Bridging the Divide. An Interdisciplinary Analysis of Trust in Science

Zeybek Kabakci, Gökçe; Kara, Umut Yener; Baydar Çavdar, Gökçe; Toros, Emre Article — Published Version Bridging the Divide. An Interdisciplinary Analysis of Trust in Science Sage Open Provided in Cooperation with: WZB Berlin Social Science Center Suggested Citation: Zeybek Kabakci, Gökçe; Kara, Umut Yener; Baydar Çavdar, Gökçe; Toros, Emre (2025) : Bridging the Divide. An Interdisciplinary Analysis of Trust in Science, Sage Open, ISSN 2158-2440, Sage, Thousand Oaks, CA, Vol. 15, Iss. 3, pp. 1-23, https://doi.org/10.1177/21582440251352376 This Version is available at: https://hdl.handle.net/10419/329652 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Original Research SAGE Open July-September 2025: 1–23 ÓThe Author(s) 2025 DOI: 10.1177/21582440251352376 journals.sagepub.com/home/sgo Bridging the Divide: An Interdisciplinary Analysis of Trust in Science Go ¨kcxe Zeybek Kabakci 1 , Umut Yener Kara 1,2 ,Go ¨kcxe Baydar Cxavdar 1 , and Emre Toros 3 Abstract For several reasons, trust in science in recent years has eroded, throwing serious doubts on once-reliable scientific resources. Although multiple scientific disciplines try to explain the causes and consequences of this worrying decline, we have only scant knowledge about these disciplines’ interconnected arguments. Focusing on this niche, this study aims to bridge the literature from diverse academic disciplines and identify dominant themes by utilising a cutting-edge methodology. This attempt is crucial since we need a comprehensive understanding of the complex factors influencing public trust in science, allowing us to approach the problem from multiple angles and enabling the crafting of evidence-based policies that better resonate with the public and are more likely to be effective in restoring trust. Hence, this study contributes to the existing literature both substantially and methodologically. Substantially, we show that there are dominant recurring research themes across the disciplines, such as science communication, compliance with scientific advice, and public engagement. Methodologically, we contend that identifying these vital crosscutting themes can only be possible by combining state-of-theart computational techniques with conventional qualitative content analysis. Plain language summary How do different scientific disciplines define trust in science? In recent years, trust in science considerably fluctuated, raising concerns about the reliability of scientific information. While different scientific fields have tried to explore why this is happening and what it means, there is limited understanding of how their ideas are connected. This study aims to bring together research from various academic areas to identify common themes related to public trust in science. By doing so, we hope to offer a clearer understanding of the many factors that influence trust. This approach will help create better, evidence-based policies that resonate with the public and can effectively rebuild trust. Our research highlights key themes, such as science communication, public engagement, and how people follow scientific advice. We also introduce a new method that combines advanced computational tools with traditional content analysis to uncover these important themes. Keywords communication studies, communication, social sciences, trust, science, trust in science, interdisciplinary, text mining, network analysis 1 Hacettepe University, Ankara, Turkey 2 WZB Berlin Social Science Center 3 Bilkent University, Ankara, Turkey Corresponding Author: Emre Toros, Bilkent University, Department of Communication and Design, FC 206 Bilkent-Cxankaya, Ankara 06800, Turkey. Email: [email protected] Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). If I listened totally to the scientists, we would right now have a country that would be in a massive depression instead —we’re like a rocket ship. Take a look at the numbers. D. Trump, October 18, 2020 Introduction Even though the above epigraph belongs to Donald Trump, unfortunately, it resembles a dominant and worrying understanding of science and scientists in the era that we live in. Although technical advancement and scientific knowledge are entwined with practically all of our daily practices, we, at the same time, observe absurd activities, such as the flat-Earth or anti-vaccine movements, which became components of the political discourses of several countries and global public debates. Moreover, the conspiracy-based beliefs that scientific institutions are engaged in secret plots or cover-ups, the spread of false information or misleading claims about scientific topics through social media and other channels, concerns about genetically modified organisms and biotechnology, instances of scientific misconduct or unethical behaviour by researchers or scientific institutions and scepticism towards public health measures and vaccine development, continuously fuel this worrying tendency. Significantly, the COVID-19 pandemic has boosted this process and revealed disputes among scientists, politicians and the general public. Accordingly, the demise of public trust in science is now recognised as one of the most pressing concerns confronting modern societies, which poses significant dangers to health and the longterm viability of civilisation itself. A rising body of literature exposes the causes and consequences of this erosion in domains as diverse as immunisations, tobacco sickness, and climate science, highlighting the limits of many contemporary methods and institutions that appear inadequate in the face of enormous complexity. Despite the extensive