How do psychobehavioural variables shed light on heterogeneity in COVID-19 vaccine acceptance? Evidence from United States general population surveys on a probability panel and social media.

OBJECTIVES: To (1) understand what behaviours, beliefs, demographics and structural factors predict US adults' intention to get a COVID-19 vaccination, (2) identify segments of the population ('personas') who share similar factors predicting vaccination intention, (3) create a 'typing tool' to predict which persona people belong to and (4) track changes in the distribution of personas over time and across the USA. DESIGN: Three surveys: two on a probability-based household panel (NORC's AmeriSpeak) and one on Facebook. SETTING: The first two surveys were conducted in January 2021 and March 2021 when the COVID-19 vaccine had just been made available in the USA. The Facebook survey ran from May 2021 to February 2022. PARTICIPANTS: All participants were aged 18+ and living in the USA. OUTCOME MEASURES: In our predictive model, the outcome variable was self-reported vaccination intention (0-10 scale). In our typing tool model, the outcome variable was the five personas identified by our clustering algorithm. RESULTS: Only 1% of variation in vaccination intention was explained by demographics, with about 70% explained by psychobehavioural factors. We identified five personas with distinct psychobehavioural profiles: COVID Sceptics (believe at least two COVID-19 conspiracy theories), System Distrusters (believe people of their race/ethnicity do not receive fair healthcare treatment), Cost Anxious (concerns about time and finances), Watchful (prefer to wait and see) and Enthusiasts (want to get vaccinated as soon as possible). The distribution of personas varies at the state level. Over time, we saw an increase in the proportion of personas who are less willing to get vaccinated. CONCLUSIONS: Psychobehavioural segmentation allows us to identify why people are unvaccinated, not just who is unvaccinated. It can help practitioners tailor the right intervention to the right person at the right time to optimally influence behaviour.

Discovery of interconnected causal drivers of COVID-19 vaccination intentions in the US using a causal Bayesian network.

Holistic interventions to overcome COVID-19 vaccine hesitancy require a system-level understanding of the interconnected causes and mechanisms that give rise to it. However, conventional correlative analyses do not easily provide such nuanced insights. We used an unsupervised, hypothesis-free causal discovery algorithm to learn the interconnected causal pathways to vaccine intention as a causal Bayesian network (BN), using data from a COVID-19 vaccine hesitancy survey in the US in early 2021. We identified social responsibility, vaccine safety and anticipated regret as prime candidates for interventions and revealed a complex network of variables that mediate their influences. Social responsibility's causal effect greatly exceeded that of other variables. The BN revealed that the causal impact of political affiliations was weak compared with more direct causal factors. This approach provides clearer targets for intervention than regression, suggesting it can be an effective way to explore multiple causal pathways of complex behavioural problems to inform interventions.

"Nice You Share in Return": Informational Sharing, Reciprocal Sharing, and Life Satisfaction Amid COVID-19 Pandemic.

Social media become an important space where people receive and share up-to-date health-related information during the rapid global spread of the novel coronavirus (COVID-19). While information sharing in social media has been shown to improve relations, reduce stress, and enhance life satisfaction, little is known about reciprocal sharing. Situated in COVID-19 pandemic, this study conceptualizes information sharing as a communication process during which sharers expect the receivers to reciprocate, while receivers feel obligated to return the favor. Building upon social exchange theory and studies on social media sharing, the study tested a model of moderated mediation in which sharing of COVID-19 information was predicted to enhance life satisfaction by encouraging reciprocal sharing, i.e., information reciprocity. Subjective norms, attitudes, and perceived usefulness of the information was predicted to moderate the mediation. The hypothesized mediation was supported by data from a survey of 511 online participants in China. Furthermore, the indirect effect appeared stronger among the respondents who found the information more useful, reported more positive attitude, or perceived more subjective norms. The findings suggest that expected reciprocation may be an important incentive for social sharing, and received reciprocation may be a central part of the mechanism through which sharing benefits the sharer. Policymakers and communicators may need to take information reciprocity into consideration when designing health information campaign to confront communal threats.

"""Nice You Share in Return"": Informational Sharing, Reciprocal Sharing, and Life Satisfaction Amid COVID-19 Pandemic"

Social media become an important space where people receive and share up-to-date health-related information during the rapid global spread of the novel coronavirus (COVID-19). While information sharing in social media has been shown to improve relations, reduce stress, and enhance life satisfaction, little is known about reciprocal sharing. Situated in COVID-19 pandemic, this study conceptualizes information sharing as a communication process during which sharers expect the receivers to reciprocate, while receivers feel obligated to return the favor. Building upon social exchange theory and studies on social media sharing, the study tested a model of moderated mediation in which sharing of COVID-19 information was predicted to enhance life satisfaction by encouraging reciprocal sharing, i.e., information reciprocity. Subjective norms, attitudes, and perceived usefulness of the information was predicted to moderate the mediation. The hypothesized mediation was supported by data from a survey of 511 online participants in China. Furthermore, the indirect effect appeared stronger among the respondents who found the information more useful, reported more positive attitude, or perceived more subjective norms. The findings suggest that expected reciprocation may be an important incentive for social sharing, and received reciprocation may be a central part of the mechanism through which sharing benefits the sharer. Policymakers and communicators may need to take information reciprocity into consideration when designing health information campaign to confront communal threats.

