Effects of trust, risk perception, and health behavior on COVID-19 disease burden: Evidence from a multi-state US survey

Can shared decision-making interventions increase trust/trustworthiness in the physician-patient encounter? A scoping review

OBJECTIVES

To summarize the existing literature on the impact of shared decision-making (SDM) interventions on patient trust, with a focus on the specific characteristics that influence the effectiveness of each intervention regarding the outcome of trust.

METHODS

We conducted a systematic search of the literature with the aid of a research librarian. Data was extracted via Covidence regarding the characteristics of the study including interventions performed, trust scale used, primary and secondary outcomes, and effect size.

RESULTS

From 6090 articles, 97 met criteria for full text review and 20 met inclusion criteria. Sixteen of these were original studies while the remaining 4 were secondary analyses. Eight studies reported a statistically significant increase in trust within the intervention group compared to controls while 12 reported no statistically significant changes. None had trust as a primary outcome.

CONCLUSION

Interventions aimed at increasing SDM have the ability to increase trust, but do not always succeed at doing so.

PRACTICE IMPLICATIONS

The results indicate that increasing SDM can improve trust in the physician-patient relationship, especially when SDM results in improved communication from clinicians. Further studies should look at populations with low baseline trust since a ceiling effect can occur with trust scales.

Rebuilding Public Trust: Factors Influencing Dengue Vaccine Uptake in the Aftermath of the Dengvaxia Controversy in the Philippines: A Partial Least Structural Equation Modeling Approach

This study examines the factors influencing Dengue vaccine adoption in the Philippines, utilizing an integrated framework based on the Social Cognitive Theory (SCT) and the Trust-Confidence-Cooperation Framework (TCCF). Data were collected from 2863 respondents and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to explore the relationships between key constructs such as government trust, self-efficacy, observational learning, confidence in vaccines, accessibility, cooperation, and outcome expectations. Ethical clearance was obtained for the study to ensure compliance with research ethics guidelines. The findings reveal that government trust, self-efficacy, observational learning, and accessibility significantly enhance cooperation and vaccine uptake, highlighting their critical roles in shaping vaccination behaviors. However, confidence in vaccines and social influence showed limited direct effects on outcome expectations and self-efficacy, suggesting the need for targeted strategies to bridge these gaps. The study emphasizes the importance of transparent government communication, leveraging trusted role models, and improving accessibility to increase vaccine adoption. While the study offers valuable insights, it acknowledges limitations in sample diversity and the exclusion of certain mediating factors, such as cultural and socio-economic variables. These findings contribute to the theoretical understanding of vaccine adoption and provide practical recommendations for designing effective public health interventions to address vaccine hesitancy and improve adoption rates.

Epidemiological model can forecast COVID-19 outbreaks from wastewater-based surveillance in rural communities

Wastewater has emerged as a crucial tool for infectious disease surveillance, offering a valuable means to bridge the equity gap between underserved communities and larger urban municipalities. However, using wastewater surveillance in a predictive manner remains a challenge. In this study, we tested if detecting SARS-CoV-2 in wastewater can forecast outbreaks in rural communities. Under the CDC National Wastewater Surveillance program, we monitored the SARS-CoV-2 in the wastewater of five rural communities and a small city in Idaho (USA). We then used a particle filter method coupled with a stochastic susceptible-exposed-infectious-recovered (SEIR) model to infer active case numbers using quantities of SARS-CoV-2 in wastewater. Our findings revealed that while high daily variations in wastewater viral load made real-time interpretation difficult, the SEIR model successfully factored out this noise, enabling accurate forecasts of the Omicron outbreak in five of the six towns shortly after initial increases in SARS-CoV-2 concentrations were detected in wastewater. The model predicted outbreaks with a lead time of 0 to 11 days (average of 6 days +/- 4) before the surge in reported clinical cases. This study not only underscores the viability of wastewater-based epidemiology (WBE) in rural communities-a demographic often overlooked in WBE research-but also demonstrates the potential of advanced epidemiological modeling to enhance the predictive power of wastewater data. Our work paves the way for more reliable and timely public health guidance, addressing a critical gap in the surveillance of infectious diseases in rural populations.