body of work investigating the erosion of public trust in science, research in this area often remains siloed within distinct academic disciplines. Although specific reviews (Goldenberg, 2023) focus on public trust in science, they are not systematic, and studies integrating insights from different research strands and disciplines by identifying dominant themes and blind spots and limitations are needed. Scholars in fields such as communication studies, sociology, political science, philosophy, public health, and environmental sciences have each offered valuable insights into why trust in science declines or fluctuates and how these dynamics manifest themselves. Yet most of these investigations proceed independently, focusing on discipline-specific theories, methodologies, and questions. As a result, we are left with rich but disjointed understandings that fail to capture the full complexity of how and why trust in science erodes across multiple contexts. While each of these disciplinary sub-fields captures crucial pieces of the broader ‘‘trust in science’’ puzzle, there is a noticeable lack of integrative efforts that systematically connect their findings which limits our ability to understand the deeper, cross-cutting mechanisms that erode or destabilise trust in science. Without synthesising commonalities across disciplines, we risk overlooking significant overlaps in factors contributing to mistrust—such as perceived conflicts of interest, politicisation, misinformation, sociodemographic disparities, and scepticism of institutional authority. Furthermore, the siloed nature of existing research may prevent us from recognising how these factors intersect or reinforce one another in ways that transcend individual disciplines. In an era when challenges like public health crises and climate change increasingly demand collaborative responses, failing to see the entire picture hampers our capacity to design effective and consistent interventions. Our study aims to map and synthesise research on trust in science across multiple fields, thereby revealing shared thematic patterns and neglected intersections. By employing both computational text-mining techniques and qualitative content analysis, we seek to unearth not only the distinct approaches each discipline brings to the table but also the threads that bind them together. This integrated perspective allows us to demonstrate how several domains—ranging from philosophy and communication studies to sociology and health sciences—can collectively contribute to a more holistic understanding of trust in science, and gaps in the field. Accordingly, this work has two main objectives. The first objective is to present a concrete picture of research themes across the various scientific disciplines about eroding trust in science. Given that distrust in science or outright science denial has potentially drastic effects, we depict the body of research from different fields that explicitly or implicitly eliminate distrust and foster trust in science, such as sociology, psychology, environmental sciences, political science, and data sciences. By doing so, we hope to demonstrate the similarities among various scientific disciplines and provide a joint base for possible policy agendas. Our second objective is to offer a novel methodological approach to the subject. Although there are some literature reviews on eroding trust, we broaden the scope by including several scientific disciplines by employing a fresh approach. As we present in the related part, we show that identifying these vital crosscutting themes can only be possible by combining state-of-the-art computational techniques with conventional qualitative 2SAGE Open content analysis. Lastly, based on the study’s findings, we briefly revisit routes to policy plans for restoring trust in science. The paper is structured as follows: First, in the following part, we present a broader rationale for studying trust in science in an interdisciplinary manner. Followingly, we present our methodology, data and findings. Third, we discuss our results, outline how to consider possible policy suggestions as future work and conclude. Why Is It Important to Study Trust in Science in an Interdisciplinary Manner? Trust in science is a fundamental component of modern society, shaping public attitudes toward scientific expertise, policy decisions, and technological advancements. At its core, trust in science implies that the public has confidence in scientists’ ability to produce reliable, evidence-based knowledge while simultaneously ensuring that such knowledge serves the broader societal good (Gundersen & Holst, 2022, Irzik & Kurtulmus, 2021). Hence, trust is a multifaceted concept that involves key dimensions such as competence, integrity, and benevolence (O’Neill, 2002; Rolin, 2020). Consequently, trust in science is not a monolithic or static quality; rather, it is a relational phenomenon rooted in the perceived epistemic reliability, ethical commitment, and communicative openness of scientific institutions, and it must be understood within a broader interdisciplinary context that spans philosophy, political science, and sociology (O’Doherty, 2022; Resnik, 2011). In that sense, establishing trust in science is critical in fostering cooperation and facilitating the exchange of information, yielding substantial advantages for advancing scientific progress among various disciplines. Accordingly, establishing and maintaining trust within the scientific community is an indispensable prerequisite for advancing and progressing knowledge. Through trust, scientists can only effectively collaborate, build upon one another’s findings, and