Abstract
-
Objectives
This study aimed to assess the impact of high-level versus low-level construal messages about the coronavirus disease 2019 (COVID-19) Vaccine Injury Compensation Program (CVICP) on public attitudes toward the program and COVID-19 vaccination.
-
Methods
A randomized controlled experimental design was employed. Adults aged 18 to 64 residing in the Republic of Korea were randomly assigned to either an experimental group (high-level construal message) or a control group (low-level construal message). Both groups viewed a 2-minute video about the CVICP, with construal level as the sole variable. Pre- and post-intervention questionnaires evaluated attitudes toward the CVICP and COVID-19 vaccination, including satisfaction, perceived necessity, and perceived effectiveness in enhancing vaccine acceptance. Data were analyzed using the paired t-test, repeated measures 2-way analysis of variance, and multiple linear regression.
-
Results
The experimental group showed statistically significant improvements across all 6 attitude measures following exposure to the high-level construal message. By contrast, the control group demonstrated significant improvement in only 3 attitudes: satisfaction with the CVICP, willingness to recommend vaccination, and willingness for future vaccination. A significant difference between groups was observed for perceived effectiveness of the CVICP in enhancing vaccine acceptance (p=0.01), with high-level construal messaging being more impactful.
-
Conclusion
High-level construal messages are more effective than low-level messages in shaping public perceptions and addressing vaccine hesitancy. Policymakers and health authorities should incorporate high-level construal elements into communication strategies to build trust and support for vaccination programs.
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Keywords: Compensation and redress; COVID-19; Health communication; Psychological distance; Vaccine hesitancy
Introduction
Since its emergence in December 2019, the coronavirus disease 2019 (COVID-19) pandemic has posed a global challenge, prompting a wide array of policy responses to manage and mitigate its impact. In the Republic of Korea, COVID-19 vaccine approval began in February 2021, launching a nationwide vaccination campaign. Despite these efforts, vaccine hesitancy has remained a substantial barrier, fueled by concerns over rapid vaccine development, accelerated authorization, and perceived insufficiency of long-term safety data. Such hesitancy has impeded both individual vaccination and the broader attainment of community or national herd immunity [
1].
To address these issues, the Republic of Korea implemented the COVID-19 Vaccine Injury Compensation Program (CVICP) in 2021, subsequently enhancing it by relaxing compensation criteria, expanding coverage, and streamlining claims processes [
2]. Nevertheless, a 2023 survey found that most adults remained unaware of the CVICP, perceived it as the least effective COVID-19-related policy, and viewed it as unreliable [
3]. Although the government expanded the CVICP in July 2023, public skepticism persisted into 2024. Given the substantial investment and its implications for vaccine hesitancy, effective communication strategies are urgently needed.
According to the theory of planned behavior, individuals’ attitudes are predictive of their behavioral intentions [
4]. Similarly, population attitudes toward policy are critical determinants of program participation in democratic societies. Positive attitudes enhance compliance and, consequently, policy effectiveness. Cognitive Appraisal Theory further suggests that individuals assess policies based on their perceived impact, controllability, and relevance, a framework used by Li’s team to evaluate perceived severity, controllability, and knowledge of disease [
5,
6]. In the Republic of Korea, Choi et al. [
7] measured ‘perceived value’ and ‘patient satisfaction’ to gauge attitudes toward healthcare interventions. Drawing from these theories and studies, public attitudes can be conceptualized in terms of perceived severity, value (explained by perceived necessity and effectiveness), and satisfaction. Knowledge is also an important determinant of attitude. However, in this study, all participants received the same program information before attitudes were measured. Thus, attitudes toward the CVICP were operationally defined as a composite of satisfaction, perceived necessity, and perceived effectiveness.
Recognizing the need for strategies to foster favorable attitudes towards the CVICP—especially in light of increased funding and expansion efforts— the importance of strategic communication is clear. Effective communication strategies are crucial for building public support for policies, particularly given current deficits in awareness and trust surrounding the CVICP. Construal level theory (CLT) offers a valuable framework for designing such public communication messages [
8].
CLT posits that people mentally represent events differently depending on their psychological distance: events perceived as close are construed concretely, while distant events are construed more abstractly [
9]. This framework suggests that both perceived distance and construal level are mutually influential. Prior studies have shown that varying the construal level in health-related messages can significantly affect persuasiveness and behavioral outcomes [
10,
11]. Thus, adjusting the construal level of CVICP messages may effectively alter public attitudes toward the program.
Currently, the Korea Disease Control and Prevention Agency (KDCA) communicates information about the CVICP primarily through its website, detailing administrative procedures, eligibility requirements, documentation, and compensation timelines [
12]. However, these communications predominantly use concrete, procedural language, lacking higher-level framing that highlights the program’s rationale and social benefits. Framing the CVICP in more abstract terms—emphasizing social solidarity—may resonate more strongly in the Republic of Korea, where collective responsibility is a key element of the 5C model of vaccine hesitancy (confidence, complacency, constraints, calculation of risk, and collective responsibility) [
3]. Given the KDCA’s current focus on concrete, procedural messaging, this low-construal style was selected as the control condition to reflect real-world public communication.
