Article
Details
Citation
Williams L, Rasmussen S, Kleczkowski A, Maharaj S & Cairns N (2015) Protection motivation theory and social distancing behaviour in response to a simulated infectious disease epidemic. Psychology, Health and Medicine, 20 (7), pp. 832-837. https://doi.org/10.1080/13548506.2015.1028946
Abstract
Epidemics of respiratory infectious disease remain one of the most serious health risks facing the population. Non-pharmaceutical interventions (e.g. hand-washing or wearing face masks) can have a significant impact on the course of an infectious disease epidemic. The current study investigated whether protection motivation theory (PMT) is a useful framework for understanding social distancing behaviour (i.e. the tendency to reduce social contacts) in response to a simulated infectious disease epidemic. There were 230 participants (109 males, 121 females, mean age 32.4years) from the general population who completed self-report measures assessing the components of PMT. In addition, participants completed a computer game which simulated an infectious disease epidemic in order to provide a measure of social distancing behaviour. The regression analyses revealed that none of the PMT variables were significant predictors of social distancing behaviour during the simulation task. However, fear (β=.218,p<.001), response efficacy (β=.175,p<.01) and self-efficacy (β=.251,p<.001) were all significant predictors of intention to engage in social distancing behaviour. Overall, the PMT variables (and demographic factors) explain 21.2% of the variance in intention. The findings demonstrated that PMT was a useful framework for understanding intention to engage in social distancing behaviour, but not actual behaviour during the simulated epidemic. These findings may reflect an intention-behaviour gap in relation to social distancing behaviour.
Keywords
infectious disease; protection motivation; social distancing
Journal
Psychology, Health and Medicine: Volume 20, Issue 7
Status | Published |
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Publication date | 31/12/2015 |
Publication date online | 02/04/2015 |
Date accepted by journal | 09/03/2015 |
URL | |
Publisher | Taylor and Francis |
ISSN | 1354-8506 |
eISSN | 1465-3966 |
People (1)
Senior Lecturer, Computing Science