Attitudes toward COVID-19 vaccination and willingness to pay: comparison of people with and without mental disorders in China

Hao, Fengyi; Wang, Bokun; Tan, Wanqiu; Husain, Syeda Fabeha; McIntyre, Roger S.; Tang, Xiangdong; Zhang, Ling; Han, Xiaofan; Jiang, Li; Chew, Nicholas; Tan, Benjamin Yong‐Qiang; Tran, Bach Xuan; Zhang, Zhisong; Vu, Gia Linh; Vu, Giang Thu; Ho, Roger; Ho, Cyrus S.H.; Sharma, Vijay K.

doi:10.1192/bjo.2021.979

Cited by 81 publications

(79 citation statements)

References 33 publications

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“…The same study also finds that having private health insurance and living with children or dependents are associated with a higher willingness to be vaccinated. At the same time, these findings are not significant in our study [ 39 ]. Another study looking at healthcare workers in Asia–Pacific finds that 95% of the respondents are willing to be vaccinated, in contrast to 86.8% in our study [ 40 ].…”

Section: Discussioncontrasting

confidence: 77%

“…However, some considerations should be taken into account when accounting for the higher rate of vaccination in healthcare workers, such as mandate bias by the institutions or state [ 41 , 42 ], fear of contracting the virus as a frontline worker [ 43 ], and attitudes towards vaccination [ 44 ]. Gauging vaccine acceptance in healthcare workers also needs further research as results are still conflicting as to whether healthcare workers embrace or oppose COVID-19 vaccination [ 39 , 40 , 44 – 47 ].…”

Section: Discussionmentioning

confidence: 99%

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Psychological factors affecting COVID-19 vaccine acceptance in Indonesia

Yanto

Octavius

Heriyanto

et al. 2021

Egypt J Neurol Psychiatry Neurosurg

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Introduction Increasing the rate of vaccination is crucial in combating the COVID-19 pandemic. However, a survey of 112,888 Indonesians found that only 64.8% Indonesians were willing to be vaccinated, with 7.6% refusing all vaccines and 27.6% are unsure. Several factors were related to this vaccine hesitancy and refusal, such as cognitive reflection, trust in authoritative figures, and personality traits. This study aims to identify psychological determinants and other factors associated with vaccine hesitancy and vaccine refusal. This was a cross-sectional study with data collection done in March 2021 using a questionnaire. We collected demographic data, respondents' stance on vaccination, as well as their psychology measurement. IBM SPSS 26.0 (Statistical Package for the Social Sciences, IBM Corp., Armonk, NY, USA) was used for statistical analysis. Results The data of 190 respondents were collected for this study. There are 165 respondents (86.8%) who belong to “vaccine acceptance”, while 25 are “vaccine hesitance” or “vaccine resistance.” Multivariate analysis shows that frequency of COVID-19 tests (p = 0.03), smoking status (p = 0.035), agreeableness trait (p = 0.001), trust in government (p = 0.04) and trust in scientist (p = 0.049) are significantly associated with the two population. Conclusion Several demographic and psychological factors affect the COVID-19 vaccine acceptance. The government and other related parties should consider these factors when adjusting for future policies controlling the COVID-19 pandemic and increasing the vaccination rate.

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Section: Discussioncontrasting

confidence: 77%

Section: Discussionmentioning

confidence: 99%

Psychological factors affecting COVID-19 vaccine acceptance in Indonesia

Yanto

Octavius

Heriyanto

et al. 2021

Egypt J Neurol Psychiatry Neurosurg

View full text Add to dashboard Cite

show abstract

“…As the global and review evidence show adverse mental effect due to the pandemic is not country-specific, we call for fellow researchers to include these under-researched countries so that useful and timely assistance can be provided to its people as well. Finally, more recent studies have begun to explore the effects and roles of COVID-19 vaccination targeting various cohorts including parents (Yılmaz & Sahin, 2021 ) and general population (Hao et al, 2021 ), with findings suggesting individuals with adverse psychological symptoms such as depression and anxiety to exhibit a higher willingness to pay for the said vaccine compared to healthy individuals (Hao et al, 2021 ). Therefore, it would be interesting to further examine risk factors associated with COVID-19 vaccination and their associations with adverse mental health effects as well.…”

