 or more studies as advised in Cochrane handbook; NA=Estimate not applicable.
*Fixed eect results were reported when fewer than ve studies were reported and the meta-analysis involved varied sample and eect sizes.
†Assessment of publication bias was done using Eggers’s test in all meta-analysis of 10 or more studies as advised in Cochrane handbook, and also checked using trim-and-ll method (see
appendix 13 for full results). Forest plots for each analysis are provided in appendix 10, where the log odds ratio estimates are also available within the plots.
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
6 doi: 10.1136/bmj-2022-070442 |
BMJ
2022;378:e070442 | thebmj
Study characteristics
77 (45%) of the 170 studies were conducted in the US,
48 (28%) in European countries, four (2%) of which
were in the UK, two (1%) in the African Region, eight
(5%) in the Region of the Americas, two (1%) in the
South-East Asian Region, three (2%) in the Eastern
Mediterranean Region, 29 (17%) in the Western Pacific
Region, and one (1%) multinational study.38-44 107
(63%) of the studies were based in a hospital setting, 33
(19%) involved mixed settings, 29 (17%) were based in
primary care setting, and one study45 was unclear but
involved medically qualified academics. We aimed to
exclude studies with fewer than 70% of responses from
physicians, however, in reality, only three (2%) of 170
studies with a mixed sample of physicians (70% and
over) and other health professionals were included in
our analyses.
The median number of physicians across studies
was 312 (interquartile range 162-1015 ) with a median
age of 42 years (32-48) and where data for sex were
reported, 112 (66%) studies involved mostly male
physicians. The physician specialty varied across
studies: 42 (25%) mixed specialties, 32 (19%) internal
medicine, 21 (12%) surgery (ie, trauma, plastic, and
neurosurgical), 19 (11%) emergency medicine and
intensive care, 11 (6%) general practitioners, eight
(5%) interns or residents, eight (5%) paediatrics,
seven (4%) oncology (ie, gynaecologist, radiation,
or palliative care), six (4%) neurology, three (2%)
psychiatry, and 13 (8%) involving other specialties.
Physicians had more than seven years of experience in
52 (31%) studies, a mixture of experience was reported
in 47 (28%) studies, and 38 (22%) studies involved
residents, junior doctors, or interns with fewer than
seven years of experience.
The most common measure of burnout was the
full 22-item Maslach Burnout Inventory (81 (48%) of
170 studies). An abbreviated version of the Maslach
Burnout Inventory was used in 50 (29%) studies, other
types were used in 34 (20%) studies and only five
Burnout
Attenello 2018
Baghdadi 2020
Dominguez 2019
Duan 2019
Estryn-Behar 2011
Goldberg 1996
Hamidi 2018
Hartwell 2010
Huang 2019
Karayurek 2021
Kassam 2021
Khalafallah 2020
Khorfan 2021
Lall 2020
O'Connor 2019
Pantenburg 2016
Rabatin 2016
Shanafelt 2009
Shanafelt 2014
Sinsky 2017
Soler 2007
Sun 2021
Voultsos 2020
Willard-Grace 2019
Zhang 2011
Fixed effects model
Random effects model
Heterogeneity: I2=97% (96-97%), τ2=0.49
4.54 (2.69 to 7.67)
3.09 (1.43 to 6.64)
4.05 (2.36 to 6.96)
5.44 (4.36 to 6.79)
1.43 (1.02 to 2.01)
2.64 (1.96 to 3.57)
2.40 (1.38 to 4.18)
4.44 (1.98 to 9.93)
4.05 (3.13 to 5.25)
1.40 (1.02 to 1.92)
64.00 (7.71 to 531.60)
4.57 (1.35 to 15.41)
2.26 (1.62 to 3.17)
5.20 (3.68 to 7.35)
16.24 (5.08 to 51.91)
1.05 (1.00 to 1.10)
4.94 (3.10 to 7.86)
2.28 (1.13 to 4.60)
2.17 (1.53 to 3.09)
2.16 (1.81 to 2.58)
1.83 (1.05 to 3.20)
10.07 (7.53 to 13.47)
2.67 (0.87 to 8.16)
1.57 (1.02 to 2.41)
1.98 (1.52 to 2.59)
1.44 (1.38 to 1.50)
3.10 (2.30 to 4.17)
0.01 0.1 10 1001
Study
Favours low
turnover
intention
Favours high
turnover
intention
Odds ratio
(95% CI)
Odds ratio
(95% CI)
1.51
1.13
1.40
1.69
0.36
0.97
0.88
1.49
1.40
0.33
4.16
1.52
0.82
1.65
2.79
0.05
1.60
0.82
0.77
0.77
0.61
2.31
0.98
0.45
0.68
TE
0.27
0.39
0.28
0.11
0.17
0.15
0.28
0.41
0.13
0.16
1.08
0.62
0.17
0.18
0.59
0.03
0.24
0.36
0.18
0.09
0.28
0.15
0.57
0.22
0.14
seTE
Fig | Association of physician burnout with turnover intention. TE=log odds ratio; seTE=standard error of log odds ratio; OR=odds ratio;
CI=condence interval
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
thebmj
BMJ
2022;378:e070442 | doi: 10.1136/bmj-2022-070442 7
(3%) studies used the Copenhagen burnout inventory
(see appendix 8 in supplement for breakdown of the
measures used). Thirty one (18%) studies reported
secondary measures of depression and 24 (14%)
studies reported emotional distress, which were
analysed separately. In terms of career engagement for
physicians, 81 (48%) studies reported on decreased job
satisfaction compared with increased job satisfaction,
19 (11%) on career choice regret compared with
being satisfied with career choice, three (2%)42 46-48
Emotional exhaustion
Blanchard 2010
Campbell 2001
Golub 2008
Gyorffy 2016, 2018
Hewitt 2020
Karayurek 2021
Khan 2018
Khorfan 2021
Makara-Studzinska 2020
Moreno-Jimenez 2012
Ochoa 2018
Pantenburg 2016
Pit 2014
Salles 2019
Soler 2007
Zhang 2011
Fixed effects model
Random effects model
Heterogeneity: I2=99% (99-99%), τ2=0.67
Depersonalisation
Blanchard 2010
Campbell 2001
Gyorffy 2016, 2018
Hewitt 2020
Karayurek 2021
Khan 2018
Khorfan 2021
Pantenburg 2016
Salles 2019
Soler 2007
Zhang 2011
Fixed effects model
Random effects model
Heterogeneity: I2=99% (98-99%), τ2=0.27
Personal accomplishment
Karayurek 2021
Khorfan 2021
Pantenburg 2016
Soler 2007
Zhang 2011
Fixed effects model
Random effects model
Heterogeneity: I2=86% (70-94%), τ2=0.04
2.75 (1.64 to 4.64)
8.12 (5.77 to 11.42)
2.02 (1.37 to 2.97)
1.58 (1.44 to 1.74)
1.39 (1.28 to 1.52)
1.19 (0.80 to 1.77)
2.18 (1.62 to 2.94)
2.98 (2.45 to 3.63)
1.08 (0.72 to 1.61)
11.69 (7.90 to 17.28)
5.44 (3.22 to 9.18)
1.09 (1.08 to 1.10)
2.45 (0.93 to 6.45)
18.97 (9.32 to 38.61)
3.36 (3.14 to 3.59)
2.35 (1.94 to 2.84)
1.13 (1.12 to 1.14)
2.81 (1.80 to 4.40)
1.39 (0.84 to 2.30)
3.26 (2.39 to 4.45)
1.40 (0.93 to 2.11)
1.35 (1.24 to 1.47)
1.01 (0.68 to 1.51)
1.67 (1.24 to 2.24)
2.39 (1.96 to 2.91)
1.01 (0.99 to 1.03)
7.28 (3.88 to 13.65)
1.70 (1.63 to 1.77)
2.19 (1.81 to 2.65)
1.14 (1.12 to 1.16)
1.82 (1.26 to 2.62)
1.58 (1.06 to 2.36)
1.59 (1.23 to 2.05)
1.04 (1.02 to 1.06)
1.08 (1.00 to 1.16)
1.52 (1.26 to 1.83)
1.05 (1.03 to 1.07)
1.28 (0.98 to 1.68)
0.01 0.1 10 1001
Study
Favours low
turnover
intention
Favours high
turnover
intention
Odds ratio
(95% CI)
Odds ratio
(95% CI)
1.01
2.09
0.70
0.46
0.33
0.17
0.78
1.09
0.07
2.46
1.69
0.09
0.90
2.94
1.21
0.85
0.33
1.18
0.34
0.30
0.01
0.51
0.87
0.01
1.98
0.53
0.78
0.46
0.46
0.04
0.08
0.42
TE
0.27
0.17
0.20
0.05
0.04
0.20
0.15
0.10
0.20
0.20
0.27
0.00
0.49
0.36
0.03
0.10
0.26
0.16
0.21
0.04
0.20
0.15
0.10
0.01
0.32
0.02
0.10
0.20
0.13
0.01
0.04
0.10
seTE
Fig | Association of emotional exhaustion, depersonalisation, and personal accomplishment of physicians with turnover intention. TE=log odds
ratio; seTE=standard error of log odds ratio; OR=odds ratio; CI=condence interval
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
8 doi: 10.1136/bmj-2022-070442 |
BMJ
2022;378:e070442 | thebmj
poor career development compared with good career
development, nine (5%)47 49-59 on reduced productivity
compared with sustained productivity, and 36 (21%)
on turnover intention compared with retention.
Concerning quality of patient care outcomes, 39 (23%)
studies reported patient safety incidents compared
with no patient safety incidents, 43 (25%) reported
indicators of low professionalism compared with
maintained professionalism, and eight (5%) studies
reported measures of patient dissatisfaction compared
with satisfied patients. Nineteen (11%) studies
reported more than one of these outcomes.
Of the 119 (70%) studies reporting career
engagement, all were self-reported by the physician.
Physicians self-reported across most of the studies
for patient safety incidents (31 (79%) of 39) and
professionalism (37 (80%) of 46 studies), whereas
the remaining studies used patient record reviews and
surveillance systems. Patient satisfaction was based
on self-reports by patients.
