Prioritizing heat stress indices for cognitive performance assessment using a Fuzzy Delphi–FAHP framework

Occupational heat exposure induces physiological strain and can impair cognitive performance, exacerbating occupational error and accident risks. Although numerous heat stress indices exist, their theoretical and practical suitability for cognitive-related assessments remains ambiguous. This study established a structured multicriteria decision-making framework integrating the Fuzzy Delphi Method (FDM) and Fuzzy Analytic Hierarchy Process (FAHP) to prioritize candidate heat stress indices for occupational cognitive risk evaluation. Candidate indices and screening criteria identified via literature review and expert consensus ( \(n=25\) ) were evaluated using FDM, followed by FAHP with Chang’s extent analysis to derive criteria weights and overall index priorities. A one-at-a-time \(+10\%\) sensitivity analysis was performed to verify model stability. Following FDM screening, six criteria and seven indices were retained. Predictive capability for cognitive performance (weight: 0.265), physiological relevance (0.229), and reliability/reproducibility (0.177) emerged as the most critical evaluation criteria. Among evaluated indices, the Universal Thermal Climate Index (UTCI, priority: 0.214) ranked highest, followed by Predicted Heat Strain (PHS, 0.201) and Wet-Bulb Globe Temperature (WBGT, 0.168), whereas traditional empirical indices demonstrated lower suitability. Sensitivity analysis confirmed exceptional rank stability (Spearman’s \(\rho\:=0.964-1.000\) ). Overall, comprehensive, physiologically grounded thermal indices provide superior suitability for cognitive-related heat stress assessment over simple empirical metrics. The proposed framework delivers a transparent, robust decision-support tool for occupational safety and health practitioners.