Volume 36, Issue 144 (November 2023)                   IJN 2023, 36(144): 386-397 | Back to browse issues page


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Moghimi S, Seraji M, Arab Borzu Z. Predicting the Factors Related to the Acceptance of COVID-19 Vaccination by Pregnant and Lactating Women Referring to Comprehensive Health Service Centers in Zahedan, Iran, Using the Health Belief Model. IJN 2023; 36 (144) :386-397
URL: http://ijn.iums.ac.ir/article-1-3716-en.html
1- Student Research and Technology Committee, Zahedan University of Medical Sciences, Zahedan, Iran.
2- Health Education and Health Promotion, Health Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran. , serajimaryam@gmail.com
3- Department of Epidemiology & Biostatistics, Zahedan University of Medical Sciences, Zahedan, Iran.
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Introduction
The COVID-19 pandemic caused high damages to the health of people and the economy of many countries. Vaccination is the most successful method to control the COVID-19 pandemic. Although vaccination is an effective method to reduce infected cases, its use depends on the willingness of people to receive the vaccine. Vaccine hesitancy may relate to several factors, including lack of information about COVID-19 and distrust in vaccine or healthcare providers and policy makers. Pregnant women are at higher risk of complications associated with COVID-19 infection including admission to the intensive care unit, invasive ventilation, preterm birth, hypertensive disorders of pregnancy, and maternal and neonatal morbidity and mortality.
It was first recommended that women should not receive the COVID-19 vaccine during pregnancy or lactation; however, with increasing evidence for the substantial risks of COVID-19 during pregnancy, pregnant women were later considered to be high priority for vaccination. The health belief model (HBM) is one of the most widely used models for examining the relationship between health-related behaviors and the use of health services. HBM has been widely used in the context of vaccination, especially the influenza vaccination. According to this model, individuals’ beliefs about health play a role in determining health-related behaviors. The HBM was used in the present study to predict the factors affecting the acceptance of COVID-19 vaccines among pregnant or lactating women referring to comprehensive health service centers in Zahedan, Iran.

Methods
This is a cross-sectional study that was conducted from July to September 2022. The statistical population included all pregnant and lactating women referring to comprehensive health service centers in Zahedan city. Using the Cochran formula and based on the previous studies, the sample size was determined 230. By considering a 10% sample dropout, 260 women were selected by convenience sampling method. The city of Zahedan was divided into four regions of North, South, East and West. Then, two comprehensive health service centers were selected from each region. The entry criteria were pregnancy or lactation and declaring informed consent. To collect data, a researcher-made questionnaire based on the HBM constructs was used. 
The reliability of the questionnaire was evaluated using Cronbach’s alpha coefficient, which was obtained 0.7. Moreover, the content validity index value was 0.81 and the content validity ratio was 0.77. After collecting, the questionnaires, to analyze the data, descriptive statistics including mean, standard deviation, frequency, and percentage were used. Due to non-normality of data distribution based on the Kolmogorov-Smirnov test results, non-parametric Mann-Whitney U test and Kruskal-Wallis test and regression analysis were used. The significance level was set at 0.05 and data analysis was done in SPSS software, version 22.

Results
Among the participants. 61% were in the age group of 20-30 years, and most of participants had middle school education or higher (47.7%) and were housekeeper (93.8%). Based on the age factor, the difference between women in the HBM domains was significant (P<0.05) except for perceived sensitivity and perceived barriers (P>0.05). There was a bivariate correlation between HBM domains and vaccine acceptance behavior in women. The demographic variables could predict 12.6% of the variance in the vaccine acceptance behavior, where only the variables of age and education level were found to be significant, such that younger age and higher educational level had a positive effect on the vaccine acceptance behavior (P<0.05). Moreover, the HBM constructs predicted 26.3% of the variance in vaccine acceptance behavior, where only self-efficacy and perceived benefits had a significant effect on the behavior (P<0.05).

