Vaccination Intention against COVID-19 among the Unvaccinated in Jordan during the Early Phase of the Vaccination Drive: A Cross-Sectional Survey
Abstract
:1. Introduction
2. Methods
2.1. Study Design and Participant
2.2. Assessment and Outcomes
2.3. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Adhikari, S.P.; Meng, S.; Wu, Y.-J.; Mao, Y.-P.; Ye, R.-X.; Wang, Q.-Z.; Sun, C.; Sylvia, S.; Rozelle, S.; Raat, H.; et al. Epidemiology, causes, clinical manifestation and diagnosis, prevention and control of coronavirus disease (COVID-19) during the early outbreak period: A scoping review. Infect. Dis. Poverty 2020, 9, 29. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhu, N.; Zhang, D.; Wang, W.; Li, X.; Yang, B.; Song, J.; Zhao, X.; Huang, B.; Shi, W.; Lu, R.; et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N. Engl. J. Med. 2020, 382, 727–733. [Google Scholar] [CrossRef] [PubMed]
- Shimul, S.N.; Alradie-Mohamed, A.; Kabir, R.; Al-Mohaimeed, A.; Mahmud, I. Effect of easing lockdown and restriction measures on COVID-19 epidemic projection: A case study of Saudi Arabia. PLoS ONE 2021, 16, e0256958. [Google Scholar] [CrossRef]
- World Health Organization WHO Coronavirus (COVID-19) Dashboard. Available online: https://covid19.who.int/ (accessed on 25 May 2022).
- Hodgson, S.H.; Mansatta, K.; Mallett, G.; Harris, V.; Emary, K.R.W.; Pollard, A.J. What defines an efficacious COVID-19 vaccine? A review of the challenges assessing the clinical efficacy of vaccines against SARS-CoV-2. Lancet. Infect. Dis. 2021, 21, e26–e35. [Google Scholar] [CrossRef]
- World Health Organization Ten threats to global health in 2019. Available online: https://www.who.int/news-room/spotlight/ten-threats-to-global-health-in-2019 (accessed on 28 May 2022).
- Lazarus, J.V.; Ratzan, S.C.; Palayew, A.; Gostin, L.O.; Larson, H.J.; Rabin, K.; Kimball, S.; El-Mohandes, A. A global survey of potential acceptance of a COVID-19 vaccine. Nat. Med. 2021, 27, 225–228. [Google Scholar] [CrossRef] [PubMed]
- Mahmud, I.; Kabir, R.; Rahman, M.A.; Alradie-Mohamed, A.; Vinnakota, D.; Al-Mohaimeed, A. The Health Belief Model Predicts Intention to Receive the COVID-19 Vaccine in Saudi Arabia: Results from a Cross-Sectional Survey. Vaccines 2021, 9, 864. [Google Scholar] [CrossRef] [PubMed]
- Kabir, R.; Mahmud, I.; Chowdhury, M.T.H.; Vinnakota, D.; Jahan, S.S.; Siddika, N.; Isha, S.N.; Nath, S.K.; Hoque Apu, E. COVID-19 Vaccination Intent and Willingness to Pay in Bangladesh: A Cross-Sectional Study. Vaccines 2021, 9, 416. [Google Scholar] [CrossRef] [PubMed]
- Larson, H.J.; Jarrett, C.; Eckersberger, E.; Smith, D.M.D.; Paterson, P. Understanding vaccine hesitancy around vaccines and vaccination from a global perspective: A systematic review of published literature, 2007–2012. Vaccine 2014, 32, 2150–2159. [Google Scholar] [CrossRef]
- Sallam, M.; Dababseh, D.; Eid, H.; Al-Mahzoum, K.; Al-Haidar, A.; Taim, D.; Yaseen, A.; Ababneh, N.A.; Bakri, F.G.; Mahafzah, A. High Rates of COVID-19 Vaccine Hesitancy and Its Association with Conspiracy Beliefs: A Study in Jordan and Kuwait among Other Arab Countries. Vaccines 2021, 9, 42. [Google Scholar] [CrossRef]
- Abu Farha, R.K.; Alzoubi, K.H.; Khabour, O.F.; Alfaqih, M.A. Exploring perception and hesitancy toward COVID-19 vaccine: A study from Jordan. Hum. Vaccines Immunother. 2021, 17, 2415–2420. [Google Scholar] [CrossRef]
- El-Elimat, T.; AbuAlSamen, M.M.; Almomani, B.A.; Al-Sawalha, N.A.; Alali, F.Q. Acceptance and attitudes toward COVID-19 vaccines: A cross-sectional study from Jordan. PLoS ONE 2021, 16, e0250555. [Google Scholar] [CrossRef] [PubMed]
- Rosenstock, I.M.; Strecher, V.J.; Becker, M.H. Social learning theory and the Health Belief Model. Health Educ. Q. 1988, 15, 175–183. [Google Scholar] [CrossRef] [PubMed]