This study aimed to examine how different message framings (specifically, high-level versus low-level construal messages) affect attitudes toward the CVICP. In particular, it investigates how these messages influence public perceptions of the CVICP and their willingness to accept COVID-19 vaccination.
Construal Level Theory
CLT, developed by Trope and Liberman [
9], provides a framework for understanding how individuals mentally represent events according to their psychological distance. The theory differentiates between high-level construals, which are abstract, generalized, and goal-oriented, and low-level construals, which are concrete, detailed, and context-dependent. Psychological distance may arise from temporal, spatial, social, or hypothetical sources, thereby shaping whether individuals focus on the “why” (high-level) or the “how” (low-level) aspects of an issue.
In public policy settings, including health programs, CLT offers valuable insight into variations in public engagement and the formation of attitudes. When a program such as the CVICP is presented using high-level construals—emphasizing concepts like fairness, collective responsibility, or public health equity—it may better align with the broader values of society. Conversely, low-level construals present specific operational or procedural details, such as compensation steps or eligibility requirements, which may be more immediately relevant for individuals directly affected.
Prior research supports the utility of CLT in designing public information campaigns. Park et al. [
8] demonstrated that construal-level fit between message framing and an individual’s cognitive orientation significantly enhances the effectiveness of health-related messaging. Similarly, studies in behavioral medicine and nutrition have demonstrated that high-level construals increase the perceived importance of preventive behaviors, while low-level construals may facilitate clarity and promote immediate action [
6,
7].
Applying CLT to the CVICP is especially pertinent given the abstract and complex nature of compensation policies, as well as the generally low public awareness of their existence and function. The CVICP operates within socio-political and legal frameworks that often appear remote to ordinary citizens, potentially reducing trust and perceived relevance. Utilizing high-level construal messages may elevate the program’s perceived legitimacy and moral rationale. This strategy is particularly compatible with values central to Korean public health culture, such as social solidarity and institutional trust, which have been identified as key antecedents of vaccine acceptance in the 5C model [
9].
In summary, CLT provides a scientifically grounded foundation for tailoring message strategies related to the CVICP. Its application in this study offers empirical evidence regarding how abstract versus concrete messaging can alter public attitudes and help mitigate vaccine hesitancy (
Figure 1).
Materials and Methods
Participants
An online survey was conducted by Hankook Research Co. Ltd., which managed both data collection and the de-identification of respondents. The survey commenced on April 12, 2024. Eligible participants were adults aged 18 to 64 years residing in the Republic of Korea who could read and understand Korean. Individuals were excluded if they declined to participate or had conditions likely to affect study outcomes. The sample size was determined to be 520 adults, providing 90% power to detect a 30% difference in attitude ratings between the experimental and control groups, with an alpha level of 0.05.
Intervention
The study was designed to evaluate the effects of different construal levels in messaging about the CVICP on attitudes toward both the program and COVID-19 vaccination. A professional communication company was contracted to produce 2 short videos, with construal level as the sole manipulated variable. All other video components—including background music, color scheme, and voice tone—were held constant to minimize confounding. Across multiple planning sessions, the research team clarified the study’s aims, detailed desired content, and suggested visual elements for inclusion. Narrative scripts were developed collaboratively by the research team and the communication company, ensuring alignment with both research objectives and communication best practices. The company produced initial video drafts, which were revised in consultation with the research team through several iterations until final approval. Throughout the process, oversight by a communication expert and the research team ensured consistency and quality. A pilot test was conducted with 12 participants recruited from the survey company’s panel to assess the clarity and feasibility of the intervention. Participants were asked whether the survey content was understandable, whether the videos were clear, and if they experienced any confusion or difficulty completing the survey. All participants completed the survey in full, and there were no dropouts. Feedback confirmed that both the survey and video content were clear and appropriate, validating the suitability of the intervention materials for the target audience.
The experimental group received a video framed at a high construal level, emphasizing the CVICP’s fundamental values, abstract principles, and overarching messages (
Figure S1). Key points included (1) The Korean government operates the vaccine injury compensation program (VICP) as part of its responsibility to ensure public safety, particularly concerning unavoidable adverse effects from COVID-19 vaccination; (2) Despite the clear public health benefits of vaccination, some individuals inevitably experience adverse effects; (3) Vaccination is not only a personal health decision but also a contribution to herd immunity and societal well-being. On the principle of social solidarity, the government compensates individuals who suffer harm from vaccines administered for public purposes; (4) The government distributes the risk of adverse events, ensuring the burden does not fall solely on the individual, but is shared collectively by society.