Conclusion
The results of this research showed that younger age and high educational level are factors that the can predict the COVID-19 vaccine acceptance behavior of pregnant or lactating women in the south of Iran. The self-efficacy and perceived benefits as two constructs of the HBM can also predict the acceptance of vaccination. These findings can help policymakers and health care providers to use this model in designing programs for improving vaccination acceptance behaviors of these high-risk groups. In addition, it is necessary to use methods to increase the acceptance of vaccination for COVID-19, in pregnant or lactating women with low educational level.

Ethical Considerations
Compliance with ethical guidelines

Informed consent was obtained from the participants. The present study was approved by the Ethics Committee of Zahedan University of Medical Sciences (Code: IR.ZAUMS.REC.1401.087).

Funding
The present study was extracted from a research project (Grand No.: 10637), funded by Zahedan University of Medical Sciences.

Authors' contributions
Sara Moghimi: preparing the initial draft, collecting data, writing, and editing the article; Maryam Seraji: supervision, design; Zahra Arab Borzu: data analysis.

Conflict of interest
The authors declare no conflict of interest. 

Acknowledgments
The authors would like to thank the staff of comprehensive health centers in Zahedan and all the women participated in this research for their cooperation. 
 
References
  1. Hassan B, Gupta D. COVID-19 vaccine uptake in papua new guinea: An uphill challenge-exploring key options. J Dev Commun. 2022; 33(2):14-23. [Link]
  2. Odejinmi F, Mallick R, Neophytou C, Mondeh K, Hall M, Scrivener C, et al. COVID-19 vaccine hesitancy: A midwifery survey into attitudes towards the COVID-19 vaccine. BMC Public Health. 2022; 22(1):1219. [DOI:10.1186/s12889-022-13540-y] [PMID]   
  3. Ramlawi S, Muldoon KA, Dunn SI, Murphy MSQ, Dingwall-Harvey ALJ, Rennicks White R,  et al. Worries, beliefs and factors influencing perinatal COVID-19 vaccination: A cross-sectional survey of preconception, pregnant and lactating individuals. BMC Public Health. 2022; 22(1):2418.  [DOI:10.1186/s12889-022-14617-4] [PMID]   
  4. Chekol Abebe E, Ayalew Tiruneh G, Asmare Adela G, Mengie Ayele T, Tilahun Muche Z, Behaile T/Mariam A, et al. COVID-19 vaccine uptake and associated factors among pregnant women attending antenatal care in Debre Tabor public health institutions: A cross-sectional study. Front Public Health. 2022; 10:919494. [DOI:10.3389/fpubh.2022.919494] [PMID]   
  5. Rehman E, Rehman N, Akhlaq M, Hussain I, Holy O. COVID-19 vaccine reluctance and possible driving factors: A comparative assessment among pregnant and non-pregnant women. Front Public Health. 2023; 10:1100130.  [DOI:10.3389/fpubh.2022.1100130] [PMID]   
  6. Shook LL, Fallah PN, Silberman JN, Edlow AG. COVID-19 vaccination in pregnancy and lactation: Current research and gaps in understanding. Front Cell Infect Microbiol. 2021; 11:735394. [DOI:10.3389/fcimb.2021.735394] [PMID]   
  7. Bender JM, Lee Y, Cheng WA, Ruiz CJM, Pannaraj PS. Coronavirus disease 2019 vaccine booster effects are seen in human milk antibody response. Front Nutr. 2022; 9:898849. [DOI:10.3389/fnut.2022.898849] [PMID]   
  8. Mongua-Rodríguez N, Rodríguez-Álvarez M, De-la-Rosa-Zamboni D, Jiménez-Corona ME, Castañeda-Cediel ML, Miranda-Novales G, et al. Knowledge, attitudes, perceptions, and COVID-19 hesitancy in a large public university in Mexico city during the early vaccination rollout. BMC Public Health. 2022; 22(1):1853. [DOI:10.1186/s12889-022-14225-2] [PMID]   
