Trust in the scientific research community predicts intent to comply with COVID-19 prevention measures: An analysis of a large-scale international survey dataset

A Big Data and FRAM-Based Model for Epidemic Risk Analysis of Infectious Diseases

Purpose

The use of multi-source precursor data to predict the epidemic risk level would aid in the early and timely identification of the epidemic risk of infectious diseases. To achieve this, a new comprehensive big data fusion assessment method must be developed.

Methods

With the help of the Functional Resonance Analysis Method (FRAM) model, this paper proposes a risk portrait for the whole process of a pandemic spreading. Using medical, human behaviour, internet and geo-meteorological data, a hierarchical multi-source dataset was developed with three function module tags, ie, Basic Risk Factors (BRF), the Spread of Epidemic Threats (SET) and Risk Influencing Factors (RIF).

Results

Using the dynamic functional network diagram of the risk assessment functional module, the FRAM portrait was applied to pandemic case analysis in Wuhan in 2020. This new-format FRAM portrait model offers a potential early and rapid risk assessment method that could be applied in future acute public health events.

A Method to Explore the Best Mixed-Effects Model in a Data-Driven Manner with Multiprocessing: Applications in Public Health Research

In the present study, I developed and tested an R module to explore the best models within the context of multilevel modeling in research in public health. The module that I developed, explore.models, compares all possible candidate models generated from a set of candidate predictors with information criteria, Akaike information criterion (AIC), and Bayesian information criterion (BIC), with multiprocessing. For testing, I ran explore.models with datasets analyzed in three previous studies in public health, which assumed candidate models with different degrees of model complexity. These three studies examined the predictors of psychological well-being, compliance with preventive measures, and vaccine intent during the COVID-19 pandemic. After conducting model exploration with explore.models, I cross-validated the nomination results with calculated model Bayes Factors to examine whether the model exploration was performed accurately. The results suggest that explore.models using AIC and BIC can nominate best candidate models and such nomination outcomes are supported by the calculated model Bayes Factors. In particular, all the identified models are superior to the full models in terms of model Bayes Factors. Also, by employing AIC and BIC with multiprocessing, explore.models requires a shorter processing time than model Bayes Factor calculations. These results indicate that explore.models is a reliable, valid, and feasible tool to conduct data-driven model exploration with datasets collected from multiple groups in research on health psychology and education.

How social evaluations shape trust in 45 types of scientists

Science can offer solutions to a wide range of societal problems. Key to capitalizing on such solutions is the public's trust and willingness to grant influence to scientists in shaping policy. However, previous research on determinants of trust is limited and does not factor in the diversity of scientific occupations. The present study (N = 2,780; U.S. participants) investigated how four well-established dimensions of social evaluations (competence, assertiveness, morality, warmth) shape trust in 45 types of scientists (from agronomists to zoologists). Trust in most scientists was relatively high but varied considerably across occupations. Perceptions of morality and competence emerged as the most important antecedents of trust, in turn predicting the willingness to grant scientists influence in managing societal problems. Importantly, the contribution of morality (but not competence) varied across occupations: Morality was most strongly associated with trust in scientists who work on contentious and polarized issues (e.g., climatologists). Therefore, the diversity of scientific occupations must be taken into account to more precisely map trust, which is important for understanding when scientific solutions find their way to policy.

Exploring Attitudes Toward "Sugar Relationships" Across 87 Countries: A Global Perspective on Exchanges of Resources for Sex and Companionship

The current study investigates attitudes toward one form of sex for resources: the so-called sugar relationships, which often involve exchanges of resources for sex and/or companionship. The present study examined associations among attitudes toward sugar relationships and relevant variables (e.g., sex, sociosexuality, gender inequality, parasitic exposure) in 69,924 participants across 87 countries. Two self-report measures of Acceptance of Sugar Relationships (ASR) developed for younger companion providers (ASR-YWMS) and older resource providers (ASR-OMWS) were translated into 37 languages. We tested cross-sex and cross-linguistic construct equivalence, cross-cultural invariance in sex differences, and the importance of the hypothetical predictors of ASR. Both measures showed adequate psychometric properties in all languages (except the Persian version of ASR-YWMS). Results partially supported our hypotheses and were consistent with previous theoretical considerations and empirical evidence on human mating. For example, at the individual level, sociosexual orientation, traditional gender roles, and pathogen prevalence were significant predictors of both ASR-YWMS and ASR-OMWS. At the country level, gender inequality and parasite stress positively predicted the ASR-YWMS. However, being a woman negatively predicted the ASR-OMWS, but positively predicted the ASR-YWMS. At country-level, ingroup favoritism and parasite stress positively predicted the ASR-OMWS. Furthermore, significant cross-subregional differences were found in the openness to sugar relationships (both ASR-YWMS and ASR-OMWS scores) across subregions. Finally, significant differences were found between ASR-YWMS and ASR-OMWS when compared in each subregion. The ASR-YWMS was significantly higher than the ASR-OMWS in all subregions, except for Northern Africa and Western Asia.

