The Subjective Causal Impact of COVID-19 on Graduate Medical Education and Recommendations for Bridging the Educational Gap: A Global Cross-sectional Study

Abstract

Background: COVID-19 generated a system-wide shock causing an unbalanced equilibrium be- tween producing adequately trained physicians and meeting extraordinary operational needs. Pre- vious studies report the experience of surgical residents during COVID-19 on a regional level. This study measures the learning losses causally associated with the re-deployment of highly special- ized medical professionals to the care of COVID-19 patients, while we systematically investigate proposed remedial strategies.
Methods: We administered an online cross-sectional survey in 67 countries capturing training inputs (i.e., surgeries and seminars residents participated in) before and during the pandemic and retrieved residents’ expected learning outputs, career prospects and recommended remedial mea- sures for learning losses. We compared responses of residents working in (treatment group) and out (control group) of hospitals with COVID-19 patients.
Results: The analysis included 432 plastic surgery residents who were in training during the pandemic. Most of the learning losses were found in COVID-19 hospitals with 37% and 16% loss of surgeries and seminars, respectively, per week. Moreover, 74%, 44%, and 55% of residents ex- pected their surgical skill, scientific knowledge, and overall competence, respectively, to be lower than those of residents who graduated prior to COVID. Residents in COVID-19 hospitals reported participating in significantly (p < 0.001) fewer surgeries and having significantly (p < 0.001) lower surgical skill relative to those not in COVID-19 hospitals.
Conclusions: The perceived lower competence and the fall-off in surgical skill and scientific knowl- edge among future surgeons suggest that healthcare systems globally may have limited capacity to perform delicate and costly procedures in the future.

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The Subjective Causal Impact of COVID-19 on Graduate
Medical Education and Recommendations for Bridging
the Educational Gap: A Global Cross-sectional Study
Sofoklis Goulas
Brookings Institution
Georgios Karamitros (  pmd100116@uoi.gr )
University of Ioannina
Research Article
Keywords: COVID-19, Graduate Medical Education, Plastic Surgery, Learning Losses, Sub- jective Causal
Inference
Posted Date: June 1st, 2023
DOI: https://doi.org/10.21203/rs.3.rs-3001293/v1
License:   This work is licensed under a Creative Commons Attribution 4.0 International License.  Read Full
License

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Abstract
Background: COVID-19 generated a system-wide shock causing an unbalanced equilibrium be- tween producing
adequately trained physicians and meeting extraordinary operational needs. Pre- vious studies report the
experience of surgical residents during COVID-19 on a regional level. This study measures the learning losses
causally associated with the re-deployment of highly special- ized medical professionals to the care of COVID-19
patients, while we systematically investigate proposed remedial strategies.
Methods: We administered an online cross-sectional survey in 67 countries capturing training inputs (i.e.,
surgeries and seminars residents participated in) before and during the pandemic and retrieved residents’
expected learning outputs, career prospects and recommended remedial mea- sures for learning losses. We
compared responses of residents working in (treatment group) and out (control group) of hospitals with COVID-
19 patients.
Results: The analysis included 432 plastic surgery residents who were in training during the pandemic. Most of
the learning losses were found in COVID-19 hospitals with 37% and 16% loss of surgeries and seminars,
respectively, per week. Moreover, 74%, 44%, and 55% of residents ex- pected their surgical skill, scientic
knowledge, and overall competence, respectively, to be lower than those of residents who graduated prior to
COVID. Residents in COVID-19 hospitals reported participating in signicantly (p
<
0.001) fewer surgeries and
having signicantly (p
<
0.001) lower surgical skill relative to those not in COVID-19 hospitals.
Conclusions: The perceived lower competence and the fall-off in surgical skill and scientic knowl- edge among
future surgeons suggest that healthcare systems globally may have limited capacity to perform delicate and
costly procedures in the future.
Key Messages
Ourresultsfromaninternationalsurveyof432plasticsurgeryresidentsillustratethesigni-
cantnegativeimpactofCOVID-19,asasystem-wideshock,ongraduatemedicaleducation.
The learning losses among surgery residents suggest that healthcare systems globally might have limited
capacity to perform delicate and costly procedures in the future.
Residents reportplanningtopursue furtherclinicaltrainingto mitigatetheirlearninglosses.
The resident-recommended reform policies are consistent with a Competency-Based Time- Variant Graduate
Medical Education (CB-TV GME) model.
Our subjective causal inference strategy serves as a blueprint for other contexts where ad- ministrative or
experimental data are limited.
1. Introduction
By May 15th, 2022, 1 million people have lost their lives in the US alone since the COVID- 19 pandemic started [1].
The public health emergency created operational pressure on healthcare systems around the world, re-set care
provision priorities, and derailed Graduate Medical Education (GME) [2, 3]. Early studies documented the
changes in resident training during the pandemic [4, 5, 6, 7]. Residents’ training, in surgical specialties in