  9. Ezati Rad R, Kahnouji K, Mohseni S, Shahabi N, Noruziyan F, Farshidi H, et al. Predicting the COVID-19 vaccine receive intention based on the theory of reasoned action in the south of Iran. BMC Public Health. 2022; 22(1):229. [DOI:10.1186/s12889-022-12517-1] [PMID]   
  10. Seangpraw K, Pothisa T, Boonyathee S, Ong-Artborirak P, Tonchoy P, Kantow S, et al. Using the health belief model to predict vaccination intention among COVID-19 unvaccinated people in Thai Communities. Front Med (Lausanne). 2022; 9:890503. [DOI:10.3389/fmed.2022.890503] [PMID]   
  11. Le CN, Nguyen UTT, Do DTH. Predictors of COVID-19 vaccine acceptability among health professions students in Vietnam. BMC Public Health. 2022; 22(1):854. [DOI:10.1186/s12889-022-13236-3] [PMID]   
  12. Ashwell D, Cullinane J, Croucher SM. COVID-19 vaccine hesitancy and patient self-advocacy: A statistical analysis of those who can and can't get vaccinated. BMC Public Health. 2022; 22(1):1296.  [DOI:10.1186/s12889-022-13661-4] [PMID]   
  13. Healy CM. COVID-19 in Pregnant Women and Their Newborn Infants. JAMA Pediatr. 2021; 175(8):781-3.  [DOI:10.1001/jamapediatrics.2021.1046] [PMID]
  14. Karimy M, Bastami F, Sharifat R, Heydarabadi AB, Hatamzadeh N, Pakpour AH, et al. Factors related to preventive COVID-19 behaviors using health belief model among general population: A cross-sectional study in Iran. BMC Public Health. 2021; 21(1):1934. [DOI:10.1186/s12889-021-11983-3] [PMID]   
  15. Shmueli L. Predicting intention to receive COVID-19 vaccine among the general population using the health belief model and the theory of planned behavior model. BMC Public Health. 2021; 21(1):804. [DOI:10.1186/s12889-021-10816-7] [PMID]   
  16. Shewasinad Yehualashet S, Asefa KK, Mekonnen AG, Gemeda BN, Shiferaw WS, Aynalem YA, et al. Predictors of adherence to COVID-19 prevention measure among communities in North Shoa Zone, Ethiopia based on health belief model: A cross-sectional study. PloS One. 2021; 16(1):e0246006. [DOI:10.1371/journal.pone.0246006] [PMID]   
  17. Tadesse T, Alemu T, Amogne G, Endazenaw G, Mamo E. Predictors of coronavirus disease 2019 (COVID-19) prevention practices using health belief model among employees in Addis Ababa, Ethiopia, 2020. Infect Drug Resist. 2020; 13:3751-61. [DOI:10.2147/IDR.S275933] [PMID]   
  18. Baek J, Kim KH, Choi JW. Determinants of adherence to personal preventive behaviours based on the health belief model: a cross-sectional study in South Korea during the initial stage of the COVID-19 pandemic. BMC Public Health. 2022; ;22(1):944. [DOI:10.1186/s12889-022-13355-x] [PMID]  
  19. Zampetakis LA, Melas C. The health belief model predicts vaccination intentions against COVID-19: A survey experiment approach. Appl Psychol Health Well Being. 2021; 13(2):469-84. [DOI:10.1111/aphw.12262] [PMID]   
  20. Nguyen LH, Hoang MT, Nguyen LD, Ninh LT, Nguyen HTT, Nguyen AD, et al. Acceptance and willingness to pay for COVID-19 vaccines among pregnant women in Vietnam. Trop Med Int Health. 2021; 26(10):1303-13. [DOI:10.1111/tmi.13666] [PMID]   
  21. Tao L, Wang R, Han N, Liu J, Yuan C, Deng L, et al. Acceptance of a COVID-19 vaccine and associated factors among pregnant women in China: A multi-center cross-sectional study based on health belief model. Hum Vaccin Immunother. 2021; 17(8):2378-88.  [DOI:10.1080/21645515.2021.1892432] [PMID]   