Section: Discussionmentioning

confidence: 99%

COVID-19 mental health prevalence and its risk factors in South East Asia

Balakrishnan

Kaur

et al. 2022

Curr Psychol

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With the record surge of positive cases in Southeast Asia, there is a need to examine the adverse mental effects of COVID-19 among the under-researched countries. This study aims to synthesize the extant literature reporting the effects of COVID-19 pandemic on the psychological outcomes of people in Southeast Asia, and its risk factors. A scoping review was adopted targeting articles published in PubMed, Google Scholar and Scopus from January 2020 to March 30, 2021. Articles were screened using predetermined eligibility criteria, resulting in 26 papers. Elevated prevalence of adverse mental effects was noted in most of the countries as the pandemic progressed over time, with Malaysia and Philippines reporting higher prevalence rates. Mental decline was found to be more profound among the general population compared to healthcare workers and students. Dominant risk factors reported were age (younger), sex (females), education (higher), low coping skill and social/family support, and poor reliability in COVID-19 related information. Adverse mental effects were noted among population, healthcare workers and students in most of the Southeast Asian countries. Intervention and prevention efforts should be based at community-level and prioritize young adults, females, and individuals with dire financial constraints.

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“…Although not the main focus of this study, our evaluation framework can also be applied to assess the vaccination deployment worldwide, in order to contribute to the perception of vaccine safety and increase willingness to receive it, as pointed out by [ 55 ]. Recently, [ 56 ] have made available a free-to-access global dataset that tracks the scale and rate of vaccine rollout.…”

Section: Discussionmentioning

confidence: 99%

Using GAM functions and Markov-Switching models in an evaluation framework to assess countries’ performance in controlling the COVID-19 pandemic

et al. 2021

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Background The COVID-19 pandemic has initiated several initiatives to better understand its behavior, and some projects are monitoring its evolution across countries, which naturally leads to comparisons made by those using the data. However, most “at a glance” comparisons may be misleading because the curve that should explain the evolution of COVID-19 is different across countries, as a result of the underlying geopolitical or socio-economic characteristics. Therefore, this paper contributes to the scientific endeavour by creating a new evaluation framework to help stakeholders adequately monitor and assess the evolution of COVID-19 in countries, considering the occurrence of spikes, "secondary waves" and structural breaks in the time series. Methods Generalized Additive Models were used to model cumulative and daily curves for confirmed cases and deaths. The Root Relative Squared Error and the Percentage Deviance Explained measured how well the models fit the data. A local min-max function was used to identify all local maxima in the fitted values. The pure Markov-Switching and the family of Markov-Switching GARCH models were used to identify structural breaks in the COVID-19 time series. Finally, a quadrants system to identify countries that are more/less efficient in the short/long term in controlling the spread of the virus and the number of deaths was developed. Such methods were applied in the time series of 189 countries, collected from the Centre for Systems Science and Engineering at Johns Hopkins University. Results Our methodology proves more effective in explaining the evolution of COVID-19 than growth functions worldwide, in addition to standardizing the entire estimation process in a single type of function. Besides, it highlights several inflection points and regime-switching moments, as a consequence of people’s diminished commitment to fighting the pandemic. Although Europe is the most developed continent in the world, it is home to most countries with an upward trend and considered inefficient, for confirmed cases and deaths. Conclusions The new outcomes presented in this research will allow key stakeholders to check whether or not public policies and interventions in the fight against COVID-19 are having an effect, easily identifying examples of best practices and promote such policies more widely around the world.

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Attitudes toward COVID-19 vaccination and willingness to pay: comparison of people with and without mental disorders in China

Cited by 81 publications

References 33 publications

Psychological factors affecting COVID-19 vaccine acceptance in Indonesia

Psychological factors affecting COVID-19 vaccine acceptance in Indonesia

COVID-19 mental health prevalence and its risk factors in South East Asia

Using GAM functions and Markov-Switching models in an evaluation framework to assess countries’ performance in controlling the COVID-19 pandemic

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