collectively contribute to the growth and development of scientific inquiry (Rolin, 2020). Without this fundamental element, the scientific enterprise would face significant impediments, potentially resulting in a stagnation of scientific progress and a hindrance to the overall scientific endeavour. So, the establishment and maintenance of trust hold paramount significance in fostering a symbiotic relationship between the realms of science and society. Indeed, as Hendriks et al. (2016b) state trust is both essential for scientists in conducting research and for the general public as they navigate science-related issues in their daily lives. It is crucial to acknowledge that most individuals lack the expertise to independently assess scientific assertions, thereby necessitating their reliance on the competence and integrity of scientists. Nevertheless, it is imperative to acknowledge that the trust placed in the scientific community is a delicate construct that can be easily eroded and destabilised. In line with this perspective, Smith (2022) argues that the foundation of scientific endeavours lies in establishing public confidence in the methodologies and establishments of science rather than solely relying on the credibility of individual scientists. Gundersen et al. (2022) also note that empirical evidence in environmental science demonstrates how distrust in science is linked to distrust in the institutions that implement it into policy. However, it is also critical to admit that these particular practices exhibit a certain level of opacity when observed by external entities, necessitating a fundamental reliance on interpersonal trust in the scientific community to elucidate and illustrate them. The susceptibility of science to contestation in manners that have the potential to undermine trust is a matter of concern. According to Whyte and Crease (2010), for example, it is imperative for philosophers of science to actively contribute to the establishment of trust by formulating comprehensive frameworks of expertise that elucidate the rationale behind placing trust in diverse forms of knowledge within distinct contexts. In this vein, Metzen (2024) argues that the nature of trust in science should be grounded in both objectivity and shared values. Another point about the nature of trust in science is its contingency upon various factors encompassing individual and societal dimensions. At the individual level, factors such as education and personal beliefs are the pivotal determinants that revolve around the perceived level of expertise, integrity, and benevolence exhibited by the source (Hendriks et al., 2016b). However, it is also critical to note that trust judgements are contingent upon various contextual factors. In that manner, it is plausible to assert that individuals may exhibit a certain level of scepticism towards scientific findings that potentially challenge their personal interests or deeply ingrained beliefs. It is also imperative to note that the realm of science has historically encountered resistance (Oreskes, 2019). Yet, the prevailing sentiment of scepticism appears to be intensifying in light of the escalating urgency surrounding matters such as climate change. Some scholars (Gauchat, 2012; Hamilton et al., 2015) highlight that this scepticism is particularly high among conservatives on certain issues, including environmental regulations and public health interventions, along with climate change. Based on the above arguments, it is possible to argue that to achieve the desired levels of trust in science, scientists must possess an interdisciplinary understanding of the underlying mechanisms of the erosion of trust in scientific inquiry. This is mainly because particular improvements within specific scientific disciplines are Kabakcxi et al. 3 insufficient to build trust in science, as we have clearly seen during the COVID-19 pandemic: although the scientists managed to produce the vaccines in a very short time, due to the global anti-vaccine movement, there were delays in vaccination which hindered the combat against the virus seriously. As shown in a scoping review (Majid et al., 2022) vaccine hesitancy is influenced by various factors, including risk perception and trust in health authorities, which are deeply rooted in sociocultural contexts. Emphasising the plurality of trust, Metzen (2024) uses the case of MMR vaccine (measles, mumps, and rubella) hesitancy to argue that addressing vaccine hesitancy requires not only presenting objective data, but also acknowledging and engaging with the values underlying parents’ concerns. Hence, to foster more robust compliance with scientific knowledge, it was imperative to advocate for the cultivation of discursive practices such as explanation and argumentation, which are within the domains of other scientific disciplines, like sociology, psychology, and political science, than medicine. For instance ‘‘Building Bridges, Earning Trust: The WHY and the HOW of Public Trust in Science’’ Report of the Aspen Institute’s Science and Society Program (Goud et al., 2023, pp. 19–20) highlights the importance of active and ongoing collaboration with fields including sociology, political science, communication, anthropology, history, psychology, theology, business in order to ask the right questions and communicate the findings in meaningful ways. Only such practices serve as effective tools in facilitating comprehension of scientific concepts and enhancing individuals’ awareness of the boundaries of their own knowledge. In essence, the dynamics of trust in science are inherently intricate and desired trust is contingent upon the interplay between the perceived credibility of various scientific disciplines and the populace’s comprehension of the underlying mechanisms governing scientific inquiry. Accordingly, cultivating trust within science and society is crucial, albeit not without its inherent complexities and obstacles. Utilising the above-explained logic and explanations of the pressing need for an interdisciplinary approach, we formulated the following research questions: 1. How is trust in science studied, and through which methods and techniques? 