Ozbey, Mehmet FurkanTurhan, Cihan2025-06-052025-06-0520250143-62441477-084910.1177/014362442513466402-s2.0-105005875278https://doi.org/10.1177/01436244251346640https://hdl.handle.net/20.500.14411/10599Mood states, categorized into subscales such as Tension (TEN), Anger (ANG), Fatigue (FAT), Vigour (VIG), Confusion (CON), and Depression (DEP), affect occupants' perceptions of thermal environments. This study investigates the influence of these subscales on thermal sensation, exploring both positive and negative effects. Experiments were conducted in a temperate climate zone over an extended period, including both heating and cooling seasons, with 1159 volunteers. The Morris Method was used to assess the impact of psychological parameters (TEN, ANG, FAT, VIG, CON, DEP) on thermal sensation. Markov Chain Monte Carlo (MCMC) simulations, performed via Python code developed by the authors, evaluated the positive and negative impacts of these subscales across 30,000 simulations. Results showed that VIG was the most influential parameter, while CON and FAT had negative effects (feeling cooler) on thermal sensation. These findings emphasize the complex relationship between psychological factors and thermal perception, underlining the importance of mood states in designing environments that enhance thermal comfort. The study offers valuable insights into the interplay of emotional well-being and physiological responses, contributing to environmental psychology and climate-responsive design.eninfo:eu-repo/semantics/closedAccessAdaptive Thermal ComfortHuman PsychologyMarkov Chain Monte Carlo (Mcmc)Morris MethodProfile Of Mood States (Poms)Practical ApplicationArticleQ3Q2WOS:001493712100001