Following the WHO’s declaration of the pandemic in March 2020, COVID-19 has transitioned into an endemic phase after mass outbreaks and variants, leading South Korea to downgrade COVID-19 from a Class 2 to a Class 4 infectious disease as of August 3...
Following the WHO’s declaration of the pandemic in March 2020, COVID-19 has transitioned into an endemic phase after mass outbreaks and variants, leading South Korea to downgrade COVID-19 from a Class 2 to a Class 4 infectious disease as of August 31, 2023. Nevertheless, COVID-19 vaccination is expected to continue as a seasonal immunization program to prevent severe illness and death among high-risk groups.
While surveys on uptake intention for upcoming vaccinations can serve as a basis for predicting vaccine demand and prioritizing public health interventions, a gap often exists where intention does not reliably predict actual behavior in vaccination, potentially reducing the effectiveness of interventions designed based on reported intentions. Conversely, approaches that categorize individuals’ attitudes based solely on vaccination status have limitations in addressing cases where individuals without uptake intention receive vaccines due to social influences. Previous studies are limited by a lack of timeliness, reliance on self-reported data, or a fragmentary analysis of the intention-behavior gap. Therefore, this study aims to investigate factors influencing COVID-19 vaccine uptake intention-behavior patterns by linking survey data with COVID-19 vaccination records from the Korea Disease Control and Prevention Agency (KDCA).
The data source was the third and fifth waves of the Korea Seroprevalence Study of Monitoring of SARS-CoV-2 Antibody Retention and Transmission (K-SEROSMART). Study participants were 3,835 adults who reported their uptake intention for the 2023-2024 season and had verified vaccination records. The dependent variable comprised four patterns combining COVID-19 vaccine uptake intention and actual uptake behavior: inclined actors, inclined abstainers, disinclined actors, and disinclined abstainers. Independent variables included sociodemographic, health-related, COVID-19-related experience, and psychological factors. To identify the influencing factors for each pattern, a weighted multinomial logistic regression analysis was performed, setting each of the four patterns as a reference group to enable comprehensive comparisons. Additionally, a sensitivity analysis on influenza vaccination for the same season was conducted to confirm the generalizability of the findings. The analysis results are as follows.
First, among 3,835 adults, 15.9% were identified as inclined actors, 43.8% as inclined abstainers, 2.1% as disinclined actors, and 38.1% as disinclined abstainers. Second, compared to the inclined actors, the inclined abstainers were significantly associated with higher education, higher annual income, and non-uptake in the previous season. The disinclined actors showed a significant association with previous non-uptake. The disinclined abstainers were associated with higher education, higher annual income, self-employment, previous non-uptake, and complacency (a complacent attitude toward immunity levels and disease risk).
These findings confirm that the composition and magnitude of influencing factors differ across COVID-19 vaccine uptake intention-behavior patterns. This suggests the need for differentiated public health interventions considering the characteristics of each pattern. For inclined abstainers, particularly those in higher SES groups, it is important to develop strategies that respect their autonomy in health decisions while helping them act on their intention. For disinclined actors, the possibility of vaccination driven by external pressures should be considered. For disinclined abstainers, in addition to strategies for inclined abstainers, messaging about vaccine necessity and disease risk would be effective.
By presenting policy intervention points for each COVID-19 vaccine uptake intention-behavior pattern, this study is expected to provide empirical evidence for establishing tailored public health interventions. However, there are limitations including potential selection bias due to restricting the sample to longitudinal study participants, the small proportion of disinclined actors (2.1%), the approximate six-month interval between the uptake intention survey and actual uptake, and the inability to capture COVID-19 infection history after August 31, 2023. Despite these limitations, this study is significant as it provides practical evidence for vaccination policy and tailored intervention design in the endemic phase by identifying the factors influencing COVID-19 vaccine uptake intention-behavior patterns through the linkage of representative community-based survey data and vaccination records from the KDCA.