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particular, has been severely held back by the pandemic [8, 9, 10, 11, 12, 13, 14]. Previous studies, although
informative, may not depict the learning losses causally associated with the re-deployment of hospital resources
and highly specialized medical professionals to the care of COVID-19 patients. We conduct the rst global study
on the causal impact of the COVID-19 pandemic on residents of a highly specialized surgical specialty: plastic,
reconstructive, and aesthetic surgery.
We focus on plastic surgery residents for a number of reasons. First, the learning losses of plastic surgery
residents due to the COVID-19 disruptions may be comparable to those of residents in other surgical specialties.
Training inputs and core competences such as procedural skills and medical knowledge are similar across
specialties (Table 1) [15]. For example, the Accreditation Council for Graduate Medical Education (ACGME)
expects residents, regardless their specialty, to obtain competency in six core competencies.
Second, plastic surgeons contribute to patient care well beyond aesthetic or reconstructive con- sultation [16, 17].
Similar to other physicians, plastic surgeons play an integral role in healthcare systems as their input is often
crucial in treatment design and generates a substantial economic impact [18]. By targeting a single specialty we
achieve a homogeneous sample of respondents, al- lowing us to infer the COVID-related learning losses of
residents with comparable baseline medical background and comparable training expectations and professional
aspirations.
So far, the experiences of plastic surgery residents during the pandemic have been investigated non-causally and
only at a regional level [19, 20, 21, 22, 23, 24, 25]. Policy-makers and medical education leaders around the world
rely on comparisons with national and international standards to advocate for policy and curriculum reforms.
Single-country studies feature a more homogeneous sampled population allowing for a high degree of internal
validity but are limited in the insights they can provide to non-studied populations (i.e., limited external validity)
[26, 27].
Our study is the rst to mobilize national and international resident networks in so many countries to understand
the consequences of COVID-19 for graduate medical education under a unied research methodology that gets
as close as possible to causality. For example, our methodology adjusts for reported pre-pandemic levels of
training inputs and provides a control
group of residents, which none of the previous studies features. This allows the fair comparison of the impact of
COVID-19 on training inputs and outputs across countries. To the best of our knowledge, this is the rst
international study to evaluate residents’ perceptions on changes in learning inputs and expected outputs during
the pandemic.
Our methodology implements a causal inference framework to identify the component of train- ing disruption
associated with re-deployment of resources and personnel to the care of COVID-19 patients. The objective is to
account for contemporaneous training disruptions in healthcare sys- tems that did not treat COVID-19 patients.
2 Methods
2.1 Subjective Causal Identication Strategy