Predictors of the willingness to accept a free COVID-19 vaccine among households in Nigeria

BACKGROUND

To inform vaccination policy and programmatic strategies to increase COVID-19 vaccine uptake, an understanding of the factors associated with the willingness to vaccinate is needed.

METHODS

We analyzed data collected from the sixth and tenth round of the Nigerian COVID-19 National Longitudinal Phone Survey conducted by the National Bureau of Statistics and the World Bank in 2020 and 2021, respectively. Exploratory data analysis and feature selection techniques were used to identify important variables. Multivariable logistic regression models were fitted to assess the association between socio-demographic and economic factors and the willingness to receive a free COVID-19 vaccine among Nigerian households at two different time points before vaccines became widely available.

RESULTS

Data from 1,733 and 1,651 Nigerian households who completed the sixth and tenth round of the survey, respectively, were included. Most respondents (>85% of households) were willing to receive a free COVID-19 vaccine from both survey rounds. The median household size was 6 (IQR: [4, 8]) with females heading about 18% of the households. Approximately 22% of the household heads had not received any formal education. Compared to households whose head had no education, households whose heads had completed tertiary education or higher had significantly lower odds of willingness to be vaccinated (ORround 6: 0.46, 95% CI: [0.31, 0.68], ORround 10: 0.49, 95% CI: [0.34, 0.71]). An increasing proportion of male household members was associated with greater willingness to receive a free COVID-19 vaccine (ORround 6: 1.84, 95% CI: [1.01, 3.33], ORround 10: 5.25, 95% CI: [2.86, 9.65]). Significant associations with vaccine willingness were also observed across geopolitical zones of residence with households in South-East Nigeria (ORround 6: 0.16, 95% CI: [0.10, 0.24]; ORround 10: 0.29, 95% CI: [0.19, 0.43]) and South-South Nigeria (ORround 6: 0.57, 95% CI: [0.36, 0.90], ORround 10: 0.32, 95% CI: [0.22, 0.48]) less likely to be willing to receive a free vaccine compared to households in North-Central Nigeria.

CONCLUSION

These findings from two different time points before vaccine roll-out suggest that the educational level of household head, proportion of male household members, and the geopolitical zone of residence are important baseline predictors of the willingness to receive a free COVID-19 vaccine in Nigeria. These factors should be carefully considered and specifically targeted when designing public health programs to inform early-stage strategies that address underlying vaccine hesitancy, improve vaccine uptake, promote ongoing COVID-19 vaccination efforts, and potentially enhance other immunization programs in Nigeria.

Exploring the exponential sensitivity of risk perception in the COVID-19 pandemic

Individual's risk perception regarding specific hazards is a dynamic process that evolves over time. This study analyzed the relationship between the number of COVID-19 cases and the South Korean public's risk perceptions from the outset of the pandemic to the recent past. More than 70 repeated cross-sectional surveys were conducted biweekly to measure individuals' risk perception. An autoregressive integrated moving average with explanatory variable time series analysis was used to characterize the relationship between the number of COVID-19 cases and level of risk perceptions. It revealed that individuals' risk perception and the number of COVID-19 cases were not linearly related but were logarithmically correlated. This finding can be understood as a psychic numbing effect, suggesting that people's perception of risk is not linear but rather exponentially sensitive to changes. The findings also revealed a significant influence of individuals' trust in local governments on their risk perceptions, highlighting the substantial role played by local governments in direct risk management during the COVID-19 pandemic.

