Predicted and user perceived heat strain using the ClimApp mobile tool for individualized alert and advice

Thermal models and indices integrated into a mobile application could provide relevant information regarding thermal stress and strain to the general public. The aim of the current paper is to validate such a mobile application, ClimApp, to the users needs in the heat. ClimApp combines weather data with personal user data, thermal models and indices to estimate the thermal strain of the user. The output of ClimApp ranges from -4 to +4, where values below 0 indicate cold strain and values above 0 indicate heat strain. 134 Participants filled in the required personal settings into the app, and indicated if the estimated thermal strain by ClimApp matched their thermal perception. 45 of the participants filled in a user satisfaction questionnaire. Results show that ClimApp is able to predict the heat strain of the user, but may underestimate perceived heat strain when ambient temperature increases. Furthermore, participants were positive about the user-friendliness of ClimApp, but did not think they would use ClimApp frequently and believed the information was irrelevant for them. This is quite remarkable as the number of heat illness cases are increasing and the negative effects of heat occur in all populations exposing themselves to the heat. There needs to be more focus on making people aware of the negative health risks of the heat. ClimApp could play a role as a tool to make heat warnings more accessible for everyone and make people aware of appropriate behavior during periods with high ambient temperatures.