Trends in the Implementation of Workplace COVID-19 Measures in Japanese Companies: A One-Year Prospective Cohort Study

This study evaluated trends in the implementation of workplace measures against COVID-19 by Japanese companies. We conducted a prospective cohort study, using data from December 2020 and December 2021, with 13,419 respondents participating in the follow-up survey. We evaluated nine workplace measures against COVID-19 (e.g., encouraging mask-wearing at work) and used the McNemar test and the Chi-square test for trend in the analysis. Small-sized companies (1-9 employees) exhibited a significant increase in the implementation of all the measures, with a rate of increase ranging from 8.4% to 16.1% (P-value: <0.001). Medium-sized companies (10-49 employees) also showed significant improvements in nearly all the measures (rate of increase: 3.5% to 10.5%, P-values: <0.001 to 0.004), except for one specific measure. Larger companies (more than 50 employees) displayed a mixed pattern, with some measures increasing and others decreasing. A persistent gap was observed between smaller (fewer than 50 employees) and larger companies in the implementation rates of these measures. The findings revealed a positive shift in workplace measures against COVID-19 among smaller companies in Japan over 1 year, although gaps between them and larger companies persisted.

Do Italian people still wear masks? Analysis of personality and dispositional correlates of facemask use in post Covid-19 scenario

Face mask wearing is a low-cost preventative measure for the Covid-19 pandemic. In Italy, face masks are no longer mandatory indoors from the 1st of May 2022. Some research focused on factors that influence the choice of using masks, but less is known about mask-wearing when non-mandatory. The present study aims to compare those who were still wearing masks indoors when non-mandatory and those who were not, in personality traits, anxiety, depression, and trust in healthcare professions, in Italy, in 2022. Furthermore, we analyze if resilience, reactance, political orientation, and Covid-19 vaccinations moderate between negative affectivity and the choice of wearing masks. 1151 adults, aged 18-64, were recruited. Using the Qualtrics platform, participants filled in a socio-demographic interview, and self-report questionnaires. Results showed that people who were still wearing a mask indoors had higher levels of psychoticism and negative affectivity, worse mental health, greater trust in healthcare professions, and worries about the pandemic. Moreover, resilience partially moderates the relationship between negative affectivity and the choice of wearing a mask. These findings provide a better understanding of individuals' responses to post-pandemic changes, identifying the personal and contextual aspects that can make people struggle with the process of returning to normality.

Cross-language validation of COVID-19 Compliance Scale in 28 languages

Although compliance scales have been used to assess compliance with health guidelines to reduce the spread of COVID-19, no scale known to us has shown content validity regarding global guidelines and reliability across an international sample. We assessed the validity and reliability of a Compliance Scale developed by a group of over 150 international researchers. Exploratory factor analysis determined reliable items on the English version. Confirmatory factor analysis confirmed the reliability of the six-item scale and convergent validity was found. After invariance testing and alignment, we employed a novel R code to run a Monte Carlo simulation for alignment validation. This scale can be employed to measure compliance across multiple languages, and our alignment validation method can be conducted with future cross-language surveys.

Using normative language when describing scientific findings: Randomized controlled trial of effects on trust and credibility (Preprint)

BACKGROUND

Scientists often make cognitive claims (eg, the results of their work) and normative claims (eg, what should be done based on those results). Yet, these types of statements contain very different information and implications. This randomized controlled trial sought to characterize the granular effects of using normative language in science communication.

OBJECTIVE

Our study examined whether viewing a social media post containing scientific claims about face masks for COVID-19 using both normative and cognitive language (intervention arm) would reduce perceptions of trust and credibility in science and scientists compared with an identical post using only cognitive language (control arm). We also examined whether effects were mediated by political orientation.

METHODS

This was a 2-arm, parallel group, randomized controlled trial. We aimed to recruit 1500 US adults (age 18+) from the Prolific platform who were representative of the US population census by cross sections of age, race/ethnicity, and gender. Participants were randomly assigned to view 1 of 2 images of a social media post about face masks to prevent COVID-19. The control image described the results of a real study (cognitive language), and the intervention image was identical, but also included recommendations from the same study about what people should do based on the results (normative language). Primary outcomes were trust in science and scientists (21-item scale) and 4 individual items related to trust and credibility; 9 additional covariates (eg, sociodemographics, political orientation) were measured and included in analyses.

RESULTS

From September 4, 2022, to September 6, 2022, 1526 individuals completed the study. For the sample as a whole (eg, without interaction terms), there was no evidence that a single exposure to normative language affected perceptions of trust or credibility in science or scientists. When including the interaction term (study arm × political orientation), there was some evidence of differential effects, such that individuals with liberal political orientation were more likely to trust scientific information from the social media post's author if the post included normative language, and political conservatives were more likely to trust scientific information from the post's author if the post included only cognitive language (β=0.05, 95% CI 0.00 to 0.10; P=.04).

CONCLUSIONS

This study does not support the authors' original hypotheses that single exposures to normative language can reduce perceptions of trust or credibility in science or scientists for all people. However, the secondary preregistered analyses indicate the possibility that political orientation may differentially mediate the effect of normative and cognitive language from scientists on people's perceptions. We do not submit this paper as definitive evidence thereof but do believe that there is sufficient evidence to support additional research into this topic, which may have implications for effective scientific communication.

