Protection motivation theory and social distancing behaviour in response to a simulated infectious disease epidemic

Williams, Lynn; Rasmussen, Susan; Kleczkowski, A.; Maharaj, Savi; Cairns, Nicole

doi:10.1080/13548506.2015.1028946

Cited by 105 publications

(103 citation statements)

References 14 publications

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“…Data from questionnaires were used to measure the four factors of Protection Motivation Theory, namely, perceived severity of illness, perceived vulnerability, response-efficacy, and self-efficacy. A detailed analysis of the questionnaire results has been published separately [ 39 ]. It was found that fear, response efficacy, and self-efficacy were all significant predictors of intention to engage in social distancing behaviour.…”

Section: Comparison With Psychological Measuresmentioning

confidence: 99%

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Spontaneous social distancing in response to a simulated epidemic: a virtual experiment

et al. 2015

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BackgroundStudies of social distancing during epidemics have found that the strength of the response can have a decisive impact on the outcome. In previous work we developed a model of social distancing driven by individuals’ risk attitude, a parameter which determines the extent to which social contacts are reduced in response to a given infection level. We showed by simulation that a strong response, driven by a highly cautious risk attitude, can quickly suppress an epidemic. However, a moderately cautious risk attitude gives weak control and, by prolonging the epidemic without reducing its impact, may yield a worse outcome than doing nothing. In real societies, social distancing may arise spontaneously from individual choices rather than being imposed centrally. There is little data available about this as opportunistic data collection during epidemics is difficult. Our study uses a simulated epidemic in a computer game setting to measure the social distancing response.MethodsTwo hundred thirty participants played a computer game simulating an epidemic on a spatial network. The player controls one individual in a population of 2500 (with others controlled by computer) and decides how many others to contact each day. To mimic real-world trade-offs, the player is motivated to make contact by being rewarded with points, while simultaneously being deterred by the threat of infection. Participants completed a questionnaire regarding psychological measures of health protection motivation. Finally, simulations were used to compare the experimentally-observed response to epidemics with no response.ResultsParticipants reduced contacts in response to infection in a manner consistent with our model of social distancing. The experimentally observed response was too weak to halt epidemics quickly, resulting in a somewhat reduced attack rate and a substantially reduced peak attack rate, but longer duration and fewer social contacts, compared to no response. Little correlation was observed between participants’ risk attitudes and the psychological measures.ConclusionsOur cognitive model of social distancing matches responses to a simulated epidemic. If these responses indicate real world behaviour, spontaneous social distancing can be expected to reduce peak attack rates. However, additional measures are needed if it is important to stop an epidemic quickly.

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Section: Comparison With Psychological Measuresmentioning

confidence: 99%

“…Further work is needed to investigate the reasons for this. Some possible explanations are discussed in [ 28 ] and [ 39 ].…”

Section: Comparison With Psychological Measuresmentioning

confidence: 99%

Spontaneous social distancing in response to a simulated epidemic: a virtual experiment

et al. 2015

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“…β, γ and p interaction are infection recovery and interaction avoiding probabilities, respectively. Probability of interaction correspond to the social distancing [4]. When the information of severity of the results of infection reaches an individual, the individual tries to avoid interaction with the neighbors.…”

Section: Spread Of Infectionmentioning

confidence: 99%

“…In the contact layer, the interactions of the individuals result in the spread of infection, while in the second layer, the information on the contagiousness of the disease motivates the individuals to take preventive measures. The preventive measures can be in two categories: vaccination and social distancing [4].…”

Section: Introductionmentioning

confidence: 99%

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The Effects of Diffusion of Information on Epidemic Spread --- A Multilayer Approach

Gündüç

2019

Acta Phys. Pol. B

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In this work, the aim is to study the spread of a contagious disease and information on a multilayer social system. The main idea is to find a criterion under which the adoption of the spreading information blocks or suppresses the epidemic spread. A two-layer network is the base of the model. The first layer describes the direct contact interactions, while the second layer is the information propagation layer. Both layers consist of the same nodes. The society consists of five different categories of individuals: susceptibles, infective, recovered, vaccinated and precautioned. Initially, only one infected individual starts transmitting the infection. Direct contact interactions spread the infection to the susceptibles. The information spreads through the second layer. The SIR model is employed for the infection spread, while the Bass equation models the adoption of information. The control parameters of the competition between the spread of information and spread of disease are the topology and the density of connectivity. The topology of the information layer is a scale-free network with increasing density of edges. In the contact layer, regular and scale-free networks with the same average degree per node are used interchangeably. The observation is that increasing complexity of the contact network reduces the role of individual awareness. If the contact layer consists of networks with limited range connections, or the edges sparser than the information network, spread of information plays a significant role in controlling the epidemics.

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The impact of social distancing on community case count in the United States: Testing the efficacy of protection motivation theory during early stages of the COVID‐19 pandemic

Yeom

Stewart

2021

Risk Hazard & Crisis Pub Pol

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Centuries of practice and an array of public health literature support social distancing (SD), or selfquarantine, as a valuable nonpharmaceutical intervention. To convince individuals to engage in behaviors that limit infection, public health professionals communicate risk and hazard based on application of protection motivation theory (PMT). The COVID-19 pandemic presents an opportunity to explore the efficacy of PMT in the context of a novel coronavirus with unique public health implications. We test an integrative conceptual model of social distancing compliance in U.S. counties and examine the mediating impact of SD on community spread of infection. We find that PMT does impact individual behavior, observing that the proportion of vulnerable populations affects social distancing compliance. However, actions to protect individual health are made within the context of economic concerns and priorities. While results indicate that PMT influences behavior, the expected relationship between that behavior and spread of disease in the community is not found. We do not repudiate SD or the value of PMT, but we suggest that these results may indicate that communication of risk in the context of COVID-19 may need community, as well as individual, framing.

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Protection motivation theory and social distancing behaviour in response to a simulated infectious disease epidemic

Cited by 105 publications

References 14 publications

Spontaneous social distancing in response to a simulated epidemic: a virtual experiment

Spontaneous social distancing in response to a simulated epidemic: a virtual experiment

The Effects of Diffusion of Information on Epidemic Spread --- A Multilayer Approach

The impact of social distancing on community case count in the United States: Testing the efficacy of protection motivation theory during early stages of the COVID‐19 pandemic

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