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Predicting vaccine uptake during COVID-19 crisis: A motivational approach.

ABSTRACT: The present research examined which motivational factors contribute to individuals' intention to take a vaccine that protects against SARS-CoV-2-virus and their self-reported vaccine uptake several months later. The role of different types of motivation was investigated (i.e., autonomous and controlled regulation) as well as vaccine distrust and effort to obtain a vaccine. Across two large-scale cross-sectional (N = 8887) and longitudinal (N = 6996) studies and controlling for various covariates, autonomous motivation and distrust-based amotivation contributed positively and negatively, respectively, to a) concurrent vaccination intentions, b) self-reported vaccination and c) subsequent subscription to a waitlist to obtain a vaccine. Participants' infection-related risk perception predicted more positive vaccination outcomes through fostering greater autonomous motivation for vaccination and lower distrust, whereas pandemic-related health concerns failed to yield such adaptive effects. The results emphasize the importance of fostering autonomous motivation for vaccination and handling distrust.

SUBMITTER: Schmitz M

PROVIDER: S-EPMC8626229 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Predicting vaccine uptake during COVID-19 crisis: A motivational approach.

Schmitz Mathias M Luminet Olivier O Klein Olivier O Morbée Sofie S Van den Bergh Omer O Van Oost Pascaline P Waterschoot Joachim J Yzerbyt Vincent V Vansteenkiste Maarten M

Vaccine 20211127 2

The present research examined which motivational factors contribute to individuals' intention to take a vaccine that protects against SARS-CoV-2-virus and their self-reported vaccine uptake several months later. The role of different types of motivation was investigated (i.e., autonomous and controlled regulation) as well as vaccine distrust and effort to obtain a vaccine. Across two large-scale cross-sectional (N = 8887) and longitudinal (N = 6996) studies and controlling for various covariates ...[more]

PMID: 34961635

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Project description:Rationale Due to lack of vaccine or cure, the COVID-19 pandemic presents a threat to all human beings, undermining people's basic sense of safety and increasing distress symptoms. Objective To investigate the extent to which individual resilience, well-being and demographic characteristics may predict two indicators of Coronavirus pandemic: distress symptoms and perceived danger. Method Two independent samples were employed: 1) 605 respondents recruited through an internet panel company; 2) 741 respondents recruited through social media, using snowball sampling. Both samples filled a structured online questionnaire. Correlations between psychological/demographic variables and distress and perceived danger were examined. Path analysis was conducted to identify predictive indicators of distress and perceived danger. Results Significant negative correlations were found between individual/community resilience and sense of danger (?0.220 and ?0.255 respectively; p < .001) and distress symptoms (- 0.398 and ?0.544 respectively; p < .001). Significant positive correlations were found between gender, community size, economic difficulties and sense of danger (0.192, 0.117 and 0.244 respectively; p < .001). Gender and economic difficulties also positively correlated with distress symptoms (0.130 and 0.214 respectively; p < .001). Path analysis revealed that all paths were significant (p < .008 to .001) except between family income and distress symptoms (p = .12). The seven predictors explained 20% of sense of danger variance and 34% the distress symptoms variance. The most highly predictive indicators were the two psychological characteristics, individual resilience, and well-being. Age, gender, community size, and economic difficulties due to COVID-19 further add to predicting distress, while community and national resilience do not. . Conclusions Individual resilience and well-being have been found as the first and foremost predictors of COVID-19 anxiety. Though both predictors are complex and may be influenced by many factors, given the potential return of COVID-19 threat and other future health pandemic threats to our world, we must rethink and develop ways to reinforce them. Highlights • Current study was conducted during a peak in the COVID-19 pandemic, 1st wave.• Two pandemic effects, distress symptoms and perceived danger, were examined.• Best pandemic effect psychological predictors: individual resilience well-being.• Best pandemic effect’ demographic predictors: age, gender, economic difficulties.• Community and national resilience did not significantly add to predictions.

Dataset Information

Predicting vaccine uptake during COVID-19 crisis: A motivational approach.

Publications

Predicting vaccine uptake during COVID-19 crisis: A motivational approach.

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