What Motivates People to Receive Continuous COVID-19 Vaccine Booster Shots? An Expectation Confirmation Theory Perspective
Abstract
:1. Introduction
1.1. Background
1.2. The Goals and Innovations of Our Work
2. Literature Review
2.1. Studies Related to Vaccination Intention
2.2. Studies Related to the Vaccination Intention for COVID-19 Vaccine Boosters
2.3. Studies Related to Expectation Confirmation Theory
3. Research Model and Hypotheses
3.1. Research Hypotheses
3.1.1. Perceived Performance
- (1)
- Perceived Vaccine Efficacy
- (2)
- Perceived Vaccination Convenience
- (3)
- Perceived Vaccine Safety
3.1.2. Expectation Confirmation and Vaccination Intention for COVID-19 Vaccine Boosters
3.1.3. Moderator Variables
- (1)
- Health Consciousness
- (2)
- Time Interval
3.2. Research Model
4. Materials and Methods
4.1. Variables and Measurement
4.2. Sample Size and Data Collection
4.2.1. Sample Size
4.2.2. Data Collection
4.3. Data Analysis
5. Results
5.1. Reliability and Validity Test
5.2. Structural Model
5.2.1. Main Effect Test
5.2.2. Moderating Effect Test
6. Discussion and Contributions
6.1. Key Findings
6.2. Theoretical Contributions
6.3. Practical Implications
6.4. Limitations and Future Directions
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
TI | Time interval |
PVE | Perceived vaccine efficacy |
PVS | Perceived vaccine safety |
PVC | Perceived vaccination convenience |
EC | Expectation confirmation |
VI | Vaccination intention for COVID-19 vaccine boosters |
HC | Health consciousness |
References
- WHO Coronavirus (COVID-19) Dashboard. Available online: https://covid19.who.int/ (accessed on 14 May 2022).
- Chenchula, S.; Karunakaran, P.; Sharma, S.; Chavan, M. Current evidence on efficacy of COVID-19 booster dose vaccination against the Omicron variant: A systematic review. J. Med. Virol. 2022, 94, 2969–2976. [Google Scholar] [CrossRef]
- Burckhardt, R.M.; Dennehy, J.J.; Poon, L.L.M.; Saif, L.J.; Enquist, L.W. Are COVID-19 vaccine boosters needed? the science behind boosters. J. Virol. 2022, 96, e01973-21. [Google Scholar] [CrossRef]
- Shekhar, R.; Garg, I.; Pal, S.; Kottewar, S.; Sheikh, A.B. COVID-19 Vaccine Booster: To Boost or Not to Boost. Infect. Dis. Rep. 2021, 13, 924–929. [Google Scholar] [CrossRef]
- SARS-CoV-2 Variants of Concern and Variants under Investigation in England. Available online: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1045619/Technical-Briefing-31-Dec-2021-Omicron_severity_update.pdf (accessed on 28 May 2022).
- Peiris, M.; Cheng, S.; Mok, C.K.; Leung, Y.; Ng, S.; Chan, K.; Ko, F.; Yiu, K.; Lam, B.; Lau, E.; et al. Neutralizing antibody titres to SARS-COV-2 omicron variant and wild-type virus in those with past infection or vaccinated or boosted with mrna BNT162B2 or inactivated Coronavac vaccines(preprint). Res. Sq. 2022. [Google Scholar] [CrossRef]
- Nemet, I.; Kliker, L.; Lustig, Y.; Zuckerman, N.S.; Erster, O.; Cohen, C.; Kreiss, Y.; Alroy-Preis, S.; Regev-Yochay, G.; Mendelson, E.; et al. Third BNT162B2 vaccination neutralization of SARS-COV-2 omicron infection. N. Engl. J. Med. 2022, 386, 492–494. [Google Scholar] [CrossRef]
- Galmiche, S.; Nguyen, L.B.L.; Tartour, E.; de Lamballerie, X.; Wittkop, L.; Loubet, P.; Launay, O. Immunological and clinical efficacy of COVID-19 vaccines in immunocompromised populations: A systematic review. Clin. Microbiol. Infect. 2022, 28, 163–177. [Google Scholar] [CrossRef]
- Zhang, K.; Wu, X.X.; Shi, Y.; Gou, X.Q.; Huang, J.Q. Immunogenicity of H5N1 influenza vaccines in elderly adults: A systematic review and meta-analysis. Hum. Vaccines Immunother. 2021, 17, 475–484. [Google Scholar] [CrossRef]
- Tohme, R.A.; Awosika-Olumo, D.; Nielsen, C.; Khuwaja, S.; Scott, J.; Xing, J.; Drobeniuc, J.; Hu, D.J.; Turner, C.; Wafeeg, T.; et al. Evaluation of hepatitis B vaccine immunogenicity among older adults during an outbreak response in assisted living facilities. Vaccine 2011, 29, 9316–9320. [Google Scholar] [CrossRef] [Green Version]