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Our 37-question survey was conducted automatically through an online link in English between January 10th and
February 6th, 2022.The timing of our survey captured roughly two years of pandemic experience.Given that prior
pandemics lasted 1-2 years, our study provides a holistic view of the impact of COVID-19 on graduate medical
education [28].We recruited the help of the International Society for Aesthetic Plastic Surgery (ISAPS) to reach
plastic surgery residents aroundtheworld.ISAPSistheleadingprofessionalbodyforboard-
certiedplasticsurgeonswitha network of residents in over 100 countries.To our knowledge, no societies in
other specialties with comparable network currently exist.The survey was disseminated by 63 associations of
plastic surgeons, including ISAPS, to their resident members via email and social media.The survey
questionsandthedisseminationstrategyareprovidedintheSupplementaryInformationAppendix.This project
was approved by the Institutional Review Board (IRB) at Stanford University.
2.2 StudyDesign
Thesurveydesignfollowsacausalinferenceframework.RecoveringtheimpactofCOVID-19at
theresidentlevelentailscomparisonoftheresident’soutcomesintwoalternatestatesoftheworld: with the
pandemic and without.With standard data on realizations, a given resident is observed inonlyone state of the
world (in our case,
COVID-19=1
).The alternate outcomes are counter- factual and unobserved.A large
econometric and statistics literature studies the identication of counterfactual outcomes from realized data
[29,30].
WefollowAucejoetal.indirectlyaskingindividualsfortheirexpectedoutcomeswithand
without COVID-19 [31].From the collected data, we directly calculate the resident-
level
subjective
treatmenteffect.Ourapproachbuildsonagrowingliteraturethatusessubjectiveexpectationsto
understand decision-making under uncertainty [32,33,34,35].The soundness of our approach
reliesonthekeyassumptionthatresidentshavewell-formedexpectationsforoutcomesinboth
therealizedandthecounterfactualstate.
Plastic surgery residents who did not work in hospitals that treated COVID-19 patients serve as the control group
for residents in hospitals with COVID-19 patients.We consider two groups of COVID-impacted residents:(1)
residents in hospitals with COVID-19 patients who did not work in COVID-19 wards and (2) residents in hospitals
with COVID-19 patients who worked in COVID-19 wards.
2.3 Outcomes
Ourstudyhastwoprimarysetsofoutcomes:thetraininginputsandtheexpectedtrainingoutputs. Inputs
include surgeries residents participated or scrubbed in, seminar or lectures attended, and independent
study.Outputs include surgical skill, scientic knowledge, overall competence, and future professional prospects.
Residents reported the number of surgeries and seminars per week or month before and during the pandemic.
We calculate the percentage change before and during the pandemic. Residents also reported the magnitude of
change in their study time before and during the pandemic. We create a score variable that takes the values -1,
-0.5, 0, 0.5, and 1 for the responses
decreased signicantly
,
decreasedslightly
,
didnotchange
,
increasedslightly
,

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and
increasedsignicantly
, respectively. We also create a binary variable that takes the value 1
when the response was
decreased slightly
or
decreasedsignicantly
. Another binary variable captures the
responses
increased slightly
and
increasedsignicantly
.
We asked residents whether the impact of the pandemic on their surgical skill and scientic knowledge has been
signicantly negative
,
slightly negative
,
zero
,
slightly positive
, or
signicantlypositive
. We also asked residents
whether they expect, in the absence of any remedial measures, the pandemic would make them
signicantlyless
,
slightlyless
,
equally
,
slightlymore
, or
signicantlymore
competentcomparedwithresidentswhodidnotfacethepandemicduringtheirresidency.
For the outputs of surgical skill, scientic knowledge, and overall competence, we construct three variables. The
rst is a score variable that assigns the values -1, -0.5, 0, 0.5, and 1 for the responses
signicantly less/negative
,
slightly less/negative
,
no impact
,
slightly more/positive
, and
signicantlymore/positiveimpact
, respectively. The
second variable is binary and takes the value one when the respondent replied slightly or signicantly
less/negative impact. The third variable is also binary and takes the value one when the respondent replied
slightly or signicantly more/positive impact. Respondents who reported slightly or signicantly lower
competence were asked whether they anticipate an impact on their professional future and development. We
create a binary variable that takes the value one when the participant replied probably or denitely yes. We also
asked residents who reported lower competence than plastic surgeons before them the reasons that contributed
to their responses. We create a binary variable for each of the reasons provided for reported lower overall
competence. Those variables allow us to causally attribute reported lower competence to pandemic-related and
non-pandemic-related justications.
2.4 StatisticalAnalysis
Ourmainanalyticstrategyisasimple-differencesmodelthatcompareschangesinlearninginputs
andexpectedoutputsbeforeandduringthepandemicofresidentsinhospitalswithCOVID- 19 patients and
those in hospitals without (specication (1) in the Supplementary Information Appendix).This approach lters
out pandemic-related inuences on residents across all hospitals.For instance, some plastic surgery procedures
may have been postponed across all hospitals duringthepandemic,regardlessofwhethertheytreatedCOVID-
19cases[36].
Weusemultivariateregressionmodelsforcontinuousoutcomes.Forbinaryoutcomes,weuse multivariate linear
probability models.All models include adjustments for gender, whether the resident has dependents, and the
different levels of training program quality.1 We directly asked respondents whether they believe that their
training program prepares competent plastic surgeons.2 All analyses use heteroskedasticity-robust standard
errors. Our analysis relies on the assumption that had the pandemic not occurred, the learning inputs and
outputs of residents in hospitals that treated COVID-19 patients would have been comparable to those of
residents in hospitals that did not treat COVID-19 patients.
The association between changes in learning inputs and expected learning outputs during the
pandemicwasalsoinvestigated.Weimplementedmodelswithpairwiseinteractiontermsbetween
indicatorsforwhetherresidentsworkedinCOVIDhospitals/wardsandchangesoflearninginputs during the