2. What is the disciplinary profile and structure of trust in science research? 3. What are the dominant research themes and contexts/cases of trust in science research among various disciplines, and how/if did they change over time? Although our investigation primarily employs a descriptive and exploratory methodology, we integrate a central hypothesis to guide the framework and future research directions. Specifically, we hypothesise that multiple disciplines recognise the importance of the declining trust in science and examine trust in science within their respective domains, yet their perspectives converge around crosscutting themes that underscore the breadth and complexity of this phenomenon. To elaborate, each discipline—ranging from communication studies and sociology to environmental sciences and public health—addresses trust in science through its own lenses and specialised methodologies. Communication scholars, for instance, frequently focus on how media narratives and information sources influence public attitudes. Sociologists and political scientists tend to highlight societal power structures, belief systems, and institutional credibility, while health sciences are more inclined to investigate compliance and public adherence to scientific guidelines. Despite these distinct angles, our study reveals recurring points of convergence, such as the significance of transparent communication, the interplay between social and political contexts, and the importance of engaging diverse stakeholders in scientific processes. By positing this overarching hypothesis, we acknowledge that an interdisciplinary synthesis is not only feasible but also essential for comprehensively understanding the erosion of trust in science. Furthermore, while the present study does not engage in formal hypothesis testing—given its descriptive orientation—it lays a foundation for subsequent, more targeted empirical investigations. Researchers can build upon our findings to design comparative studies, meta-analyses, or cross-disciplinary frameworks that directly test the impact of these identified themes on public trust levels. Ultimately, articulating a unifying hypothesis helps integrate our descriptive conclusions into broader theoretical and practical discussions about restoring and maintaining trust in science across varied social, political, and cultural contexts. Data and Methods To answer our research questions and achieve our research objectives, we performed a database search containing the author keywords ‘‘trust,’’ ‘‘mistrust,’’ ‘‘distrust,’’ and ‘‘scienc*’’ on the Web of Science. We filtered only English publications indexed in SSCI, SCI-E, ESCI, and AHCI. Search results were not limited to any specific period. Our search yielded 436 results, with publication years varying between 1999 and 2022. After excluding editorials, letters and book reviews, we manually screened all publications for inclusion according to 4SAGE Open criteria that publications must investigate or focus on public trust toward science, scientists or scientific institutions. We removed inaccessible and non-English articles, resulting in 238 eligible publications (Figure 1). In terms of methodology, we opted for a semicomputational or hybrid approach in line with our second objective. While manual and computational methods may sometimes be seen as mutually exclusive, we agree with scholars arguing that they work best together and can balance each other’s strengths and weaknesses (Boumans & Trilling, 2015; Grimmer et al., 2022; Lewis et al., 2013). Consequently, this design leverages computational techniques’ capabilities for pattern recognition and visualisation while ensuring nuanced analysis through human interpretation, allowing for a more comprehensive and validated understanding of the data. As the initial step, we employed a topic modelling strategy to analyse the content of the selected articles. Topic modelling is a powerful tool for identifying and extrapolating significant patterns from large amounts of unorganised data. Identifying latent themes or topics in a dataset is especially important when dealing with unstructured textual data as we have for uncovering clusters of interconnected information that may not be readily apparent to human analysts by determining the cooccurrence of words and phrases. Although topic modelling has demonstrated its efficacy as a technique for doing exploratory analysis on a substantial volume of publications, its use in an exploratory literature review has been infrequent. Accordingly, we have chosen structural topic model (STM) approach, a latent Dirichlet allocation (LDA) variant, implemented as an R package with enhanced functionality and options (Roberts et al., 2019). This approach is widely utilised, considered state-of-the-art, and known for its simplicity (DiMaggio et al., 2013; Elgesem et al., 2015; Grimmer, 2010; Koltsova & Koltcov, 2013). Although alternative topic modelling approaches may exist, the implementation and understanding of STM are straightforward. It is an unsupervised probabilistic modelling technique to identify and extract themes from a given corpus of content. In this framework, a