Trust In Experts Research Articles

Trust in scientific institutions and experts during the first 2 years of the COVID-19 pandemic in Finland.

To explore variations in trust in science and scientific institutions in Finland during the COVID-19 pandemic, and the factors influencing trust in experts of a key institution in the management of the pandemic, the Finnish Institute for Health and Welfare (THL). These results are contrasted with trust in the Ministry of Social Affairs and Health. Five surveys were conducted between April 2020 and March 2022 (n=5448). The changes were tested with the chi-square test. Predictors of trust in THL and the ministry was examined with binary logistic regression. Trust in science and key scientific institutions remained consistently high throughout this period. In the early pandemic, trust in the ministry declined. The most significant explanatory factors for trust in THL and the ministry were being a supporter of some other party than the right-wing Finns Party and belonging to the age groups over 50 years. Our findings indicate that the pandemic, marked by unpredictability, did not weaken trust in science and THL, whereas trust in the ministry responsible for managing the pandemic and university experts weakened. In increasingly politically polarised societies, the impact of political sentiments on health-related perceptions and choices should be analysed more in future public health studies.

A New Method Based on Belief Rule Base with Balanced Accuracy and Interpretability for Student Achievement Prediction

In the field of education, the accurate prediction of students’ future performance is essential for personalized instruction and efficient allocation of resources. Such predictions not only help education professionals develop targeted educational strategies but also identify students’ learning needs at an early stage so that timely interventions and support can be provided. To gain the trust of educational experts and ensure the practical application value of the prediction results, the prediction methods used must be highly interpretable. However, there are two problems with the current belief rule base (BRB) applied to student performance prediction. First, there is a current lack of effective strategies for enhancing the interpretability of the optimization process. Second, BRB models that overemphasize accuracy tend to exhibit characteristics of black-box models. To overcome these challenges, this paper proposes a new method based on BRB with balanced accuracy and interpretability (BRB-Bai) for student achievement prediction. First, an attribute selection method is proposed to filter out important features associated with student performance. Then, expert knowledge credibility is calculated, and four interpretability strategies are proposed to ensure the interpretability of the model and to achieve a balance between interpretability and accuracy on the basis of expert knowledge credibility. The effectiveness of the proposed model is demonstrated by conducting experiments on the student achievement dataset.

The anatomy of populist communication during COVID-19

ABSTRACT Times of crisis have been argued to function as a springboard for populist communication. But what about a crisis that triggers a rally-around-the-flag effect, which causes a period of consensus-seeking politics and increased trust in institutions and experts? The study delves into the impact of the rally-around-the-flag effect triggered by the outbreak of the COVID-19 pandemic on the use of populist communication in Finland. The findings reveal a notable and temporal decrease in populist communication across party lines and various topics during the initial year of the pandemic. The study provides novel empirical insights into the anatomy of populist communication during the pandemic’s initial year, highlighting that a crisis not only serves as a window of opportunity for populism but can also act as a deactivator of such communication.

Data Perception and Information Disorder in the Italian Context During the Pandemic

This paper aims to learn how Italian audiences received and perceived data-driven television news during the Covid-19 pandemic. During this time, the logic and practices of creating and consuming television journalism were disrupted by the pandemic emergency. The paper presents the results of research carried out as part of a wider project titled “The Social Effects of Fake News” which was conducted from 2018 to 2022 within the CoRiS department of Sapienza University of Rome. The research project was reshaped in 2020, to understand the effects of what has been called “information disorder” in the areas of health, medicine, and science at a time when, together with the pandemic, an “infodemic” also emerged.1 We use Wardle and Derakhshan’s notion of “information disorder” as presented in their Council of Europe report.2 The results of the survey research we conducted show a surprising paradox. We found an interesting pattern of receiving and using information content based on data, in which users trust those who produce and validate certain data and at the same time do not believe that same data. This pattern of use indicates a particular approach to dealing with news among the Italian public. We have labelled it “know-it-all.” This article aims to deepen the understanding of this paradox of trust in experts but not in the data they deliver and how journalistic practice should deal with this conundrum.