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pandemic (specication (2) in the Supplementary Information Appendix).We use linear models for ease of
interpretation of interaction terms, as is standard practice in differences analyses [37].
1TableS3presentsestimateswhenwedonotcontrolforreportedtrainingprogramquality.
2Thisquestionisintendedtoinferprogramqualityregardlessofthepandemic.
The Supplementary Information Appendix offers several heterogeneity analyses on the differen- tial impact of
the pandemic on residents in hospitals with COVID-19 patients by year of training, quality of training program,
hospital type, gender, whether the resident has dependents, whether the resident has prior experience in plastic
surgery, and number of surgeries and seminars prior to the pandemic.
3 Results
3.1 Demographics and Training Settings
Theoverallsampleincluded432respondentsfrom67countries(Table1).Theresponseratecould not be
calculated because the number of plastic surgery residents who were in training during the pandemic was
unknown and the methods of distribution precluded calculation of the respondent denominator.Table 1presents
summary statistics of characteristics of participants and their training settings.Ninety percent of respondents
worked in a hospital that treated COVID-19 patients, while 50% of those were asked to work in a COVID-19
ward.Males represent 62% of respondents.The majority (61%) of respondents are non-Hispanic white.The
average age is 32
years.Roughlyonethird(31%)ofrespondentshavedependents.Roughly17%ofrespondentsare international
medical school graduates. Sixty-three percent have prior general surgery experience of up to 2 years, while
approximately 42% of residents have plastic surgery training prior to their residency. The average program
duration is 4.8 years. Our sampled residents are roughly equally distributed in PGY 1 through 5+.
Regardinghospitaltype,58%ofrespondentsworkinuniversityhospitals.TheChi-squaretests of independence
show that university hospitals were more likely to treat COVID-19 patients.At the same time, plastic surgery
residents working in community, tertiary, or military hospitals are signicantlymorelikelytobere-
deployedinthecareofCOVID-19patientsthantheircolleagues in university or private hospitals.
Wendthatroughly61%ofparticipantsaresatisedwiththequalityoftheirtrainingprogram. Chi-
squaretestsrevealattendingprogramswithlowersatisfactionratingsissignicantlyassociated with greater
likelihood of being re-assigned in COVID-19 wards.
3.2 LearningInputs
The top panel of Table2 reports the impact of COVID-19 on residents’ learning inputs.Wend a 37% (
P <
0
.
01)
and a 16% (
P <
0
.
05) decrease in surgeries and seminars, respectively, across all respondents.Residents who
worked in hospitals with COVID-19 patients but not in COVIDwardsandthosewhoworkedinCOVID-
19wardsreportapercentagedecrease(increase) in surgeries (seminars) of 43% (33%) and 41% (23%),
respectively, compared with the control group.Only the differences in surgeries participated in were statistically