In contrast, the control group viewed a video at a low construal level, focusing on detailed, specific information and procedural content (
Figure S2). Key messages included (1) Submission of required documents is mandatory when applying for compensation, including a medical certificate, death certificate (if applicable), or a physician-issued diagnosis; (2) The compensation process begins when a healthcare institution, the vaccinated individual, or a guardian reports an adverse event, either through the institution or online. A claim is submitted to the local public health center, forwarded for preliminary review by the city or provincial governor, and finally sent to the KDCA for a final decision; (3) If the claimed medical expense is under 300,000 Korean won (KRW), the city or province manages the review independently; (4) Claims must be filed within 5 years from the date of injury, and the entire review process must be completed within 120 days of application submission; (5) Since 2021 and 2022, the scope of the compensation system has expanded. Previously, only cases involving out-of-pocket medical expenses exceeding 300,000 KRW were eligible. This threshold has now been removed, broadening access to compensation; (6) Additionally, to increase convenience for applicants, the application procedure has been made more flexible.
Procedure
A randomized controlled experimental design was employed. Participants accessed the study via a provided URL, gave informed consent, and completed questionnaires between April 12 and April 18, 2024. The intervention consisted of exposure to information about the CVICP. Participants randomly assigned to the experimental arm viewed a 2-minute video emphasizing the establishment of the CVICP using higher-level construal. In contrast, those in the control arm were shown a 2-minute video presenting information currently available on the KDCA website, representing lower-level construal. After viewing the assigned video, participants completed follow-up questionnaires designed to assess changes in their perceptions of the CVICP and vaccine-related attitudes. The overall study procedure is depicted in
Figure 2.
Recruitment was conducted via email or text invitation from the contracted research firm. Upon clicking the URL, participants were directed to an online platform where they first reviewed and agreed to an informed consent form. Following consent, they completed a baseline (pre-intervention) questionnaire that included demographic information, COVID-19 vaccination history, and baseline perceptions of the CVICP and COVID-19 vaccination.
After completing the baseline survey, participants were automatically and randomly allocated by the platform’s algorithm to 1 of 2 groups: the experimental group (high construal-level message) or the control group (low construal-level message). Participants then watched a 2-minute video, embedded directly within the survey platform. To ensure full exposure to the intervention, participants were required to view the entire video before proceeding. Immediately after viewing the video, participants completed a post-intervention questionnaire, which repeated the assessment of attitudes toward the CVICP and vaccination.
The survey was self-administered and designed to be completed in a single session, requiring approximately 10 minutes in total. The survey platform enforced data completeness by requiring responses to all questions before submission. No personally identifiable information was collected, thus ensuring participant anonymity.
Measures
The research team developed a questionnaire to collect demographic information, COVID-19 vaccination history and experiences, experience with adverse events following vaccination, knowledge and experience with the CVICP, and evaluations of the CVICP and COVID-19 vaccination (
Table 1). A pilot test was conducted to refine the questionnaire and ensure the clarity of its items.
Demographic data included socioeconomic status, age, gender, education level, occupation, household size, residential area, and perceived general health status. Additional items assessed experiences related to COVID-19, vaccination status, adverse effects following vaccination (either personally experienced or observed in acquaintances), and awareness and perceptions of the CVICP. Attitudes toward the CVICP—comprising satisfaction, perceived necessity, and perceived effectiveness in promoting vaccine acceptance—were measured, alongside perceived necessity of COVID-19 vaccination, willingness for future vaccination, and willingness to recommend vaccination [
13]. All attitude-related items were assessed using a 7-point Likert scale, ranging from “not at all” (1) to “strongly agree” (7).
Data Analysis
Data analysis was conducted using RStudio software ver. 2023.12.1+402 (Posit Software, PBC). Descriptive statistics were calculated for all variables. To test the hypothesis that attitudes toward the CVICP would differ between the experimental and control groups, paired t-tests were performed. Subsequently, repeated measures 2-way analysis of variance (ANOVA) was used to assess whether changes in the dependent variables differed between the groups over time. This ANOVA examined the effects of group (between-subjects), time (within-subjects), and their interaction. Multiple linear regression analyses were then conducted to determine whether significant differences in the dependent variables persisted between groups after controlling for demographic characteristics, COVID-19 infection history, vaccine uptake, prior adverse events, and CVICP awareness and experience, all of which might influence perceptions of the compensation system and COVID-19 vaccination [
14–
17]. We used a tiered approach: the paired t-test for within-group changes, ANOVA for group × time interaction, and regression to control for covariates and explore predictors of attitude change. This strengthened internal validity and interpretability.
Ethical Considerations
The study protocol was approved by the Institutional Review Board of Korea University Anam Hospital (IRB No: 2024 AN 0065). All procedures adhered to ethical standards for human experimentation and conformed to the principles outlined in the Helsinki Declaration of 1975, as revised in 2000.
Results
Participant Characteristics
Although the target sample size was 520, the final number of participants reached 526 due to simultaneous access to the study URL.
Table 2 summarizes the socio-demographic characteristics of the participants.