Burnout
Baer 2017
Brunsberg 2019
Coombs 2019, 2020
Dirvar 2020
Faivre 2018
Frahrenkopt 2008
Garrouste-Orgeas 2015
Grover 2018
Hansen 2011
Hayashino 2012
Huang 2019
Kang 2013
Kassam 2020
Kemper 2020
Klein 2010
Kwah 2017
Linzer 2009
Linzer 2017
Lu 2015
Nwosu 2020
O'Connor 2017
Prins 2010
Qureshi 2015
Shanafelt 2010
Sulaiman 2017
Tawfik 2018
Trockel 2018
Vanhaecht 2019
Voultsos 2020
Watson 2018
Welp 2015
Wen 2016
West 2006
West 2009
Williams 2007
Fixed effects model
Random effects model
Heterogeneity: I2=87% (84-90%), τ2=0.26
7.10 (1.98 to 25.50)
1.03 (0.71 to 1.49)
2.12 (1.16 to 3.89)
1.36 (1.17 to 1.59)
8.90 (1.35 to 58.79)
0.72 (0.35 to 1.52)
2.07 (1.27 to 3.38)
1.18 (0.75 to 1.88)
0.83 (0.56 to 1.22)
1.69 (1.36 to 2.10)
5.36 (4.11 to 6.99)
2.48 (1.57 to 3.92)
2.08 (0.50 to 8.66)
2.55 (1.94 to 3.36)
1.94 (1.39 to 2.70)
0.35 (0.05 to 2.23)
1.06 (0.72 to 1.57)
1.44 (0.93 to 2.22)
2.89 (1.13 to 7.42)
6.22 (4.70 to 8.24)
2.75 (1.78 to 4.24)
1.93 (1.76 to 2.11)
1.89 (1.56 to 2.28)
1.10 (0.76 to 1.58)
1.90 (1.47 to 2.46)
3.25 (2.70 to 3.92)
2.88 (1.80 to 4.62)
2.81 (2.21 to 3.56)
4.16 (0.87 to 19.84)
1.97 (1.33 to 2.91)
2.07 (1.58 to 2.71)
2.28 (1.63 to 3.18)
2.44 (1.77 to 3.37)
2.56 (2.02 to 3.24)
1.61 (1.14 to 2.28)
2.05 (1.96 to 2.15)
2.04 (1.69 to 2.45)
0.1 0.5 210
1
Study
Favours no
patient safety
incidents
Favours
patient safety
incidents
Odds ratio
(95% CI)
Odds ratio
(95% CI)
1.96
0.03
0.75
0.31
2.19
-0.32
0.73
0.17
-0.19
0.52
1.68
0.91
0.73
0.94
0.66
-1.05
0.06
0.36
1.06
1.83
1.01
0.66
0.64
0.09
0.64
1.18
1.06
1.03
1.43
0.68
0.73
0.82
0.89
0.94
0.48
TE
0.65
0.19
0.31
0.08
0.96
0.38
0.25
0.24
0.20
0.11
0.14
0.23
0.73
0.14
0.17
0.95
0.20
0.22
0.48
0.14
0.22
0.05
0.10
0.19
0.13
0.09
0.24
0.12
0.80
0.20
0.14
0.17
0.17
0.12
0.18
seTE
Fig | Association of burnout with patient safety incidents. TE=Log odds ratio; seTE=standard error of log odds ratio; OR=odds ratio; CI=condence
interval
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
thebmj
BMJ
2022;378:e070442 | doi: 10.1136/bmj-2022-070442 9
Emotional exhaustion
Bressi 2009
Dirvar 2020
Hayashino 2012
Kang 2013
O'Connor 2017
Prins 2010
Prudenzi 2021
Shanafelt 2010
Sulaiman 2017
Tawfik 2018
Torppa 2015
Trockel 2018
Watson 2018
Welp 2015
West 2006
West 2009
Yost 2014
Fixed effects model
Random effects model
Heterogeneity: I2=73% (56-83%), τ2=0.07
Depersonalisation
Dirvar 2020
Hayashino 2012
Kang 2013
O'Connor 2017
Prins 2010
Shanafelt 2010
Sulaiman 2017
Tawfik 2018
Trockel 2018
Watson 2018
Welp 2015
West 2006
West 2009
Yost 2014
Fixed effects model
Random effects model
Heterogeneity: I2=90% (85-94%), τ2=0.18
Personal accomplishment
Dirvar 2020
Hayashino 2012
Kang 2013
O'Connor 2017
Prins 2010
Shanafelt 2010
Sulaiman 2017
Tawfik 2018
Trockel 2018
Watson 2018
Welp 2015
West 2006
West 2009
Yost 2014
Fixed effects model
Random effects model
Heterogeneity: I2=87% (79-91%), τ2=0.08 0.1 0.5 2 10
1
Favours no
patient safety
incidents
Favours
patient safety
incidents
1.24 (0.56 to 2.79)
2.02 (1.55 to 2.65)
1.68 (1.16 to 2.43)
3.35 (1.50 to 7.46)
2.16 (1.16 to 4.00)
2.10 (1.79 to 2.46)
1.61 (0.77 to 3.36)
1.32 (1.15 to 1.52)
2.01 (1.29 to 3.14)
2.64 (2.23 to 3.13)
2.15 (0.97 to 4.80)
2.36 (1.48 to 3.76)
6.17 (2.78 to 13.70)
2.55 (1.59 to 4.10)
2.43 (1.39 to 4.26)
2.66 (1.77 to 4.00)
2.18 (0.74 to 6.44)
1.95 (1.81 to 2.10)
2.15 (1.82 to 2.53)
1.17 (0.90 to 1.53)
2.72 (1.15 to 6.43)
2.85 (1.29 to 6.32)
5.89 (2.48 to 14.02)
3.00 (2.55 to 3.53)
1.32 (1.15 to 1.52)
2.16 (1.38 to 3.39)
3.33 (2.83 to 3.92)
5.63 (3.41 to 9.30)
2.45 (1.36 to 4.42)
1.80 (1.13 to 2.87)
2.47 (1.41 to 4.33)
3.05 (2.02 to 4.60)
1.16 (0.40 to 3.38)
2.20 (2.03 to 2.37)
2.44 (1.84 to 3.23)
1.06 (0.81 to 1.39)
1.61 (1.22 to 2.13)
1.62 (0.74 to 3.55)
2.09 (0.90 to 4.86)
1.20 (1.03 to 1.40)
0.76 (0.66 to 0.87)
1.59 (1.02 to 2.47)
2.03 (1.69 to 2.45)
1.24 (0.79 to 1.96)
1.59 (0.80 to 3.15)
1.94 (1.22 to 3.10)
2.43 (1.39 to 4.26)
2.07 (1.38 to 3.11)
1.39 (0.47 to 4.07)
1.24 (1.15 to 1.33)
1.47 (1.20 to 1.80)
Study Odds ratio
(95% CI)
Odds ratio
(95% CI)
0.22
0.71
0.52
1.21
0.77
0.74
0.48
0.28
0.70
0.97
0.77
0.86
1.82
0.94
0.89
0.98
0.78
0.16
1.00
1.05
1.77
1.10
0.28
0.77
1.20
1.73
0.90
0.59
0.90
1.12
0.15
0.06
0.48
0.48
0.74
0.18
-0.28
0.46
0.71
0.22
0.46
0.66
0.89
0.73
0.33
TE
0.41
0.14
0.19
0.41
0.31
0.08
0.38
0.07
0.23
0.09
0.41
0.24
0.41
0.24
0.29
0.21
0.55
0.14
0.44
0.41
0.44
0.08
0.07
0.23
0.08
0.26
0.30
0.24
0.29
0.21
0.55
0.14
0.14
0.40
0.43
0.08
0.07
0.23
0.10
0.23
0.35
0.24
0.29
0.21
0.55
seTE
Fig | Association of emotional exhaustion, depersonalisation, and personal accomplishment with patient safety incidents. TE=Log odds ratio;
seTE=standard error of log odds ratio; OR=odds ratio; CI=condence interval
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
10 doi: 10.1136/bmj-2022-070442 |
BMJ
2022;378:e070442 | thebmj
Quality assessment
One hundred and 30 studies provided a representative
sample of the target population (76% met criterion
1); 103 studies provided an ample sample size of
physicians (61% met criterion 2); 58 studies reported
a response rate of 60% or greater (34% met criterion
3); 25 studies satisfied low risk of bias for the
ascertainment of exposure mostly due to many of the
surveys being self-reported (15% met criterion 4); 100
of the studies adequately adjusted for confounding
factors (59% met criterion 5); 165 reported a low
risk of bias due to assessment of outcome (97% met
criterion 6); and 118 studies had used adequate
statistical tests and measures to report their findings
(69% met criterion 7). Overall, 32 (19%) of the studies
reported low risk of bias (total score 6-7), 23 (14%)
reported high risk of bias (total score: 0-2), and 115
(67%) studies reported medium risk of bias (total score
3-5). The full results of the Newcastle Ottawa critical
appraisals are presented in appendix 9.
Meta-analysis of association of burnout with career
engagement and quality of patient care
The results of all the meta-analyses are provided in
table 1. All forest plots for each outcome are available in
appendix 10. Only significant results are reported here.
Physician burnout was associated with almost
fourfold decreases in job satisfaction compared
with increased job satisfaction based on measures
of overall burnout (3.79, 95% confidence interval
3.24 to 4.43, I2=97%, k=73 studies, n=146 980
physicians), emotional exhaustion (4.81, 3.67 to 6.30,
I2=98%, k=33, n=22 699), depersonalisation (2.89,
2.37 to 3.53, I2=92%, k=30, n=22 002) and personal
accomplishment (2.88, 2.28 to 3.63, I2=93%, k=32,
n=27 374). Burnout was associated with threefold
increases in career choice regrets compared with being
satisfied with their career choice based on measures
of overall burnout (3.49, 2.43 to 5.00, I2=97%, k=16,
n=33 871) and emotional exhaustion (4.16, 3.34 to
5.19, I2=90%, k=4, n=2014). Burnout was associated
with up to threefold increases in turnover intention
compared with retention based on measures of overall
burnout (3.10, 2.30 to 4.17, I2=97%, k=25, n=32 271;
fig 3), emotional exhaustion (2.81, 1.80 to 4.40,
I2=99%, k=16, n=23 625), and depersonalisation
(1.82, 1.26 to 2.62, I2=99%, k=11, n=23 257; fig 4)
but no eect was seen for personal accomplishment.
Burnout was associated with small but significant
decreases in productivity compared with sustained
productivity based on measures of overall burnout
(1.82, 1.08 to 3.07, I2=83%, k=7, n=9581),
depersonalisation (1.23, 1.18 to 1.28, I2=96%, k=3,
n=2969) and personal accomplishment (1.53, 1.43
to 1.63, I2=97%, k=3, n=2969). Finally, only two
studies46-48 reported a significant pooled association
between overall burnout and career development
concerns compared with good career development
(3.77, 2.77 to 5.14, I2=0%, k=2, n=3411).