topic is a probability distribution over a predetermined set of words. Accordingly, this initial step of our analysis conducts a comprehensive examination of the words in each article and computes the combined probability distribution between the observable words in the paper and the unobserved underlying subjects. It is presumed that the most common terms associated with a topic will indicate the essence or subject matter of the issue. When determining the number of topics (K), we utilised measures of semantic coherence and exclusivity and asked for 10 topics to grasp a comprehensive picture of the field, as seen in Supplemental Appendix 1A. After conducting the topic modelling, the research team validated and labelled the topics based on top and frex terms as well as reading most representative documents for individual topics. This served as an initial thematic categorisation scheme for later manual coding consisting of seven dimensions: Article type (empirical article, essay, theoretical article, literature review), methodology (qualitative, quantitative, mixed), method (survey, experiment, etc.), scientific case/context, research theme, variable operationalisation, and discipline. Discipline is coded based on affiliations of first authors as recorded by WoS. Using this coding scheme, three researchers manually coded the publications, distributing them equally among themselves, and made joint decisions on uncertain cases. For network analysis of relationships between disciplines and research themes, we opted for bibliographic coupling technique to map the structure of the research field. Bibliographic coupling works on the assumption that two publications sharing common references are intellectually related in terms of research subject and scientific approach (Donthu et al., 2021). This technique has been demonstrated to be one of the most effective clustering methods for science mapping (Boyack & Klavans, 2010). For this, we created a co-occurrence matrix in R, set a minimum co-occurrence threshold of 3, and visualised the results using Gephi (0.10), a network analysis and visualisation software. To visualise the network structure of the field we utilised ForceAtlas 2 algorithm, a popular layout algorithm in network analysis, using a physics-based approach to position nodes (publications) in a way that reflects their relationships, with nodes (publications) sharing references being placed nearer to each other. Finally, we merged these networks with our manually coded data. Figure 1. Literature identification and screening process. Kabakcxi et al. 5 Results General Profile of the Field. Based on the graph of yearly distribution of published articles (Figure 2), we can see a sharp increase around 2020, coinciding with the beginning of COVID-19 pandemic. So much that number of published articles in the last 3 years account for 62% of all articles published. Admittedly, increase in overall research output (Bornman et al., 2021) might also have played a role in the results but increasing academic attention towards trust in science in the context of COVID-19 pandemic is likely to be the biggest contributor. Disciplinary Profile and Journals. Our study shows that trust in science is a highly inter-disciplinary or even trans-disciplinary research field. In addition to social science disciplines, we also see contributions from humanities, environmental sciences and health sciences. According to Web of Science classification of journals, most common categories on journal level were ‘‘History & Philosophy of Science’’ (11.8%), ‘‘Communication’’ (10.8%), and ‘‘Public, Environmental & Occupational Health (9.3%). ‘‘Environmental Studies’’ and ‘‘Environmental Sciences’’ categories together accounted for 7.1% of all publications. The rest were highly varied, and categories spanned from ‘‘Meteorology & Atmospheric Sciences’’ to ‘‘Cultural Studies.’’ The majority of first authors were affiliated with departments in the Social Sciences, accounting for 58.5% of all first authors, followed by those in the Humanities at 11.2%, Health Sciences at 10.4%, and Environmental Sciences at 8.7%. In terms of countries, a total of 623 authors contributed to the studies in our sample and most of them were affiliated with research institutions from ‘‘Western’’ countries (Figure 3). Among these countries, United States was leading with 37% of all authors affiliated to an institution in the United States. Authors affiliated to non-Western institutions were quite rare, most frequent were People’s Republic of China (0.8%), South Africa (0.6%), India (0.5%), and Indonesia (0.5%). These findings indicate that the field is heavily biased towards the West. Methodological-Empirical Profile. In terms of methodology, the majority of empirical articles employed quantitative designs (78.3%), while a smaller proportion utilised qualitative methods (12%) or combined both qualitative and quantitative approaches (9.6%). Reflecting the diverse disciplines and traditions contributing to research on trust in science, methods were highly diverse, but surveys were most popular, utilised by more than half of the empirical studies (57.1%). Experiments were also relatively common (24.9%) generally applied via surveys. Figure 2. Number of studies published by year. 6SAGE Open Most common qualitative method was in-depth interview, utilised by 60% of the qualitative studies and 12% of mixed methodology studies. In terms of how trust in science and related variables are operationalised in quantitative and mixed methodology studies, 39.7% of studies utilised them as a dependent variable while 32.2% of studies as independent variable, that is, gave the concept an