The sample was stratified by gender, age, and region. Office workers comprised the largest occupational group (36.5%), and 63.7% of respondents resided in large cities. In terms of health status, 49.0% reported their health as average. Households with 3 or more members accounted for 62.0% of the sample. There were no significant differences between the experimental and control groups in most socio-demographic variables, except for political tendency (p=0.003) and residential area (p=0.006). To address these differences, political ideology and residential area were included as covariates in the multiple linear regression analyses. This ensured that any observed effects of the intervention were independent of these socio-demographic factors. Additionally, sensitivity analyses were performed to confirm the robustness of the findings by excluding participants with extreme or outlier values in these variables.
Experience with COVID-19, the CVICP, and Attitudes Toward the CVICP and Vaccination
Table 3 provides details on participants’ experiences with COVID-19 vaccination and the CVICP. Overall, 78.1% of respondents reported a history of COVID-19 infection, and 94.3% had received at least 1 dose of a COVID-19 vaccine. The largest subgroup (35.9%) consisted of participants who had received 3 or more booster doses. The most frequently reported side effects following vaccination were fever and chills (34.5%), followed by localized pain, redness, or swelling at the injection site (28.8%). About a quarter of respondents reported no side effects. No significant differences were found between the experimental and control groups in terms of vaccine or CVICP experience. Awareness of the CVICP was reported by 52.1% of the experimental group and 49.8% of the control group, with no significant difference between groups (
p=0.601).
Table 3 also presents participants’ baseline attitudes toward the CVICP and COVID-19 vaccination. No significant differences were observed between the experimental and control groups for any of the measured attitudes, including satisfaction with the CVICP, perceived necessity of the CVICP, perceived effectiveness in enhancing vaccine acceptance, perceived necessity of COVID-19 vaccination, willingness to recommend COVID-19 vaccination, and willingness for future vaccination (all
p>0.05). These findings confirm that both groups had comparable baseline attitudes before the intervention, allowing for a fair assessment of the effects of the message frames.
Changes in Attitudes Toward the CVICP and COVID-19 Vaccination
In the experimental group, statistically significant improvements were observed across all 6 measured attitudes after exposure to the high-level construal message. For instance, satisfaction with the CVICP increased from mean (M)±standard deviation (SD)=3.63±1.38 to 4.27±1.30, t(262)=–8.18, p<0.001; and perceived effectiveness of the CVICP in enhancing vaccine acceptance increased from 4.99±1.40 to 5.26±1.23, t(262)=–3.64, p<0.001. Similarly, willingness to recommend vaccination rose from 4.74±1.65 to 4.91±1.64, t(262)=–2.74, p=0.01.
In the control group, improvements were limited to 3 areas: satisfaction with the CVICP (M=3.61 to M=4.32, t(262)=–8.77,
p<0.001), willingness to recommend COVID-19 vaccination (M=4.72 to M=4.83, t(262)=–1.98,
p=0.05), and willingness for future vaccination (M=4.59 to M=4.89, t(262)=–4.80,
p<0.001) (
Table 4).
Results from repeated measures 2-way ANOVA revealed significant main effects for time (pre- vs. post-intervention) across all attitudes (e.g., satisfaction with the CVICP: F(1, 524)=143.75,
p<0.001; willingness for future vaccination: F=48.71,
p<0.001) (
Table 5). However, interaction effects (group×pre–post) were significant only for “perceived effectiveness in enhancing vaccine acceptance” (F(1, 524)=7.29,
p=0.01), indicating that the experimental group experienced a significantly greater improvement on this measure compared to the control group.
Socio-demographic variables associated with each attitude variable were explored using multiple regression analysis. Variables that increased the explained variance (F-value) were retained in the final model. Even after adjusting for demographic factors, the experimental group showed a significant positive effect on “perceived effectiveness in enhancing vaccine acceptance” (β=0.28,
p=0.01). No other significant group effects were observed (
Tables 6,
7).
These results indicate that high-level construal messages significantly enhanced perceptions of the CVICP’s effectiveness in promoting vaccine acceptance compared to low-level construal messages. While both message types led to overall improvements in attitudes, high-level construal messaging had a more pronounced impact on perceptions of program effectiveness.
Discussion
The COVID-19 pandemic has necessitated rapid and effective policy responses worldwide. Although vaccines have been available in the Republic of Korea since early 2021, vaccine hesitancy continues to pose a significant barrier to achieving herd immunity. The CVICP was introduced to address these concerns by compensating for adverse events following vaccination. However, a 2023 survey revealed substantial gaps in public awareness and trust regarding the CVICP, highlighting the urgent need for strategic communication to shape public perceptions and support vaccination policies.
CLT, as a theoretical framework for message framing, offers valuable insights into strategies that can influence attitudes and behaviors. The present study demonstrates that varying the construal level of CVICP messages leads to differing changes in policy attitudes toward both the CVICP and vaccination. High-level construal messages significantly improved participants’ perceptions of the CVICP’s effectiveness in enhancing vaccine acceptance and produced broader improvements across all measured attitudes. In contrast, low-level construal messages led to more limited gains, improving only satisfaction with the CVICP, willingness to recommend COVID-19 vaccination, and willingness to receive additional vaccination.