Risk evaluation of livestream e-commerce platforms based on expert trust networks and CODAS

As an emerging e-commerce model, livestream e-commerce (LEC) has presented novel opportunities for the advancement of the retail industry. While retailers reap the benefits by this platform, they also encounter challenges associated with platform risks. This paper aims to propose a novel hybrid model to address the risks inherent in livestream e-commerce platforms (LECPs) evaluation problems. Firstly, the paper makes use of q-Rung orthopair fuzzy (q-ROF) trust network (TN) to handle the intricate and uncertain evaluation environment of LECPs and utilizes combinative distance-based assessment (CODAS) to rank the alternative platforms. Secondly, considering that experts have different levels of familiarity with different indicator, a q-ROF-TN matrix between experts is established for each indicator to ascertain their respective weights, which adds robustness to the evaluation process. Thirdly, the dual feedback mechanism is designed to enhance group consensus that attempts to ensure that the evaluation process is collaborative and considers diverse expert opinions, leading to more reliable outcomes. Finally, a set of evaluation indicators is constructed covering various aspects like capital flow management capability and public domain traffic support, and the level of risk of the four LECPs is evaluated using the proposed method. Furthermore, the reliability and effectiveness of the proposed evaluation model are validated through sensitivity analysis and comparative study.

‘Trust the messenger’: Public trust in sources of information on COVID-19

Abstract A key lesson of the coronavirus pandemic was the importance for pro-social behaviour of popular trust in key information sources. Yet existing studies rarely consider the role of people’s trust in a range of different information sources, and the relationship between such trust and particular attitudes and behaviours among individuals. This study goes beyond the general mantra that ‘trust matters’ and explores more specific effects, relating to trust in particular actors and for particular outcomes. Based on a survey fielded on a representative sample of the British population conducted towards the end of the pandemic, we find evidence that people’s coronavirus attitudes and behaviours are particularly related to their trust in scientific experts and, in some cases, to their trust in local councils. However, trust in these actors is not uniformly associated with people’s coronavirus beliefs and actions. This suggests that the link between people’s trust and their pro-social attitudes and behaviours is often specific rather than general. The results hold important implications for the design of effective public communication strategies in the event of any future health emergency.

"I'm worth saving"- A Qualitative Study of People with Alzheimer's Disease Considering Lecanemab Treatment.

People with Alzheimer's disease (AD) now have access to disease-modifying treatment with anti-amyloid monoclonal antibodies (mAbs). Their perception of risks and benefits and approach to treatment decisions remain unknown. To understand how people with early AD consider benefits and costs of anti-amyloid mAbs and make decisions about treatment. Qualitative semi-structured interviews. Memory care clinics at two academic medical centers. People with biomarker or imaging-confirmed early AD referred for evaluation for treatment with anti-amyloid mAbs. Themes identified through content analysis. Among 22 participants, mean age was 70 years, 8 (36%) were women, 22 (100%) were White, 8 (36%) had less than a college degree, 11 (50%) had annual income less than $100,000, and 6 (27%) lived in a rural area. The analysis revealed 3 major themes and associated subthemes: 1) People with AD sought and obtained information from different sources-advocacy organizations, the Internet, and clinicians; 2) hopes, expected benefits, and the existential threat of dementia drove willingness and readiness to start lecanemab-hopes included more time feeling like themselves and doing enjoyable activities; expected benefits included stalling progression, reversing cognitive decline or cure; 3) individual traits and preferences, family factors, and degree of trust in expertise influenced how people balanced risks and benefits- some would accept treatment at any cost; others carefully weighed risks and burdens carefully, but were motivated to pursue treatment by supportive families, insurance coverage, and trust in expertise; for a few, costs decidedly outweighed their personal benefits. People with AD desired more individualized information on risks and benefits and wanted to hear more from patients who took the medication. Results from this qualitative analysis inform clinician, health system and policy efforts to promote individualized treatment decisions for anti-amyloid mAb treatment through multimodal education and outreach, evidence-based communication skills, and adaptation of similar care models. Question: How do people with Alzheimer's disease (AD) decide on treatment with newly available anti-amyloid monoclonal antibodies?Findings: In this qualitative analysis, people with AD considering treatment relied on multiple information sources; were motivated by hope to delay cognitive decline and preserve independence; and worried side effects would impair quality of life. Personality traits, family support, and trust in expertise determined how they balanced these tradeoffs. People with AD wanted more personalized information and to hear from others who had taken the medications.Meaning: As access to treatment expands, these findings inform how clinicians can help people with AD make individualized treatment decisions.