- Patwary, M.M.; Bardhan, M.; Disha, A.S.; Hasan, M.; Haque, M.Z.; Sultana, R.; Hossain, M.R.; Browning, M.H.; Alam, M.A.; Sallam, M. Determinants of COVID-19 vaccine acceptance among the adult population of Bangladesh using the health belief model and the theory of planned behavior model. Vaccines 2021, 9, 1393. [Google Scholar] [CrossRef]
- Li, L.; Wang, J.; Nicholas, S.; Maitland, E.; Leng, A.; Liu, R. The intention to receive the COVID-19 vaccine in China: Insights From Protection Motivation theory. Vaccines 2021, 9, 445. [Google Scholar] [CrossRef]
- Eberhardt, J.; Ling, J. Predicting COVID-19 vaccination intention using protection motivation theory and conspiracy beliefs. Vaccine 2021, 39, 6269–6275. [Google Scholar] [CrossRef]
- Zhu, W.L.; Zou, H.; Song, Y.; Ren, L.L.; Xu, Y.J. Understanding the continuous vaccination of the COVID-19 vaccine: An empirical study from China. Hum. Vaccines Immunother. 2021, 17, 4954–4963. [Google Scholar] [CrossRef]
- Charron, J.; Gautier, A.; Jestin, C. Influence of information sources on vaccine hesitancy and practices. Med. Mal. Infect. 2020, 50, 727–733. [Google Scholar] [CrossRef]
- Nan, X.; Xie, B.; Madden, K. Acceptability of the H1N1 vaccine among older adults: The interplay of message framing and perceived vaccine safety and efficacy. Health Commun. 2012, 27, 559–568. [Google Scholar] [CrossRef]
- Nan, X.L.; Madden, K.; Richards, A.; Holt, C.; Wang, M.Q.; Tracy, K. Message Framing, Perceived Susceptibility, and Intentions to Vaccinate Children Against HPV Among African American Parents. Health Commun. 2016, 31, 798–805. [Google Scholar] [CrossRef] [Green Version]
- Karlsson, L.C.; Soveri, A.; Lewandowsky, S.; Karlsson, L.; Karlsson, H.; Nolvi, S.; Karukivi, M.; Lindfelt, M.; Antfolk, J. Fearing the disease or the vaccine: The case of COVID-19. Personal. Individ. Differ. 2021, 172, 110590. [Google Scholar] [CrossRef]
- Tandy, C.B.; Jabson Tree, J.M. Attitudes of East Tennessee residents towards general and pertussis vaccination: A qualitative study. BMC Public Health 2021, 21, 446. [Google Scholar] [CrossRef]
- Beraud, G. Shortages Without Frontiers: Antimicrobial Drug and Vaccine Shortages Impact Far Beyond the Individual! Front. Med. 2021, 8, 593712. [Google Scholar] [CrossRef]
- Bouchez, M.; Ward, J.K.; Bocquier, A.; Benamouzig, D.; Peretti-Watel, P.; Seror, V.; Verger, P. Physicians’ decision processes about the HPV vaccine: A qualitative study. Vaccine 2021, 39, 521–528. [Google Scholar] [CrossRef]
- Latkin, C.A.; Dayton, L.; Yi, G.; Colon, B.; Kong, X.R. Mask usage, social distancing, racial, and gender correlates of COVID-19 vaccine intentions among adults in the US. PLoS ONE 2021, 16, e0246970. [Google Scholar] [CrossRef]
- Yoda, T.; Katsuyama, H. Willingness to Receive COVID-19 Vaccination in Japan. Vaccines 2021, 9, 48. [Google Scholar] [CrossRef]
- Gunes, N. Parents’ Perspectives about Vaccine Hesitancies and Vaccine Rejection, in the West of Turkey. J. Pediatr. Nurs. 2020, 53, E186–E194. [Google Scholar] [CrossRef]
- Krasnicka, J.; Krajewska-Kulak, E.; Klimaszewska, K.; Cybulski, M.; Guzowski, A.; Kowalewska, B.; Jankowiak, B.; Rolka, H.; Doroszkiewicz, H.; Kulak, W. Mandatory and recommended vaccinations in Poland in the views of parents. Hum. Vaccines Immunother. 2018, 14, 2884–2893. [Google Scholar] [CrossRef] [Green Version]
- Townsend, M.J.; Kyle, T.K.; Stanford, F.C. COVID-19 Vaccination and Obesity: Optimism and Challenges. Obesity 2021, 29, 634–635. [Google Scholar] [CrossRef] [PubMed]
- Vasudevan, L.; Baumgartner, J.N.; Moses, S.; Ngadaya, E.; Mfinanga, S.G.; Ostermann, J. Parental concerns and uptake of childhood vaccines in rural Tanzania - a mixed methods study. Bmc Public Health 2020, 20, 1573. [Google Scholar] [CrossRef]