Physician burnout was associated with double
the risk of patient safety incidents compared with
no patient safety incidents based on measures of
overall burnout (odds ratio 2.04, 95% confidence
interval 1.69 to 2.45, I2=87%, k=35, n=41 059; fig 5),
emotional exhaustion (2.15, 1.82 to 2.53, I2=73%,
k=17, n=20 213), depersonalisation (2.44, 1.84
to 3.23, I2=90%, k=14, n=19 616), and personal
accomplishment (1.47, 1.20 to 1.80, I2=87%, k=14,
n=19 616; fig 6). Burnout was associated with more
than twofold decreases in professionalism compared
with maintained professionalism based on measures
of overall burnout (2.33, 1.96 to 2.70, I2=96%, k=40,
n=32 321), emotional exhaustion (2.45, 1.71 to 3.53,
I2=94%, k=16, n=11 861), depersonalisation (2.93,
1.93 to 4.46, I2=93%, k=12, n=10 488), and personal
accomplishment (2.17, 1.36 to 3.46, I2=92%, k=9,
n=2992). Burnout was also associated with up to
threefold decreases in patient satisfaction compared
with patients being satisfied based on measures of
overall burnout (2.22, 1.38 to 3.57, I2=75%, k=8,
n=1002), depersonalisation (3.82, 1.57 to 9.29,
I2=81%, k=6, n=571), and personal accomplishment
(1.79, 1.44 to 2.81, I2=5%, k=5, n=527). Publication
bias was found after visual inspection of funnel plots
and the test statistics for most comparisons were
significant (appendix 13).
Some studies had used dierent scales to measure
burnout, therefore, we also did analyses using
standardised mean dierence to account for measures
of dierent length (see forest plots in appendix 11).
However, we found no significant dierences in this
analysis and the results were consistent with those
reported when analysed with the odds ratio.
The subgroup meta-analyses for the dierent
measures of burnout used for the outcomes job
satisfaction, patient safety incident, professionalism,
and turnover intention is provided in appendix 8 in
supplement.
For job satisfaction, the abbreviated version of
Maslach Burnout Inventory provided the largest
association with burnout (odds ratio 4.62, 95%
confidence interval 3.21 to 6.65, I2=99%) and
smallest with the Copenhagen burnout inventory
(2.59, 2.22 to 3.01, I2=95%). The Copenhagen
inventory had the highest association of burnout
with patient safety incidents (3.59, 2.92 to 4.42,
I2=95%) and the abbreviated versions of the Maslach
Burnout Inventory had the lowest association (1.68,
1.16 to 2.43, I2=79%). The association between
burnout and low professionalism was greatest
when using an abbreviated version of the Maslach
Burnout Inventory (2.91, 1.65 to 5.13, I2=87%) and
lowest when using the Copenhagen inventory (1.89,
1.69 to 2.12, I2=43%). The association between
burnout and turnover intention was greatest when
other non-specific measures of burnout were used
(7.23, 5.93 to 3.18, I2=77%) and lowest when an
abbreviated version of Maslach Burnout Inventory
was used (2.53, 1.39 to 4.59, I2=98%). No significant
dierences were noted between the dierent burnout
measures when tested using the ratio of odds ratios
(appendix 8).
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
thebmj
BMJ
2022;378:e070442 | doi: 10.1136/bmj-2022-070442 11
Meta regressions
The results of the univariable and multivariable meta-
regression analyses are provided in appendix 12. In the
univariable regression results, a stronger association
of overall burnout with low job satisfaction was found
in physicians working in hospitals compared with
primary care settings (1.88, 0.91 to 3.86, P=0.09),
and more specifically in emergency medicine and
intensive care (2.16, 0.98 to 4.76, P=0.06) compared
with a general internal medicine specialty, and in
physicians older than the age of 50 years compared
with individuals aged 31-50 years (2.41, 1.02 to 5.64,
P=0.04). The association was weakest in GPs (0.16,
0.03 to 0.88, P=0.04). However, these associations
did not remain significant in the multivariable
regressions. The association between burnout and
patient safety incidents in the univariable regression
results was found to be larger in younger physicians
(20-30 years; 1.88, 1.07 to 3.29, P=0.03), working
in emergency medicine and intensive care settings
(2.10, 1.09 to 3.56, P=0.02), or in training based
in the Commonwealth region (3.03, 0.83 to 11.25,
P=0.09). The only association to remain significant
in the multivariable regression results was that found
in younger physicians (1.55, 0.94 to 2.56, P=0.08).
The univariable regression results of the association
of burnout with low professionalism was found to be
smaller in physicians aged older than 50 years (0.36,
0.19 to 0.69, P=0.003) and larger in physicians still
in training or residency (2.27, 1.45 to 3.60, P=0.001),
who worked in a hospital (2.16, 1.46 to 3.19, P<0.001),
specifically in the emergency medicine specialty and
intensive care (1.48, 1.01 to 2.34, P=0.04), or when
situated in a low to middle income country (1.68,
0.94 to 2.97, P=0.08). Multivariable regression results
show that the association remained significant in
middle aged physicians aged 31-50 years (0.45, 0.26
to 0.76, P=0.003), working in a hospital (3.82, 1.84 to
8.00, P<0.001), or specialising in cancer (0.25, 0.09
to 0.74, P=0.01) or neurology (0.22, 0.07 to 0.73,
P=0.01). The univariable regression results of the
association of burnout with career choice regret was
found to be largest in physicians with a specialisation
in emergency medicine and intensive care (2.89,
0.97 to 14.89, P=0.10) and neurology (2.52, 0.82 to
7.80, P=0.10). The association between burnout and
turnover intentions did not vary according to any other
factors included in the univariable regression analyses
(appendix 12). No significant associations were found
between burnout and job satisfaction.
Discussion
Principal ndings
This systematic review and meta-analysis provides
compelling evidence that physician burnout is
strongly associated with the career disengagement
of physicians and suboptimal patient care. However,
even after confirming the consistency of the data in
up 84 (49%) of 170 study authors, the results should
be considered in tandem with the large amount of
heterogeneity presented in all comparisons.
We found that physicians with burnout were up to
four times more likely to be dissatisfied with their job
compared with being satisfied with their job, three
times as likely to have thoughts or intentions to quit
their job (turnover) compared with job retention,
and three times as likely to regret their career choice
compared with being satisfied with their career choice.
Emotional exhaustion contributed most to increases
in the turnover intention of physicians compared with
retention. The association of physician burnout with
lower job satisfaction compared with increased job
satisfaction was more prevalent in older physicians
working in emergency medicine and intensive care.
Physicians with burnout are twice as likely to be
involved in patient safety incidents compared with no
patient safety incidents and show low professionalism
compared with maintained professionalism, and over
two times more likely to receive low satisfaction ratings
from patients compared with satisfied patient ratings.
The depersonalisation subscale of burnout appeared
to have the most adverse association with the quality
of care and patient dissatisfaction. Patient safety
incidents compared with no patient safety incidents
were more likely to occur in younger physicians
working in emergency medicine and intensive care.
Comparisons with similar research
No previous meta-analysis has examined the
association of burnout with the career engagement of
physicians. Only one review,60 predominately based on
studies of nurses, has linked inter-professional work
with employee outcomes. A number of systematic
reviews have assessed the association of burnout
with the quality of patient care, however, these
studies mostly included mixed samples of healthcare
professionals and rarely used meta-analysis due to
heterogeneous samples and outcomes.14 15 We chose
to focus on physicians because they are twice as
likely to experience burnout than any other worker,
including other healthcare professionals8 12 and
this choice has improved our confidence in using a
meta-analysis. Moreover, both career engagement of
physicians and quality of patient care were chosen
because these dimensions of health service quality are
complimentary and some of our outcomes including
low professionalism, low job satisfaction, and reduced
patient satisfaction, are precursors of safety risks with
potential to lead to active patient safety incidents and
have serious career implication on the physician.61
This balanced approach (to be comprehensive in terms
of outcomes but specific on physicians) was agreed
by our core research team involving physicians and
patients.
Policy implications
Many countries including the US and the UK have
described levels of physician burnout as the highest in
the history of health and care systems.2 62 63 Our findings
arm that physician burnout can be a catalyst for the
career disengagement of physicians and that burnout
is associated with unsafe patient care,64 65 which costs
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
12 doi: 10.1136/bmj-2022-070442 |
BMJ
2022;378:e070442 | thebmj
billions to healthcare systems annually.66-68 Physician
burnout deepens the workforce crisis and undermines
a fundamental societal need to be in receipt of safe care.
In line with our results, a survey from the US concluded
that physicians at the front line of care access are at
greatest risk of burnout, work longer hours, and
have greater struggles with work-life balance and job
satisfaction than other healthcare workers.69 These
factors often unite as a result of burnout, and can lead
to higher physician turnover rates,70 which in itself
has substantial costs in terms of both the interruption
in continuity of care relationships and high expense
associated with recruiting new clinicians and sta.71
Eective interventions that can curtail physician
burnout are needed now more than ever as health
and care systems across the globe are encountering a
workforce crisis.72 A range of eective interventions for
reducing burnout in physicians are available, including
interventions focusing on improving the culture on
healthcare organisations, interventions supporting
individual physicians through organisational funded
initiatives, and multicomponent interventions.21 73
We found that physicians with high scores of
depersonalisation are especially likely to be involved
in lower quality of patient care whereas physicians
with high scores of emotional exhaustion are especially
likely to express intentions to leave their job. Thus,
interventions targeting specific dimensions of burnout
could be oered to subgroups of physicians with career
concerns or adverse patient care experiences taking
also into consideration their reciprocal relationships
between burnout, career engagement, and quality of
patient care. For example, physicians experiencing
burnout might have less time or commitment to
optimise the care of their patients, can take more
unnecessary risks, or might lack accountability.74
Conversely, exposure to adverse patient events or
recognition of poor quality of care can result in
burnout, which in turn could force physicians to quit.
This process can often be referred to as secondary
trauma, particularly in relation to sentinel events or
important safety incidents.75
Our results highlight subgroups of physicians
with burnout who could be at particularly high risk
for career disengagement and provision of unsafe
patient care. These physicians are mainly frontline
physicians in emergency medicine and intensive care.
