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Social media have been playing a critical role in seeking and sharing health related information and consequently shaping individuals’ health behaviors. This study investigates how information seeking about Covid-19 vaccine on social media is related to vaccine receiving intentions. The study furthers explores the association of trust in social media and uncertainty about Covid-19 with information seeking and the moderating role of prior social media experience on this association.

We developed a questionnaire and collected data from 525 educated social media users through “Google Forms.” Further, we applied ordinary least squares (OLS) regress to test the study hypothesis.

We noted that trust in social media and uncertainty about Covid-19 vaccine positively influenced information seeking which further positively affected vaccine receiving intentions. However, the moderating effect of prior social media experience was not only noted as weak but also found negatively affecting the associations of trust in social media and uncertainty about Covid-19 vaccine with information seeking.

The findings provide insights into understanding of public perceptions regarding Covid-19 vaccine in the cultural contexts of a developing country. Further, it informs about the public patterns of seeking information related to health issues on social media, an understanding which may likely benefit policymakers, health care providers and researchers to understand the antecedents and behavioral outcomes of seeking information through social media during health crisis. The study also elucidates the leveraging power of social media to motivate the public to accept the Covid-19 vaccines.

The study uniquely combines the antecedents and behavioral outcomes of information seeking through social media in the particular context of Covid-19. It further extends the literature by introducing the conditional role of prior social media experience.

Many countries have a significant vaccination hesitancy rate regardless of vaccine prosperity. This study aims to identify factors restricting hesitancy and fostering vaccination intention and uptake against coronavirus in Vietnam.

The study has proposed an extended COM-B model based on the Theoretical Domains Framework to explore critical factors influencing vaccination intention and uptake in Vietnam. A database was collected from 1,015 suitable respondents who had received at least one dose of the COVID-19 vaccine, and ten hypotheses were tested by the partial least squares structural equation model.

The findings showed that six factors, including knowledge, experience, resource, social influence, belief and reinforcement, have either direct or indirect positive effects on COVID-19 vaccine uptake behavior. The output also indicated that personal experience positively affects vaccination intention and uptake.

This study contributes to understanding COVID-19 vaccine uptake behavior by identifying several direct and indirect factors of the extended COM-B model that include “knowledge” and “reinforcement” in shaping behavior change. The study adds to the literature on COVID-19 vaccine uptake behavior and could help achieve higher vaccination rates, ultimately leading to better control of the pandemic.

This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.