These findings partially contradict previous research on the general effects of CLT in health messaging, which suggested that messages framed to reduce psychological distance (low-level construal) are typically more persuasive [
18]. Instead, this study highlights the potential for high-level construal messages to drive broader attitudinal shifts, particularly in contexts where abstract values such as social solidarity and institutional trust are central.
To our knowledge, this is the first empirical investigation of how different construal levels in messaging affect attitudes toward the CVICP and vaccination. While extensive research has explored the impact of various message frames on vaccine uptake, little is known about how messaging influences attitudes toward VICPs specifically. Schoch-Spana et al. [
19] have indicated that raising awareness and understanding of the vaccine safety system can positively influence public attitudes toward vaccination by addressing concerns about potential vaccine injuries. Transparent communication regarding eligibility criteria, processes, and benefits of compensation programs has been shown to foster trust and confidence in vaccination efforts [
20]. When individuals understand that a reliable system exists to address vaccine injuries, their confidence in vaccines grows—an effect crucial for mitigating vaccine hesitancy and promoting vaccine acceptance. The present study extends this knowledge, showing that high-level construal messages emphasizing the broader purpose and societal benefits of compensation programs are particularly effective in improving attitudes toward the CVICP.
This study offers both theoretical and practical contributions. Theoretically, it extends the application of CLT to health policy communication. While CLT has been widely used to study health behaviors and patient decision-making, this research is among the first to apply it to public communication about compensatory health policies like VICPs. The findings illustrate how message abstraction can influence public perceptions of institutional responsibility and highlight the importance of tailoring communication strategies to enhance confidence in vaccination programs. Additionally, this study suggests that different components of attitudes, such as satisfaction, perceived necessity, and perceived effectiveness, may vary in their sensitivity to abstract framing, offering new insights for message targeting within the CLT framework. Practically, these findings provide evidence-based recommendations for governments on how to frame communication about vaccine injury compensation. Abstract, value-based messaging may better foster institutional trust and vaccine confidence than procedural, detail-heavy information. In the context of vaccine hesitancy, this study demonstrates that not only the content, but also the construal level of communication, can influence attitudes. These results have important implications for addressing vaccine hesitancy and strengthening trust in public health infrastructure, both during pandemics and in other health emergencies.
There are several limitations of the present study that warrant consideration. This study assessed immediate attitudinal changes following the intervention; thus, the long-term effects on attitudes toward the CVICP and vaccination remain unknown. This limits insight into the persistence of observed attitude changes. Furthermore, the study’s generalizability may be constrained by cultural factors specific to the Republic of Korea, which could influence both the framing and reception of CVICP messages. Future research should assess whether these effects persist over time and replicate these findings in different cultural and policy contexts to determine the broader applicability of construal-level messaging strategies.
Despite these limitations, the study’s findings provide valuable insights for public health communication aimed at reducing vaccine hesitancy and increasing vaccine acceptance. By adopting evidence-based message frames and supporting further research, policymakers and health authorities can improve public trust and confidence in vaccination programs, thereby contributing to the overall success of immunization efforts.
Conclusion
This study highlights the importance of strategic communication in shaping public attitudes toward vaccination policies, with a specific focus on the CVICP. In the present study, which applied CLT, we demonstrated that high-level construal messages are more effective than low-level messages in improving perceptions of the CVICP’s effectiveness in enhancing vaccine acceptance. The results suggest that while both high-level and low-level construal messages can positively influence attitudes toward the CVICP and vaccination, high-level messages are particularly effective at highlighting the program’s broader societal role in supporting vaccine acceptance.
Policymakers and health authorities should consider integrating high-level construal elements into communication strategies about VICPs to enhance public understanding and support. Such strategies should focus on conveying the fundamental values of these programs, such as equity and social solidarity, alongside clear procedural information about compensation processes.
Future research should examine the long-term impact of these messaging strategies on public attitudes and behaviors, as well as their applicability to other public health policies and contexts. By further refining and validating these communication approaches, we can more effectively address vaccine hesitancy and support the successful implementation of vaccination programs.
HIGHLIGHTS
• High-level construal messages, emphasizing abstract values and collective benefits, significantly improved perceptions of the COVID-19 Vaccine Injury Compensation Program’s effectiveness in promoting vaccine acceptance, outperforming low-level construal messages.
• The findings suggest that integrating high-level construal elements into public health messaging can enhance vaccine acceptance by fostering trust, highlighting social solidarity, and promoting the broader societal benefits of vaccination policies.
• This study provides actionable recommendations for policymakers and public health authorities to improve communication strategies, thereby ensuring more effective engagement with the public regarding vaccination programs.
Supplementary Material
Article information
Ethics Approval
The study protocol received approval from the Institutional Review Board of Korea University Anam Hospital (IRB No: 2024 AN 0065). All procedures were conducted in accordance with ethical standards on human experimentation and with the Helsinki Declaration of 1975, as revised in 2000.