- Rosenstock, I.M. The Health Belief Model and Preventive Health Behavior. Health Educ. Monogr. 1974, 2, 354–386. [Google Scholar] [CrossRef]
- Wong, L.P.; Alias, H.; Wong, P.F.; Lee, H.Y.; AbuBakar, S. The use of the health belief model to assess predictors of intent to receive the COVID-19 vaccine and willingness to pay. Hum. Vaccines Immunother. 2020, 16, 2204–2214. [Google Scholar] [CrossRef] [PubMed]
- Zampetakis, L.A.; Melas, C. The health belief model predicts vaccination intentions against COVID-19: A survey experiment approach. Appl. Psychol. Health Well-Being 2021, 13, 469–484. [Google Scholar] [CrossRef] [PubMed]
- Mercadante, A.R.; Law, A.V. Will they, or Won’t they? Examining patients’ vaccine intention for flu and COVID-19 using the Health Belief Model. Res. Soc. Adm. Pharm. 2020, 17, 1596–1605. [Google Scholar] [CrossRef]
- Chen, M.-F.; Wang, R.-H.; Schneider, J.K.; Tsai, C.-T.; Jiang, D.D.-S.; Hung, M.-N.; Lin, L.-J. Using the Health Belief Model to Understand Caregiver Factors Influencing Childhood Influenza Vaccinations. J. Community Health Nurs. 2011, 28, 29–40. [Google Scholar] [CrossRef]
- Nexøe, J.; Kragstrup, J.; Søgaard, J. Decision on influenza vaccination among the elderly. A questionnaire study based on the Health Belief Model and the Multidimensional Locus of Control Theory. Scand. J. Prim. Health Care 1999, 17, 105–110. [Google Scholar] [CrossRef] [Green Version]
- Coe, A.B.; Gatewood, S.B.S.; Moczygemba, L.R.; Goode, J.-V.K.R.; Beckner, J.O. The use of the health belief model to assess predictors of intent to receive the novel (2009) H1N1 influenza vaccine. Innov. Pharm. 2012, 3, 1–11. [Google Scholar] [CrossRef]
- Fall, E.; Izaute, M.; Chakroun-Baggioni, N. How can the health belief model and self-determination theory predict both influenza vaccination and vaccination intention? A longitudinal study among university students. Psychol. Health 2018, 33, 746–764. [Google Scholar] [CrossRef]
- Donadiki, E.M.; Jiménez-García, R.; Hernández-Barrera, V.; Sourtzi, P.; Carrasco-Garrido, P.; López de Andrés, A.; Jimenez-Trujillo, I.; Velonakis, E.G. Health Belief Model applied to non-compliance with HPV vaccine among female university students. Public Health 2014, 128, 268–273. [Google Scholar] [CrossRef] [PubMed]
- Tan, M.; Straughan, P.T.; Cheong, G. Information trust and COVID-19 vaccine hesitancy amongst middle-aged and older adults in Singapore: A latent class analysis Approach. Soc. Sci. Med. 2022, 296, 114767. [Google Scholar] [CrossRef] [PubMed]
- Murphy, J.; Vallières, F.; Bentall, R.P.; Shevlin, M.; McBride, O.; Hartman, T.K.; McKay, R.; Bennett, K.; Mason, L.; Gibson-Miller, J.; et al. Psychological characteristics associated with COVID-19 vaccine hesitancy and resistance in Ireland and the United Kingdom. Nat. Commun. 2021, 12, 29. [Google Scholar] [CrossRef] [PubMed]
- Zintel, S.; Flock, C.; Arbogast, A.L.; Forster, A.; von Wagner, C.; Sieverding, M. Gender differences in the intention to get vaccinated against COVID-19: A systematic review and meta-analysis. J Public Health 2022. [Google Scholar] [CrossRef] [PubMed]
- Wong, M.C.S.; Wong, E.L.Y.; Huang, J.; Cheung, A.W.L.; Law, K.; Chong, M.K.C.; Ng, R.W.Y.; Lai, C.K.C.; Boon, S.S.; Lau, J.T.F.; et al. Acceptance of the COVID-19 vaccine based on the health belief model: A population-based survey in Hong Kong. Vaccine 2021, 39, 1148–1156. [Google Scholar] [CrossRef]
- Khoo, Y.S.K.; Ghani, A.A.; Navamukundan, A.A.; Jahis, R.; Gamil, A. Unique product quality considerations in vaccine development, registration and new program implementation in Malaysia. Hum. Vaccines Immunother. 2020, 16, 530–538. [Google Scholar] [CrossRef] [Green Version]
- The New York Times Is the Vaccine Halal? Indonesians Await the Answer. Available online: https://www.nytimes.com/2021/01/05/world/asia/indonesia-sinovac-vaccine-halal.html (accessed on 28 May 2022).
