A fuzzy intelligent system to assess midwives’ burnout conditions

INTRODUCTION: Midwives’ burnout affects their effectiveness and the quality of the services they provide to pregnant women as well as the quality of the collaboration with medical staff. The burnout depends on a number of factors that can exhibit high variability over time. This creates the necessity of introducing intelligent approaches that assess changes in behavior, environmental factors, working conditions, and to make decisions to optimize the physical and mental health of midwives. The aim of this study was to employ fuzzy logic to design a Fuzzy Intelligent or Inference System (FIS) that assesses midwives’ burnout level by emulating the reasoning of human experts. METHODS: The proposed FIS addresses the assessment of midwives’ burnout comprehensively since it incorporates findings following a thorough analysis of the relevant literature, as well as assimilates experts’ knowledge elicited through semi-structured interviews. Additionally, fuzzy rules are more intuitive and thus easier to understand and modify by human users than dealing and translating numerical results. The FIS performance is compared and evaluated against experienced midwives. RESULTS: Findings confirm the ability of the proposed FIS to produce judgments that are closer to experts’ consensus, as expressed by their aggregated assessment. CONCLUSIONS: The proposed FIS is evaluated by comparing its results with judgments made by experts, suggesting that fuzzy logic allows precise and personalized assessment of midwives’ burnout levels. The proposed FIS can be used to evaluate burnout, support organizations to develop burnout policies as well as used as a research instrument to investigate interrelationships of burnout factors.