explanatory role. Due to the nature of their analysis methods we weren’t able to ascertain variable operationalisation of certain studies (Other category) (See Table 1). Contexts and Cases of Studies. Most studies have taken one of two approaches when researching trust in science: they either focused on trust in science in a general manner or they analysed trust in science with a particular focus on specific cases and contexts. The majority of the studies chose the latter approach (71.1%). Among studies with a specific focus, most of them focused on COVID-19 pandemic (33%), followed by other health-related cases (17.0%) such as Ebola (Gesser-Edelsburg et al., 2015), human immunodeficiency virus (HIV; Jaspal et al., 2022), and non-COVID vaccines (Hornsey et al., 2020). Second major context was environmental topics, specifically climate change (9.89%) and other environmental issues (12.1%), including diverse cases ranging from fisheries to lead pollution and natural resource management (Gray et al., 2012) (See Figure 4). Network Analysis The results of topic modelling and manual coding provided five dominant research themeson trust in science among various disciplines. Before going into the detailed analysis of these themes, it would be worthwhile to depict the analysis visually based on the interactions between umbrella disciplines, sub-disciplines, and themes. Figure 5 below shows the bibliographic coupling network of publications in various scientific disciplines based on their umbrella disciplines. The above figure shows that works from social sciences dominate the terrain of research on trust. It is also noticeable that the domain of social sciences is in interaction with other umbrella disciplines in separate networks. We also observe that humanities and health sciences constitute two visible sub-networks of natural and health sciences, respectively, as shown in the figure’s upper left and lower right parts, that only loosely interact with other main disciplines. It is also observable that their link as disciplines is handled via the works in social sciences. Figure 6 breaks down the above network into further sub-disciplines. Figure 3. Affiliated countries of authors. Kabakcxi et al. 7 Figure 6 shows essential evidence of the interdisciplinary nature of the phenomenon. The figure depicts psychology, philosophy and communication studies as dominant sub-disciplines, followed by sociology, business, and health sciences. Lastly, Figure 7 provides a graphical illustration of this study’s themes, which are discussed in the following section. The similar network maps showing the names and corresponding journals of the articles can be found in Supplemental Appendix 1B. Research Themes Theme 1: Trust in Science/Theoretical Conceptualisations. A running theme among many studies in this category is related to ways of fostering or restoring public trust in science and scientific advice in the context of changing scientific institutions, research ecosystems and societal conditions. We also see that these works dominantly appear under the humanities and cover the areas of philosophy, political science and sociology disciplines regarding several crosscutting issues. For instance, Carrier (2022) discusses the limitations of the traditional model of trustworthy science associated with value freeness and objectivity and suggests an alternative strategy based on being more transparent about non-epistemic values in scientific advice. Similarly, Sztompka (2007) argues that Robert K. Merton’s model of science, characterised by four institutional norms, is inadequate in Table 1. Methodology and Methods of Empirical Studies (n= 166) in Addition to Variable Operationalisation of Quantitative and Mixed Method Studies (n= 146). Methodological-Empirical Profile Frequency (%) Methodology Quantitative 130 (78.3) Qualitative 20 (12) Mixed 16 (9.6) Methods (not exclusively coded) Survey 108 (57.1) Experiment 47 (24.9) In-depth interview 20 (10.6) Focus group 4 (2.1) Workshop 2 (1.1) Thematic analysis 1 (0.5) Content analysis (manual) 2 (1.1) Network analysis 1 (0.5) Ethnography 1 (0.5) Concept mapping 1 (0.5) Other 1 (0.5) Operationalisation (for quantitative and mixed studies only) Dependent variable 58 (39.7) Independent variable 47 (32.2) Not applicable 10 (6.8) Mediator 10 (6.8) Other 8 (5.5) Multiple 6 (4.1) Moderator 4 (2.7) Covariate 3 (2.1) Figure 4. Research contexts and cases of publications over the years. 8SAGE Open studies on social sciences and humanities can be theoretically informative, particularly in the context of widespread concerns about politicisation of science, as the knowledge produced in these fields has been traditionally more embedded in social and political contexts. In terms of research themes, beside the conceptual and theoretical research, the focus of empirical research was evenly distributed across science communication, factors related to trust in science, compliance with scientific advice and public engagement. There were some possible gaps for specific research themes; for example, studies on religion were rare, while we expected to find more studies on social media in the theme of science communication and more compliance studies outside of the context of the COVID-19 pandemic. Concerning the findings and results of the reviewed studies, 1 studies in the first theme emphasise the need to rethink and reconceptualise basic concepts such as science, public, and trust, alongside traditional models of trustworthy science, in the context of changing scientific institutions, research ecosystems, and societal conditions. The second theme demonstrates how socio-demographic and ideological factors influence