Conflicts of Interest
Jong-Koo Lee has been the editor-in-chief of Osong Public Health and Research Perspectives since October 2021. Young June Choe was not involved in the editorial process or review of this manuscript, despite being a member of the Editorial Board of the Osong Public Health and Research Perspectives. The other authors have no potential conflicts of interest to disclose.
Funding
This study was supported by KDCA.
Availability of Data
All data analyzed during this study are included in this published article. Additional data may be requested from the corresponding author.
Authors’ Contributions
Conceptualization: JM, YJC, JKL; Data curation: JM, DK; Formal analysis: JM; Funding acquisition: JKL; Investigation: JM, YJC, CRK, JKL; Methodology: JM, SHJ; Project administration: TK; Supervision: JKL; Writing–original draft: JM, YJC; Writing–review & Editing: all authors. All authors read and approved the final manuscript.
Additional Contributions
Hankook Research Co. Ltd. provided data collection services. Hapoom Studio produced the video messages used in the study.
Figure 1.Conceptual diagram of construal level theory as applied to message framing for the COVID-19 Vaccine Injury Compensation Program.
Figure 2.Procedure of the randomized controlled experiment.
Table 1.Measurement items of the questionnaire
Table 1.
| Category |
Variable |
Item description |
Response format/scale |
| Demographics |
Gender |
What is your gender? |
1=Male, 2=female |
|
Age |
What is your birth year? |
Open numeric |
|
Education level |
What is your highest level of education completed? |
1=Middle school or less, 2=high school, 3=college, 4=graduate school |
|
Self-rated health |
How would you rate your overall health? |
1=Very poor, 5=very good |
|
Household size |
How many people live in your household (including yourself)? |
1=One, 2=two, 3=three or more |
|
Monthly household income |
What is your household’s average monthly income? |
1=<1 M KRW, 2=1–3 M, 3=3–5 M, 4=>5 M |
|
Occupation |
What is your current occupation? |
1=Production, 2=office, 3=sales/service, 4=health/medical, 5=homemaker, 6=other (e.g., student, military) |
|
Region |
Where do you currently live? |
1=Large city, 2=small/medium city, 3=rural |
|
Political orientation |
What is your political ideological tendency? |
1=Liberal, 2=moderate, 3=conservative, 4=no comment |
| COVID-19 experience |
COVID-19 infection |
Have you ever been infected with COVID-19? |
1=No, 2=yes |
|
Vaccination status |
What is your COVID-19 vaccination status? |
1=None, 2=partial primary series, 3=completed primary, 4=1st booster, 5=2nd booster, 6=3rd or more boosters |
|
Adverse events after vaccination |
What adverse events did you experience after COVID-19 vaccination? (multiple responses allowed) |
1=None, 2=injection site pain/swelling/bruising, 3=fever/chills, 4=fatigue/drowsiness, 5=headache/dizziness, 6=muscle pain/cramps, 7=menstrual irregularities, 8=nausea/vomiting, 9=loss of appetite, 10=diarrhea, 11=other (free text) |
| CVICP awareness & experience |
Awareness of CVICP |
Are you aware of the CVICP? |
1=No, 2=yes |
|
Experience with CVICP |
Have you or someone you know applied for the compensation program? |
1=no, 2=yes (from methods; inferred) |
| Attitudes toward the CVICP |
Satisfaction |
I am satisfied with the government’s compensation program. |
7-Point Likert scale (1=not at all, 7=strongly agree) |
|
Perceived necessity |
The compensation program is necessary for our society. |
7-Point Likert scale |
|
Perceived effectiveness |
The program helps improve vaccine acceptance. |
7-Point Likert scale |
| Attitudes toward COVID-19 vaccination |
Perceived necessity |
COVID-19 vaccination is necessary for our society. |
7-Point Likert scale |
|
Willingness to recommend |
I would recommend COVID-19 vaccination to others. |
7-Point Likert scale |
|
Willingness to receive |
I am willing to receive COVID-19 vaccination in the future. |
7-Point Likert scale |
Table 2.Characteristics of the survey respondents
Table 2.