Why Do We Not Wear Masks Anymore during the COVID-19 Wave? Vaccination Precludes the Adoption of Personal Non-Pharmaceutical Interventions: A Quantitative Study of Taiwanese Residents

Background and Objectives: This study examined whether the decline in people's adoption of personal NPIs (e.g., mask wearing) results from the preclusion by vaccination. This study also incorporates the concepts of risk perception and the risk-as-feelings model to elucidate the possible mechanisms behind this preclusion. Materials and Methods: Two cross-sectional surveys (N = 462 in Survey 1 and N = 505 in Survey 2) were administered before and during the first outbreak of COVID-19 in Taiwan. The survey items were designed to measure participants' perceived severity of COVID-19, worry about COVID-19, intention to adopt personal NPIs, and attitudes toward COVID-19 vaccines. Utilizing the risk perception framework, we conducted multigroup SEM (Structural Equation Modeling) to construct the optimal structural model for both samples. Results and Conclusions: The multigroup SEM results showed that worry (i.e., the emotional component of risk perception) fully mediates the influence of the perceived severity of COVID-19 (i.e., the cognitive component of risk perception) on the intention to adopt NPIs in both surveys [z = 4.03, p < 0.001 for Survey 1 and z = 2.49, p < 0.050 for Survey 2]. Before the outbreak (i.e., Survey 1), people's attitudes toward COVID-19 vaccines showed no significant association with their worry about COVID-19 [z = 0.66, p = 0.508]. However, in Survey 2, following the real outbreak of COVID-19, people's attitudes toward COVID-19 vaccines negatively predicts their worry about COVID-19 [z = -4.31, p < 0.001], indirectly resulting in a negative effect on their intention to adopt personal NPIs. This suggests the occurrence of the Peltzman effect. That is, vaccination fosters a sense of safety, subsequently diminishing alertness to COVID-19, and thus reducing the intention to adopt personal NPIs.

Epidemiological model can forecast COVID-19 outbreaks from wastewater-based surveillance in rural communities

Wastewater can play a vital role in infectious disease surveillance, especially in underserved communities where it can reduce the equity gap to larger municipalities. However, using wastewater surveillance in a predictive manner remains a challenge. We tested if detecting SARS-CoV-2 in wastewater can predict outbreaks in rural communities. Under the CDC National Wastewater Surveillance program, we monitored several rural communities in Idaho (USA). While high daily variations in wastewater viral load made real-time interpretation difficult, a SEIR model could factor out the data noise and forecast the start of the Omicron outbreak in five of the six cities that were sampled soon after SARS-CoV-2 quantities increased in wastewater. For one city, the model could predict an outbreak 11 days before reported clinical cases began to increase. An epidemiological modeling approach can transform how epidemiologists use wastewater data to provide public health guidance on infectious diseases in rural communities.

Beyond the Books: COVID-19's Influence on Future Life Behaviors of Aspiring Medical and Health Professionals

BACKGROUND

The lifestyle of most people was forced to change due to the COVID-19 pandemic. Perhaps after the pandemic, we will find that these subtle changes in life and from the depths of our hearts are thorough and profound. They may form our conceptual consensus and behavioral habits, becoming part of our long-term personal consciousness. This study explored the impacts of the COVID-19 pandemic on the future life behavior intentions of medical and health-related students studying at universities in China.

METHODS

Electronic questionnaires were distributed to students studying at 3 universities in China. A total of 251 valid questionnaires were obtained, and the chi-squared test was used to compare the corresponding groups.

RESULTS

In the future, students plan to pay more attention to wearing masks and maintaining social distance in public places, do more online shopping, have more meals at home or in the canteen, engage in less international travel, and have fewer gatherings with friends. However, compared with Chinese students, more non-Chinese students plan to increase domestic and international travel and reduce online learning. Furthermore, only among non-Chinese students did gender, urban or rural origin, and family economic conditions influence how the COVID-19 pandemic affected their future life behaviors.

CONCLUSION

The COVID-19 pandemic changed the future life behavior intentions of medical and health-related students. The future behaviors of these students will impact the entire society. This study will help the government and policymakers predict and prepare for general lifestyle changes in our society.

Influence of social and psychological factors on smartphone usage during the COVID-19 pandemic

Objective

This study investigates the influence of psychological factors-specifically affective and cognitive risk perceptions, social distancing attitudes, subjective norms, and cabin fever syndrome-on smartphone usage intensity during the COVID-19 pandemic, with a particular focus on university students.