How the crisis of trust in experts occurs on social media in China? Multiple-case analysis based on data mining

The importance of experts in the communication of scientific knowledge cannot be ignored, however, the crisis of trust in experts persists and is widening on social media in China. In this study, nine cases related to experts’ communication of scientific knowledge on Chinese social media Weibo during the period of 11 November 2022 to 22 January 2023 were selected based on the principles of high relevance, high discussion, and high visibility, and public comments on key post under the case were clustered and compared through data mining methods to understand what aspects of the public questioned the experts. The study found that the crisis of trust in experts on social media was the result of the combined effect of the experts, the media, and the public. Conflicting knowledge in expert systems, the perceived common-sense character of communicated knowledge, the lack of rigor and data-supported knowledge, the blurring of the boundaries between experts and administration and between experts and capital, and the dominance of instrumental rationality for experts could all affect public trust in experts. The media’s conscious or unconscious artistic processing of knowledge communicated by experts might mislead the public. The irrational emotion and populist tendencies of the public can amplify feelings of distrust towards experts. This study provides a theoretical and factual basis for understanding the mechanisms of the public’s behavior after receiving knowledge communicated by experts and for enhancing the effectiveness of science communication on social media.

An Overview of Explainable AI Studies in the Prediction of Sepsis Onset and Sepsis Mortality.

Explainable artificial intelligence (AI) focuses on developing models and algorithms that provide transparent and interpretable insights into decision-making processes. By elucidating the reasoning behind AI-driven diagnoses and treatment recommendations, explainability can gain the trust of healthcare experts and assist them in difficult diagnostic tasks. Sepsis is characterized as a serious condition that happens when the immune system of the body has an extreme response to an infection, causing tissue and organ damage and leading to death. Physicians face challenges in diagnosing and treating sepsis due to its complex pathogenesis. This work aims to provide an overview of the recent studies that propose explainable AI models in the prediction of sepsis onset and sepsis mortality using intensive care data. The general findings showed that explainable AI can provide the most significant features guiding the decision-making process of the model. Future research will investigate explainability through argumentation theory using intensive care data focused on sepsis patients.

Technocracy without society: a critique of nudging as an approach to managing risk

ABSTRACT This article considers the evolution of public risk management over the past half century in the United States, focusing on ‘nudging’ as a technique to manage a variety of risks – environmental, health, and financial – through shifts in individual behaviour. I argue that nudging operates according to a privatised, market-based logic of security that displaces more democratic approaches. I further show how nudging aims to go beyond the political – which is to say beyond the realm of democratic contestation over the assessment and mitigation of risk, thereby reinforcing an unsustainable view of risk management as an apolitical set of ‘best practices’. I further argue that this technocratic approach to risk has become particularly problematic amid a populist backlash against scientific expertise and elite institutions, and may even leave advanced democracies less able to manage the risks they face: the erosion of public trust in experts and government undermines both the attempt to nudge individuals towards ‘prudential’ choices and government mandates to manage risks through more aggressive regulatory means.