Information-seeking patterns during the COVID-19 pandemic across the United States: Longitudinal analysis of Google trends data

Background: The COVID-19 pandemic has impacted people's lives at unprecedented speed and scale, including how they eat and work, what they are concerned about, how much they move, and how much they can earn. Traditional surveys in the area of public health can be expensive and time-consuming, and they can rapidly become outdated. The analysis of big data sets (such as electronic patient records and surveillance systems) is very complex. Google Trends is an alternative approach that has been used in the past to analyze health behaviors;however, most existing studies on COVID-19 using these data examine a single issue or a limited geographic area. This paper explores Google Trends as a proxy for what people are thinking, needing, and planning in real time across the United States. Objective: We aimed to use Google Trends to provide both insights into and potential indicators of important changes in information-seeking patterns during pandemics such as COVID-19. We asked four questions: (1) How has information seeking changed over time? (2) How does information seeking vary between regions and states? (3) Do states have particular and distinct patterns in information seeking? (4) Do search data correlate with-or precede-real-life events? Methods: We analyzed searches on 38 terms related to COVID-19, falling into six themes: social and travel;care seeking;government programs;health programs;news and influence;and outlook and concerns. We generated data sets at the national level (covering January 1, 2016, to April 15, 2020) and state level (covering January 1 to April 15, 2020). Methods used include trend analysis of US search data;geographic analyses of the differences in search popularity across US states from March 1 to April 15, 2020;and principal component analysis to extract search patterns across states. Results: The data showed high demand for information, corresponding with increasing searches for coronavirus linked to news sources regardless of the ideological leaning of the news source. Changes in information seeking often occurred well in advance of action by the federal government. The popularity of searches for unemployment claims predicted the actual spike in weekly claims. The increase in searches for information on COVID-19 care was paralleled by a decrease in searches related to other health behaviors, such as urgent care, doctor's appointments, health insurance, Medicare, and Medicaid. Finally, concerns varied across the country;some search terms were more popular in some regions than in others. Conclusions: COVID-19 is unlikely to be the last pandemic faced by the United States. Our research holds important lessons for both state and federal governments in a fast-evolving situation that requires a finger on the pulse of public sentiment. We suggest strategic shifts for policy makers to improve the precision and effectiveness of non-pharmaceutical interventions and recommend the development of a real-time dashboard as a decision-making tool. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Information-Seeking Patterns During the COVID-19 Pandemic Across the United States: Longitudinal Analysis of Google Trends Data.

BACKGROUND: The COVID-19 pandemic has impacted people's lives at unprecedented speed and scale, including how they eat and work, what they are concerned about, how much they move, and how much they can earn. Traditional surveys in the area of public health can be expensive and time-consuming, and they can rapidly become outdated. The analysis of big data sets (such as electronic patient records and surveillance systems) is very complex. Google Trends is an alternative approach that has been used in the past to analyze health behaviors; however, most existing studies on COVID-19 using these data examine a single issue or a limited geographic area. This paper explores Google Trends as a proxy for what people are thinking, needing, and planning in real time across the United States. OBJECTIVE: We aimed to use Google Trends to provide both insights into and potential indicators of important changes in information-seeking patterns during pandemics such as COVID-19. We asked four questions: (1) How has information seeking changed over time? (2) How does information seeking vary between regions and states? (3) Do states have particular and distinct patterns in information seeking? (4) Do search data correlate with-or precede-real-life events? METHODS: We analyzed searches on 38 terms related to COVID-19, falling into six themes: social and travel; care seeking; government programs; health programs; news and influence; and outlook and concerns. We generated data sets at the national level (covering January 1, 2016, to April 15, 2020) and state level (covering January 1 to April 15, 2020). Methods used include trend analysis of US search data; geographic analyses of the differences in search popularity across US states from March 1 to April 15, 2020; and principal component analysis to extract search patterns across states. RESULTS: The data showed high demand for information, corresponding with increasing searches for coronavirus linked to news sources regardless of the ideological leaning of the news source. Changes in information seeking often occurred well in advance of action by the federal government. The popularity of searches for unemployment claims predicted the actual spike in weekly claims. The increase in searches for information on COVID-19 care was paralleled by a decrease in searches related to other health behaviors, such as urgent care, doctor's appointments, health insurance, Medicare, and Medicaid. Finally, concerns varied across the country; some search terms were more popular in some regions than in others. CONCLUSIONS: COVID-19 is unlikely to be the last pandemic faced by the United States. Our research holds important lessons for both state and federal governments in a fast-evolving situation that requires a finger on the pulse of public sentiment. We suggest strategic shifts for policy makers to improve the precision and effectiveness of non-pharmaceutical interventions and recommend the development of a real-time dashboard as a decision-making tool.

Telemedicine in the era of COVID-19: a neurosurgical perspective

Despite the substantial growth of telemedicine and the evidence of its advantages, utilization of telemedicine in neurosurgery has been limited. Barriers have included medicolegal issues surrounding provider reimbursement, interstate licensure, and malpractice liability as well as technological challenges. Recently, the COVID-19 pandemic has limited typical evaluation of patients with neurological issues and resulted in a surge in demand for virtual medical visits. Meanwhile, federal and state governments took action to facilitate the rapid implementation of telehealth programs, placing a temporary lift on medicolegal barriers that had previously limited its expansion. This created a unique opportunity for widespread telehealth use to meet the surge in demand for remote medical care. After initial hurdles and challenges, our experience with telemedicine in neurosurgery at Penn Medicine has been overall positive from both the provider and the patients’ perspective. One of the unique challenges we face is guiding patients to appropriately set up devices in a way that enables an effective neuro exam. However, we argue that an accurate and comprehensive neurologic exam can be conducted through a telemedicine platform, despite minor weaknesses inherent to absence of physical presence. Additionally, certain neurosurgical visits such as post-operative checks, vascular pathology, and brain tumors inherently lend themselves to easier evaluation through telehealth visits. In the era of COVID-19 and beyond, telemedicine remains a promising and effective approach to continue neurologic patient care.