Predicting intention to receive a seasonal influenza vaccination using Protection Motivation Theory

Abstract

Rationale: Seasonal influenza vaccination rates are below the recommended targets, contributing to significant preventable harms. Protection Motivation Theory (PMT), a widely applied model of motivation to respond to threats, may provide some insights into strategies to increase the rate of vaccine uptake. However, previous research has omitted some of the proposed predictors of intention when applying this model to vaccination. Objective: The aim of the study is to assess the utility of the PMT in predicting intention to obtain the seasonal influenza vaccine. This study will be the first to examine the role of all six PMT constructs in predicting intention to receive the seasonal influenza vaccine. Method: A cross-sectional study of 547 US residents was conducted using Amazon MTurk. Results: All constructs show significant bivariate correlations in the direction expected from the prior literature. However, examination of the theory within a linear regression model found that perceived costs of vaccinating (response costs) did not uniquely account for variance in intention. All other components, perceived severity of and susceptibility to influenza, the perceived benefits of not vaccinating (maladaptive response rewards), the self-efficacy to vaccinate, and the perceived efficacy of vaccinating in preventing influenza (response efficacy) were unique predictors of intention. Overall, the PMT accounted for 62% of the variance in intention to vaccinate. Conclusions: The study is the first to investigate influenza vaccination using all six theorised predictors of intention from the PMT. The findings highlight the importance of the simultaneous inclusion of all components of the model in assessing their potential utility as targets for intervention. Importantly, the results identify under-utilised constructs in the promotion of vaccine uptake, such as maladaptive response rewards, which should be considered targets for future intervention.

Preprint of "COVID-19 Increases Online Emotional and Health-Related Searches"

“…The present findings are in line with the fear appeal approach that threat of a disease arouses fear emotions, which in turn motivates people to seek for behavioral changes and gain health knowledge (Floyd et al, 2000;Kok et al, 2014;Ling et al, 2019;Rogers & Prentice-Dunn, 1997). Moreover, the present study used a socioecological factor (prevalence rate of COVID-19) to predict psychological reactions, which corroborates the perspective of socioecological psychology (Du, Chi, & Li, 2018;Oishi, 2014), and demonstrates that the prevalence rate of a disease can be considered as a direct psychological threat and useful for changing health-related intentions.…”

“…More specifically, we hypothesized that searches related to fear-related emotions would explain associations of cases of COVID-19 with searches on protective behaviors, health knowledge, and maladaptive behaviors. This prediction is consistent with fear appeal theories, which posit that threat of a disease elicits fear, which in turn motivates people to initiate behavioral changes and improve health knowledge (Floyd, Prentice Dunn, & Rogers, 2000;Kok, Bartholomew, Parcel, Gottlieb, & Fern ndez, 2014;Ling, Kothe, & Mullan, 2019;Rogers & Prentice-Dunn, 1997). There are several reasons which justify our theoretical model (COVID-19 prevalence à fear à health-related knowledge and behavioral outcomes) we posited.…”

What drives unverified information sharing and cyberchondria during the COVID-19 pandemic?

“…The reasoning is that the two are featured in both HBM and PMT, and previous studies have found these constructs to be the significant predictors for health motivation during pandemic situations (Bish & Michie, 2010;Farooq et al, 2020). Perceived severity is defined as the individual's appraisal of the severity of the situation with regards to health consequences (Ling et al, 2019) whereas perceived susceptibility is an appraisal of the probability of being vulnerable in the given situation (Ling et al, 2019). In addition to the theories explaining health behaviours, a theoretical viewpoint accounting for the impact of technology is also necessary.…”

“…Construct and Source Item Information Overload (Whelan et al, 2020a) IO1: I am often distracted by the excessive amount of information on social medial about Coronavirus (COVID-19) IO2: I find that I am overwhelmed by the amount of information that I process on a daily basis from social media about Coronavirus (COVID-19) IO3: I receive too much information regarding the Coronavirus (COVID-19) pandemic to form a coherent picture of what's happening Perceived susceptibility (Ling et al, 2019;Farooq et al, 2020)…”

Social Influences on Influenza Vaccination Decision Among Senior Citizens in Taiwan, South Korea, and Switzerland

“…Cognitive factors figuring in risk calculation (Galvani et al, 2007;Xia and Liu, 2013;Commodari, 2017;Ling et al, 2018) are well established predictors of vaccination behavior [e.g., for the swine flu pandemic of 2009: (Eastwood et al, 2010;Liao et al, 2011;Myers and Goodwin, 2011); for different vaccinations at once: (Streefland, 2001;Francois et al, 2005); for influenza: Coups, 1999, 2006), and for immunizing Taiwanese children against influenza: (Chen et al, 2015)]. A recent systematic review pertaining to all of Asia singled out safety concerns and concerns about efficacy of the flu vaccination as important predictors (Sheldenkar et al, 2019), but concentrating on them misses an important point.…”