| Socio-demographic characteristic |
Experimental group (n=263) |
Control group (n=263) |
χ2 (p) |
| Sex |
|
|
0.37 (0.541) |
| Male |
131 (49.8) |
138 (52.5) |
|
| Female |
132 (50.2) |
125 (47.5) |
|
| Age (y) |
|
|
6.71 (0.152) |
| 18–29 |
49 (18.6) |
61 (23.2) |
|
| 30–39 |
59 (22.4) |
39 (14.8) |
|
| 40–49 |
66 (25.2) |
61 (23.2) |
|
| 50–59 |
59 (22.4) |
71 (27.0) |
|
| 60–64 |
30 (11.4) |
31 (11.8) |
|
| Education |
|
|
0.25 (0.969) |
| Middle school or lower education |
1 (0.4) |
1 (0.4) |
|
| High school or equivalent |
53 (20.2) |
55 (20.9) |
|
| Undergraduate education |
179 (68.1) |
174 (66.2) |
|
| Postgraduate education |
30 (11.4) |
33 (12.5) |
|
| Political ideological tendency |
|
|
13.93 (0.003**) |
| Liberal |
75 (28.5) |
78 (29.7) |
|
| Middle |
117 (44.5) |
121 (46.0) |
|
| Conservative |
47 (17.9) |
59 (22.4) |
|
| No comment |
24 (9.1) |
5 (1.9) |
|
| Perceived general health status |
|
|
1.08 (0.898) |
| Very bad |
2 (0.8) |
2 (0.8) |
|
| Bad |
28 (10.6) |
24 (9.1) |
|
| Not good, not bad |
131 (49.8) |
127 (48.3) |
|
| Good |
90 (34.2) |
100 (38.0) |
|
| Very good |
12 (4.6) |
10 (3.8) |
|
| No. of household members |
|
|
0.28 (0.87) |
| 1 |
42 (16.0) |
43 (16.3) |
|
| 2 |
60 (22.8) |
55 (20.9) |
|
| ≥3 |
161 (61.2) |
165 (62.7) |
|
| Household income (million KRW) |
|
|
3.27 (0.352) |
| 1 or below |
9 (3.4) |
12 (4.6) |
|
| 1–3 |
52 (19.8) |
67 (25.4) |
|
| 3–5 |
89 (33.8) |
78 (29.7) |
|
| ≥5 |
113 (43.0) |
106 (40.3) |
|
| Occupation |
|
|
2.63 (0.756) |
| Production worker |
15 (5.7) |
14 (5.3) |
|
| Office worker |
102 (38.8) |
90 (34.2) |
|
| Service and sales worker |
47 (17.9) |
53 (20.2) |
|
| Healthcare worker |
12 (4.6) |
8 (3.0) |
|
| Housewife |
34 (12.9) |
37 (14.1) |
|
| Other |
53 (20.2) |
61 (23.2) |
|
| Residential area |
|
|
10.19 (0.006**) |
| Metropolitan city |
174 (66.2) |
161 (61.2) |
|
| Small and medium sized city |
81 (30.8) |
76 (28.9) |
|
| Rural area |
8 (3.0) |
26 (9.9) |
|
Table 3.Experiences and attitudes regarding COVID-19, CVICP, and vaccination
Table 3.
|
Experimental group (n=263) |
Control group (n=263) |
χ2 (p)a)/t-value (p)b)
|
| Experiences of COVID-19 |
|
|
|
| Have been affected by COVID-19 |
|
|
0.01 (0.916)a)
|
| No |
57 (21.7) |
58 (22.1) |
|
| Yes |
206 (78.3) |
205 (77.9) |
|
| COVID-19 vaccination |
|
|
6.23 (0.284)a)
|
| Never |
14 (5.3) |
16 (6.1) |
|
| Part of basic vaccination |
6 (2.3) |
12 (4.6) |
|
| Basic vaccination |
49 (18.6) |
43 (16.3) |
|
| First booster |
25 (9.5) |
15 (5.7) |
|
| Second booster |
72 (27.4) |
85 (32.3) |
|
| Third booster or more |
97 (36.9) |
92 (35.0) |
|
| Adverse events following COVID-19 vaccination |
|
|
4.63 (0.796)a)
|
| None |
71 (27.0) |
59 (22.4) |
|
| Pain, redness, swelling, or bruising at the injection site |
70 (26.6) |
73 (27.8) |
|
| Fever and chills |
58 (22.1) |
57 (21.7) |
|
| Fatigue and drowsiness |
23 (8.7) |
21 (8.0) |
|
| Headache and dizziness |
6 (2.3) |
9 (3.4) |
|
| Muscle pain and muscle cramps |
15 (5.7) |
15 (5.7) |
|
| Abnormal uterine bleeding and menstrual irregularities |
2 (0.8) |
5 (1.9) |
|
| Nausea and vomiting |
2 (0.8) |
3 (1.1) |
|
| Loss of appetite |
2 (0.8) |
5 (1.9) |
|
| Diarrhea |
71 (27.0) |
59 (22.4) |
|
| Others |
70 (26.6) |
73 (27.8) |
|
| Aware of CVICP |
|
|
0.27 (0.601)a)
|
| No |
126 (47.9) |
132 (50.2) |
|
| Yes |
137 (52.1) |
131 (49.8) |
|
| Attitudes toward the CVICP and COVID-19 vaccination |
|
|
|
| CVICP: satisfaction levels |
3.63±1.38 |
3.61±1.53 |
–0.15 (0.88)b)
|
| CVICP: perceived necessity |
5.33±1.32 |
5.33±1.33 |
0.03 (0.97)b)
|
| CVICP: enhancing vaccine acceptance |
4.99±1.40 |
5.08±1.47 |
0.76 (0.45)b)
|
| COVID-19 vaccination: perceived necessity |
5.10±1.45 |
5.12±1.49 |
0.21 (0.84)b)
|
| COVID-19 vaccination: willingness to recommend |
4.74±1.65 |
4.72±1.67 |
–0.11 (0.92)b)
|
| COVID-19 vaccination: willingness for future vaccination |
4.58±1.79 |
4.59±1.81 |
0.05(0.96)b)
|
Table 4.Changes in attitudes toward the CVICP and COVID-19 vaccination in each group
Table 4.
