ArticleInternational journal of environmental research and public health2020
Factorial Validity and Variance of the Maslach Burnout Inventory between Demographic and Workload Groups among Dentists of Lithuania.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 16 citations in OpenAlex.
- Review
- Prevalence and Management of Burnout Among Dental Professionals Before, During, and After the COVID-19 Pandemic: A Systematic Review.Healthcare (Basel, Switzerland) · 2024Review
- Factor structure of the Maslach Burnout Inventory Human Services Survey in Spanish urgency healthcare personnel: a cross-sectional study.BMC medical education · 2022Article
- Burnout, lifestyle and relaxation among dentists in Lithuania: a cross-sectional study.BMC health services research · 2021Article
- Burnout and Its Relationship with Demographic and Job-Related Variables among Dentists in Lithuania: A Cross-Sectional Study.International journal of environmental research and public health · 2021Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is a lack of evidence about burnout syndrome among Lithuanian dentists; as a reliable instrument to examine the syndrome in this professional group has not yet been tested. The study aimed to investigate the performance of the items and the subscales of the Maslach burnout inventory (MBI) by validating its factorial structure and analyzing its variance between demographic and workload groups of dental professionals in Lithuania. The survey was conducted among practicing dentists online or during the scientific conferences for dentists using an anonymous questionnaire. To evaluate the level of burnout the MBI was chosen. Reports of a total of 380 respondents were examined. Three-factor structure of the MBI with cross-loading of two items suggested a good fit to data (χ
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