Methods

Utilizing a cross-sectional survey design, data were collected from 314 university students from South Korea and Vietnam. Structural equation modeling was employed to analyze the relationships between the psychological constructs and their impact on smartphone usage.

Results

The analysis confirms that both affective and cognitive risk perceptions significantly influence attitudes towards social distancing. Furthermore, these social distancing attitudes are found to significantly affect cabin fever syndrome, suggesting that positive attitudes towards social distancing are closely associated with higher reports of cabin fever. Notably, cabin fever syndrome emerges as a significant predictor of increased smartphone usage, underscoring its role as a mediator between prolonged isolation and digital engagement. Additionally, subjective norms are also shown to significantly influence smartphone usage intensity, highlighting the impact of social expectations on digital behaviors during the pandemic.

Conclusion

The study highlights the complex interplay between psychological distress induced by social restrictions and increased reliance on digital technology for social connectivity. These insights suggest that mental health interventions and digital literacy programs tailored to university students' needs can be effective in managing the negative impacts of prolonged social isolation.

Longitudinal validation of the Fear of COVID-19 Scale in a nationwide United States sample: An item response theory model across three inflection points of the pandemic

The COVID-19 pandemic's global emergence/spread caused widespread fear. Measurement/tracking of COVID-19 fear could facilitate remediation. Despite the Fear of COVID-19 Scale (FCV-19S)'s validation in multiple languages/countries, nationwide United States (U.S.) studies are scarce. Cross-sectional classical test theory-based validation studies predominate. Our longitudinal study sampled respondents to a 3-wave, nationwide, online survey. We calibrated the FCV-19S using a unidimensional graded response model. Item/scale monotonicity, discrimination, informativeness, goodness-of-fit, criterion validity, internal consistency, and test-retest reliability were assessed. Items 7, 6, and 3 consistently displayed very high discrimination. Other items had moderate-to-high discrimination. Items 3, 6, and 7 were most (items 1 and 5 the least) informative. [Correction added on 18 May 2023, after first online publication: In the preceding sentence, the term 'items one-fifth least' has been changed to 'items 1 and 5 the least'.] Item scalability was 0.62-0.69; full-scale scalability 0.65-0.67. Ordinal reliability coefficient was 0.94; test-retest intraclass correlation coefficient 0.84. Positive correlations with posttraumatic stress/anxiety/depression, and negative correlations with emotional stability/resilience supported convergent/divergent validity. The FCV-19S validly/reliably captures temporal variation in COVID-19 fear across the U.S.

Using wastewater to overcome health disparities among rural residents

The SARS-CoV-2 pandemic highlighted the need for novel tools to promote health equity. There has been a historical legacy around the location and allocation of public facilities (such as health care) focused on efficiency, which is not attainable in rural, low-density, United States areas. Differences in the spread of the disease and outcomes of infections have been observed between urban and rural populations throughout the COVID-19 pandemic. The purpose of this article was to review rural health disparities related to the SARS-CoV-2 pandemic while using evidence to support wastewater surveillance as a potentially innovative tool to address these disparities more widely. The successful implementation of wastewater surveillance in resource-limited settings in South Africa demonstrates the ability to monitor disease in underserved areas. A better surveillance model of disease detection among rural residents will overcome issues around the interactions of a disease and social determinants of health. Wastewater surveillance can be used to promote health equity, particularly in rural and resource-limited areas, and has the potential to identify future global outbreaks of endemic and pandemic viruses.

Social divisions and risk perception drive divergent epidemics and large later waves