- Mardian, Y.; Shaw-Shaliba, K.; Karyana, M.; Lau, C.-Y. Sharia (Islamic Law) Perspectives of COVID-19 Vaccines. Front. Trop. Dis. 2021. [Google Scholar] [CrossRef]
- Shams, A.B.; Hoque Apu, E.; Rahman, A.; Sarker Raihan, M.M.; Siddika, N.; Preo, R.B.; Hussein, M.R.; Mostari, S.; Kabir, R. Web Search Engine Misinformation Notifier Extension (SEMiNExt): A Machine Learning Based Approach during COVID-19 Pandemic. Healthcare 2021, 9, 156. [Google Scholar] [CrossRef]
- Kabamba Nzaji, M.; Kabamba Ngombe, L.; Ngoie Mwamba, G.; Banza Ndala, D.B.; Mbidi Miema, J.; Luhata Lungoyo, C.; Lora Mwimba, B.; Cikomola Mwana Bene, A.; Mukamba Musenga, E. Acceptability of Vaccination Against COVID-19 Among Healthcare Workers in the Democratic Republic of the Congo. Pragmat. Obs. Res. 2020, 11, 103–109. [Google Scholar] [CrossRef]
- Roozenbeek, J.; Schneider, C.R.; Dryhurst, S.; Kerr, J.; Freeman, A.L.J.; Recchia, G.; van der Bles, A.M.; van der Linden, S. Susceptibility to misinformation about COVID-19 around the world. R. Soc. Open Sci. 2020, 7, 201199. [Google Scholar] [CrossRef]
- Szmyd, B.; Bartoszek, A.; Karuga, F.F.; Staniecka, K.; Błaszczyk, M.; Radek, M. Medical Students and SARS-CoV-2 Vaccination: Attitude and Behaviors. Vaccines 2021, 9, 128. [Google Scholar] [CrossRef] [PubMed]
- Chapman, G.; Al Imam, M.H.; Khan, A.; Smoll, N.; Adegbija, O.; Kirk, M.; Khandaker, G.; Wiley, K. “Scary to get, more scary not to”: COVID-19 vaccine acceptance among healthcare workers in Central Queensland, Australia, a cross-sectional survey. Commun. Dis. Intell. 2022, 2018, 46. [Google Scholar] [CrossRef] [PubMed]
Variables | Levels | Intention to Receive a COVID-19 Vaccine | ||||
---|---|---|---|---|---|---|
No | Yes | Total | Univariable Analysis | Multivariable Analysis a | ||
N (Row %) | N (Col. %) | OR (95% CI of OR, p Value) | ||||
Age group | 18–29 | 61 (11.9) | 452 (88.1) | 513 (22.2) | - | - |
30–39 | 70 (6.9) | 951 (93.1) | 1021 (44.3) | 1.83 (1.28–2.63, p = 0.001) | 0.98 (0.53–1.81, p = 0.960) | |
40–49 | 88 (20.0) | 351 (80.0) | 439 (19.0) | 0.54 (0.38–0.77, p = 0.001) | 0.81 (0.43–1.54, p = 0.526) | |
50–64 | 157 (47.0) | 177 (53.0) | 334 (14.5) | 0.15 (0.11–0.21, p < 0.001) | 0.20 (0.10–0.41, p < 0.001) | |
Sex | Female | 233 (18.5) | 1024 (81.5) | 1257 (54.5) | - | - |
Male | 143 (13.6) | 906 (86.4) | 1049 (45.5) | 1.44 (1.15–1.81, p = 0.002) | 2.56 (1.78–3.72, p < 0.001) | |
Education | Secondary or below | 228 (25.3) | 674 (74.7) | 902 (39.1) | - | - |
Tertiary | 148 (10.5) | 1257 (89.5) | 1405 (60.9) | 2.87 (2.29–3.61, p < 0.001) | 1.01 (0.64–1.58, p = 0.973) | |