A Student Performance Prediction Model Based on Hierarchical Belief Rule Base with Interpretability

Predicting student performance in the future is a crucial behavior prediction problem in education. By predicting student performance, educational experts can provide individualized instruction, optimize the allocation of resources, and develop educational strategies. If the prediction results are unreliable, it is difficult to earn the trust of educational experts. Therefore, prediction methods need to satisfy the requirement of interpretability. For this reason, the prediction model is constructed in this paper using belief rule base (BRB). BRB not only combines expert knowledge, but also has good interpretability. There are two problems in applying BRB to student performance prediction: first, in the modeling process, the system is too complex due to the large number of indicators involved. Secondly, the interpretability of the model can be compromised during the optimization process. To overcome these challenges, this paper introduces a hierarchical belief rule base with interpretability (HBRB-I) for student performance prediction. First, it analyzes how the HBRB-I model achieves interpretability. Then, an attribute grouping method is proposed to construct a hierarchical structure by reasonably organizing the indicators, so as to effectively reduce the complexity of the model. Finally, an objective function considering interpretability is designed and the projected covariance matrix adaptive evolution strategy (P-CMA-ES) optimization algorithm is improved. The aim is to ensure that the model remains interpretable after optimization. By conducting experiments on the student performance dataset, it is demonstrated that the proposed model performs well in terms of both accuracy and interpretability.

Applicability of machine learning techniques to analyze Microplastic transportation in open channels with different hydro-environmental factors

This research utilized machine learning to analyze experiments conducted in an open channel laboratory setting to predict microplastic transport with varying discharge, velocity, water depth, vegetation pattern, and microplastic density. Four machine learning (ML) models, incorporating Random Forest (RF), Decision Tree (DT), Extreme Gradient Boost (XGB) and K-Nearest Neighbor (KNN) algorithms, were developed and compared with the Linear Regression (LR) statistical model, using 75% of the data for training and 25% for validation. The predictions of ML algorithms were more accurate than the LR, while XGB and RF provided the best predictions. To explain the ML results, Explainable artificial intelligence (XAI) was employed by using Shapley Additive Explanations (SHAP) to predict the global behavior of variables. RF was the most reliable model, with a coefficient of correlation of 0.97 and a mean absolute percentage error of 1.8% after hyperparameter tuning. Results indicated that discharge, velocity, water depth, and vegetation all influenced microplastic transport. Discharge and vegetation enhanced and reduced microplastic transport, respectively, and showed a response to different vegetation patterns. A strong linear positive correlation (R2 = 0.8) was noted between microplastic density and retention. In the absence of dedicated microplastic transport analytical models and infeasibility of using classical sediment transport models in predicting microplastic transport, ML proved to be helpful. Moreover, the use of XAI will reduce the black-box nature of ML models with effective interpretation enhancing the trust of domain experts in ML predictions. The developed model offers a promising tool for real-world open channel predictions, informing effective management strategies to mitigate microplastic pollution.

The Role of Higher Education in the Post-Truth Era

The rise in populism and movements that threaten trust in science and expertise has been labeled a post-truth world. What challenges does this environment present for higher education, and how should it respond? This article examines the characteristics of a post-truth world and how that challenges the fundamental purposes of higher education. It then examines how higher education might respond, what risks come with that response, and how effectively it might resist attempts to attack and undermine its different purposes. These movements undermine possibilities for truth or objective knowledge, presenting a clear threat to higher education. Its response focuses around improving research and communication with the public, but the nature of cognitive processes in a polarized world leads people to discount information that does not fit with their existing worldviews and values. Simply providing better research will not solve the problem, and actively engaging with these movements can make higher education seem more partisan, further reducing trust. In the face of such intractable problems, it is important for higher education to also nurture communities with its students that foster trust and “critical loyalty” to knowledge and truth over falsehoods and conspiracy.

'Follow the science': Popular trust in scientific experts during the coronavirus pandemic.

