Psychometric properties of the Maslach Burnout Inventory for Medical Personnel (MBI-HSS-MP)
2022 (English)In: Heliyon, E-ISSN 2405-8440, Vol. 8, no 2, article id e08868Article in journal (Refereed) Published
Abstract [en]
Background: This study aimed to validate the Persian version of Maslach Burnout Inventory for Medical Personnel (MBI-HSS-MP), an instrument developed to capture burnout for health professionals. The specific aims were to psychometrically assess the Persian MBI-HSS-MP in relation to its structure, test-retest reliability, and item properties. Methods: The study setting was all eight hospitals in Qazvin province, Iran (study period from 10 September to 16 November 2020). Health professionals of physicians (n = 106) and nurses (n = 200) participated in the study. The psychometric properties of the 22-item MBI-HSS-MP was then examined for its factor structure via confirmatory factor analysis (CFA) and Rasch models, test-retest reliability, item fit, and differential item functioning (DIF). Results: The MBI-HSS-MP was verified as having a three-factor structure and each item was embedded well in its belonging construct (comparative fit index = 0.941, Tucker-Lewis index = 0.929 derived from CFA results; infit and outfit MnSq = 0.71 to 1.38 derived from Rasch models). Test-retest reliability of each MBI-HSS-MP item was satisfactory and no substantial DIF items were displayed across gender or across health professionals. Conclusion: The MBI-HSS-MP has good psychometric properties to assess burnout accurately among healthcare professionals in the three dimensions of emotional exhaustion, personal accomplishment, and depersonalization.
Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 8, no 2, article id e08868
Keywords [en]
Burnout, Factor analysis, Nurse, Physician, Validation
National Category
Nursing
Identifiers
URN: urn:nbn:se:hj:diva-55897DOI: 10.1016/j.heliyon.2022.e08868ISI: 000767225100033PubMedID: 35169645Scopus ID: 2-s2.0-85123927287Local ID: GOA;intsam;796258OAI: oai:DiVA.org:hj-55897DiVA, id: diva2:1637877
2022-02-152022-02-152025-10-13Bibliographically approved