Prediction Equation for Estimating COVID-19 Vaccination Intentions among Older Adults: A Case Study of Chanthaburi Province

Main Article Content

Kessuda Khowsroy
Virat Khowsoi


The study aims to determine the logistic regression equation to predict among older adults

whether to receive the COVID-19 vaccination or not. The study population comprised 272 respondents who were above 60 years of age and resided in Chanthaburi Province. Using multi-stage cluster sampling, the data were gathered via paper and online platforms. Structured questionnaire based on the components of theory of planned behavior to assess the attitudes towards COVID-19 vaccine, subjective norm, perceived behavioral control, and COVID-19 vaccination intention. The results of content validity index (CVI) showed between 0.87-1.00, the reliability value of the alpha coefficient of Cronbach is between 0.80-0.84. Then Binary logistic regression was employed to analyze the data by using Enter method.There are 6 significant variables associated with the COVID-19 vaccine decision making for older adults as follows: 1) The belief that an elderly person needs a vaccination. 2) The belief that if people obtain the vaccine, their lives would return to normal. 3) Influence of family members 4) Medical professionals’s recommendation. 5) The belief in the effectiveness of vaccines.  6) The belief lowering the chance of getting severe COVID-19.  The model could predict overall correctly at 84.6% with Cox & Snell R2 = 0.502 and Nagelkerke R2 = 0.736. It could account for the COVID-19 vaccine intention's variation, which is 50.2% and 73.6%, respectively.

Article Details

How to Cite
Khowsroy, K., & Khowsoi, V. (2023). Prediction Equation for Estimating COVID-19 Vaccination Intentions among Older Adults: A Case Study of Chanthaburi Province. Rajamangala University of Technology Tawan-Ok Research Journal, 16(2), 14–23. Retrieved from
Research article
Author Biographies

Kessuda Khowsroy, Rambhai Barni Rajabhat University

Faculty of Nursing, Rambhai Barni Rajabhat University, Chanthaburi

Virat Khowsoi, Rajamangala University of Technology Tawan-Ok

Establishment Project Faculty of Integration Engineering and Technology, Chanthaburi Campus,


Abusalem, S., Abuhammad, S., Sha, S., Mar, M.M., Aljeesh, Y. & Eldeirawi, K.M. (2022). Intentions to Receive COVID-19 Vaccination among People in Gaza Strip. Electronic Journal of General Medicine, 19(6): em412.

Adu, P., Poopola, T., Medvedev, O.N., Collings, S., Mbinta, J., Aspin, C. & Simpson, C.R. (2023). Implications for COVID-19 Vaccine Uptake: A Systematic Review. Journal of Infection and Public Health, 16(3): 441-466.

Ajzen, I. (1991). The Theory of Planned Behavior. Organ Behav Hum Decis Process., 50(2): 179-211.

Ajzen, I. (2006). Behavioral Interventions Based on the Theory of Planned Behavior. Retrieved 30 May 2021, from ventions_Based _on_the_Theory_of_Planned_Behavior.

Al Janabi, T. & Pino, M. (2021). Predictors for Actual COVID-19 Vaccine Uptake and Intended Booster Dosage among Medical Students of an Osteopathic Medical School in New York. Epidemiologia., 2(4): 553-563.

Ali-Saleh, O., Khatib, M. & Hadid, S. (2023). Factors Predicting Compliance with the Uptake of the Third COVID-19 Vaccine among the Arab Minority in Israel. Health & Social Care in the Community, 2023: 1-10.

Berger, E. (2023). Covid Officials Say New ‘Arcturus’ Variant Could Be Linked to Conjunctivitis | Coronavirus | The Guardian. Retrieved 8 June 2023, from https://www.theguardian.Com/world/2023/may/09/covid-variant-arcturus-conjunctivitis.

Boontawee, C. (2022). Factors Affecting the Decision to Vaccinate Booster Shots of the Coronavirus (COVID-19) among the Personnel of Nursing Department, Police General Hospital. Journal of Research for Health Improvement and Quality of Life, 12(2):49-60.

Callow, M.A & Callow, D.D. (2021). Older Adults’ Behavior Intentions Once a COVID-19 Vaccine Becomes Available. J Appl Gerontol., 40(9): 943-952.

Caple, A., Dimaano, A., Sagolili, M.M., Uy, A.A., Aguirre, P.M., Alano, D.L., Camaya, G.S., Ciriaco, B.J.,Clavo, P.J.M., Cuyugan D., Fermo, C.F.G., Lanete, P.J., La Torre A.J., Loteyro, T., Lua, R.M.,Manansala, N.J., Mosquito, R.W., Orfanel A.E., Pascual G.M., Sale A.J., Tendenilla S.L., Trinidad,M.S.L, Trinidad, N.J, Verano D.L, Austriaco, N. (2022). Interrogating COVID-19 Vaccine Intent in the Philippines with a Nationwide Open-Access Online Survey. PeerJ., 10: e12887.

Charoensit, O. (2017). Binary Logistic Regression Analysis for Social Science Research. SAU Journal of Social Sciences & Humanities, 1(2): 1-9. (in Thai)

Chu, H. & Liu, S. (2021). Integrating Health Behavior Theories to Predict American’s Intention to Receive a COVID-19 Vaccine. Patient Educ Couns., 104(8): 1878-1886.

