TY - JOUR
AU - van Lissa, Caspar J.
AU - Stroebe, Wolfgang
AU - vanDellen, Michelle R.
AU - Leander, N. Pontus
AU - Agostini, Maximilian
AU - Draws, Tim
AU - Grygoryshyn, Andrii
AU - Gützkow, Ben
AU - Kreienkamp, Jannis
AU - Vetter, Clara S.
AU - Abakoumkin, Georgios
AU - Abdul Khaiyom, Jamilah Hanum
AU - Ahmedi, Vjollca
AU - Akkas, Handan
AU - Almenara, Carlos A. 
AU - Atta, Mohsin
AU - Bagci, Sabahat Cigdem
AU - Basel, Sima
AU - Berisha Kida, Edona
AU - Bernardo, Allan B. I.
AU - Buttrick, Nicholas R. 
AU - Chobthamkit, Phatthanakit
AU - Choi, Hoon-Seok
AU - Cristea, Mioara
AU - Csaba, Sára
AU - Damnjanović, Kaja
AU - Danyliuk, Ivan
AU - Dash, Arobindu
AU - Di Santo, Daniela
AU - Douglas, Karen M.
AU - Enea, Violeta
AU - Faller, Daiane Gracieli
AU - Fitzsimons, Gavan
AU - Gheorghi, Alexandra
AU - Gómez, Ángel
AU - Grzymala‑Moszczynska, Joanna
AU - Hamaidia, Ali
AU - Han, Qing
AU - Helmy, Mai
AU - Hudiyana, Joevarian
AU - Jeronimus, Bertus F.
AU - Jiang, Ding-Yu
AU - Jovanović, Veljko
AU - Kamenov, Željka
AU - Kende, Anna
AU - Keng, Shian-Ling
AU - Kieu, Tra Thi Thanh
AU - Koc, Yasin
AU - Kovyazina, Kamila
AU - Kozytska, Inna
AU - Krause, Joshua
AU - Kruglanski, Arie W.
AU - Kurapov, Anton
AU - Kutlaca, Maja
AU - Lantos, Nóra Anna
AU - Lemay, Edward P.
AU - Lemsmana, Cokorda Bagus Jaya
AU - Louis, Winnifred R. 
AU - Lueders, Adrian
AU - Malik, Najma Iqbal
AU - Martinez, Anton P.
AU - McCabe, Kira O.
AU - Mehulić, Jasmina
AU - Milla, Mirra Noor
AU - Mohammed, Idris
AU - Molinario, Erica
AU - Moyano, Manuel
AU - Muhammad, Hayat
AU - Mula, Silvana
AU - Muluk, Hamdi
AU - Myroniuk, Solomiia
AU - Najafi, Reza
AU - Nisa, Claudia F. 
AU - Nyúl, Boglárka
AU - O'Keefe, Paul A. 
AU - Olivas Osuna, Jose Javier
AU - Osin, Evgeny N.
AU - Park, Joonha
AU - Pica, Gennaro
AU - Pierro, Antonio
AU - Rees, Jonas H.
AU - Reitsema, Anne Margit
AU - Resta, Elena
AU - Rullo, Marika
AU - Ryan, Michelle K.
AU - Samekin, Adil
AU - Santtila, Pekka
AU - Sasin, Edyta
AU - Schumpe, Birga M.
AU - Selim, Heyla A.
AU - Stanton, Michael Vicente
AU - Sultana, Samiah
AU - Sutton, Robbie M. 
AU - Tseliou, Eleftheria
AU - Utsugi, Akira
AU - van Breen, Jolien Anne
AU - van Veen, Kees
AU - Vázquez, Alexandra
AU - Wollast, Robin
AU - Yeung, Victoria Wai-Lan
AU - Zand, Somayeh
AU - Žeželj, Iris Lav
AU - Zheng, Bang
AU - Zick, Andreas
AU - Zúñiga, Claudia
AU - Bélanger, Jocelyn J.
PY - 2022
DA - March
TI - Using Machine Learning to Identify Important Predictors of COVID-19 Infection Prevention Behaviors During the Early Phase of the Pandemic
JO - Patterns
VL - 3
IS - 4
DO - https://doi.org/10.1016/j.patter.2022.100482
AB - In the early phase of the COVID-19 pandemic, before vaccines became available, a set of infection prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors–information essential for guiding follow-up research and interventions. Whereas social and health psychological theories suggest a limited set of predictors, machine learning analyses can identify correlates of health behaviors from a larger pool of candidate predictors. We used random forests, a machine learning algorithm, to rank 115 candidate correlates of infection prevention behavior in a study of 56,072 participants across 28 countries, administered in March-May 2020. Results indicated that the two most important predictors related to individual-level injunctive norms—beliefs that people in the community should engage in social distancing and self-isolation, followed by endorsement of restrictive containment measures. The machine-learning model predicted 52% of the variance in infection prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically-derived predictors did not turn out to be important.
PB - Elsevier
UR - https://researchportal.hw.ac.uk/en/publications/e1ea824f-87a2-44fa-9b8d-4b41a28d4235
KW - Coronavirus (COVID-19)
KW - Research methods
ER