The coronavirus pandemic increased the role played by scientific advisers in counselling governments and citizens on issues around public health. This raises questions about how citizens evaluate scientists, and in particular the grounds on which they trust them. Previous studies have identified various factors associated with trust in scientists, although few have systematically explored a range of judgements and their relative effects. This study takes advantage of scientific advisers' heightened public profile during the pandemic to explore how people's trust in scientists is shaped by perceptions of their features and traits, along with evaluations of their behaviour and role within the decision-making process. The study also considers people's trust in politicians, thereby enabling us to identify whether trust in scientists reflects similar or distinctive considerations to trust in partisan actors. Data are derived from specially designed conjoint experiments and surveys of nationally representative samples in Britain and the United States.

The Pitfalls of Epistemic Autonomy without Intellectual Humility

ABSTRACT Individuals who possess the virtue of epistemic autonomy rely upon themselves in their reasoning, judgment and decision making in virtuous ways. Philosophers working on intellectual virtue agree that if the pursuit of epistemic autonomy is not tempered by other virtues such as intellectual humility, it can lead to vices such as extreme intellectual individualism. Virtue theorists have made a number of empirical claims about the consequences of possessing this vice – e.g. that it will lead to significantly fewer epistemic goods and a greater number of faulty beliefs. This paper reports the results of two pilot studies and initial results from a larger series of studies that attempt to shed light on some of the intellectual pitfalls of pursuing unrestricted epistemic autonomy. The studies provide empirical support for the philosophical claim that epistemic autonomy and intellectual humility are mutually supporting virtues by showing that epistemic autonomy without intellectual humility leads to increased belief in misinformation, conspiracy theories and pseudoscience and decreased trust in scientific experts. They also reveal important contours of the complex and often delicate relationship between the virtue of epistemic autonomy and its more vicious cousin, strong intellectual individualism.

Rally Around the Government or a Populist Response? How Concerns About COVID-19 and Emotional Responses Relate to Institutional Trust and Support for Right-Wing Populism

Recent studies have shown that the coronavirus pandemic not only temporarily increased support for incumbent politicians and trust in experts but also triggered an authoritarian response. Because the pandemic has significantly affected individuals’ goals, needs, and control over their lives, we expect that it has generated emotional reactions. In this article, we study how concerns about COVID-19 relate to institutional trust (trust in political institutions and experts) and a preference for populist right parties—directly and indirectly—via emotions. Our theoretical framework relies on the “rally around the flag” hypothesis, the cultural backlash theory, as well as appraisal theories of emotions. We analyze a novel data set collected as part of the Longitudinal Internet Studies for the Social Sciences Panel Survey for the Netherlands at the beginning of the second wave of the pandemic (October 2020). Our findings reveal that concerns about COVID-19 are positively related to institutional trust but unrelated to preferences for right-wing populism. The relationship between concerns about the coronavirus crisis and trust in political institutions is mediated via fear and sadness; these emotions also explain opposition to right-wing populist parties. We interpret our findings in relation to research on the rally around the flag effect, right-wing populism, and emotions. We discuss the implications of our results in the context of the coronavirus pandemic and other “rally”-inducing events.

Reliance on sources of immunization information and vaccine uptake among older adults in a rural state: The mediating role of trust

Older adults are more vulnerable to the negative impacts of infectious diseases than younger individuals. However, regardless of the importance and effectiveness of vaccines to reduce morbidity and mortality, issues remain with vaccine hesitancy among this population. Older adults’ sources of immunization information and their level of trust in those sources may play a role in their vaccination behaviors. This research aimed to better understand the role of information sources and related issues of trust as related to vaccine uptake among older adults. A community-based, cross-sectional survey was conducted with 901 older adults in North Dakota in May-July 2022. Measures included extent of reliance on specific sources of immunization information, levels of trust, and uptake for influenza, pneumonia, shingles, and COVID-19 vaccinations. Immunization information sources were grouped into medical experts, informal, and public outlets. Results indicated older adults were more likely to rely on medical experts than informal sources or public outlets for immunization information. Greater reliance on medical experts was associated with a greater likelihood of vaccine uptake for all vaccines, while reliance on public outlets was associated with a greater likelihood of vaccine uptake only for COVID primary series and boosters. Reliance on informal sources for immunization information was associated with a reduced likelihood of vaccine uptake for all vaccines except shingles. Nearly half of respondents were uncertain who to trust for vaccine information. Uncertainty who to trust for immunization information significantly mediated the associations between reliance on medical experts and uptake for most vaccines indicating that trust in medical experts fosters vaccine uptake. Increasing reliance on medical experts as sources of immunization information is vital to increasing vaccine uptake among older adults. Additionally, this population must be assisted in increasing their ability to successfully assess the trustworthiness of immunization information sources.

