Predictive modeling of burnout dimensions based on basic socio-economic determinants in health service managers and support personnel in a resource-limited health center

Bibliographic Details
Title: Predictive modeling of burnout dimensions based on basic socio-economic determinants in health service managers and support personnel in a resource-limited health center
Authors: Grey Castro-Tamayo, Mario Hernandez-Tapia, Ivan David Lozada-Martinez, Ivan Portnoy, Jessica Manosalva-Sandoval, Tobías Parodi-Camaño
Source: Frontiers in Psychiatry, Vol 15 (2025)
Publisher Information: Frontiers Media S.A., 2025.
Publication Year: 2025
Collection: LCC:Psychiatry
Subject Terms: psychological burnout, risk factors, hospital personnel, resource-limited settings, health services, Psychiatry, RC435-571
More Details: BackgroundBurnout is a prevalent condition in the healthcare sector, and although it has been extensively studied among healthcare professionals, less is known about its impact on non-professional workers, particularly in low-resource settings. This study aimed to test a preliminary predictive model based on basic socioeconomic and sociodemographic determinants to predict symptoms of burnout among support personnel and health services managers in a resource-limited health center.MethodsA prospective cross-sectional study was conducted. Using simple random sampling, symptoms of burnout were surveyed among health service managers and support personnel using the Maslach Burnout Inventory (MBI). Statistical analyses included correlation tests and predictive models using random forest models to identify significant associations and cast predictions.ResultsA total of 76 participants were included. Of these, 34.21% exhibited high levels of emotional exhaustion (EE), 42.11% showed elevated depersonalization (DP), and 7.89% reported low personal accomplishment (PA). Significant negative correlations were observed between household income and the EE and DP dimensions. The predictive models demonstrated acceptable performance in identifying socioeconomic factors associated with burnout, with prediction errors ranging from 7.68% to 20.31%.ConclusionsBurnout is common among support personnel and health services managers in resource-limited settings, particularly among those with lower incomes. The findings underscore the importance of implementing policies that address both working conditions and economic well-being to mitigate the risk of burnout. More robust predictive models could serve as a valuable tool for early identification and prevention of burnout in this type of setting.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1664-0640
Relation: https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1519930/full; https://doaj.org/toc/1664-0640
DOI: 10.3389/fpsyt.2024.1519930
Access URL: https://doaj.org/article/e2e5e7eeb0534cc4896598a05df9e0e5
Accession Number: edsdoj.2e5e7eeb0534cc4896598a05df9e0e5
Database: Directory of Open Access Journals
More Details
ISSN:16640640
DOI:10.3389/fpsyt.2024.1519930
Published in:Frontiers in Psychiatry
Language:English