- Yadete, T.; Batra, K.; Netski, D.M.; Antonio, S.; Patros, M.J.; Bester, J.C. Assessing Acceptability of COVID-19 Vaccine Booster Dose among Adult Americans: A Cross-Sectional Study. Vaccines 2021, 9, 1424. [Google Scholar] [CrossRef]
- Qin, C.; Wang, R.; Tao, L.; Liu, M.; Liu, J. Acceptance of a third dose of COVID-19 vaccine and associated factors in China based on Health Belief Model: A national cross-sectional study. Vaccines 2022, 10, 89. [Google Scholar] [CrossRef]
- Hu, T.; Li, L.; Lin, C.; Yang, Z.; Chow, C.; Lu, Z.; You, C. An analysis of the willingness to the COVID-19 vaccine booster shots among urban employees: Evidence from a megacity H in eastern China. Int. J. Environ. Res. Public Health 2022, 19, 2300. [Google Scholar] [CrossRef]
- Neely, S.R.; Scacco, J.M. Receptiveness of American adults to COVID-19 vaccine boosters: A survey analysis. PEC Innov. 2022, 1, 100019. [Google Scholar] [CrossRef]
- Oliver, R.L. A cognitive model of the antecedents and consequences of satisfaction decisions. J. Mark. Res. 1980, 17, 460–469. [Google Scholar] [CrossRef]
- Vijay, T.S.; Prashar, S.; Gupta, S. Intention to provide online reviews: An expectation-confirmation model with review involvement. Pac. Asia J. Assoc. Inf. Syst. 2018, 10, 25–54. [Google Scholar] [CrossRef]
- Bhattacherjee, A. Understanding information systems continuance: An expectation-confirmation model. Mis Q. 2001, 25, 351–370. [Google Scholar] [CrossRef]
- Ott, J.J.; Wiersma, S.T. Single-dose administration of inactivated hepatitis A vaccination in the context of hepatitis A vaccine recommendations. Int. J. Infect. Dis. 2013, 17, E939–E944. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- La Torre, G.; Mannocci, A.; Colamesta, V.; D’Egidio, V.; Sestili, C.; Spadea, A. Influenza and pneumococcal vaccination in hematological malignancies: A systematic review of efficacy, effectiveness and safety. Mediterr. J. Hematol. Infect. Dis. 2016, 8, e2016044. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chi-Cheng, C.-F.C.; Yan, C.-F.; Tseng, J.-S. Perceived convenience in an extended technology acceptance model mobile technology and English learning for college students. Australas. J. Educ. Technol. 2012, 28, 809–826. [Google Scholar] [CrossRef] [Green Version]
- Valikodath, N.G.; Leveque, T.K.; Wang, S.Y.; Lee, P.P.; Newman-Casey, P.A.; Hansen, S.O.; Woodward, M.A. Patient attitudes toward telemedicine for diabetic retinopathy. Telemed. e-Health 2017, 23, 205–212. [Google Scholar] [CrossRef] [Green Version]
- Li, D.; Hu, Y.; Pfaff, H.; Wang, L.; Deng, L.; Lu, C.; Xia, S.; Cheng, S.; Zhu, X.; Wu, X. Determinants of patients’ intention to use the online inquiry services provided by internet hospitals: Empirical evidence from China. J. Med Internet Res. 2020, 22, e22716. [Google Scholar] [CrossRef]
- Olson, M.J. The Logic of Collective Action: Public Goods and the Theory of Groups; Harvard University Press: Cambridge, MA, USA, 1965. [Google Scholar]
- Bickham, S.B.; Francis, D.B. The Public’s Perceptions of Government Officials’ Communication in the Wake of the COVID-19 Pandemic. J. Creat. Commun. 2021, 16, 190–202. [Google Scholar] [CrossRef]
- Chen, Y.Y.; Feng, J.H.; Chen, A.; Lee, J.E.; An, L. Risk perception of COVID-19: A comparative analysis of China and South Korea. Int. J. Disaster Risk Reduct. 2021, 61, 102373. [Google Scholar] [CrossRef]
- Hong, Y.; Hashimoto, M. I will get myself vaccinated for others: The interplay of message frame, reference point, and perceived risk on intention for COVID-19 vaccine. Health Commun. 2021, 1–11. [Google Scholar] [CrossRef]
- Official Website of China’s National Health Commission. Available online: http://www.nhc.gov.cn/ (accessed on 10 October 2022).