| Attitudes toward the CVICP and COVID-19 vaccination |
Experimental group |
Control group |
| Pre |
Post |
Change |
Pre |
Post |
Change |
| Mean±SD |
Mean±SD |
t |
p |
Mean±SD |
Mean±SD |
t |
p |
| CVICP: satisfaction levels |
3.63±1.38 |
4.27±1.30 |
–8.18 |
0.00**
|
3.61±1.53 |
4.32±1.29 |
–8.77 |
0.00**
|
| CVICP: perceived necessity |
5.33±1.32 |
5.50±1.23 |
–2.27 |
0.02*
|
5.33±1.33 |
5.38±1.27 |
–0.65 |
0.52 |
| CVICP: enhancing vaccine acceptance |
4.99±1.40 |
5.26±1.23 |
–3.64 |
0.00**
|
5.08±1.47 |
5.08±1.36 |
0.11 |
0.92 |
| COVID-19 vaccination: perceived necessity |
5.10±1.45 |
5.30±1.36 |
–3.55 |
0.00**
|
5.12±1.49 |
5.20±1.41 |
–1.27 |
0.2 |
| COVID-19 vaccination: willingness to recommend |
4.74±1.65 |
4.91±1.64 |
–2.74 |
0.01**
|
4.72±1.67 |
4.83±1.56 |
–1.98 |
0.05*
|
| COVID-19 vaccination: willingness for future vaccination |
4.58±1.79 |
4.88±1.70 |
–5.09 |
0.00**
|
4.59±1.81 |
4.89±1.69 |
–4.80 |
0.00**
|
Table 5.Changes in attitudes toward the CVICP and COVID-19 vaccination: repeated measures 2-way analysis of variance
Table 5.
| Attitudes toward the CVICP and COVID-19 vaccination |
Group |
Pre–post |
Group:pre–post |
| F |
p |
F |
p |
F |
p |
| CVICP: satisfaction levels |
0.02 |
0.90 |
143.75 |
0.00**
|
0.33 |
0.56 |
| CVICP: perceived necessity |
0.35 |
0.55 |
4.44 |
0.04*
|
1.49 |
0.22 |
| CVICP: enhancing vaccine acceptance |
0.17 |
0.68 |
6.52 |
0.01*
|
7.29 |
0.01*
|
| COVID-19 vaccination: perceived necessity |
0.11 |
0.75 |
11.26 |
0.00**
|
2.25 |
0.13 |
| COVID-19 vaccination: willingness to recommend |
0.11 |
0.74 |
11.33 |
0.00**
|
0.56 |
0.46 |
| COVID-19 vaccination: willingness for future vaccination |
0.00 |
0.95 |
48.71 |
0.00**
|
0.00 |
0.96 |
Table 6.Changes in attitudes toward the CVICP: multiple linear regression models
Table 6.
| Variable |
Attitude toward the CVICP |
| Satisfaction |
Necessity |
Enhancing acceptance |
| β |
SE |
t |
p |
β |
SE |
t |
p |
β |
SE |
t |
p |
| (Intercept) |
0.92 |
0.62 |
1.47 |
0.14 |
–0.41 |
0.58 |
–0.71 |
0.46 |
–1.39 |
0.58 |
–2.39 |
0.02*
|
| Experimental group |
–0.10 |
0.12 |
–0.84 |
0.40 |
0.10 |
0.11 |
0.90 |
0.37 |
0.28 |
0.11 |
2.60 |
0.01*
|
| Gender |
|
|
|
| Age |
|
x |
|
| Region |
|
|
|
| Education |
x |
|
|
| Income |
|
x |
|
| Occupation |
|
|
|
| Ideological tendency |
x |
x |
|
| Residential area |
x |
|
|
Table 7.Changes in attitudes toward the COVID-19 vaccination: multiple linear regression models
Table 7.
| Variable |
Attitude toward COVID-19 vaccination |
| Necessity |
Recommend |
Future vaccination |
| β |
SE |
t |
p |
β |
SE |
t |
p |
β |
SE |
t |
p |
| (Intercept) |
0.43 |
0.48 |
0.89 |
0.37 |
0.18 |
0.46 |
0.38 |
0.70 |
1.01 |
0.47 |
2.13 |
0.03*
|
| Experimental group |
0.10 |
0.09 |
1.14 |
0.26 |
0.06 |
0.09 |
0.69 |
0.49 |
–0.03 |
0.09 |
–0.39 |
0.70 |
| Gender |
x |
|
x |
| Age |
x |
|
|
| Region |
|
|
|
| Education |
x |
x |
x |
| Income |
x |
|
x |
| Occupation |
|
|
|
| Ideological tendency |
|
|
x |
| Residential area |
|
|
|
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Citations
Citations to this article as recorded by
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