CoChat
Sign Up
Cited by 130Healthcare professionals’ stress and burnoutStress and Burnout ResearchOccupational Health and Burnout

Assessment of burnout in medical students using the Maslach Burnout Inventory-Student Survey: a cross-sectional data analysis

Open access
Obregon, Michael, Luo, Jessica, Shelton, Jarod, Blevins, Terri, MacDowell, Martin·2020·BMC Medical Education
DOI 10.1186/s12909-020-02274-3PMC PMC7579892

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

Background: Medical student burnout can cause emotional and physical exhaustion and detachment. The objectives of this study were to evaluate burnout using the Maslach Burnout Inventory-Student Survey (MBI-SS), identify factors that may predict burnout, and assess wellness initiatives effectiveness at reducing burnout. Methods: The MBI-SS was administered to all medical students (Classes 2019 to 2022) at the University of Illinois College of Medicine (UICOM) from February to May 2019. Factor analysis and internal consistency of the MBI-SS were assessed. Mean MSBI-SS subscale scores for burnout were calculated for cynicism (CY), emotional exhaustion (EE), and academic efficacy (AE). Multiple regression analysis was used to identify student factors that may predict burnout. Results: A total of 273 (21.6%) UICOM students completed the survey and 110 (40.3%) respondents reported self-perceived burnout. MBI-SS subscale scores were significantly higher for CY and EE, and significantly lower for AE in students who reported suffering from burnout versus students who did not report burnout. Mean ± SD subscale scores for CY, EE, and AE in burnout students were 14.44 ± 5.59, 23.23 ± 4.74, and 24.81 ± 5.35, respectively. In comparison, mean ± SD subscale scores for CY, EE, and AE in non-burnout students were 7.59 ± 5.16, 14.96 ± 5.71, and 28.74 ± 3.21, respectively. Regression analysis denoted significant associations between burnout and being out-of-phase in the curriculum, the effectiveness of wellness initiatives, and strength of motivation for medical school (SMMS) in both the two- and three-dimensional MBI-SS models. Gender was significantly associated with burnout in only the two-dimensional model. Conclusions: Self-reported burnout in medical students at UICOM was validated using the MBI-SS. Being out-of-phase in the curriculum, being female, rating wellness initiatives as less effective, and demonstrating lower motivation for continued medical school education may be used as predictors of medical student burnout. This investigation may act as a guide for measuring burnout in medical student populations and how the implementation of wellness initiatives may ameliorate burnout.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s12909-020-02274-3

Cites

54 of 54 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Medical students' cynicism scores (mean 10.87, SD 6.92) were significantly lower than those of the burnout sample (mean 14.44, SD 5.59; t216=4.19; P<.001) but higher than those of the nonburnout sample (mean 7.59, SD 5.16; t269=4.46; P<.001).

    “cynicism scores (mean 10.87, SD 6.92) significantly lower than those of the burnout sample (mean 14.44, SD 5.59; t216=4.19; P<.001) but higher than those of the nonburnout sample (mean 7.59, SD 5.16; t269=4.46; P<.001)”

    From Evaluation of an App-Delivered Psychological Flexibility Skill Training Intervention for Medical Student Burnout and Well-being: Randomized Controlled Trial (2023) · cites this paper as [66]

    Table 2 in the Results reports cynicism scores of 14.44 ± 5.59 for the burnout group and 7.59 ± 5.16 for the nonburnout group. It does not report the 10.87 ± 6.92 score or the stated t-tests comparing that score with its groups; its P-value concerns the comparison between its own burnout and nonburnout groups. (LLM, conf=0.90)

    Experimental — accuracy not yet measured

  • Medical students' exhaustion levels (mean 16.29, SD 7.20) were comparable with those of a sample of medical students not experiencing burnout (mean 14.96, SD 5.71; t269=1.69; P=.09).