- Cochran, W.G. Sampling Techniques, 3rd ed.; Wiley: Hoboken, NJ, USA, 1977. [Google Scholar]
- Smith, D.J.; Hakim, A.J.; Leung, G.M.; Xu, W.; Schluter, W.W.; Novak, R.T.; Marston, B.; Hersh, B.S. Covid-19 mortality and vaccine coverage — hong kong special administrative region, China, January 6, 2022–March 21, 2022. MMWR. Morb. Mortal. Wkly. Rep. 2022, 71, 545–548. [Google Scholar] [CrossRef] [PubMed]
- Mistry, S.K.; Ali, A.R.M.M.; Yadav, U.N.; Huda, M.N.; Parray, A.A.; Mahumud, R.A.; Mitra, D. COVID-19 vaccination coverage is extremely low among older population in Bangladesh: Findings from a cross-sectional study. Hum. Vaccines Immunother. 2022, 18, 2030624. [Google Scholar] [CrossRef] [PubMed]
- Sarstedt, M.; Cheah, J.H. Partial least squares structural equation modeling using SmartPLS: A software review. J. Mark. Anal. 2019, 7, 196–202. [Google Scholar] [CrossRef]
- Gorondutse, A.H.; Hilman, H. Does organizational culture matter in the relationship between trust and SMEs performance. Manag. Decis. 1988, 57, 1638–1658. [Google Scholar] [CrossRef]
- Fornell, C.; Larcker, D.F. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
- Anderson, J.C.; Gerbing, D.W. Structural equation modeling in practice: A review and recommended two-step approach. Psychol. Bull. 1988, 103, 411–423. [Google Scholar] [CrossRef]
- MacDonald, N.E.; SAGE Working Group on Vaccine Hesitancy. Vaccine hesitancy: Definition, scope and determinants. Vaccine 2015, 33, 4161–4164. [Google Scholar] [CrossRef]
Variables | Name | Items | Sources |
---|---|---|---|
Perceived Vaccine Efficacy | PVE1 | I believe the COVID-19 vaccine is effective in preventing the COVID-19. | [16,17] |
PVE2 | I believe if I get the COVID-19 vaccine, I will be less likely to get the COVID-19. | ||
PVE3 | I believe the COVID-19 vaccine works in preventing the COVID-19. | ||
Perceived Vaccine Safety | PVS1 | I worry about the short term side effects of the COVID-19 vaccine. | [16,17] |
PVS2 | I worry that the COVID-19 vaccine might negatively affect my body. | ||
PVS3 | I worry that the COVID-19 vaccine might have unknown long term side effects. | ||
Perceived Vaccination Convenience | PVC1 | I think it is very convenient to get the COVID-19 vaccine. | [27,39] |
PVC2 | I think I am able to get the COVID-19 vaccine in a hospital or community health center. | ||
PVC3 | I think the place providing vaccination service is close to my home/work. | ||
PVC4 | I think the cost of COVID-19 vaccination is low (or no cost). | ||
PVC5 | I think that getting the COVID-19 vaccine could be helpful to decrease losses such as the physical damage and the loss of normal income due to quarantine or infection. | ||
Expectation Confirmation | EC1 | My experience with the Covid-19 vaccine has been better than I expected. | [32,34] |
EC2 | The vaccination service was better than I expected. | ||
EC3 | Overall, getting vaccinated against COVID-19 can meet demand beyond my expectations. | ||
Vaccination Intention | VI1 | I am willing to receive vaccination for the COVID-19 vaccine boosters. | [43] |
VI2 | I plan to get vaccinated for the COVID-19 vaccine boosters when the vaccine becomes available. | ||
VI3 | I will get vaccinated for the COVID-19 vaccine boosters as soon as it becomes available. | ||