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signicant (
P <
0
.
05).ThecontrolgroupofresidentswhoworkedinhospitalsthatdidnottreatCOVID-
19patientsreport
a2%increaseinthenumberofsurgeriestheyparticipated/scrubbedinanda39%decreaseinthe number of
seminars attended.Hospitals treating COVID-19 patients during the pandemic might havere-
directednecessarypersonnelforoperations,suchasnursingstaff,tothecareofCOVID-19patients.As a result,
their capacity to perform surgical procedures during the pandemic may have been limited relative to hospitals
that did not receive COVID-19 patients.
Changes in independent study time during the pandemic seem to be insubstantial across the entire sample.
Among control group residents in hospitals without COVID-19 patients, a slightly
higherpercentagereportlessstudytimethanthepercentagereportingincreasedstudytimeduring the
pandemic, suggesting decreased study efforts on average.We nd that residents in hospitals withCOVID-
19patients,regardlessofhavingworkedinCOVIDwards,aremorelikelytoreport increased study efforts
compared with the control group, but the estimates are imprecise.
3.3 LearningOutputs
ThemiddlepanelofTable2 presentstheestimatedimpactofthepandemicontraininginputs and on expected
outputs, when adjusting for pandemic shocks across all hospitals, regardless of whether they treated COVID-19
patients. We nd that 74% and 44% of all participants reported
signicantlylowersurgicalskillandscienticknowledge,respectively(
P<
0
.
01).Morethan half of all residents
(55%) report having a lower overall competence compared with residents who
completedtheirtrainingbeforethepandemic(
P <
0
.
01).
We nd that residents in hospitals with COVID-19 patients are roughly 25-34% more likelyto report having lower
surgical skill due to the pandemic (
P <
0
.
01).We do not nd signicant differences in the likelihood to report
lower scientic knowledge or overall lower competence by residents in hospitals with COVID-19 patients
compared with residents in hospitals without.
Two thirds (67%) of participants anticipate their self-reported lower overall competence due
tothepandemictonegativelyimpacttheirfutureprofessionalprospects(
P<
0
.
01).Wedonotnd
the impact on future professional prospects to signicantly differ between residents in and out of hospitals that
treated COVID-19 patients.
3.4 Country-levelResults
Weestimatethechangesinlearninginputsandoutputsassociatedwithattendingatraining program in a
hospital that treats COVID-19 patients during the pandemic in each country.Our control group comprises of
residents in hospitals that did not treat COVID-19 patients during the
pandemic.TableS5providesdetailedcountry-levelestimates.Figure1 summarizeskeypatterns in the estimated
impact of COVID-19 on residents in COVID-19 hospitals in each country relativeto the control group.We focus on

Page 8/16
countries with at least ve residents in COVID-19 wards or ve residents who were not asked to work in COVID-19
wards.
We nd substantially wide variation in the impact of COVID-19 on resident training across the world.3 Residents
who were asked to work in COVID-19 wards report severe learning losses in both surgical skill and scientic
knowledge in a number of countries such as Egypt, Germany, Greece, Italy, Romania, and Turkey.Residents who
were not asked to work in COVID-19 wards
seemtoberathershieldedfromthelearninglosses,whilesuchresidentsinanumberofcountries such as
Russia, South Korea, Taiwan, and the US report learning gains during the pandemic.
3.5 OriginsofLearningLosses
The bottom panel of Table 2 shows the reported reasons associated with residents’ learning losses during the
pandemic. The most frequently cited justication for lower overall competence is the decreased number of
surgeries residents participated in (85%,
P<
0
.
01), followed by the decreased number of seminars or lectures
residents attended (60%,
P <
0
.
01).
We nd that no resident attributes his/her learning losses to justications unrelated to the pandemic.
We also investigate what drives expectations of learning losses. A learning input is found to drive an expected
output if its estimated effect is statistically signicant at
α
= 0
.
05. Panels A, B, and C of Figure 2 show to what
extent the changes in surgeries, seminars, or studying inuence expectations of lower surgical skill, lower
scientic knowledge, and lower overall competence, respectively, of residents who worked in COVID-19 hospitals
in and out of COVID-19 wards. The association between learning inputs and outputs of residents in hospitals
without COVID-19 pa- tients serve as benchmark. Panel A of Figure 2 suggests that the expectation of lower
surgical skill is driven only by the change in the number of surgeries participated in, especially among residents
in COVID hospitals who did not work in COVID wards. Panel B shows that the expectation of lower scientic
knowledge is driven primarily by the change in study time. Changes in the num- ber of surgeries also explains the
expectation of lower scientic knowledge among residents who worked in COVID hospitals but not in COVID
wards. The expectation of lower overall competence among residents in COVID hospitals but not in COVID wards
is driven by changes in all learn- ing inputs (Panel C). No learning input is found to explain the expectation of
lower competence among residents who worked in COVID wards. This nding suggests that their expectation of
lower competence may represent expressed emotion.
3.6 CountermeasuresofLearning Losses
Table 3 shows the countermeasures planned or recommended by respondents. Our results show that 65% and
25% of residents plan on pursuing a fellowship or an extension of residency, respectively. These percentages are
substantially higher than pre-pandemic trends suggested [39]. Overall, 94% of residents plan to pursue more
hands-on surgical training to counter the crisis-driven learning decits. Less than half percent of respondents
have no individual plans to mitigate their learning losses. In terms of policy measures recommended, roughly
70% and 35% of respondents propose intensive training on surgical skills or lectures on targeted topics,
respectively. More than one third and more than one quarter of participants recommended interim assessments