  22. Rezakhani Moghaddam H, Ranjbaran S, Babazadeh T. The role of e-health literacy and some cognitive factors in adopting protective behaviors of COVID-19 in Khalkhal residents. Front Public Health. 2022; 10:916362. [DOI:10.3389/fpubh.2022.916362] [PMID]   
  23. Alipour J, Payandeh A. Assessing the level of digital health literacy among healthcare workers of teaching hospitals in the southeast of Iran. Inf Med Unlocked. 2022; 29:100868. [DOI:10.1016/j.imu.2022.100868]
  24. Zakar R, Iqbal S, Zakar MZ, Fischer F. COVID-19 and health information seeking behavior: Digital health literacy survey amongst university students in Pakistan. Int J Environ Res Public Health. 2021; 18(8):4009. [DOI:10.3390/ijerph18084009] [PMID]   
  25. Du M, Tao L, Liu J. Association between risk perception and influenza vaccine hesitancy for children among reproductive women in China during the COVID-19 pandemic: A national online survey. BMC Public Health. 2022; 22(1):385. [DOI:10.1186/s12889-022-12782-0] [PMID]   
  26. Yoda T, Katsuyama H. Willingness to receive COVID-19 vaccination in Japan. Vaccines. 2021; 9(1):48. [DOI:10.3390/vaccines9010048] [PMID]   
  27. Malik AA, McFadden SM, Elharake J, Omer SB. Determinants of COVID-19 vaccine acceptance in the US. EClinicalMedicine. 2020; 26:100495. [DOI:10.1016/j.eclinm.2020.100495] [PMID]  
  28. Kuciel N, Mazurek J, Hap K, Marciniak D, Biernat K, Sutkowska E. COVID-19 vaccine acceptance in pregnant and lactating women and mothers of young children in Poland. International Journal of Women's Health. 2022; 2022:415-24. [DOI:10.2147/IJWH.S348652] [PMID]   
  29. Fathian-Dastgerdi Z, Khoshgoftar M, Tavakoli B, Jaleh M. Factors associated with preventive behaviors of COVID-19 among adolescents: Applying the health belief model. Res Social Adm Pharm. 2021; 17(10):1786-90. [DOI:10.1016/j.sapharm.2021.01.014] [PMID]   
  30. Shahnazi H, Ahmadi-Livani M, Pahlavanzadeh B, Rajabi A, Hamrah MS, Charkazi A. Assessing preventive health behaviors from COVID-19: A cross sectional study with health belief model in Golestan Province, Northern of Iran. Infect Dis Poverty. 2020; 9(06):91-9. [DOI:10.1186/s40249-020-00776-2]
  31. Glanz K, Rimer BK, Viswanath K. Health behavior and health education: Theory, research, and practice. New Jersey: John Wiley & Sons; 2008. [Link]
  32. Kim S, Kim S. Analysis of the impact of health beliefs and resource factors on preventive behaviors against the COVID-19 pandemic.  Int J Environ Res Public Health. 2020; 17(22):8666.  [DOI:10.3390/ijerph17228666] [PMID]   
  33. Dror AA, Eisenbach N, Taiber S, Morozov NG, Mizrachi M, Zigron A, et al. Vaccine hesitancy: The next challenge in the fight against COVID-19. Eur J Epidemiol. 2020; 35(8):775-9. [DOI:10.1007/s10654-020-00671-y] [PMID]   
  34. Smith LE, Amlôt R, Weinman J, Yiend J, Rubin GJ. A systematic review of factors affecting vaccine uptake in young children. Vaccine. 2017; 35(45):6059-69. [DOI:10.1016/j.vaccine.2017.09.046] [PMID]
  35. Reiter PL, Pennell ML, Katz ML. Acceptability of a COVID-19 vaccine among adults in the United States: How many people would get vaccinated? Vaccine. 2020; 38(42):6500-7. [DOI:10.1016/j.vaccine.2020.08.043] [PMID]   

 
Type of Study: Research | Subject: nursing
Received: 2023/07/22 | Accepted: 2023/10/1 | Published: 2023/11/2

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