During infectious disease outbreaks, individuals may adopt protective measures like vaccination and physical distancing in response to awareness of disease burden. Prior work showed how feedbacks between epidemic intensity and awareness-based behaviour shape disease dynamics. These models often overlook social divisions, where population subgroups may be disproportionately impacted by a disease and more responsive to the effects of disease within their group. We develop a compartmental model of disease transmission and awareness-based protective behaviour in a population split into two groups to explore the impacts of awareness separation (relatively greater in- vs. out-group awareness of epidemic severity) and mixing separation (relatively greater in- vs. out-group contact rates). Using simulations, we show that groups that are more separated in awareness have smaller differences in mortality. Fatigue (i.e. abandonment of protective measures over time) can drive additional infection waves that can even exceed the size of the initial wave, particularly if uniform awareness drives early protection in one group, leaving that group largely susceptible to future infection. Counterintuitively, vaccine or infection-acquired immunity that is more protective against transmission and mortality may indirectly lead to more infections by reducing perceived risk of infection and therefore vaccine uptake. Awareness-based protective behaviour, including awareness separation, can fundamentally alter disease dynamics. Social media summary: Depending on group division, behaviour based on perceived risk can change epidemic dynamics & produce large later waves.

Need dissatisfaction and its consequences on support for anti-pandemic behaviors in China: The mediation of attribution and local government satisfaction, and the moderation of social class

Introduction

The COVID-19 pandemic has greatly impacted the global economy, resulting in a substantial increase in inequality. There is a need to understand need dissatisfaction in this context, its group differences, and its consequences on support for anti-pandemic behaviors.

Methods

Using data from a survey round of the Chinese Social Mentality Survey from 21 April to 26 May 2022, 6,022 participants aged between 18 and 70 years (M = 32.27; SD = 8.74; men = 46.76%) from 29 provinces of Mainland China were included in the study.

Results

1) Need dissatisfaction was negatively related with support for anti-pandemic behaviors and was completely mediated by attribution and local government satisfaction. 2) Internal/external attribution acted as a double-edged sword: they were negatively/positively related with support for anti-pandemic behaviors, while they became positively/negatively related with support for anti-pandemic behaviors via the mediation of local government satisfaction. 3) People who were unemployed and in the subjectively middle class reported higher need dissatisfaction and less support for anti-pandemic behaviors compared to their counterparts. 4) Social class moderated the relationship between need dissatisfaction and internal attribution: when needs were dissatisfied, participants with higher income and subjective social class tended to attribute more internally.

Discussion

This study contributes to the attribution theory and social identity theory in the context of major global public health events and provides practical implications for promoting behavioral compliance in the context of COVID-19. In particular, facilitating a positive interaction between the public and local governments may be helpful to create a shared identity and, ultimately, prevent and control the pandemic together.

Infection preventive behaviors and its association with perceived threat and perceived social factors during the COVID-19 pandemic in South Korea: 2020 community health survey

BACKGROUND

This study examined why some individuals have not properly performed health prevention behavior during the coronavirus disease 2019 (COVID-19) pandemic. We used data from a community health survey conducted by public health centers in South Korea to identify factors affecting COVID-19 prevention behavior in urban and rural areas. Also, we examined whether individual-level demographic, socio-psychological, and structural variables affected COVID-19 prevention behavior by referring to a model explaining individuals' health prevention behavior. In particular, the study is significant as not many other measures were suggested besides compliance with personal quarantine rules during the early phase of the pandemic in 2020. We hope that the results of this study will be considered in further analysis of infection preventive behavior and in future health crises.

METHODS

Probability proportional and systematic sampling were used to collect data in 2020 from 229,269 individuals. After exclusion, the valid data from 141,902 adults (86,163 urban and 44,739 rural) were analyzed. We performed t-tests and analyses of variance to ascertain the differences in COVID-19 preventive behaviors according to demographic characteristics, and a post-hoc analysis was conducted using Scheffé's test. Factors that affected participants' COVID-19 preventive behaviors were analyzed using multiple regression analyses.

RESULTS

The variables significantly influencing COVID-19 preventive behaviors in urban areas were age, gender, living with two or more people, educational level, monthly household income, working status, influenza vaccination, daily life stress, and perceived threat. In rural areas, age, gender, living with two or more people, education level, influenza vaccination, daily life stress, perceived threat, and perceived social factors were significantly associated with increased COVID-19 preventive behaviors.

CONCLUSIONS

Several demographic characteristics were associated with urban and rural residents' COVID-19-related preventive behaviors. A different approach is needed for the two regions in future policy. Future studies should aim to improve the power of the model and include other factors that may be related to COVID-19 preventive behavior.