Unsurprisingly, reports from frontline physicians
advocate that the field of medicine is almost reaching
crisis point with an increasing number of physicians
working part time, resigning from their job, or retiring
early in response to excessive workload and symptoms
of burnout.6 76
Limitations
The large heterogeneity for some of the outcomes
such as, patient safety, professionalism, and job
satisfaction, might have been due to variations of
outcome definition. Despite this variation, we selected
these definitions based on theories and consultations
with stakeholders. For example, the outcome job
dissatisfaction includes many dierent aspects such as
poor work engagement, dissatisfaction with workload,
and poor relationships with patients. This diversity in
the outcome definition might lead to overestimating
the association with physician burnout, as the
prediction intervals (which conveniently express
heterogeneity) suggest. Therefore, the results should
be interpreted with this potential overestimation
in mind. Similarly, patient safety incidents often
originate from complex and interchangeable factors
including the dierent nature and types (preventable
or not), severity, dispensing stage, and systems used.77
Meaning that the observed meta-analytical association
with physician burnout might be more attributable
to general factors of the whole organisation or work
setting in healthcare.78 Additionally, our definition for
the patient safety incidents was broad and captured
any of the following incidents; potentially avoidable
readmission, prescribing errors, monitoring errors,
and potentially avoidable adverse events. Thus, owing
to the large variation in the possible cause of a safety
incident, we urge some caution when interpreting the
pooled eect sizes for patient safety incidents.
The tools or questionnaires used to assess these
above outcomes varied considerably and this variation
did not allow us to make any meaningful subgroup or
sensitivity analyses. Reaching consensus about a gold
standard set of tools to assess at least some of these
outcomes would be an important step for improving
the precision of the eect sizes in future meta-
analyses. Moreover, career engagement outcomes
have conceptual similarities with the personal
accomplishment subscale of burnout but exclusive
focus on only the other two subscales of burnout
(emotional exhaustion and depersonalisation)
could introduce more bias than omitting personal
accomplishment would avoid. Our findings call for
future studies to examine the causal and temporal
relations (eg, structural equation modelling) between
the dierent career engagement outcomes and the
three subscales of burnout.
We extracted and analysed the rawest available data
in each study where possible, standardised these data
using odds ratios (and standardised mean dierences),
and then performed several meta-regressions and
sensitivity analyses to validate the findings. Despite
these precautions, some degree of imprecision is still
possible in the pooled eect sizes driven by variations
in the aggregate data that we used. Accessing
individual participant data could considerably
improve the precision of the eect sizes, which we
strongly recommend in future research.
Although the focus of this investigation was on
physicians, this population should still be considered
as working in various settings and specialties. We
performed meta-regressions, which did explain
some of the heterogeneity due to specialty area, but
because of the low numbers of participants in some
groups, these meta-regressions had to be combined
into hierarchical categories of healthcare settings
or specialties, which could conflate some findings.
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
thebmj
BMJ
2022;378:e070442 | doi: 10.1136/bmj-2022-070442 13
Furthermore, because fewer patient safety incidents
were found in studies with response rates above 70%,
this might have attributed to possible bias in studies
with lower response rates.79
Our protocol amendment resulted in excluding grey
literature from this review. Although the exclusion
of this type of literature could actually lead to an
increase in publication bias80; the sheer high volume
of additional grey literature (eg, mostly engagement
surveys by medical associations or colleges and
universities) were of poor quality and provided
limited, if any, association data that could be used
in a meta-analysis. Thus, we have captured the
highest quality of evidence providing meta-analytical
pertinent data. However, peer reviewed literature
is likely to be subject to some exaggeration of the
association of burnout when assessed against similar
patient care outcomes.10 Also, only English language
publications were included so other studies could
have been missed.
Sensitivity analysis of the reporting method (ie,
by physician or patient surveillance system) was not
possible because more than 79% of the reports were
self-reports by physicians for both patient safety
incidents and low professionalism. The design of the
original studies (mostly cross-sectional) inevitably
imposes limits on our ability to establish causal links
between physician burnout and patient care or career
engagement, and the mechanisms that underpin these
links.81 However, with only 20 prospective cohort or
longitudinal studies, assessment of direct causality
would not have been feasible in this study. Finally,
method bias is a common problem in cross-sectional
studies, when measuring one or more constructs
with the same method it can have significant eects
on the relationship between them.82 Method bias can
influence inventory validation and reliabilities as well
as the covariation between latent constructs, such as
measures of physician wellness. Thus, researchers need
to be knowledgeable about ways to control for method
biases thorough the use of more suited statistical
remedies, such as structural equational models, which
provide an explicit assessment of measurement error
and estimation of latent constructs.83
Conclusions
Burnout is a strong predictor for career disengagement
in physicians as well as for patient care. Moving
forward, investment strategies to monitor and improve
physician burnout are needed as a means of retaining
the healthcare workforce and improving the quality
of patient care. Scalable implementation of eective
interventions for physician burnout, such as those
improving the culture of healthcare organisations, and
multicomponent interventions are strongly supported
by our findings.21 73
AUTHOR AFFILIATIONS
1National Institute for Health and Care Research (NIHR) School
for Primary Care Research, Division of Population Health, Health
Services Research and Primary Care, School of Health Sciences,
Faculty of Biology, Medicine and Health, Manchester Academic
Health Science Centre, University of Manchester, Manchester, UK
2School of Psychology, University of Leeds, Leeds, UK
3Bradford Institute for Health Research, Bradford Royal Inrmary,
Bradford, UK
4School of Health Sciences, Faculty of Health and Medical Sciences,
University of Surrey, Guildford, UK
5School of Clinical Medicine, University of Cambridge, Cambridge,
UK
6Laboratory of Hygiene, Aristotle Medical School, Aristotle University
of Thessaloniki, Thessaloniki, Greece
7School of Medicine, Keele University, Keele, Newcastle, UK
8Westminster Centre for Resilience, Faculty of Science and
Technology, University of Westminster, London, UK
9National Institute for Health Research Greater Manchester Patient
Safety Translational Research Centre, Division of Population
Health, Health Services Research and Primary Care, University of
Manchester, Manchester, UK
We thank the following for conrming their study data: Colin West,
Mark Linzer, Daniel S Tawk, Sami Abdo Radman Al-Dubai, Hamzeh
Mohammad Alrawashdeh, Ala’a B Al-Tammemi, Tamara Elizabeth
Baer, Suphi Bahadirli, Pierre Blanchard, Tom Bourne, Katherine A
Brunsberg, Neil A Busis, Demetrius M Coombs, Risal Djohan, Mao
Ding, Oksana Babenko, Sergio Dominguez-Lara, Ingrid Gilles, Justin
S Golub, Michael M Johns III, Zsuzsa Győry, Rikke P Hansen, D Brock
Hewitt, Karl Y Bilimoria, Matthew R Janko, Matthew R Smeds, Hakan
Demirci, Julie Welch, Kathi J Kemper, Debraj Mukherjee, Atir Khan, Jens
Klein, Michael Kriss, Henry M Kuerer, Shailesh Kumar, Jason Kwah,
Michelle D Lall, John Leung, Kerry H Levin, Dave W Lu, Laxmi S Mehta,
Leonardo Potenza, Maha Sulaiman Younis, Bernardo Moreno-Jiménez,
Paul O’Connor, Alec O’Connor, Geon Ho Bahn, Sabrina Pit, Jelle T
Prins, Vinay Rawlani, Ashim Roy, Arghavan Salles, Wilmar B Schaufeli,
Christine A Sinsky, James A Sliwa, Leyla Ozturk Sonmez, Colm M P
O’Tuathaigh, Lois J Surgenor, Hyo Jung Tak, Okan Taycan, Yasuharu
Tokuda, Wakako Umene-Nakano, Deborah Seys, David Ring, Krzysztof
A Tomaszewski, Lars Peterson, Alexander G Watson, Matthias Weigl,
Hui-Ching Weng, Robin R Whitebird, Rachel Willard-Grace, James
Gardner Wright, Xiaowei Zhang, Morgan G Yost, Sandeep Grover, and
Peng Xie.
Contributors: MP, AH, and AE had the initial research idea and
obtained funding for this study. AH, MP, AE formulated the research
questions and designed the study. AH searched for published
work, selected articles, extracted and analysed data, and draed
the protocol and manuscript. MP, AZ, JJ, RR, AZ, and KG helped in
the searching of articles and data selection and extraction. Data
extraction was conrmed by 49% of the authors. MP substantially
contributed to designing the searches and the statistical analysis plan,
writing of the manuscript, and interpreting the ndings. AE, CAC-G, JJ,
DP, and RR substantially contributed to the manuscript by providing
review comments and edits. AH is the guarantor. All authors have read
and approved the nal manuscript. The corresponding author attests
that all listed authors meet authorship criteria and that no others
meeting the criteria have been omitted.
Funding: This study is funded by the UK National Institute for Health
Research (NIHR) School for Primary Care Research (project 411). AH is
also funded by the University of Manchester through his Presidential
Fellowship. The NIHR Greater Manchester Patient Safety Translational
Research Centre funded MP’s time contributed to this project.
CCG would also like to acknowledge the NIHR Applied Research
Collaboration West Midlands who is responsible for partly funding her
research. The study funder had no role in the design and conduct of
the study; collection, management, analysis, or interpretation of the
data; preparation, review, or approval of the manuscript; or decision to
submit the manuscript for publication. The views expressed are those
of the author(s) and not necessarily those of the UK National Institute
for Health Research or the Department of Health and Social Care.
Competing interests: All authors have completed the ICMJE
uniform disclosure form at www.icmje.org/coi_disclosure.pdf and
declare: support from the UK National Institute for Health and Care
Research School for Primary Care Research for the submitted work;
no nancial relationships with any organisations that might have an
interest in the submitted work in the previous three years; no other
relationships or activities that could appear to have influenced the
submitted work.
Ethical approval: Not required in this study.
Data sharing: Because this meta-analysis was based on data
extracted from previously published research, most of the data and
study materials are available in the public domain. However, the
raw data extractions, transformed data sheets and author emails
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
14 doi: 10.1136/bmj-2022-070442 |
BMJ
2022;378:e070442 | thebmj
conrming the data will be made available and will be published on
Mendeley.
The lead author AH (the manuscript’s guarantor) arms that the
manuscript is an honest, accurate, and transparent account of the
study being reported; that no important aspects of the study have
been omitted; and that any discrepancies from the study as planned
(and, if relevant, registered) have been explained.
Dissemination to participants and related patient and public
communities: The results will be presented at this year’s Annual
Society of Academic Primary Care (SAPC) Annual Scientic Meeting
2022 (https://sapc.ac.uk/conference/2022) and at the WELL-Med’s
4th International Meeting on Well Being and Performance in Clinical
Practice (https://www.well-med.gr). The results will also be shared
through press releases through the aliated universities of the
author’s involved, social medial including twitter and with funders
including the NIHR SPCR.