Page 9/16
during residency and log book requirements for board exam eligibility, respectively. Both of those
recommendations are consistent with the competency-based, time-variable GME model. More than 98% of
respondents call for policy measures, suggesting the need for system-level actions to counter learning losses.
3Figures S3-S6 in the Supplementary Information Appendix investigate the association between country-level
changes in surgeries attended, seminars, and study effort with system-wide indices of
preparedness
and
response
to the COVID-19 crisis obtained from Schiller et al (2021) [38]. We nd greater declines in learning
inputs (i.e., surgeries, seminars) and greater increases in independent study effort in countries with low
healthcare system preparedness and high levels of system response to COVID-19. Our associations are mostly
statistically imprecise.
4 Discussion
The method we use to identify the impact of COVID-19 on training inputs and outputs can benet any framework
in which competing priorities exist between operational needs and investment in training, such as GME
programs. A benet of using subjective measures of learning outputs is that they constitute a leading indicator
of training quality, program satisfaction and trainee fatigue, and may closely predict subsequent individual
success and system resilience.
We cannot afford for the COVID crisis to go to waste. The pandemic has been an external system shock, similar
to which others might appear in the future. On one hand, the American Board of Medical Specialties (ABMS) and
the ACGME have recognized the challenges in time and volume based GMEs the COVID crisis revealed and the
need for reforms [40]. On the other hand, a competency-based and time-variable (CB-TV) approach has been
successfully introduced and rened GME programs in many countries (e.g., the UK, the Netherlands, Canada),
presenting the paradigm shift in the education of the next generation of physicians [41, 42]. Our ndings serve as
a reference point, underscoring residents’ needs and readiness to transition to CB-TV GME to galvanize
healthcare systems against future crises [43, 44, 45, 46, 47, 48].
Our results provide a key metric of the fall-off in global healthcare systems’ future capacity to meet their needs in
delicate and costly procedures, potentially widening access gaps in health care, under the current GME structure.
CB-TV GME will allow healthcare systems to successfully produce qualied medical professionals and
adequately shield themselves against future crises.
4.1 Limitations
Our study has some inherent limitations. Our laser focus on plastic surgery trainees constrains the statistical
power of our analyses. However, our objective was to collect the views of residents with comparable training
inputs and outputs from different nations. The inclusion of only plastic surgery residents serves that purpose,
decreasing interviariabilty and creating a more homogeneous sample. In order to collect a global sample of
respondents and gather the views of a global audience of plastic surgery residents, we reached out to as many
societies of plastic surgery as we could. The main objective was to reach plastic surgery societies that had a
teaching national footprint and gathered the attention of plastic surgery residents. In our extensive
dissemination strategy we included 67 national and international societies of plastic surgery. We nd that 19 out
of the 67 societies are specically focused on aesthetic surgery. The remaining societies do not differentiate

