Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic

Research output: Journal contributionsJournal articlesResearchpeer-review

Authors

  • Caspar J. Van Lissa
  • Ben Gützkow
  • Michelle R. vanDellen
  • Arobindu Dash
  • Tim Draws
  • Wolfgang Stroebe
  • N. Pontus Leander
  • Maximilian Agostini
  • Andrii Grygoryshyn
  • Jannis Kreienkamp
  • Clara S. Vetter
  • Georgios Abakoumkin
  • Jamilah Hanum Abdul Khaiyom
  • Vjollca Ahmedi
  • Handan Akkas
  • Carlos A. Almenara
  • Mohsin Atta
  • Sabahat Cigdem Bagci
  • Sima Basel
  • Edona Berisha Kida
  • And 85 others
  • Allan B.I. Bernardo
  • Nicholas R. Buttrick
  • Phatthanakit Chobthamkit
  • Hoon Seok Choi
  • Mioara Cristea
  • Sára Csaba
  • Kaja Damnjanović
  • Ivan Danyliuk
  • Daniela Di Santo
  • Karen M. Douglas
  • Violeta Enea
  • Daiane G. Faller
  • Gavan Fitzsimons
  • Alexandra Gheorghiu
  • Ángel Gómez
  • Ali Hamaidia
  • Qing Han
  • Mai Helmy
  • Joevarian Hudiyana
  • Bertus F. Jeronimus
  • Ding Yu Jiang
  • Veljko Jovanović
  • Željka Kamenov
  • Anna Kende
  • Shian Ling Keng
  • Tra Thi Thanh Kieu
  • Yasin Koc
  • Kamila Kovyazina
  • Inna Kozytska
  • Joshua Krause
  • Arie W. Kruglanksi
  • Anton Kurapov
  • Maja Kutlaca
  • Nóra Anna Lantos
  • Edward P. Lemay
  • Cokorda Bagus Jaya Lesmana
  • Winnifred R. Louis
  • Adrian Lueders
  • Najma Iqbal Malik
  • Anton Martinez
  • Kira O. McCabe
  • Jasmina Mehulić
  • Mirra Noor Milla
  • Idris Mohammed
  • Erica Molinario
  • Manuel Moyano
  • Hayat Muhammad
  • Silvana Mula
  • Hamdi Muluk
  • Solomiia Myroniuk
  • Reza Najafi
  • Claudia F. Nisa
  • Boglárka Nyúl
  • Paul A. O’Keefe
  • Jose Javier Olivas Osuna
  • Evgeny N. Osin
  • Joonha Park
  • Gennaro Pica
  • Antonio Pierro
  • Jonas H. Rees
  • Anne Margit Reitsema
  • Elena Resta
  • Marika Rullo
  • Michelle K. Ryan
  • Adil Samekin
  • Pekka Santtila
  • Edyta M. Sasin
  • Birga M. Schumpe
  • Heyla A. Selim
  • Michael Vicente Stanton
  • Samiah Sultana
  • Robbie M. Sutton
  • Eleftheria Tseliou
  • Akira Utsugi
  • Jolien Anne van Breen
  • Kees Van Veen
  • Alexandra Vázquez
  • Robin Wollast
  • Victoria Wai lan Yeung
  • Somayeh Zand
  • Iris Lav Žeželj
  • Bang Zheng
  • Andreas Zick
  • Claudia Zúñiga
  • Jocelyn J. Bélanger

Before vaccines for coronavirus disease 2019 (COVID-19) 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. Whereas social and health psychological theories suggest a limited set of predictors, machine-learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection-prevention behavior in 56,072 participants across 28 countries, administered in March to May 2020. 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. Results indicated the two most important predictors related to individual-level injunctive norms. 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 were relatively unimportant.

Original languageEnglish
Article number100482
JournalPatterns
Volume3
Issue number4
Number of pages14
DOIs
Publication statusPublished - 08.04.2022

Bibliographical note

Publisher Copyright:
© 2022 The Author(s)

    Research areas

  • COVID-19, Economic burden, Health behaviors, Infection risk, random forest, social norms, DSML2: Proof-of-concept: Data science output has been formulated, implemented, and tested for one domain/problem, machine learning, public goods dilemma, health behaviors
  • Health sciences

Documents

DOI

Recently viewed

Researchers

  1. Eva Kern

Publications

  1. Parallelworlds. On Joseph Beuys and Alice Channer
  2. To regulate or not to regulate
  3. Sustainability in Business: Integrated Management of Value Creation and Disvalue Mitigation
  4. Patients' experiences in a guided Internet- and App-based stress intervention for college students
  5. Group membership does not modulate automatic imitation
  6. Law-making in complex processes
  7. Global Governance and the Interplay of Coordination and Contestation
  8. Advancing Decision-Visualization Environments—Empirically informed Design Recommendations
  9. Sprache
  10. Klimapaket
  11. The Actions that Make a Musical Instrument
  12. Bis in den Kern
  13. Simulation of composite hot extrusion with high reinforcing Volumes
  14. Why Art Criticism? A Reader
  15. Is Lean Production Really Lean?
  16. Intelligent Diagnostics of Radial Internal Clearance in Ball Bearings with Machine Learning Methods
  17. Development of a magnesium secondary alloy system for mixed magnesium post-consumer scrap
  18. Ecologies of Change
  19. Drachen über Helsinki
  20. TIMSS
  21. How art becomes organization
  22. Datenmodellierung mit dem Entity-Relationship-Ansatz
  23. Endogenous Environmental Policy when Pollution is Transboundary
  24. The impact of supervisory board composition on CSR reporting
  25. Bias-corrected estimation for speculative bubbles in stock prices
  26. Institutional Perspectives on Digital Transformation
  27. What Is the Impact of Financial Penalties on the Performance and Stock Returns of Banks?
  28. Walter Benjamin
  29. Foundation of digital badges and micro-credentials
  30. Consumer reaction on tumbling funds
  31. The rhetorical structure of marketisation in selected emails of tertiary institutions
  32. Wer oder was bestimmt "Wirklichkeit" in Organisationen?
  33. Markierungen in Sprache und Raum
  34. Managing CSR Communication
  35. Ist Dauerreflexion kommunizierbar?
  36. China schweigt