Provenance and peer review: Not commissioned; externally peer
reviewed.
This is an Open Access article distributed in accordance with the
Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license,
which permits others to distribute, remix, adapt, build upon this work
non-commercially, and license their derivative works on dierent
terms, provided the original work is properly cited and the use is non-
commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
1 Maslach C. Burnout, Psychology of. In: Wright JD, ed. International
Encyclopedia of the Social & Behavioral Sciences.2nd ed. Elsevier,
2015: 929-32. doi:10.1016/B978-0-08-097086-8.26009-1.
2 The Lancet. Physician burnout: a global crisis. Lancet2019;394:93.
doi:10.1016/S0140-6736(19)31573-9
3 Shanafelt TD, West CP, Sinsky C, et al. Changes in burnout and
satisfaction with work-life integration in physicians and the general
US working population between 2011 and 2020. Mayo Clin
Proc2022;97:491-506. doi:10.1016/j.mayocp.2021.11.021
4 General Medical Council. National Training Survey 2021 results.
2021https://www.gmc-uk.org/-/media/documents/national-training-
survey-results-2021-summary-report_pdf-87050829.pdf.
5 Wright T, Mughal F, Babatunde OO, Dikomitis L, Mallen CD, Helliwell T.
Burnout among primary health-care professionals in low- and middle-
income countries: systematic review and meta-analysis. Bull World
Health Organ2022;100:385-401A. doi:10.2471/BLT.22.288300
6 Gergen K. The self as social construction. Psychol Stud
(Mysore)2011;56:108. doi:10.1007/s12646-011-0066-1.
7 American Medical Association (AMA). Coping with covid-19 for
caregivers survey. National comparison report prepared May 2021.
https://www.ama-assn.org/system/les/coping-with-covid-19-
caregivers-survey-national-comparison-report.pdf.
8 Shanafelt TD, Hasan O, Dyrbye LN, et al. Changes in burnout and
satisfaction with work-life balance in physicians and the general
US working population between 2011 and 2014. Mayo Clin
Proc2015;90:1600-13. doi:10.1016/j.mayocp.2015.08.023
9 Shanafelt TD, Balch CM, Bechamps GJ, et al. Burnout and career
satisfaction among American surgeons. Ann Surg2009;250:463-71.
doi:10.1097/SLA.0b013e3181ac4dfd
10 Tawk DS, Scheid A , Prot J, et al. Evidence relating health care provider
burnout and quality of care: a systematic review and meta-analysis.
Ann Intern Med2019;171:555-67. doi:10.7326/M19-1152
11 Olson KD. Physician burnout-a leading indicator of health system
performance?Mayo Clin Proc2017;92:1608-11. doi:10.1016/j.
mayocp.2017.09.008
12 Wallace JE, Lemaire JB, Ghali WA. Physician wellness: a missing
quality indicator. Lancet2009;374:1714-21. doi:10.1016/S0140-
6736(09)61424-0
13 Welle D, Trockel MT, Hamidi MS, et al. Association of occupational
distress and sleep-related impairment in physicians with unsolicited
patient complaints. Mayo Clin Proc2020;95:719-26. doi:10.1016/j.
mayocp.2019.09.025
14 Hall LH, Johnson J, Watt I, Tsipa A, O’Connor DB. Healthcare sta
wellbeing, burnout, and patient safety: a systematic review. PLoS
One2016;11:e0159015. doi:10.1371/journal.pone.0159015
15 Dewa CS, Loong D, Bonato S, Trojanowski L. The relationship between
physician burnout and quality of healthcare in terms of safety and
acceptability: a systematic review. BMJ Open2017;7:e015141.
doi:10.1136/bmjopen-2016-015141
16 Owoc J, Mańczak M, Jabłońska M, Tombarkiewicz M, Olszewski R.
Association between physician burnout and self-reported errors:
meta-analysis. J Patient Saf2022;18:e180-8. doi:10.1097/
PTS.0000000000000724
17 Hodkinson A, Johnson J, Geraght K, et al. Associations of physician
burnout with patient care and career outcomes: a systematic
review and meta-analysis. PROSPERO 2021 CRD42021249492.
https://www.crd.york.ac.uk/prospero/display_record.
php?ID=CRD42021249492.
18 Stroup DF, Berlin JA, Mor ton SC, et al. Meta-analysis of observational
studies in epidemiology: a proposal for reporting. Meta-analysis
Of Observational Studies in Epidemiology (MOOSE) group.
JAMA2000;283:2008-12. doi:10.1001/jama.283.15.2008
19 Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020
statement: an updated guideline for reporting systematic reviews.
BMJ2021;372:n71. doi:10.1136/bmj.n71
20 Kanter MH, Nguyen M, Klau MH, Spiegel NH, Ambrosini VL. What does
professionalism mean to the physician?. Perm J2013;17:87-90.
doi:10.7812/TPP/12-120
21 Panagioti M, Panagopoulou E, Bower P, et al. Controlled interventions
to reduce burnout in physicians: a systematic review and meta-
analysis. JAMA Intern Med2017;177:195-205. doi:10.1001/
jamainternmed.2016.7674
22 Conner KR, Beautrais AL, Brent DA, Conwell Y, Phillips MR, Schneider
B. The next generation of psychological autopsy studies. Part I.
Interview content. Suicide Life Threat Behav2011;41:594-613.
doi:10.1111/j.1943-278X.2011.00057.x
23 Holm AL, Severinsson E. Struggling to recover by changing suicidal
behaviour: narratives from women with borderline personality
disorder. Int J Ment Health Nurs2011;20:165-73. doi:10.1111/
j.1447-0349.2010.00713.x
24 Wells G, Shea B, O’Connell D, et al, The Newcastle–Ottawa Scale (NOS)
for assessing the quality of non-randomized studies in meta-analysis.
2000; https://www.researchgate.net/publication/261773681_The_
Newcastle-Ottawa_Scale_NOS_for_Assessing_the_Quality_of_Non-
Randomized_Studies_in_Meta-Analysis
25 DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin
Trials1986;7:177-88. doi:10.1016/0197-2456(86)90046-2
26 Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-
analysis. Stat Med2002;21:1539-58. doi:10.1002/sim.1186
27 IntHout J, Ioannidis JP, Borm GF. The Hartung-Knapp-Sidik-Jonkman
method for random eects meta-analysis is straightforward and
considerably outperforms the standard DerSimonian-Laird method.
BMC Med Res Methodol2014;14:25. doi:10.1186/1471-2288-14-
25
28 Altman DG, Bland JM. Interaction revisited: the dierence
between two estimates. BMJ2003;326:219. doi:10.1136/
bmj.326.7382.219
29 Sterne JA, Egger M, Smith GD. Systematic reviews in health care:
Investigating and dealing with publication and other biases in meta-
analysis. BMJ2001;323:101-5. doi:10.1136/bmj.323.7304.101
30 Riley RD, Higgins JPT, Deeks JJ. Interpretation of random eects meta-
analyses. BMJ2011;342:d549. doi:10.1136/bmj.d549
31 Maslach C, Jackson SE. The measurement of experienced burnout. J
Organ Behav1981;2:99-113. doi:10.1002/job.4030020205.
32 Rotenstein LS, Torre M, Ramos MA, et al. Prevalence of burnout
among physicians: a systematic review. JAMA2018;320:1131-50.
doi:10.1001/jama.2018.12777
33 Thiese MS, Ronna B, Ott U. P value interpretations and
considerations. J Thorac Dis2016;8:E928-31. doi:10.21037/
jtd.2016.08.16
34 Harrell FEJr. Regression modeling strategies.Springer International
Publishing, 2016.
35 Lather P. Getting lost: feminist practices toward a double(d). State
University of New York Press. 2007.
36 Balduzzi S, Rücker G, Schwarzer G. How to perform a meta-analysis
with R: a practical tutorial. Evid Based Ment Health2019;22:153-60.
doi:10.1136/ebmental-2019-300117
37 Marsh I.Suicide: Foucault, history and truth. Cambridge University
Press.2010.
38 Bourne T, Wynants L, Peters M, et al. The impact of complaints
procedures on the welfare, health and clinical practise
of 7926 doctors in the UK: a cross-sectional survey. BMJ
Open2015;5:e006687. doi:10.1136/bmjopen-2014-006687
39 Bourne T, De Cock B, Wynants L, et al. Doctors’ perception of
support and the processes involved in complaints investigations
and how these relate to welfare and defensive practice: a cross-
sectional survey of the UK physicians. BMJ Open2017;7:e017856.
doi:10.1136/bmjopen-2017-017856
40 Bourne T, Shah H, Falconieri N, et al. Burnout, well-being and
defensive medical practice among obstetricians and gynaecologists
in the UK: cross-sectional survey study. BMJ Open2019;9:e030968.
doi:10.1136/bmjopen-2019-030968
41 Hall LH, Johnson J, Watt I, O’Connor DB. Association of GP wellbeing and
burnout with patient safety in UK primary care: a cross-sectional survey.
Br J Gen Pract2019;69:e507-14. doi:10.3399/bjgp19X702713
42 Khan A, Teoh KR, Islam S, Hassard J. Psychosocial work
characteristics, burnout, psychological morbidity symptoms
and early retirement intentions: a cross-sectional study of NHS
consultants in the UK. BMJ Open2018;8:e018720. doi:10.1136/
bmjopen-2017-018720
43 Sharma A, Sharp DM, Walker LG, Monson JR. Stress and burnout
in colorectal and vascular surgical consultants working in the
UK National Health Service. Psychooncology2008;17:570-6.
doi:10.1002/pon.1269
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
RESEARCH
thebmj
BMJ
2022;378:e070442 | doi: 10.1136/bmj-2022-070442 15
44 Prudenzi AD, Graham C, Flaxman PE, et al. Wellbeing, burnout, and
safe practice among healthcare professionals: predictive influences
of mindfulness, values, and self-compassion. Psychol Health
Med2022;27:1130-43. doi:10.1080/13548506.2021.1898651
45 van Wulen Palthe OD, Neuhaus V, Janssen SJ, Guitton TG, Ring
D, Science of Variation Group. Among musculoskeletal surgeons,
job dissatisfaction is associated with burnout. Clin Orthop Relat
Res2016;474:1857-63. doi:10.1007/s11999-016-4848-6
46 Estryn-Behar M, Doppia MA, Guetarni K, et al. Emergency physicians
accumulate more stress factors than other physicians-results
from the French SESMAT study. Emerg Med J2011;28:397-410.
doi:10.1136/emj.2009.082594
47 Kassam AF, Cortez AR, Winer LK, et al. Extinguishing burnout: National
analysis of predictors and eects of burnout in abdominal transplant
surgery fellows. Am J Transplant2021;21:307-13. doi:10.1111/
ajt.16075
48 McAbee JH, Ragel BT, McCartney S, et al. Factors associated
with career satisfaction and burnout among US neurosurgeons:
results of a nationwide survey. J Neurosurg2015;123:161-73.
doi:10.3171/2014.12.JNS141348
49 Block L, Wu AW, Feldman L, Yeh HC, Desai SV. Residency schedule,
burnout and patient care among rst-year residents. Postgrad Med
J2013;89:495-500. doi:10.1136/postgradmedj-2012-131743
50 Ochoa P. Impact of Burnout on Organizational Outcomes, the
Influence of Legal Demands: The Case of Ecuadorian Physicians.
