Abstract:This study examines how online vaccine information seeking is related to vaccination intention in the United States and China during the initial stage of their coronavirus disease 2019 vaccination programs. Analysis of the pooled sample showed a positive relationship between online vaccine information seeking and vaccination intention. There was also a negative indirect effect via perceived information overload, vaccine risk perception, and negative affective response. Multigroup analysis revealed differences … Show more
“…Less is known about the relations between socioeconomic indicators and health, HIS, and HB among the older adults (Zhao et al, 2022;Jia et al, 2021;Eriksson-Backa et al, 2018;Asla and Williamson, 2015), especially during the COVID-19 pandemic. Zheng et al (2022) analyzed the relationship between online vaccine information seeking and vaccination intention. They found a positive correlation between these two variables.…”
Section: Older Adults' Online Hi Seekingmentioning
confidence: 99%
“…Zheng et al. (2022) analyzed the relationship between online vaccine information seeking and vaccination intention.…”
PurposeThe purpose of the article is to introduce the outcomes of a study analyzing the relationships between willingness to use technology for health purposes, health information behavior (HIB), health behavior (HB) choices, readiness for COVID-19 vaccination, socioeconomic indicators and self-reported health among older adults aged = 50 years living in Estonia.Design/methodology/approachA cross-sectional survey was conducted among 501 people aged = 50 in Estonia in 2020, a month after the end of lockdown.FindingsThe results of the study indicate that the more recurrent the need for HI was (rho = 0.11, p < 0.05) and the more regularly one searched for it (rho = 0.14, p < 0.01), the more willing a person was to get vaccinated. Also, interest in digital applications corresponded to vaccination readiness (rho = 0.25, p < 0.001). However, this relationship did not emerge in the case of other HBs such as healthy eating and exercise. Differences in HIB should be taken into account when developing effective means of health communication designed especially for crisis situations.Originality/valueEstonia is known as one of the digital front runners in the world. However, social welfare and the well-being of disadvantaged groups among the population (e.g. older people) have not yet caught up with the more developed Western countries. Thus, learning more about the health-related information behavior of older adults, e.g. the kind of health information they are seeking and using in Estonia, allows policymakers, health information providers and libraries in Estonia to plan and carry out more effective interventions and help them to improve the existing systems so as to furnish older adults with relevant information.
“…Less is known about the relations between socioeconomic indicators and health, HIS, and HB among the older adults (Zhao et al, 2022;Jia et al, 2021;Eriksson-Backa et al, 2018;Asla and Williamson, 2015), especially during the COVID-19 pandemic. Zheng et al (2022) analyzed the relationship between online vaccine information seeking and vaccination intention. They found a positive correlation between these two variables.…”
Section: Older Adults' Online Hi Seekingmentioning
confidence: 99%
“…Zheng et al. (2022) analyzed the relationship between online vaccine information seeking and vaccination intention.…”
PurposeThe purpose of the article is to introduce the outcomes of a study analyzing the relationships between willingness to use technology for health purposes, health information behavior (HIB), health behavior (HB) choices, readiness for COVID-19 vaccination, socioeconomic indicators and self-reported health among older adults aged = 50 years living in Estonia.Design/methodology/approachA cross-sectional survey was conducted among 501 people aged = 50 in Estonia in 2020, a month after the end of lockdown.FindingsThe results of the study indicate that the more recurrent the need for HI was (rho = 0.11, p < 0.05) and the more regularly one searched for it (rho = 0.14, p < 0.01), the more willing a person was to get vaccinated. Also, interest in digital applications corresponded to vaccination readiness (rho = 0.25, p < 0.001). However, this relationship did not emerge in the case of other HBs such as healthy eating and exercise. Differences in HIB should be taken into account when developing effective means of health communication designed especially for crisis situations.Originality/valueEstonia is known as one of the digital front runners in the world. However, social welfare and the well-being of disadvantaged groups among the population (e.g. older people) have not yet caught up with the more developed Western countries. Thus, learning more about the health-related information behavior of older adults, e.g. the kind of health information they are seeking and using in Estonia, allows policymakers, health information providers and libraries in Estonia to plan and carry out more effective interventions and help them to improve the existing systems so as to furnish older adults with relevant information.
“…Therefore, information-seeking patterns of misinformed and evidence-resistant citizens might systematically differ from other individuals. Moreover, research suggests that information-seeking can have important downstream effects on individuals’ intentions and behaviors during the COVID-19 pandemic ( Zheng et al, 2022 ).…”
Section: Misperceptionsmentioning
confidence: 99%
“…Specifically, this study contributes to existing research by testing not only where the misinformed segment searches for information, but also which type of information they seek out most frequently. Learning about information-seeking behavior is highly relevant since selective information-seeking and avoidance can further polarize audiences, affect compliance with preventive health measures ( Zheng et al, 2022 ), and expose them to new unsupported claims. Furthermore, knowing which information sources different audiences turn to is an important first step for designing audience-specific interventions to counter misperceptions.…”
This panel study in Austria in 2020 ( NW1 = 912, NW2 = 511) explores distinct audience segments regarding beliefs in misinformation, conspiracy, and evidence statements on COVID-19. I find that citizens fall into seven segments, three of which endorse unsupported claims: The threat skeptics selectively accept misinformation and evidence; the approvers tend to accept all types of information; and the misinformed believe in misinformation and conspiracy statements while rejecting evidence. Further analyses suggest that the misinformed increasingly sought out COVID-19 threat-negating information from scientific sources, while also overall attending to threat-confirming information. These patterns have practical implications for correcting misperceptions.
“…A social media content analysis using a Spanish corpus explored the contagious emotions present on social media and discussed how this might be an opportunity to use it as a “collective therapy” to allow for positive affect to spread ( Iglesias-Sánchez et al, 2020 ). Social media also provided a critical channel for users to proactively seek health information, such as knowledge about vaccines and preventive measures, which may be helpful in reducing the perceived risks associated with the disease ( Li and Zheng, 2022 ; Zheng et al, 2022 ). These studies, however, were unable to ascertain the causal direction between social media use and mental conditions.…”
BackgroundThe classic debate regarding the complex relationships between personal network, social media use, and mental well-being requires renewed examination in the novel context of pandemic-related social isolation.Data and methodWe present two surveys conducted at (i) the earlier months of the pandemic and (ii) the end of large scale social-lockdown measures in the U.S. to explore the social and behavioral antecedents of mental health states relating to social media use. Study 1 tracked the longitudinal changes of personal network, social media use, and anxiety level of a group of individuals (N = 147) over a three-month period during the pandemic. Study 2 replicated and extended the theoretical model to a race-representative U.S. adult sample (N = 258).ResultsBoth studies consistently show that (1) more time on social media worsens anxiety. It also mediates the relationship between personal network size and anxiety. That is, a small personal network predicts more social media use, which is in turn related to increased anxiety. (2) Moreover, the effect of social media use on anxiety is mainly explained by news consumption on social media, rather than non-news related usage. (3) This link’s strength is moderated by one’s perception of COVID-19 impact, such that news consumption on social media increases anxiety more when the perceived impact is higher.ConclusionThese results demonstrate communication technologies’ increasingly critical and multifaceted role in affecting mental health conditions.
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