TRIAL REGISTRATION

OSF Registries osf.io/kb3yh; https://osf.io/kb3yh.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/41747.

Validity testing of the conspiratorial thinking and anti-expert sentiment scales during the COVID-19 pandemic across 24 languages from a large-scale global dataset

In this study, we tested the validity across two scales addressing conspiratorial thinking that may influence behaviours related to public health and the COVID-19 pandemic. Using the COVIDiSTRESSII Global Survey data from 12 261 participants, we validated the 4-item Conspiratorial Thinking Scale and 3-item Anti-Expert Sentiment Scale across 24 languages and dialects that were used by at least 100 participants per language. We employed confirmatory factor analysis, measurement invariance test and measurement alignment for internal consistency testing. To test convergent validity of the two scales, we assessed correlations with trust in seven agents related to government, science and public health. Although scalar invariance was not achieved when measurement invariance test was conducted initially, we found that both scales can be employed in further international studies with measurement alignment. Moreover, both conspiratorial thinking and anti-expert sentiments were significantly and negatively correlated with trust in all agents. Findings from this study provide supporting evidence for the validity of both scales across 24 languages for future large-scale international research.

Using normative language when describing scientific findings: Study protocol for a randomized, controlled trial of effects on trust and credibility

Background

Trust in science and scientists has received renewed attention because of the “infodemic” occurring alongside COVID-19. A robust evidence basis shows that such trust is associated with belief in misinformation and willingness to engage in public and personal health behaviors. At the same time, trust and the associated construct of credibility are complex meta-cognitive concepts that often are oversimplified in quantitative research. The discussion of research often includes both normative language (what one ought to do based on a study’s findings) and cognitive language (what a study found), but these types of claims are very different, since normative claims make assumptions about people’s interests. Thus, this paper presents a protocol for a large randomized controlled trial to experimentally test whether some of the variability in trust in science and scientists and perceived message credibility is attributable to the use of normative language when sharing study findings in contrast to the use of cognitive language alone.

Objective

The objective of this trial will be to examine if reading normative and cognitive claims about a scientific study, compared to cognitive claims alone, results in lower trust in science and scientists as well as lower perceived credibility of the scientist who conducted the study, perceived credibility of the research, trust in the scientific information on the post, and trust in scientific information coming from the author of the post.

Methods

We will conduct a randomized controlled trial consisting of 2 parallel groups and a 1:1 allocation ratio. A sample of 1500 adults aged ≥18 years who represent the overall US population distribution by gender, race/ethnicity, and age will randomly be assigned to either an “intervention” arm (normative and cognitive claims) or a control arm (cognitive claims alone). In each arm, participants will view and verify their understanding of an ecologically valid claim or set of claims (ie, from a highly cited, published research study) designed to look like a social media post. Outcomes will be trust in science and scientists, the perceived credibility of the scientist who conducted the study, the perceived credibility of the research, trust in the scientific information on the post, and trust in scientific information coming from the author of the post. Analyses will incorporate 9 covariates.

Results

This study will be conducted without using any external funding mechanisms.

Conclusions

If there is a measurable effect attributable to the inclusion of normative language when writing about scientific findings, it should generate discussion about how such findings are presented and disseminated.

Trial Registration

Open Science Framework n7yfc; https://osf.io/n7yfc

International Registered Report Identifier (IRRID)

PRR1-10.2196/41747

Acceptance of the COVID-19 vaccine based on the health belief model: a multicenter national survey among medical care workers in China

Vaccine uptake rate is crucial for herd immunity. Medical care workers (MCWs) can serve as ambassadors of COVID-19 vaccine acceptance. This study aimed to assess MCWs’ willingness to receive the COVID-19 vaccine, and to explore the factors affecting COVID-19 vaccination acceptance. A multicenter study among medical care workers was conducted in seven selected hospitals from seven geographical territories of China, and data were collected on sociodemographic characteristics, vaccine hesitancy, and health beliefs on COVID-19 vaccination among participants. Univariate and multivariate logistic regression models were performed to explore the correlations between individual factors and the acceptance of the COVID-19 vaccine. Among the 2681 subjects, 82.5% of the participants were willing to accept the COVID-19 vaccination. Multivariate regression analyses revealed that individuals with more cues to action about the vaccination, higher level of confidence about the vaccine, and higher level of trust in the recommendations of COVID-19 vaccine from the government and the healthcare system were more likely to get the COVID-19 vaccine. In contrast, subjects with higher level of perceived barriers and complacency were less likely to accept the COVID-19 vaccine. Overall, MCWs in China showed a high willingness to get the COVID-19 vaccine. The governmental recommendation is an important driver and lead of vaccination. Relevant institutions could increase MCWs’ willingness to COVID-19 vaccines by increasing MCWs’ perception of confidence about COVID-19 vaccines and cues to action through various strategies and channels. Meanwhile, it can also provide evidence in similar circumstances in the future to develop vaccine promotion strategies.