    “exhaustion levels (mean 16.29, SD 7.20) comparable with those of a sample of medical students not experiencing burnout (mean 14.96, SD 5.71; t269=1.69; P=.09)”

    From Evaluation of an App-Delivered Psychological Flexibility Skill Training Intervention for Medical Student Burnout and Well-being: Randomized Controlled Trial (2023) · cites this paper as [66]

    Table 2 in the Results reports emotional exhaustion of 14.96 ± 5.71 for medical students who did not report burnout, matching the comparison group. It does not report the claimed 16.29 ± 7.20 group or the t(269)=1.69, P=.09 comparison; its burnout group instead scored 23.23 ± 4.74, with P=.001 versus the non-burnout group. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Medical students' academic efficacy scores (mean 24.69, SD 6.47) were comparable with those of medical students who perceived themselves to be high in burnout (mean 24.81, SD 5.35; t216=0.15; P=.88).

    “academic efficacy scores (mean 24.69, SD 6.47) comparable with those of medical students who perceived themselves to be high in burnout (mean 24.81, SD 5.35; t216=0.15; P=.88)”

    From Evaluation of an App-Delivered Psychological Flexibility Skill Training Intervention for Medical Student Burnout and Well-being: Randomized Controlled Trial (2023) · cites this paper as [66]

    Table 2 in the Results reports an academic efficacy mean of 24.81 (SD 5.35) for students reporting burnout, matching the cited comparator. It does not report the other mean of 24.69 (SD 6.47) or the stated t-test and P value; its own comparison is with students not reporting burnout, whose mean was 28.74 (SD 3.21; P=.001). (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • The reliability of the MBI-GS (S) has been demonstrated among medical students.

    “The reliability of the MBI-GS (S) has been demonstrated among medical students [66,83].”

    From Evaluation of an App-Delivered Psychological Flexibility Skill Training Intervention for Medical Student Burnout and Well-being: Randomized Controlled Trial (2023) · cites this paper as [66]

    The Results (Table 2; page not provided) report acceptable internal consistency for the MBI-SS among 273 medical students, with subscale Cronbach’s alpha values of 0.769–0.858. The Discussion calls the MBI-SS an adaptation of the General Survey, but the paper does not identify it as the MBI-GS (S) or establish that the two labels refer to the same instrument. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Baseline exhaustion and cynicism scores for this sample were suggestive of low levels of burnout compared with reference medical student samples.

    “baseline exhaustion and cynicism scores for this sample were suggestive of low levels of burnout compared with reference medical student samples [66]”

    From Evaluation of an App-Delivered Psychological Flexibility Skill Training Intervention for Medical Student Burnout and Well-being: Randomized Controlled Trial (2023) · cites this paper as [66]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

1 of the 55 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. [10]Corish B. Medical knowledge doubles every few months; how can clinicians keep up? [Internet]. Elsevier Connect. 2018 [cited 2020Jan2]. Available from: https://www.elsevier.com/connect/medical-knowledge-doubles-every-few-months-how-can-clinicians-keep-up.

Cited by

Sorted by citations

Related

Authors
Obregon, M., Luo, J., Shelton, J., Blevins, T., & MacDowell, M.
Affiliations
University of Illinois Chicago, Rockford campus (US)
Corresponding author
Shelton, Jarod
ORCID
Venue
BMC Medical Education
Publisher
Springer Science and Business Media LLC
Published
2020-10-21
Volume
20
Issue
1
Pages
376-376
ISSN
1472-6920 (ISSN-L)
DOI
10.1186/s12909-020-02274-3
PMC
PMC7579892
OpenAlex
W3094330568
Cited by
130
References
55
Citations by year
2026: 19 · 2025: 25 · 2024: 25 · 2023: 31 · 2022: 21 · 2021: 9
FWCI
15.87
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Medical Education (publishedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Health Professions › General Health Professions › Healthcare professionals’ stress and burnout
  • Social Sciences › Psychology › Social Psychology › Stress and Burnout Research
  • Health Sciences › Health Professions › Occupational Therapy › Occupational Health and Burnout
Keywords
medical student burnout, Maslach Burnout Inventory-Student Survey, emotional exhaustion, cynicism, academic efficacy, wellness programs, gender differences, predictors of burnout, medical education, student well-being, scale validation, burnout prevalence, gender differences in burnout
MeSH terms
Burnout, Psychological, Data Analysis, Burnout, Professional, Cross-Sectional Studies, Female, Humans, Psychometrics, Surveys and Questionnaires, Students, Medical

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review