Exploring Patient Trust Dimensions to Enhance Patient Satisfaction in Amarilis 2 Inpatient Ward at Dr. Adhyatma MPH Hospital Semarang

Patient trust, medical expertise, and care experience play a crucial role in shaping effective and satisfying healthcare services within a hospital setting. This research explores the dimensions of patient trust, involving the security of personal information, trust in medical expertise, and confidence in the care experience, along with their impact on overall patient satisfaction. This study aims to address this research gap by meticulously examining patient trust dimensions and their effects on patient satisfaction in the Amarilis 2 inpatient ward. The study population consists of 72 patients in the Amarilis 2 ward at Dr. Adhyatma MPH Hospital in Semarang. The sampling technique employed a census approach, resulting in a sample size of 72 respondents. Data collection was conducted through a Google Form shared via a link for questionnaire completion. The research findings indicate that trust in the security of personal information, trust in medical expertise, and trust in the care experience have a positive and significant impact on patient satisfaction.

‘A sense of the systemic’: the Bank of England and the language of inclusive capitalism

Successive crises – social, environmental and political – have led some in global governance circles to advocate a more ‘inclusive capitalism’. In this article, I show how this postcrisis language of inclusive capitalism was used by a specific subset of officials within the Bank of England: Those with high levels of experience in public sector and international official institutions. It is argued that these officials are ‘organic intellectuals’ who mobilise their experience of inter-institutional collaboration as a deliberative model for solving long-term social problems. The institutional experience of these officials and their concern with crises of trust in expertise facilitated the adoption of these models of communicative intervention. I draw on a novel dataset of Bank officials’ career data and speeches, as well as twelve interviews with current and former Bank staff, to show who used this language, in what settings and what motivated its adoption. The article makes a novel contribution to debates about the motivations of key figures in central banks, suggesting that their actions go beyond reputation defence to encompass an expansive worldview of how capitalism might solve its myriad crises.

Government-Nongovernmental Organization (NGO) Collaboration in Macao's COVID-19 Vaccine Promotion: Social Media Case Study.

The COVID-19 pandemic triggered unprecedented global vaccination efforts, with social media being a popular tool for vaccine promotion. This study probes into Macao's COVID-19 vaccine communication dynamics, with a focus on the multifaceted impacts of government agendas on social media. We scrutinized 22,986 vaccine-related Facebook posts from January 2020 to August 2022 in Macao. Using automated content analysis and advanced statistical methods, we unveiled intricate agenda dynamics between government and nongovernment entities. "Vaccine importance" and "COVID-19 risk" were the most prominent topics co-occurring in the overall vaccine communication. The government tended to emphasize "COVID-19 risk" and "vaccine effectiveness," while regular users prioritized vaccine safety and distribution, indicating a discrepancy in these agendas. Nonetheless, the government has limited impact on regular users in the aspects of vaccine importance, accessibility, affordability, and trust in experts. The agendas of government and nongovernment users intertwined, illustrating complex interactions. This study reveals the influence of government agendas on public discourse, impacting environmental awareness, public health education, and the social dynamics of inclusive communication during health crises. Inclusive strategies, accommodating public concerns, and involving diverse stakeholders are paramount for effective social media communication during health crises.