Page 10/16
between aesthetic surgery and target the whole spectrum of plastic, reconstructive and aesthetic surgery. In 12
out of the 19 aesthetic surgery societies, no counterpart association of non-aesthetic surgery societies existed in
the country. In the remaining 7 cases, were both an aesthetic and a non-aesthetic surgery society existed, we
were able to reach both and disseminate the survey to their resident members. For example, we reached both the
British Association of Aesthetic Plastic Surgeons (BAAPS) and the United Kingdom Association of Aesthetic
Plastic Surgeons (UKAAPS) to achieve better coverage in our survey. Further studies can harness future networks
of residents across multiple specialties to obtain more responses, however they run the risk of creating a wildly
heterogeneous sample of respondents.
Our self-reported measures of learning inputs and expected outputs from residents in 67 coun- tries may suffer
from recall and expectation bias and may reect residents’ perceptions in a single point in time. Future research
could use administrative data to measure training inputs and out- puts and obtain more accurate estimates of
the COVID impact. Also, training characteristics represented in the sample reect primarily the training in core
plastic surgery programs and may not capture the training in rotating subspecialties.
The pandemic has affected some regions of the world more than others and at different times. Our convenience
non-random sample of participants from 67 countries from all ve continents represent a broad geographic
distribution of resident experiences during the pandemic. COVID-19 cases were in decline globally during data
collection and procedures were expected to resume [49]. Additional waves of COVID-19 cannot be excluded
though and continued restrictions on elective procedures are possible.
5 Conclusion
Ourstudyisthersttocausallyidentifythecrisis-drivenlearningdecitsoffuturesurgeons, who will be
expected to play a critical role in complex case treatment [18,50], and investigate recommended remedial
measures. We are condent that our study increases the evidence base to catalyze the reform in GME and
provide salient reform recommendations and policy levers towards buildingresilienthealthcaresystemsglobally.
Our subjective causal inference strategy is general and can serve as a blueprint for other con- texts. Any setting
in which observational administrative or experimental data are limited can prot from our approach to combine
self-reported training inputs and outputs before and during a system-wide shock and a treatment-control group
framework. A benet of using subjective mea- sures of learning outputs is that they constitute a leading indicator
of training quality, program satisfaction and trainee fatigue, and may closely predict subsequent individual
success and system resilience.
Declarations
Ethics approval
This study was approved by the Institutional Review Board at Stanford University (protocol #63918)
Dataavailability
Dataandcodeareavailableforreplicationuponrequest.
Authorcontribution

Page 11/16
G.K.conceptualizedthesurvey,S.G.andG.K.designedtheresearch;S.G.analyzedthedata;and
S.G.andG.K.draftedthemanuscript.
Funding
ThisworkwasmadepossiblebytheBritishEmbassyinAthens,GreeceandtheStateScholarships Foundation.
ThepublicationofthearticleinOAmodewasnanciallysupportedbyHEAL-Link Greece.
Acknowledgements
The authors thank Dr.Vakis Kontoes and Dr.Maria Wiedner for mobilizing resources of the International Society
of Aesthetic Plastic Surgery (ISAPS) to reach residents is 67 countries.The authors also thank the 63 national
associations and societies of plastic surgeons who joined this international project and disseminated the online
survey to their resident members.The authors
alsokindlyacknowledgefundingfromtheBritishEmbassyinAthens,GreeceandtheStateSchol- arships
Foundation, and research support from the Institute for Social and Economic Research (ISER) at the University of
Essex.
ConictofInterest
None declared
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Tables
Tables 1 to 3 are available in the Supplementary Files section
Figures

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Figure 1
Subjective Causal Impact of COVID-19 on Residents in Hospitals treating COVID-19 Patients by Country

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Figure 2
Impact of Training Inputs on Learning Outputs in Plastic Surgery During COVID-19
Supplementary Files
This is a list of supplementary les associated with this preprint. Click to download.
siappendix.pdf
Tables.docx