Nationality | Non-Jordanian | 74 (20.2) | 293 (79.8) | 367 (15.9) | - | - |
Jordanian | 302 (15.6) | 1638 (84.4) | 1940 (84.1) | 1.37 (1.03–1.81, p = 0.029) | 0.65 (0.44–0.97, p = 0.038) | |
Region | Other cities | 362 (27.2) | 967 (72.8) | 1329 (57.6) | - | - |
Amman | 14 (1.4) | 964 (98.6) | 978 (42.4) | 25.78 (15.60-46.43, p < 0.001) | 51.78 (27.74-104.05, p < 0.001) | |
Occupation | Health professionals | 30 (12.0) | 220 (88.0) | 250 (12.7) | - | - |
Non-health professionals | 38 (5.6) | 644 (94.4) | 682 (34.5) | 2.31 (1.39–3.81, p = 0.001) | 1.57 (0.87–2.84, p = 0.136) | |
Other | 230 (32.3) | 483 (67.7) | 713 (36.1) | 0.29 (0.19–0.43, p < 0.001) | 0.16 (0.08–0.30, p < 0.001) | |
Student | 45 (13.6) | 285 (86.4) | 330 (16.7) | 0.86 (0.52–1.41, p = 0.561) | 0.53 (0.24–1.13, p = 0.102) | |
Receive flu vaccine every year | Yes | 44 (18.3) | 197 (81.7) | 241 (10.4) | - | - |
No | 332 (16.1) | 1734 (83.9) | 2066 (89.6) | 1.17 (0.82–1.64, p = 0.385) | - | |
History of COVID-19 infection | Yes | 240 (22.2) | 841 (77.8) | 1081 (46.9) | – | – |
No | 136 (11.1) | 1090 (88.9) | 1226 (53.1) | 2.29 (1.82–2.88, p < 0.001) | 5.97 (3.30–11.48, p < 0.001) | |
History of COVID-19 infection in the family | Yes | 255 (18.1) | 1153 (81.9) | 1408 (61.0) | – | – |
No | 121 (13.5) | 778 (86.5) | 899 (39.0) | 1.42 (1.13–1.80, p = 0.003) | 1.02 (0.52–1.93, p = 0.949) |
Variables | Levels | Intention to Receive COVID-19 Vaccine | ||||
---|---|---|---|---|---|---|
No | Yes | Total | Univariable Analysis | Multivariable Analysis a | ||
N (Row %) | N (Col. %) | OR (95% CI of OR, p Value) | ||||
Perceived susceptibility | ||||||
Chance of getting COVID-19 in the future is very high | Disagree | 301 (26.5) | 835 (73.5) | 1136 (49.2) | - | - |
Agree | 75 (6.4) | 1096 (93.6) | 1171 (50.8) | 5.27 (4.05–6.93, p < 0.001) | 2.81 (1.84–4.34, p < 0.001) | |
Currently, getting COVID-19 is a strong possibility | Disagree | 229 (27.9) | 591 (72.1) | 820 (35.5) | - | - |
Agree | 147 (9.9) | 1340 (90.1) | 1487 (64.5) | 3.53 (2.81–4.45, p < 0.001) | 5.00 (2.82–9.04, p < 0.001) | |
Perceived severity | ||||||
Complications of COVID-19 are very serious | Disagree | 191 (35.9) | 341 (64.1) | 532 (23.1) | - | - |
Agree | 185 (10.4) | 1590 (89.6) | 1775 (76.9) | 4.81 (3.81–6.08, p < 0.001) | 9.93 (5.35–18.76, p < 0.001) | |
I will be very sick if I get COVID-19 | Disagree | 177 (24.9) | 534 (75.1) | 711 (30.8) | - | - |
Agree | 199 (12.5) | 1397 (87.5) | 1596 (69.2) | 2.33 (1.86–2.92, p < 0.001) | 0.14 (0.06–0.28, p < 0.001) | |
Perceived benefits | ||||||
Vaccination will decrease my chances of getting COVID-19 | Disagree | 307 (63.7) | 175 (36.3) | 482 (20.9) | - | - |