Cordina, Maria, Mary A. Lauri, & Josef Lauri. (2021). Attitudes towards Covid-19 Vaccination, Vaccine Hesitancy and Intention to Take the Vaccine. Pharm Pract (Granada), 19(1): 2317.

Drazkowski, D. & Trepanowski, R. (2022). Reactance and Perceived Disease Severity as Determinants of COVID-19 Vaccination Intention: An Application of the Theory of Planned Behavior. Psychol Health Med., 27(10): 2171–2178.

Ezati Rad, R., Kahnouji, K., Mohseni, S., Shahabi, N., Noruziyan, F., Farshidi, H., Hosseinpoor, M., Kashani, S., Takhti, K., Azad, M.H., & Teamur Aghamolaei. (2022). Predicting the COVID-19 Vaccine Receive Intention Based on the Theory of Reasoned Action in the South of Iran. BMC PublicHealth, 22(1): 229.

Fadda, M., Suggs L.S. & Albanese, E. (2021). Willingness to Vaccinate against Covid-19: A Qualitative Study Involving Older Adults from Southern Switzerland. Vaccine: X, 8:100108.

Fan, C.W., Chen, I.H., Ko, N.Y., Yen, C.F., Lin, C.Y., Griffiths M.D. & Pakpour, A.H. (2021). Extended Theory of Planned Behavior in Explaining the Intention to COVID-19 Vaccination Uptake among Mainland Chinese University Students: An Online Survey Study. Hum Vacc and Immunother, 17(10): 3413-3420.

Harris, J. K. (2021). Primer on Binary Logistic Regression. Fam Med Com Health, 9: e001290.

Hayashi, Y., Romanowich, P. & Hantula, D.A. (2022). Predicting Intention to Take a COVID-19 Vaccine in the United States: Application and Extension of Theory of Planned Behavior. Am J Health Promot., 36(4): 710-713.

Husain, F., Shahnawaz, M.G., Khan, N.H., Parveen, H. & Savani, K. (2021). Intention to Get COVID-19 Vaccines: Exploring the Role of Attitudes, Subjective Norms, Perceived Behavioral Control, Belief in COVID-19 Misinformation, and Vaccine Confidence in Northern India. Hum Vaccin Immunother. 17(11): 3941-3953.,

Khowsroy, K., Yajai, S., Khowsoi, V., Khaojang, C., Tookaew, R., Wongsangnoi, P. & Limcharoen, S. (2022). COVID-19 Vaccination Intention and Related Factors among Older Adults in Chanthaburi Province. J Prapokklao Hosp Clin Med Educat Center, 39(4): 466-474. (in Thai)

Kittipimpanon, K., Maneesriwongul, W., Butsing, N., Visudtibhan, J. & Leelacharas, S. (2022). COVID-19 Vaccine Literacy, Attitudes, and Vaccination Intention Against COVID-19 Among Thai Older Adults. Patient Preference and Adherence, 16: 2365-2374.

Limbu, Y. B., Gautam, R.K. & Zhou, W. (2022). Predicting Vaccination Intention against COVID-19 Using Theory of Planned Behavior: A Systematic Review and Meta-Analysis. Vaccines, 10(12): 2026.

Manageronline. (2022). ‘MorYong’ We Will Not Achieve Herd Immunity as Everyone Have to Be Vaccinated. September 4. Retrieved 4 June 2023, from (in Thai)

Mathieu, E., Ritchie, H., Ortiz-Ospina, E., Roser, M., Hasell, J., Appel, C., Giattino, C. & Rodés-Guirao, C.(2020). Coronavirus Pandemic (COVID-19). Our World in Data, 5(7): 947-953.

O’Mary, L. (2023). Bivalent Booster Helps Prevent Symptoms from XBB.1.5: Study. Retrieved 8 June 2023, from

Seddig, D., Maskileyson, D., Davidov, E., Ajzen, I. & Schmidt, P. (2022). Correlates of COVID-19 Vaccination Intentions: Attitudes, Institutional Trust, Fear, Conspiracy Beliefs, and Vaccine Skepticism. Soc Sci Med., 302: 114981.

Shmueli, L. (2021). 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, 21(1): 804.

Thato, R. (2018). Nursing Research: Concepts to Application. 4th ed. Chulalongkorn University Printing House, Bangkok. (in Thai)

Vivek Raj, S.N. & Manivann, S.K. (2022). Machine Learning Models to Predict COVID-19 Vaccination Intention: An INDian Study. Intern Journal of Profess Bus Review, 7(6): 1-16.

Wang, J., Li, T., Ge, J., Zhou, M., Walker, A.N., Chen, J., Zhang, T., Zhang, K., Gu, S., & You, H. (2023). Applying Two Behavioral Theories to Predict the Willingness to Receive COVID-19 Vaccine Booster in the Elderly: A Cross-Sectional Study. Res Social Adm Pharm., 19(3): 495-501.

Wilson, S.L. & Wiysonge, C. (2020). Social Media and Vaccine Hesitancy. BMJ Global Health, 5(10): 4206.

Zaid, S.A. & Al Bahy, M.P. (2022). Exploring the Role of Theory of Planned Behavior on Covid-19 Vaccination Intention. JEHCP., 11(3): 608-24.