https://orcid.org/0000-0003-4368-6850
Dear editor
We read with great interest the study by AlshagrawiCitation1 on the determinants of intention to uptake COVID-19 vaccination among Saudi adults, utilizing the Health Belief Model (HBM). The comprehensive approach and insightful findings provide valuable contributions to understanding vaccine hesitancy and acceptance in a critical context. We agree with the conclusions but also have some additional suggestions to enhance the study’s implications and utility.
Firstly, while the study effectively highlights the significant predictors of vaccination intention, including perceived susceptibility, severity, benefits, and barriers, it would be beneficial to delve deeper into the role of social influence and community engagement. Previous research has shown that social norms and peer influence play a crucial role in health behavior decisions, particularly in collectivist cultures such as Saudi Arabia.Citation2,Citation3 Future studies could incorporate these social factors to provide a more holistic understanding of vaccination intentions.
Moreover, the study’s finding that marital status significantly influences vaccination intention suggests an interesting avenue for targeted interventions. However, expanding the demographic analysis to include other variables such as educational attainment, occupation, and geographic location could offer more nuanced insights. This could help in designing more tailored public health campaigns that address specific needs and concerns of different population segments.
The reliance on self-reported data and the cross-sectional nature of the study are acknowledged limitations. To address potential biases and enhance the robustness of the findings, future research could employ longitudinal designs and incorporate objective measures of vaccine uptake. This would allow for the assessment of changes in intentions over time and the actual behavior, providing a more dynamic view of the factors influencing vaccination decisions.
Additionally, the high explanatory power of the HBM in predicting vaccination intention (68%) is commendable. However, integrating other theoretical frameworks such as the Theory of Planned Behavior (TPB) or the Social Cognitive Theory (SCT) could enrich the predictive model. These theories emphasize the role of behavioral intentions, self-efficacy, and outcome expectancies, which could offer complementary perspectives and enhance the overall explanatory power.Citation4
We also suggest that future studies explore the impact of misinformation and conspiracy theories on vaccine hesitancy. Given the pervasive influence of social media and the rapid dissemination of false information, understanding how these factors affect public perception and behavior is crucial.Citation5 Strategies to combat misinformation and promote accurate, science-based information should be an integral part of vaccination campaigns.Citation6
Lastly, considering the global context, it would be valuable to compare these findings with similar studies conducted in different countries. Such comparative analyses could identify universal determinants and culturally specific factors, fostering international collaboration and the development of global strategies to combat vaccine hesitancy.
Alshagrawi’s study provides a solid foundation for understanding the determinants of COVID-19 vaccination intentions. Expanding the scope to include social influences, additional demographic factors, longitudinal data, and other theoretical models will allow future research to build on these findings and develop more effective interventions. Addressing misinformation and promoting cross-cultural studies will further enhance our ability to improve vaccine uptake globally.
We appreciate the opportunity to engage with this important work and look forward to future contributions in this vital area of public health research.
Disclosure
All authors report no conflicts of interest in this communication.
References
- Alshagrawi SS. Determinants of intention to uptake COVID-19 vaccination among Saudi adults: application of the health belief model. Risk Manag Healthc Policy. 2024;17:1803–1814. doi:10.2147/RMHP.S432153
- Ghosh S, Bhattacharya S, Mukherjee S, Chakravarty S. Promote to protect: data-driven computational model of peer influence for vaccine perception. Sci Rep. 2024;14(1):306. doi:10.1038/s41598-023-50756-3
- Khorram-Manesh A, Goniewicz K, Burkle FM. Unleashing the global potential of public health: a framework for future pandemic response. J Infect Public Health. 2023;17(1):82–95. doi:10.1016/j.jiph.2023.10.038
- Rather RA, Parrey SH, Gulzar R, Rehman SU. COVID-19-based threat vs coping appraisal: effect of psychological risk on customer engagement and behavioral intentions. J Hospital Tour Insight. 2023;6(5):2093–2114. doi:10.1108/JHTI-01-2022-0010
- Goniewicz K, Khorram-Manesh A, Burkle FM, Hertelendy AJ, Goniewicz M. The European Union’s post-pandemic strategies for public health, economic recovery, and social resilience. Glob Transit. 2023;5:201–209. doi:10.1016/j.glt.2023.10.003
- Taylor S, Taylor N, Baker P. Educating about mass vaccinations in a post-truth era. In: Challenges in Science Education: Global Perspectives for the Future 2023 Feb 9. Cham: Springer International Publishing; 2023:59–81.