作者
Hans IJzerman,Siegwart Lindenberg,İlker Dalğar,Sophia Christin Weißgerber,Rodrigo C. Vergara,Athena H. Cairo,Marija Čolić,Pınar Dursun,Natalia Frankowska,Rhonda Hadi,Calvin J. Hall,Youngki Hong,Hu Chuan-Peng,Jennifer A. Joy-Gaba,Dušanka Lazarević,Ljiljana B. Lazarević,Michał Parzuchowski,Kyle G. Ratner,David J. Rothman,Samantha Sim,Cláudia Simão,Mengdi Song,Darko Stojilović,Johanna Katarina Blomster,Rodrigo Brito,Marie Hennecke,Francisco Jaume-Guazzin,Thomas W. Schubert,Astrid Schütz,Beate Seibt,Janis Zickfeld
摘要
Social thermoregulation theory posits that modern human relationships are pleisiomorphically organized around body temperature regulation. In two studies (N = 1755) designed to test the principles from this theory, we used supervised machine learning to identify social and non-social factors that relate to core body temperature. This data-driven analysis found that complex social integration (CSI), defined as the number of high-contact roles one engages in, is a critical predictor of core body temperature. We further used a cross-validation approach to show that colder climates relate to higher levels of CSI, which in turn relates to higher CBT (when climates get colder). These results suggest that despite modern affordances for regulating body temperature, people still rely on social warmth to buffer their bodies against the cold.