Front Psychol2018;9:662-62. doi:10.3389/fpsyg.2018.00662
51 Pei P, Lin G, Li G, Zhu Y, Xi X. The association between doctors’
presenteeism and job burnout: a cross-sectional sur vey study in
China. BMC Health Serv Res2020;20:715. doi:10.1186/s12913-
020-05593-9
52 Shanafelt TD, Gradishar WJ, Kosty M, et al. Burnout and career
satisfaction among US oncologists. J Clin Oncol2014;32:678-86.
doi:10.1200/JCO.2013.51.8480
53 Sinsky C, Colligan L, Li L, et al. Allocation of physician time in
ambulatory practice: a time and motion study in 4 specialties. Ann
Intern Med2016;165:753-60. doi:10.7326/M16-0961
54 Yuguero O, Marsal JR, Buti M, Esquerda M, Soler-González J.
Descriptive study of association between quality of care and
empathy and burnout in primary care. BMC Med Ethics2017;18:54.
doi:10.1186/s12910-017-0214-9
55 Pit SW, Hansen V. Factors influencing early retirement
intentions in Australian rural general practitioners. Occup Med
(Lond)2014;64:297-304. doi:10.1093/occmed/kqu028
56 Coleman DM, Money SR, Meltzer AJ, et al, SVS Wellness Task Force.
Vascular surgeon wellness and burnout: a report from the Society for
Vascular Surgery Wellness Task Force. J Vasc Surg2021;73:1841-
1850.e3. doi:10.1016/j.jvs.2020.10.065
57 Dinibutun SR. Factors associated with burnout among physicians:
an evaluation during a period of COVID-19 pandemic. J Healthc
Leadersh2020;12:85-94. doi:10.2147/JHL.S270440
58 Kelker H, Yoder K, Musey PJr, et al. Prospective study of emergency
medicine provider wellness across ten academic and community
hospitals during the initial surge of the COVID-19 pandemic. BMC
Emerg Med2021;21:36. doi:10.1186/s12873-021-00425-3
59 Makara-Studzińska M, Wontorczyk A, Izydorczyk B. Stress
and occupational burnout in a population of Polish doctors -
Organizational-professional and non-professional-social predictors.
Ann Agric Environ Med2020;27:456-68. doi:10.26444/
aaem/110846
60 Kaiser S, Patras J, Martinussen M. Linking interprofessional
work to outcomes for employees: a meta-analysis. Res Nurs
Health2018;41:265-80. doi:10.1002/nur.21858
61 Panagioti M, Stokes J, Esmail A, et al. Multimorbidity and patient
safety incidents in primary care: a systematic review and meta-
analysis. PLoS One2015;10:e0135947. doi:10.1371/journal.
pone.0135947
62 Parliament UK. House of Commons Health and Social Care
Committee. Workforce burnout and resilience in the NHS and social
care. Second Report of Session 2021-22, HC 22: Published on 8
June 2021. https://committees.parliament.uk/publications/6158/
documents/68766/default/
63 Yates SW. Physician stress and burnout. Am J Med2020;133:160-4.
doi:10.1016/j.amjmed.2019.08.034
64 Hodkinson A, Tyler N, Ashcro DM, et al. Preventable medication harm
across health care settings: a systematic review and meta-analysis.
BMC Med2020;18:313. doi:10.1186/s12916-020-01774-9
65 Panagioti M, Khan K, Keers RN, et al. Prevalence, severity, and nature
of preventable patient harm across medical care settings: systematic
review and meta-analysis. BMJ2019;366:l4185. doi:10.1136/bmj.
l4185
66 Bates DW, Spell N, Cullen DJ, et al, Adverse Drug Events
Prevention Study Group. The costs of adverse drug events in
hospitalized patients. JAMA1997;277:307-11. doi:10.1001/
jama.1997.03540280045032
67 Estimating the attributable cost of physician burnout in the United
States. AnnIntMed2019;170:784-90. doi:10.7326/m18-
1422%m31132791.
68 Kaushik D. COVID-19 and health care workers burnout: a call for
global action. EClinicalMedicine2021;35:100808. doi:10.1016/j.
eclinm.2021.100808
69 Shanafelt TD, Boone S, Tan L, 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
70 Scanlan JN, Still M. Relationships between burnout, turnover
intention, job satisfaction, job demands and job resources for mental
health personnel in an Australian mental health service. BMC Health
Serv Res2019;19:62. doi:10.1186/s12913-018-3841-z
71 Shanafelt TD, Dyrbye LN, West CP. Addressing physician burnout:
the way forward. JAMA2017;317:901-2. doi:10.1001/
jama.2017.0076
72 Kirch DG, Petelle K. Addressing the physician shortage: the peril
of ignoring demography. JAMA2017;317:1947-8. doi:10.1001/
jama.2017.2714
73 West CP, Dyrbye LN, Erwin PJ, Shanafelt TD. Interventions to
prevent and reduce physician burnout: a systematic review and
meta-analysis. Lancet2016;388:2272-81. doi:10.1016/S0140-
6736(16)31279-X
74 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
75 Van Gerven E, Vander Elst T, Vandenbroeck S, et al. Increased
risk of burnout for physicians and nurses involved in a patient
safety incident. Med Care2016;54:937-43. doi:10.1097/
MLR.0000000000000582
76 Hartzband P, Groopman J. Physician burnout, interrupted. N Engl J
Med2020;382:2485-7. doi:10.1056/NEJMp2003149
77 Smaggus A. Safety-I, Safety-II and burnout: how complexity science
can help clinician wellness. BMJ Qual Saf2019;28:667-71.
doi:10.1136/bmjqs-2018-009147
78 National Academy of Medicine (NAM) Annual Reports. 2019. https://
nam.edu/wp-content/uploads/2020/06/NAM-Annual-Report-2019.
pdf
79 Coggon D, Rose GA, Barker DJP. Epidemiology for the uninitiated.BMJ
Books, 2003.
80 McAuley L, Pham B, Tugwell P, Moher D. Does the inclusion of grey
literature influence estimates of intervention eectiveness reported
in meta-analyses?Lancet2000;356:1228-31. doi:10.1016/S0140-
6736(00)02786-0
81 Sedgwick P. Bias in observational study designs: cross sectional
studies. BMJ2015;350:h1286. doi:10.1136/bmj.h1286
82 Podsako PM, MacKenzie SB, Podsako NP. Sources of method bias
in social science research and recommendations on how to control
it. Annu Rev Psychol2012;63:539-69. doi:10.1146/annurev-
psych-120710-100452
83 Gunzler DD, Perzynski AT, Carle AC. Structural Equation Modeling
for Health and Medicine.1st ed. Chapman and Hall/CRC, 2021.
doi:10.1201/9780203701133
Web appendix 1: Supplementary tables and text
on 15 September 2022 by guest. Protected by copyright.http://www.bmj.com/BMJ: first published as 10.1136/bmj-2022-070442 on 14 September 2022. Downloaded from
... Higher levels of psychological detachment are associated with higher selfcompassion (Wu et al. 2023). They are more likely to protect themselves when they encounter difficulties at work, leading to excessive negativity and indifference to work, that is, depersonalization (Hodkinson et al. 2022). Surveys conducted in the aftermath of the COVID-19 pandemic have shown a significant increase in positive reports about the nursing profession in the fight against COVID-19 (Ersan Yaman, Basaran-Acil, and Duygulu 2023), nurses were highly praised (Fontanini et al. 2021), the true value of nursing was recognised by the public (Catton 2020), and nurses' professional identity is greatly enhanced (Zhang et al. 2021). ...
Article
Full-text available
Aims To investigate the impacts of social support and psychological detachment on nurses' job burnout, as well as to validate psychological detachment's mediating effect. Design The study was conducted using a questionnaire‐based cross‐sectional design. Methods From October 2023 to March 2024, convenience sampling was used to distribute electronic questionnaires (including a general information questionnaire, the Maslach Burnout Inventory, the Psychological Detachment Scale, and the Social Support Scale) to investigate the current state of job burnout, psychological detachment, and social support among nurses. A total of 325 nurses were included in the study. The statistical analysis was performed using SPSS 29.0 software and the SPSS Process 4.1 plug‐in. Results Results showed that both social support and psychological detachment were negatively correlated with job burnout. Excluding general demographic characteristics, social support was negatively associated with job burnout through psychological detachment, where psychological detachment mediated social support and emotionally exhausting job burnout with a mediating effect of 8.93%. Conclusion Nurses' job burnout can be mitigated by both social support and psychological detachment, with psychological detachment acting as a mediation of the effect of social support. Impact Nursing managers should take measures to enhance the social support of nurses appropriately. At the same time, it is necessary to arrange work reasonably and establish a solid communication mechanism to improve nurses' psychological detachment and reduce nurses' job burnout. Patient or Public Contribution No patient or public involvement.
Chapter
Injuries and illnesses and their associated medical care are among the most frequent potentially traumatic events (PTEs) experienced by children worldwide. Following medical PTEs, up to 30% of children and parents develop persistent and impairing posttraumatic stress symptoms (PTSS). Impairment related to PTSS can be especially problematic in medically-involved children: PTSS is associated with poorer adherence, health-related quality of life, functional impairment, and greater use of healthcare services. Medical settings can be an ideal place to identify children and families who are experiencing emotional difficulties related to medical diagnoses and care. Identification of PTSS during medical care allows for providers to make timely referrals and to begin interventions. In healthcare settings, a trauma-informed approach can be essential for the ethical provision of pediatric medical care. Taking a trauma-informed approach to medical care, interventions, and screening can be integrated into standard care and offered consistently to meet each child’s and family’s needs. Based on these needs, interventions can be implemented at universal, targeted, and/or indicated levels across the peri-trauma, acute medical care, and ongoing care or discharge from care phases of medical PTEs. More research is necessary to establish the most efficacious treatments for those children who are experiencing significant PTSS related to the medical events.
