Literature DB >> 34089412

Examining the measurement equivalence of the Maslach Burnout Inventory across age, gender, and specialty groups in US physicians.

Keri J S Brady1, R Christopher Sheldrick2, Pengsheng Ni2,3, Mickey T Trockel4,5, Tait D Shanafelt5, Susannah G Rowe6,7, Lewis E Kazis2.   

Abstract

BACKGROUND: Disparities in US physician burnout rates across age, gender, and specialty groups as measured by the Maslach Burnout Inventory-Human Services Survey for Medical Personnel (MBI) are well documented. We evaluated whether disparities in US physician burnout are explained by differences in the MBI's functioning across physician age, gender, and specialty groups.
METHODS: We assessed the measurement equivalence of the MBI across age, gender, and specialty groups in multi-group item response theory- (IRT-) based differential item functioning (DIF) analyses using secondary, cross-sectional survey data from US physicians (n = 6577). We detected DIF using two IRT-based methods and assessed its impact by estimating the overall average difference in groups' subscale scores attributable to DIF. We assessed DIF's practical significance by comparing differences in individuals' subscale scores and burnout prevalence estimates from models unadjusted and adjusted for DIF.
RESULTS: We detected statistically significant age-, gender-, and specialty- DIF in all but one MBI item. However, in all cases, average differences in expected subscale-level scores due to DIF were < 0.10 SD on each subscale. Differences in physicians' individual-level subscale scores and burnout symptom prevalence estimates across DIF- adjusted and unadjusted IRT models were also small (in all cases, mean absolute differences in individual subscale scores were < 0.04 z-score units; prevalence estimates differed by < 0.70%).
CONCLUSIONS: Age-, gender-, and specialty-related disparities in US physician burnout are not explained by differences in the MBI's functioning across these demographic groups. Our findings support the use of the MBI as a valid tool to assess age-, gender-, and specialty-related disparities in US physician burnout.

Entities:  

Keywords:  Differential item functioning; Differential test functioning; Health outcome measurement; Measurement equivalence; Measurement invariance; Person-centered outcome measurement; Physician burnout

Year:  2021        PMID: 34089412     DOI: 10.1186/s41687-021-00312-2

Source DB:  PubMed          Journal:  J Patient Rep Outcomes        ISSN: 2509-8020


  12 in total

1.  Changes in Burnout and Satisfaction With Work-Life Balance in Physicians and the General US Working Population Between 2011 and 2014.

Authors:  Tait D Shanafelt; Omar Hasan; Lotte N Dyrbye; Christine Sinsky; Daniel Satele; Jeff Sloan; Colin P West
Journal:  Mayo Clin Proc       Date:  2015-12       Impact factor: 7.616

2.  Evaluating measurement equivalence using the item response theory log-likelihood ratio (IRTLR) method to assess differential item functioning (DIF): applications (with illustrations) to measures of physical functioning ability and general distress.

Authors:  Jeanne A Teresi; Katja Ocepek-Welikson; Marjorie Kleinman; Karon F Cook; Paul K Crane; Laura E Gibbons; Leo S Morales; Maria Orlando-Edelen; David Cella
Journal:  Qual Life Res       Date:  2007-05-05       Impact factor: 4.147

3.  The COSMIN study reached international consensus on taxonomy, terminology, and definitions of measurement properties for health-related patient-reported outcomes.

Authors:  Lidwine B Mokkink; Caroline B Terwee; Donald L Patrick; Jordi Alonso; Paul W Stratford; Dirk L Knol; Lex M Bouter; Henrica C W de Vet
Journal:  J Clin Epidemiol       Date:  2010-07       Impact factor: 6.437

4.  It Might Not Make a Big DIF: Improved Differential Test Functioning Statistics That Account for Sampling Variability.

Authors:  R Philip Chalmers; Alyssa Counsell; David B Flora
Journal:  Educ Psychol Meas       Date:  2015-06-29       Impact factor: 2.821

5.  Differential item functioning between ethnic groups in the epidemiological assessment of depression.

Authors:  Joshua Breslau; Kristin N Javaras; Deborah Blacker; Jane M Murphy; Sharon-Lise T Normand
Journal:  J Nerv Ment Dis       Date:  2008-04       Impact factor: 2.254

6.  Model-Based Measures for Detecting and Quantifying Response Bias.

Authors:  R Philip Chalmers
Journal:  Psychometrika       Date:  2018-06-15       Impact factor: 2.500

7.  Burnout and satisfaction with work-life balance among US physicians relative to the general US population.

Authors:  Tait D Shanafelt; Sonja Boone; Litjen Tan; Lotte N Dyrbye; Wayne Sotile; Daniel Satele; Colin P West; Jeff Sloan; Michael R Oreskovich
Journal:  Arch Intern Med       Date:  2012-10-08

8.  Selecting physician well-being measures to assess health system performance and screen for distress: Conceptual and methodological considerations.

Authors:  Keri J S Brady; Lewis E Kazis; R Christopher Sheldrick; Pengsheng Ni; Mickey T Trockel
Journal:  Curr Probl Pediatr Adolesc Health Care       Date:  2019-09-25

9.  Methodological Issues in Examining Measurement Equivalence in Patient Reported Outcomes Measures: Methods Overview to the Two-Part Series, "Measurement Equivalence of the Patient Reported Outcomes Measurement Information System® (PROMIS®) Short Forms".

Authors:  Jeanne A Teresi; Richard N Jones
Journal:  Psychol Test Assess Model       Date:  2016

10.  Describing the emotional exhaustion, depersonalization, and low personal accomplishment symptoms associated with Maslach Burnout Inventory subscale scores in US physicians: an item response theory analysis.

Authors:  Keri J S Brady; Pengsheng Ni; R Christopher Sheldrick; Mickey T Trockel; Tait D Shanafelt; Susannah G Rowe; Jeffrey I Schneider; Lewis E Kazis
Journal:  J Patient Rep Outcomes       Date:  2020-06-01
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