Data from the Human Penguin Project, a cross-national dataset testing social thermoregulation principles

Chuan Peng Hu, Ji Xing Yin, Siegwart Lindenberg, İlker Dalğar, Sophia C. Weissgerber, Rodrigo C. Vergara, Athena H. Cairo, Marija V. Čolić, Pinar Dursun, Natalia Frankowska, Rhonda Hadi, Calvin J. Hall, Youngki Hong, Jennifer Joy-Gaba, Dušanka Lazarević, Ljiljana B. Lazarević, Michal Parzuchowski, Kyle G. Ratner, David Rothman, Samantha SimCláudia Simão, Mengdi Song, Darko Stojilović, Johanna K. Blomster, Rodrigo Brito, Marie Hennecke, Francisco Jaume-Guazzini, Thomas W. Schubert, Astrid Schütz, Beate Seibt, Janis H. Zickfeld, Hans IJzerman

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

In the Human Penguin Project (N = 1755), 15 research groups from 12 countries collected body temperature, demographic variables, social network indices, seven widely-used psychological scales and two newly developed questionnaires (the Social Thermoregulation and Risk Avoidance Questionnaire (STRAQ-1) and the Kama Muta Frequency Scale (KAMF)). They were collected to investigate the relationship between environmental factors (e.g., geographical, climate etc.) and human behaviors, which is a long-standing inquiry in the scientific community. More specifically, the present project was designed to test principles surrounding the idea of social thermoregulation, which posits that social networks help people to regulate their core body temperature. The results showed that all scales in the current project have sufficient to good psychometrical properties. Unlike previous crowdsourced projects, this dataset includes not only the cleaned raw data but also all the validation of questionnaires in 9 different languages, thus providing a valuable resource for psychological scientists who are interested in cross-national, environment-human interaction studies.

Original languageEnglish
Article number32
Pages (from-to)1-7
Number of pages7
JournalScientific Data
Volume6
DOIs
Publication statusPublished - 17 Apr 2019

Funding

This research was supported by a Veni grant of the Netherlands Organization for Scientific Research (NWO) (016.145.049) and a French National Research Agency “Investissements d’avenir” program grant (ANR-15-IDEX-02) both awarded to Hans IJzerman.

FundersFunder number
Agence Nationale de la RechercheANR-15-IDEX-02
Nederlandse Organisatie voor Wetenschappelijk Onderzoek016.145.049

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