Using an integrated social cognition model to identify the determinants of QR code check-in compliance behaviors in the COVID-19 pandemic
Abstract
In Australia, checking in while entering venues was a legal requirement during the COVID-19 pandemic to track potential infection sites. This two-wave correlational study used an integrated theory of planned behavior model including moral norms, anticipated regret, and habit to predict check-in compliance in a sample of 181 Victorians (Mean Age = 41.88, 56.4% female) and 162 Queenslanders (Mean Age = 43.26, 47.5% female). Habit and intention predicted behavior, while perceived behavioral control did not. Intention was predicted by baseline habit, attitude, subjective norm, and moral norm in the Victorian sample, while only baseline habit and moral norm predicted intention in the Queensland sample. This study has potential implications for reviewing previous strategies and for future pandemic preparedness, both by identifying the drivers of infection control compliance, and through the discussion of how differences in effects between states may be linked to each state’s experience of the pandemic (e.g. infection rates, lockdown length).
Main Authors
Format
Articles
Research article
Published
2023
Series
Subjects
Publication in research information system
Publisher
SAGE Publications
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202311137918Käytä tätä linkitykseen.
Review status
Peer reviewed
ISSN
1359-1053
DOI
https://doi.org/10.1177/13591053231209880
Language
English
Published in
Journal of Health Psychology
Citation
- Mac, T. N., Phipps, D. J., Parkinson, J., Cassimatis, M., & Hamilton, K. (2023). Using an integrated social cognition model to identify the determinants of QR code check-in compliance behaviors in the COVID-19 pandemic. Journal of Health Psychology, OnlineFirst. https://doi.org/10.1177/13591053231209880
Additional information about funding
This research was sup-ported by the Australian Government Research Training Program as part of Thi Nhung Mac’s PhD project.
Copyright© The Author(s) 2023