Evaluation of human attention using self-reported emotion, sleepiness and perceived workload under heat exposure

Global warming is increasing the frequency and intensity of heat exposure experienced by people working in hot environments, thereby posing a threat to human attention. However, existing attention-evaluation techniques are often susceptible to environmental influences. To address this issue, a multi-dimensional framework based on human subjective perception was proposed. Fourteen participants were recruited to perform a 30-min continuous performance test under indoor temperatures of 30°C, 33°C and 36°C. During the task, emotion, sleepiness and perceived workload data were collected, and the performance index (PI) was calculated. Thereafter, a generalized linear mixed model (GLMM) was used to develop an exploratory model of attention. Results showed that PI decreased significantly with increasing indoor temperature ( p < 0.05). Although overall emotion, sleepiness and perceived workload varied across temperature conditions, no statistically significant differences were observed ( p > 0.05). However, the GLMM analysis revealed that sleepiness ( p = 0.025), positive emotion ( p < 0.001), mental demand ( p = 0.023), physical demand ( p < 0.001) and frustration ( p = 0.001) were significantly associated with PI. Based on these variables, a multi-dimensional exploratory model of attention was established ( F = 6.775, p < 0.001). The findings provide a theoretical basis for evaluating human attention under heat exposure.