Article
Full-text available
Background/Objectives: The extensive exposure of physicians to the COVID-19 pandemic has contributed to occupational stress and burnout in their daily lives. This study aimed to explore the lived experiences of intern physicians who experienced burnout during the COVID-19 pandemic and to identify potential solutions to enhance clinical practices in future pandemics. Methods: This study employed a qualitative, phenomenological study utilizing in-depth interviews. The participants were 19 first-year intern physicians from public hospitals in Thailand, selected through a purposeful sampling approach who had experienced burnout. Semi-structured interviews were conducted face-to-face and via online platforms. A thematic narrative analysis approach was used. Results: Phenomenological explorations included two parts: the first explored physicians’ workplace conditions while providing patient care, and the second focused on their proposed solutions for policy changes in clinical practices and hospital management. Four main themes in the first part were derived: (1) emotional suffering and burnout; (2) engaging with a high-intensity workplace; (3) hostile work environments; and (4) deterioration of relationships with staff and colleagues. The second part identified three main themes: (1) changes in policy of clinical practices; (2) effective hospital management; and (3) building interpersonal skills. Conclusions: The COVID-19 pandemic has exacerbated challenges faced by intern physicians, such as high-pressure working conditions, deteriorated relationships with colleagues, and ineffective management, all of which contribute to burnout. These challenges require targeted policy changes in clinical practices, effective hospital management, and building interpersonal skills. Recommendations include improved clinical practices, increased academic support, comprehensive orientation programs, effective communication, teamwork assistance, stress management, and transforming organizational culture to value physicians during internships.
Article
Emergency physicians have the highest rates of burnout among all medical specialties. There is a need for accurate and reliable burnout assessment tools to monitor changes and assess the effects of interventions. However, existing tools are typically long and/or costly. We sought to validate an abbreviated Copenhagen Burnout Inventory among emergency physicians and trainees in Canada. We conducted a planned secondary analysis of a national, cross-sectional survey of emergency physicians and trainees in Canada. Exploratory factor analysis was performed followed by confirmatory factor analysis. Kaiser’s eigenvalues rule, a scree plot, and Horn’s parallel analysis guided the number of factors to extract. Structural validity fit indices and internal consistency were compared to pre-specified cutoffs. Criterion validity was assessed compared to the full Copenhagen Burnout Inventory (burnout defined as mean ≥ 50/100). One hundred eighty-two responses were randomly split into separate cohorts for exploratory factor analysis and confirmatory factor analysis. Data were confirmed to be statistically suitable for factor analysis. Using exploratory factor analysis, a ten-item, two-factor abbreviated Copenhagen Burnout Inventory was reached after removing items based on over correlation (≥ 0.80), cross-loading (≥ 75%), and low factor loading (< 0.60). In confirmatory testing, the abbreviated inventory had a good Comparative Fit Index (0.91) though did not meet cutoffs for the remaining fit indices. Internal consistency was 0.92 (95%CI 0.90–0.95). Using a cutoff of 33/50, sensitivity was 0.99, specificity was 0.82, and area under the ROC curve was 0.86. With further validation, an abbreviated ten-item Copenhagen Burnout Inventory has potential to serve as a short, freely available burnout assessment tool among Canadian emergency physicians and trainees. This abbreviated inventory has evidence to support its internal consistency and criterion validity, albeit with inconsistent structural validity. Future validation with larger samples is required, with special attention paid to content validity, test–retest reliability, and correlation with important outcomes.
Article
Full-text available
Burnout among critical care physicians is an important issue that affects patient care and staff well-being. This study, conducted by the Korean Society of Critical Care Medicine, aimed to investigate the prevalence and associated factors of burnout among intensivists and critical care fellows in South Korea. From May to July 2019, a cross-sectional survey was conducted in 51 hospitals and 79 intensive care units offering subspecialty training in critical care medicine. Invitations were sent by email and text, and responses were collected using NownSurvey and Google Forms. Of the 502 invited participants, 253 responded (response rate: 50.4%). Significant contributing factors of burnout included being in an intensivist position (assistant professor/fellow) (odds ratio [OR], 3.916; 95% confidence interval [CI], 1.485–10.327; p = 0.006), working in a medical ICU (OR, 4.557; 95% CI, 1.745–11.900; p = 0.002), the number of stay-home night calls per month (OR, 1.070; 95% CI, 1.005–1.139; p = 0.034), and recent conflicts with colleagues (OR, 5.344; 95% CI, 1.140–25.051; p = 0.033). Similar factors were found to influence severe levels of burnout. This nationwide study indicates that a significant proportion of critical care physicians in South Korea experience burnout. Strategies to reduce overtime and workplace conflict are imperative to reduce burnout among these physicians and protect their mental health. Future research should explore targeted interventions for these specific factors.
Article
Full-text available
Background Burnout is a critical factor that can influence the quality of care that doctors provide to their patients. Previous research suggests a link between inadequate communication skills training and burnout, and various approaches to enhance communication skills have been explored as a means to address this issue. However, evidence of the effect of these approaches is lacking. The aim of this study is to assess the effect of the novel On-site Supportive Communication Training (On-site SCT) in enhancing communication skills among oncologists and thereby addressing burnout. Methods This randomized, controlled, multicenter study was conducted across three oncological departments in Denmark. Doctors were eligible if they worked in the outpatient clinic at least four days per month and provided informed consent. Doctors in the intervention group underwent a two-hour introduction followed by three full days of On-site SCT facilitated by in-house psychologists, while those in the control group continued standard practices. Pre- and post-intervention assessments on burnout (Copenhagen Burnout Inventory) were conducted, as were assessments of related constructs (job satisfaction and communication self-efficacy). Differences in pre- and post- assessments were analyzed using a paired t-test. Feasibility was assessed descriptively by comparing intervention days with planned schedule, and doctors’ satisfaction with the intervention was assessed systematically by questionnaire. Results Of 101 screened doctors, 89 (88%) consented and were randomized. 65% were female, and the mean age was 46 (range 27 to 75). Due to nine exclusions, data from 39 doctors in the intervention group and 41 doctors in the control group were available for analysis. At baseline, doctors exhibited lower levels of burnout than reported in international literature. No statistically significant improvements in burnout (p > 0.05) were demonstrated post-intervention. Despite non-significant changes, the doctors reported an improvement in communication self-efficacy. The program showed high feasibility and received positive feedback from participating doctors. Conclusions Our findings caution against assuming a causal relationship between short-term interventions and a complex phenomenon like burnout. On-site SCT demonstrated high feasibility, participation rate and acceptance. This underscores its potential value in clinical settings. Consequently, On-site SCT will be implemented at the Department of Oncology, Vejle University Hospital, to facilitate further refinement based on ongoing feedback and to explore long-term outcomes. Trial registration December 2022– The Region of Southern Denmark (22/57137). April 2023– ClinicalTrials.gov (NCT05842083). April 2023– The Research Ethics Committee at the University of Southern Denmark (23/19397).
Article
Full-text available
Background Access improvement is a fundamental component of value-based healthcare as it inherently promotes quality by eliminating chokepoints, redundancies, and inefficiencies which could hinder the provisioning of timely care. The purpose of this review is to present a 12-step framework which offers healthcare organizations a practical, thematic-based foundation for thinking about access improvement. Methods This study was designed based on the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) statement. A literature search of prospective peer-reviewed publications was undertaken to identify studies pertaining to healthcare access. Articles published from January 2014 to January 2024 were included. An interpretive synthesis was then presented. Results A total of 469 peer-reviewed studies were identified. The most common diseases analyzed were related to general medicine/family practice (N = 75), surgical care (N = 51), health screening (N = 30), mental health (N = 27), cardiovascular disease (N = 17), emergency room/critical care (N = 15), and cancer (N = 7). The remaining 247 studies (53%) did not specifically report on any specialization. The core themes could be broadly categorized into the following: workforce adequacy, patient experience, physical space utilization, template optimization, scheduling efficiency, process standardization, cost transparency, physician engagement, and data analytics. Sixty publications (13%) focused at least in part on equity issues, structural racism, and/or implicit bias; and 25 publications (5%) addressed disparities in education, training, and/or technical literacy. Seventy-three publications (16%) focused either completely or in part on digital health as a means of access improvement. Conclusion Based on this systematic review, a 12-step thematically based framework for approaching access improvement in healthcare was developed.
Article
A BSTRACT Background Primary healthcare workforce (PHCW) should be suffered from less burnout after the termination of the COVID-19 response. The current study compared the changes in the three dimensions of burnout in PHCW during and after the response. Methods Two convenience-sampling, online, cross-sectional questionnaire studies were conducted in local PHCW. Studies were administered in April 2022 and 8 months after the termination. Burnout was measured by the Chinese version of 15-item Maslach Burnout Inventory-General Survey, which assesses three dimensions: emotional exhaustion (EE), depersonalization (DP), and reduced personal accomplishment (reduced PA). The primary outcome was the prevalence of its three dimensions. Data on demographics, work environment, health conditions, and outlets for stress reduction were collected. We compared burnout and associated factors between the study periods by using Student’s t -test, Chi test, or Mann‒Whitney test. The association between factors and burnout was identified by a logistic regression model. Results In total, 162 and 200 participants completed the questionnaires during and after the response. No significant differences in demographics, including age, gender, education attainment, work experience, or seniority level were observed. The prevalence of burnout-free status was similar (9.9% vs 12.5%, P = 0.434) between the two periods. Severe burnout decreased from 45.7% to 0%, and moderate burnout nearly doubled after the response. The prevalence of EE decreased the most, by 55.0%, followed by that of DP, which decreased by 38.4% (all P < 0.001); however, there was no difference in the prevalence of reduced PA (77.2% vs 74.5%, P = 0.557). Logistic regression showed that promotion and alcohol consumption decreased the risk of EE. Considering leaving the job increases the risk of DP, a lower self-evaluated health score and more distress were associated with EE and DP. Exercise decreased the risk of reduced PA. Conclusions Inconsistent with the hypothesis, we found that severe burnout decreased, but moderate burnout increased in PHCWs after the response. EE and DP decreased more, but reduced PA had no change. Incentives, improved self-evaluated health conditions, alcohol consumption, and exercise ameliorate burnout. Healthcare policy makers must consider multiple effective ways to mitigate burnout in the post-epidemic era.