Agree | 69 (3.8) | 1756 (96.2) | 1825 (79.1) | 44.65 (33.14–60.89, p < 0.001) | 100.77 (57.09–186.95, p < 0.001) | |
Perceived barriers | ||||||
Concerned about the efficacy of the vaccine | Disagree | 17 (1.4) | 1185 (98.6) | 1202 (52.1) | - | - |
Agree | 359 (32.5) | 746 (67.5) | 1105 (47.9) | 0.03 (0.02–0.05, p < 0.001) | 0.22 (0.09–0.46, p < 0.001) | |
Concerned about the safety/side effects of the vaccine | Disagree | 17 (1.6) | 1068 (98.4) | 1085 (47.0) | - | - |
Agree | 359 (29.4) | 863 (70.6) | 1222 (53.0) | 0.04 (0.02–0.06, p < 0.001) | 0.19 (0.08–0.43, p < 0.001) | |
Concerned about the halal nature of the vaccine | Disagree | 194 (10.9) | 1587 (89.1) | 1781 (77.2) | - | - |
Agree | 182 (34.6) | 344 (65.4) | 526 (22.8) | 0.23 (0.18–0.29, p < 0.001) | 2.24 (1.31–3.92, p = 0.004) | |
Cues to action | ||||||
Will get vaccine after receiving complete information | Disagree | 64 (14.7) | 371 (85.3) | 435 (18.9) | - | - |
Agree | 312 (16.7) | 1560 (83.3) | 1872 (81.1) | 0.86 (0.64–1.15, p = 0.320) | - | |
Will get vaccine if it is first accepted by many people | Disagree | 80 (8.0) | 922 (92.0) | 1002 (43.4) | - | - |
Agree | 296 (22.7) | 1009 (77.3) | 1305 (56.6) | 0.30 (0.23–0.38, p < 0.001) | 0.29 (0.16–0.53, p < 0.001) | |
Will get vaccine if it does not cause undue problems to vaccinated people | Disagree | 64 (5.7) | 1062 (94.3) | 1126 (48.8) | - | - |
Agree | 312 (26.4) | 869 (73.6) | 1181 (51.2) | 0.17 (0.13–0.22, p < 0.001) | 0.21 (0.11–0.41, p < 0.001) |
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Mahmud, I.; Al Imam, M.H.; Vinnakota, D.; Kheirallah, K.A.; Jaber, M.F.; Abalkhail, A.; Alasqah, I.; Alslamah, T.; Kabir, R. Vaccination Intention against COVID-19 among the Unvaccinated in Jordan during the Early Phase of the Vaccination Drive: A Cross-Sectional Survey. Vaccines 2022, 10, 1159. https://doi.org/10.3390/vaccines10071159
Mahmud I, Al Imam MH, Vinnakota D, Kheirallah KA, Jaber MF, Abalkhail A, Alasqah I, Alslamah T, Kabir R. Vaccination Intention against COVID-19 among the Unvaccinated in Jordan during the Early Phase of the Vaccination Drive: A Cross-Sectional Survey. Vaccines. 2022; 10(7):1159. https://doi.org/10.3390/vaccines10071159
Chicago/Turabian StyleMahmud, Ilias, Mahmudul Hassan Al Imam, Divya Vinnakota, Khalid A. Kheirallah, Mahmoud F. Jaber, Adil Abalkhail, Ibrahim Alasqah, Thamer Alslamah, and Russell Kabir. 2022. "Vaccination Intention against COVID-19 among the Unvaccinated in Jordan during the Early Phase of the Vaccination Drive: A Cross-Sectional Survey" Vaccines 10, no. 7: 1159. https://doi.org/10.3390/vaccines10071159