Health Consciousness | HC1 | I am aware of and very concerned about my health problems. | [39] |
HC2 | I will try to manage and improve my wellness. | ||
Time Interval | TI | The time interval between the last injection (non-booster) and the present for fully vaccinated people. | – |
Variables | Value | Frequency | Percentage |
---|---|---|---|
Sex | Male | 266 | 46.50% |
Female | 306 | 53.50% | |
Age | 18–25 | 209 | 36.54% |
26–40 | 210 | 36.71% | |
41–60 | 137 | 23.95% | |
>60 | 16 | 2.80% | |
Education | Junior high school degree and below | 14 | 2.45% |
High school degree or GED | 46 | 8.04% | |
Associate degree | 80 | 13.99% | |
Bachelor degree | 334 | 58.39% | |
Master degree and above | 98 | 17.13% | |
Income (RMB per month) | <1000 | 52 | 9.09% |
1000–3000 | 101 | 17.66% | |
3001–5000 | 95 | 16.61% | |
5001–8000 | 136 | 23.77% | |
8001–10,000 | 78 | 13.64% | |
10,001–15,000 | 44 | 7.69% | |
>15,000 | 29 | 5.07% | |
sorry, I would rather not to say | 37 | 6.47% | |
BMI 1 | underweight (<18.5) | 52 | 9.09% |
healthy weight (18.5–23.9) | 377 | 65.91% | |
overweight (24.0–27.9) | 108 | 28.88% | |
obese (≥28) | 35 | 6.12% | |
Type of living area | Risk area | 153 | 26.75% |
Nonrisk area | 419 | 73.25% |
Variables | Factors | Standard Loadings | Cronbach’s | CR 1 | AVE 2 |
---|---|---|---|---|---|
HC | HC1 | 0.877 | 0.71 | 0.873 | 0.775 |
HC2 | 0.884 | ||||
VI | VI1 | 0.886 | 0.873 | 0.922 | 0.797 |
VI2 | 0.892 | ||||
VI3 | 0.901 | ||||
PVC | PVC1 | 0.786 | 0.82 | 0.874 | 0.583 |
PVC2 | 0.792 | ||||
PVC3 | 0.689 | ||||
PVC4 | 0.729 | ||||
PVC5 | 0.813 | ||||
PVE | PVE1 | 0.901 | 0.816 | 0.891 | 0.733 |
PVE2 | 0.771 | ||||
PVE3 | 0.89 | ||||
PVS | PVS1 | 0.919 | 0.925 | 0.953 | 0.87 |
PVS2 | 0.953 | ||||
PVS3 | 0.926 | ||||
EC | EC1 | 0.883 | 0.834 | 0.901 | 0.751 |
EC2 | 0.834 | ||||
EC3 | 0.882 |
HC | VI | PVC | PVE | PVS | EC | |
---|---|---|---|---|---|---|
HC | 0.881 | |||||
VI | 0.357 | 0.893 | ||||
PVC | 0.426 | 0.472 | 0.763 | |||
PVE | 0.399 | 0.455 | 0.713 | 0.856 | ||
PVS | 0.083 | 0.262 | 0.202 | 0.262 | 0.933 | |
EC | 0.403 | 0.587 | 0.538 | 0.546 | 0.254 | 0.867 |
Hypothesis | Paths | 1 | T-Statistic | Results |
---|---|---|---|---|
H1 | PVE(+)→EC | 0.266 *** | 4.855 | Supported |
H2 | PVC(+)→EC | 0.238 ** | 3.438 | Supported |
H3 | PVS(+)→EC | 0.148 *** | 3.837 | Supported |
H4 | EC(+)→VI | 0.586 *** | 12.974 | Supported |
Hypothesis | Paths | 1 | T-Statistic | Results |
---|---|---|---|---|
H5 | HC*PVS(-)→EC | −0.133 ** | 3.191 | Supported |
H6 | TI*PVE(-)→EC | −0.103 * | 2.293 | Supported |
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Liu, J.; Lu, S.; Lu, C. What Motivates People to Receive Continuous COVID-19 Vaccine Booster Shots? An Expectation Confirmation Theory Perspective. Healthcare 2022, 10, 2535. https://doi.org/10.3390/healthcare10122535
Liu J, Lu S, Lu C. What Motivates People to Receive Continuous COVID-19 Vaccine Booster Shots? An Expectation Confirmation Theory Perspective. Healthcare. 2022; 10(12):2535. https://doi.org/10.3390/healthcare10122535
Chicago/Turabian StyleLiu, Jingfang, Shuangjinhua Lu, and Caiying Lu. 2022. "What Motivates People to Receive Continuous COVID-19 Vaccine Booster Shots? An Expectation Confirmation Theory Perspective" Healthcare 10, no. 12: 2535. https://doi.org/10.3390/healthcare10122535