Article
Objetivo: Avaliar a incidência e os principais fatores de risco para o burnout em profissionais de saúde. Metodologia: Corresponde a uma revisão sistemática da literatura existente nas bases de dados científicas MEDLINE, EMBASE e Biblioteca Virtual em Saúde, mediante uma abordagem qualitativa, realizada durante o mês de novembro de 2024, através de um processo de busca direcionada utilizando combinações de descritores DeCS/MeSH com a inclusão do operador “and” entre os termos, de acordo com o representado: "Burnout" and "Health Care Professional" e "Burnout" and "Profissionais de Saúde". Resultados e Discussão: Após o processo de pesquisa dos estudos nas bases de dados elencadas, de acordo com os filtros utilizados, foram selecionados 14 estudos para participarem do embasamento teórico desta pesquisa científica. Esses estudos foram escolhidos de acordo com critérios de exclusão e inclusão, além de serem submetidos, posteriormente, por uma etapa de avaliação e sistematização dos dados, visando definir a incidência de burnout em profissionais que trabalham na área da saúde. Considerações Finais: Os profissionais de saúde enfrentam altos índices de exaustão mental, caracterizada pelo burnout, principalmente se trabalham em UTI, em emergência e em cuidados paliativos, devido a atuação com pacientes críticos, demanda excessiva e desvalorização profissional.
Article
Full-text available
Introduction The COVID-19 pandemic had a negative effect on population mental health. Medical students may have been particularly affected, whom prevalence of mental health conditions was already high before the pandemic hit, due to the difficult and stressful academic programme. In Northern Ireland specifically, mental well-being levels are the lowest across the UK; however limited research exists examining the medical student cohort. This study explores Northern Irish medical students’ perceptions on how the pandemic affected their mental health, their progress within medical education and perceived barriers to accessing support services in Northern Ireland. Methods A qualitative study of phenomenological design involving 15 in-depth semi-structured interviews. The interviews were conducted amongst individuals who were 1st-4th year medical students when the pandemic was officially declared in Northern Ireland in March 2020. The interviews were transcribed, and thematic analysis was carried out using NVivo V12 qualitative data analysis software. Results Results demonstrated the COVID-19 pandemic had a considerable negative impact on participants’ mental health; a variety of interlinked social, individual and/or psychological and organisational factors led to increased levels of stress, anxiety and depression. This had a secondary negative impact on participants’ medical education progress through reducing motivation, causing burnout and impostor syndrome. Unexpectedly; there were some perceived positive outcomes, including improved appreciation for work-life balance and resilience. Participants reported various barriers to seeking help amongst this difficult time period; also categorizable into social, individual and/or psychological and organisational factors, for example; stigmatisation, fear and perfectionistic tendencies. Discussion and conclusion There is a pressing demand for heightened support availability, personally tailored mental health assistance and an effort to reduce mental health stigma in Northern Ireland. This study highlights the complex multifactorial nature of mental health. Medical schools must provide additional services to protect well-being during particularly challenging periods and dismantle the barriers preventing individuals from accessing vital support.
Article
Full-text available
Objective: To estimate the prevalence of burnout among primary health-care professionals in low- and middle-income countries and to identify factors associated with burnout. Methods: We systematically searched nine databases up to February 2022 to identify studies investigating burnout in primary health-care professionals in low- and middle-income countries. There were no language limitations and we included observational studies. Two independent reviewers completed screening, study selection, data extraction and quality appraisal. Random-effects meta-analysis was used to estimate overall burnout prevalence as assessed using the Maslach Burnout Inventory subscales of emotional exhaustion, depersonalization and personal accomplishment. We narratively report factors associated with burnout. Findings: The search returned 1568 articles. After selection, 60 studies from 20 countries were included in the narrative review and 31 were included in the meta-analysis. Three studies collected data during the coronavirus disease 2019 pandemic but provided limited evidence on the impact of the disease on burnout. The overall single-point prevalence of burnout ranged from 2.5% to 87.9% (43 studies). In the meta-analysis (31 studies), the pooled prevalence of a high level of emotional exhaustion was 28.1% (95% confidence interval, CI: 21.5-33.5), a high level of depersonalization was 16.4% (95% CI: 10.1-22.9) and a high level of reduced personal accomplishment was 31.9% (95% CI: 21.7-39.1). Conclusion: The substantial prevalence of burnout among primary health-care professionals in low- and middle-income countries has implications for patient safety, care quality and workforce planning. Further cross-sectional studies are needed to help identify evidence-based solutions, particularly in Africa and South-East Asia.
Article
Full-text available
Poor wellbeing and burnout are significant issues among health-care professionals (HCPs) and may contribute to unsafe practice. In this exploratory study, we aimed to: provide the first investigation of the combined and unique influences of these psychological factors in predicting safe practice; confirm the role played by mindfulness in relation to wellbeing, burnout and safe practice; and investigate whether values and self-compassion predict additional variability above and beyond mindfulness skills. Ninety-eight NHS staff completed measures of wellbeing, burnout, perceived safety of practice, mindfulness, values and self-compassion. Practitioners with higher perceived safety of practice reported higher levels of mindfulness, but not values or self-compassion, particularly lower experiential avoidance and nonjudgmental attitude toward difficult thoughts. Mindfulness explained significant variability in psychological distress (20%), emotional exhaustion (8%), cognitive weariness (10%), patient safety related to oneself (7%), and related to work (8%). Values (obstruction) added unique variance for psychological distress (12%) and physical fatigue (10%). Moreover, self-compassion explained a small yet significant portion of variability in emotional exhaustion. These preliminary findings suggest that mindfulness processes may be associated with perceived safety of practice. The results also indicate that mindfulness-based interventions for HCPs may benefit from the inclusion of values-based action components and self-compassion practices.
Article
Full-text available
The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
Article
Full-text available
The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
Article
Full-text available
Abstract Background While COVID-19 has had far-reaching consequences on society and health care providers, there is a paucity of research exploring frontline emergency medicine (EM) provider wellness over the course of a pandemic. The objective of this study was to assess the well-being, resilience, burnout, and wellness factors and needs of EM physicians and advanced practice providers (e.g., nurse practitioners and physician assistants; APPs) during the initial phase of the COVID-19 pandemic. Methods A descriptive, prospective, cohort survey study of EM physicians and APPs was performed across ten emergency departments in a single state, including academic and community settings. Participants were recruited via email to complete four weekly, voluntary, anonymous questionnaires comprised of customized and validated tools for assessing wellness (Well Being Index), burnout (Physician Work Life Study item), and resilience (Brief Resilience Scale) during the initial acceleration phase of COVID-19. Univariate and multivariate analysis with Chi-squared, Fisher’s Exact, and logistic regression was performed. Results Of 213 eligible participants, response rates ranged from 31 to 53% over four weeks. Women comprised 54 to 60% of responses. Nonrespondent characteristics were similar to respondents. Concern for personal safety decreased from 85 to 61% (p
Article
Full-text available
Introduction Physician burnout has been linked to medical errors, decreased patient satisfaction, and reduced career longevity. In light of the increasing prevalence of cardiovascular disease, vascular surgeon burnout presents a legitimate public health concern due to the impact on the adequacy of the vascular surgery workforce. The aims of this study were to define the prevalence of burnout amongst practicing vascular surgeons and identify factors that contribute to burnout to facilitate future SVS initiatives to mitigate this crisis. Methods In 2018, active SVS members were surveyed electronically and confidentially using the Maslach Burnout Inventory (MBI). The survey was tailored to explore specialty-specific issues, and to capture demographic and practice-related characteristics. Emotional exhaustion (EE) and depersonalization (DP) were analyzed as dimensions of burnout. Consistent with convention, surgeons with a high score on the depersonalization and/or emotional exhaustion sub-scales of the MBI were considered to have at least one manifestation of professional burnout. Risk factors associated with symptoms of burnout were identified using bivariate analyses (Chi-square, Kruskal-Wallis). Multivariate logistic regression models were developed to identify independent risk factors for burnout. Results 960 of 2905 active SVS members responded to the survey (34% participation rate). After excluding retired surgeons and incomplete submissions, responses from 872 practicing vascular surgeons were analyzed. Mean age was 49.7 (±SD 11.0) years; the majority of respondents (81%) were male. Primary practice settings were academic (40%), community practice (41%), Veteran’s hospital (3.3%), active military practice (1.5%) or ‘other’. Years in practice averaged 15.7 (±SD 11.7). Overall, 41% of respondents had at least one symptoms of burnout (i.e. high emotional exhaustion and/or high depersonalization), 37% endorsed symptoms of depression in the past month and 8% indicated they had considered suicide in the last 12 months. In unadjusted analysis, factors significantly associated with burnout (P<0.05) included clinical work hours, on-call frequency, electronic health record (EHR)/documentation requirements, work-home conflict, and work-related physical pain. On multivariate analysis, age, work-related physical pain, and work home conflict were independent predictors for burnout. Conclusions Symptoms of burnout and depression are common among vascular surgeons. Advancing age, work-related physical pain and work-home conflict are independent predictors for burnout among vascular surgeons. Efforts to promote vascular surgeon well-being must address specialty specific challenges including the high prevalence of work-home conflict and occupational factors that contribute to work-related pain.
Article
Objective To evaluate the prevalence of burnout and satisfaction with work-life integration (WLI) among physicians and US workers in 2020 relative to 2011, 2014, and 2017. Methods Between November 20, 2020, and March 23, 2021, we surveyed US physicians and a probability-based sample of the US working population using methods similar to our prior studies. Burnout and WLI were measured using standard tools. Information about specific work-related COVID-19 experiences was collected. Results There were 7510 physicians who participated in the survey. Nonresponder analysis suggested that participants were representative of US physicians. Mean emotional exhaustion and depersonalization scores were lower in 2020 than in 2017, 2014, and 2011 (all P<.001). However, emotional exhaustion and depersonalization scores did not improve in specialties most heavily affected by COVID-19. Overall, 38.2% of physicians reported 1 or more symptoms of burnout in 2020 compared with 43.9% in 2017, 54.4% in 2014, and 45.5% in 2011 (all P<.001). Providing care without adequate personal protective equipment (odds ratio [OR], 1.53; 95% CI, 1.35 to 1.72) and having suffered disruptive economic consequences due to COVID-19 (OR, 1.49; 95% CI, 1.32 to 1.69) were independently associated with risk of burnout. On multivariable analysis, physicians were at increased risk for burnout (OR, 1.41; 95% CI, 1.25 to 1.58) and were less likely to be satisfied with WLI (OR, 0.71; 95% CI, 0.64 to 0.79) than other working US adults. Conclusion Burnout and satisfaction with WLI among US physicians improved between 2017 and 2020. The impact of the COVID-19 pandemic on physicians varies on the basis of professional characteristics and experiences. Physicians remain at increased risk for burnout relative to workers in other fields.