public attitudes towards both science, and its institutions and scientists. Research conducted under the third research theme, which examines the role of trust in science in compliance to scientific advice, particularly in contexts such as the COVID-19 pandemic, reveals that trust in science is a key factor in adherence to scientific guidance and advice. The fourth and fifth themes underscore the importance of tailored science communication strategies and active public engagement to bridge gaps in trust and facilitate informed decision-making amid complex scientific issues. Collectively, these insights point towards a need for a more nuanced and integrated understanding of public trust dynamics in science. It would be a truism to argue that public trust in science is crucial for informed decision-making and policy formation in an era of scientific progress. However, as discussed above, building policies to establish trust in science in multiple scientific domains is crucial to underlying the commonalities among these disciplines. Although policy recommendations were put forth through several academic work focusing on the interfaces of science and society, and the scholarly field of science communication have dealt with the communication between specialist and non specialists, the new contexts (such as COVID19) on a global scale will require considering science communication models adopted in times of crisis and their downfalls, such as stepping back to a deficit-model (see Scheufele, 2022). Furthermore, trust in science and their determinants vary culturally, across contexts and countries, depending on the countries’ engagement with science, institutional structures and other socially and culturally significant variables (Bicchieri et al., 2021; Cologna et al., 2025; T. L. O’Brien & Noy, 2018; Sulik et al., 2021). Thus any policy recommendation should also be contextually informed and take into account the political contexts in which science communication occurs (Scheufele, 2014). Accordingly, future work on possible policy recommendations at least consider specific aspects: we think it is crucial to encourage research initiatives and collaborations among specialists from multiple domains of scientific research (Varda et al., 2025). By offering a holistic perspective, interdisciplinary collaboration will strengthen the legitimacy of scientific discoveries, leading to successful attempts to solve complicated social problems that need ideas from several fields. Such a collaboration will encourage transparency in research by requiring researchers to freely and thoroughly reveal their techniques, data, and outcomes. Eventually, transparency in scientific domains will foster trust by permitting inspection of research procedures and outcomes, and as stated before, open data dissemination will permit independent verification and promote trust in scientific discoveries (Rosman et al., 2022). Lastly, future work on possible policy recommendations should also consider promoting diversity and inclusiveness in research teams and scientific organisations. Since inclusion stimulates innovation and creativity, when scientists from various backgrounds collaborate, they often approach problems and challenges in different ways, creating a variety of problem-solving strategies that can result in more effective and unique answers to scientific concerns. Moreover, diverse research teams are more likely to represent the populations better, especially historically underrepresented groups in science. This improved representation not only encompasses considerations of fairness but also guarantees the applicability of research findings to a broader spectrum of persons and groups. Furthermore, the credibility and trustworthiness of research are frequently perceived to be enhanced when done by varied teams. When the scientific community exhibits inclusivity, it serves as a symbolic representation to the general public that science is a domain characterised by openness and fairness, hence strengthening the notion that scientific investigations are pursued for the betterment of society as a whole rather than for the exclusive advantage of a privileged few. As with all research, this study has certain limitations. The main limitation of this study lies in its data collection procedure, which is restricted to Web of Science and author keywords. We might have missed research on trust in science, not including our search keywords or covered in other databases. Thus, although we believe that our data collection procedure gives us the core of the field, this study may fail to represent the field as a Kabakcxi et al. 15 whole. In addition, given the relatively broad scope, we had to balance depth and breadth to reveal the field’s leading trends and significant research themes. Future studies may adopt a more comprehensive data collection procedure, focus on theory or conduct in-depth reviews of specific research themes or contexts we discussed. ORCID iDs Go ¨kcxe Zeybek Kabakci https://orcid.org/0000-0001-86663179 Umut Yener Kara https://orcid.org/0000-0002-0556-4863 Go ¨kcxe Baydar Cxavdar https://orcid.org/0000-0001-97122597 Emre Toros https://orcid.org/0000-0002-7550-3185 Ethical Considerations Hacettepe University’s Ethics Committee approved the research on the ethical basis with the document number E-35853172102.01-00002140032, dated 18.04.2024. Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project is funded by TUBITAK (Scientific and Technological Research Council of Turkey) under the project scheme 1001 with the project number 122K368 ‘‘Turkey Trust Research.’’ Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Data Availability Statement The underlying dataset contains potentially identifying information and is currently under institutional embargo. In line with our ethical approvals and data-protection obligations, the full data cannot be made publicly available at this time. We will, however, share de-identified data extracts sufficient to reproduce the analyses, together with all analysis code and documentation (variable list, recodes, and model specifications), upon reasonable request to the corresponding author. Requests will be reviewed in consultation with the relevant ethics/data access body and may require a simple data-use agreement. Upon expiry of the embargo, the dataset will be deposited in an appropriate public repository with accompanying metadata and code. Supplemental Material Supplemental material for this article is available online. Note 1. For the specific findings of the reviewed empirical studies, see the Supplemental Appendix 2. References Achterberg, P., de Koster, W., & van der Waal, J. (2017). A science confidence gap: Education, trust in scientific methods, and trust in scientific institutions in the United States, 2014. Public Understanding of Science,26(6), 704–720. https://doi. org/10.1177/0963662515617367 Agley, J., Xiao, Y., Thompson, E. E., Chen, X., & GolzarriArroyo, L. (2021). Intervening on trust in science to reduce belief in COVID-19 misinformation and increase COVID19 preventive behavioral intentions: Randomized controlled trial. Journal of Medical Internet Research,23(10), e32425. https://doi.org/10.2196/32425 Agley, J., Xiao, Y., Thompson, E. E., & Golzarri-Arroyo, L. (2021a). Factors associated with reported likelihood to get vaccinated for COVID-19 in a nationally representative US survey. Public Health,196, 91–94. https://doi.org/10.1016/j. puhe.2021.05.009 Agley, J., Xiao, Y., Thompson, E. E., & Golzarri-Arroyo, L. (2021b). Using infographics to improve trust in science: A randomized pilot test. BMC Research Notes,14(1), 210. https://doi.org/10.1186/s13104-021-05626-4 Algan, Y., Cohen, D., Davoine, E., Foucault, M., & Stantcheva, S. (2021). Trust in scientists in times of pandemic: Panel evidence from 12 countries. Proc. Natl. Acad. Sci. U.S.A. https://doi.org/10.1073/pnas.2108576118 Alper, S., Yelbuz, B. E., Akkurt, S. B., & Yilmaz, O. (2022). The positive association of education with the trust in science and scientists is weaker in highly corrupt countries. Public Understanding of Science,33(1), 2–19. Altenmuller, M. S., Nuding, S., & Gollwitzer, M. (2021). No harm in being self-corrective: Self-criticism and reform intentions increase researchers’ epistemic trustworthiness and credibility in the eyes of the public. Public Understanding of Science,30(8), 962–976. https://doi.org/10.1177/ 09636625211022181 Amit Aharon, A., Ruban, A., & Dubovi, I. (2021). Knowledge and information credibility evaluation strategies regarding COVID-19: A cross-sectional study. Nursing Outlook,69(1), 22–31. https://doi.org/10.1016/j.outlook.2020.09.001 Azevedo, F., & Jost, J. T. (2021). The ideological basis of antiscientific attitudes: Effects of authoritarianism, conservatism, religiosity, social dominance, and system justification. Group Processes and Intergroup Relations,24(4), 518–549. https://doi.org/10.1177/1368430221990104 Bagasra, A. B., Doan, S., & Allen, C. T. (2021). Racial differences in institutional trust and COVID-19 vaccine hesitancy and refusal. BMC Public Health,21(1), 2104. https://doi. org/10.1186/s12889-021-12195-5 Bailey, J. L., Liu, Y., & Davidsen, J. G. (2017). Bridging the gap between fisheries science and society: Exploring fisheries science as a social activity. ICES Journal of MArine Science, 74(2), 598–611. https://doi.org/10.1093/icesjms/fsw203 16 SAGE Open Bajos, N., Spire, A., Silberzan, L., Sireyjol, A., Jusot, F., Meyer, L., Franck, J. E., & Warszawski, J. (2022). When lack of trust in the government and in scientists reinforces social inequalities in vaccination against COVID-19. Frontiers in Public Health,10, 908152. https://doi.org/10.3389/ fpubh.2022.908152 Barmoen, M., Baerum, K. M., Johansson, M., & Mathiesen, K. E. (2021). Trust in large carnivore science in Norway. European Journal of Wildlife Research,67(6), Article 98. https:// doi.org/10.1007/s10344-021-01538-7 Barnett, J., Cooper, H., & Senior, V. (2007). Belief in public efficacy, trust, and attitudes toward modern genetic science. Risk Analysis,27(4), 921–933. https://doi.org/10.1111/j. 1539-6924.2007.00932.x Bedessem, B., Gawronska-Novak, B., & Lis, P. (2021). Can citizen science increase trust in research? A case study of delineating polish metropolitan areas. Journal of Contemporary European Research,17(2), 304–325. https://doi.org/10. 30950/jcer.v17i2.1185 Benson-Greenwald, T. M., Trujillo, A., White, A. D., & Diekman, A. B. (2022). Science for Others or the Self? Presumed Motives for Science Shape Public Trust in Science. Personality and Social Psychology Bulletin,49(3), 344–360. https:// doi.org/10.1177/01461672211064456 Besley, J. C., & Tiffany, L. A. (2023). What are you assessing when you measure ‘‘trust’’ in scientists with a direct measure? Public Understanding of Science,32(6), 709–726. Bicchieri, C., Fatas, E., Aldama, A., Casas, A., Deshpande, I., Lauro, M., Parilli, C., Spohn, M., Pereira, P., & Wen, R. (2021). In science we (should) trust: Expectations and compliance across nine countries during the COVID-19 pandemic. PLoS ONE 16(6), e0252892. https://doi.org/10.1371/ journal.pone.0252892 Blankenship, B. T., & Stewart, A. J. (2019). Threat, trust, and Trump: Identity and voting in the 2016 presidential election. Politics, Groups, and Identities,7(3), 724–736. https://doi. org/10.1080/21565503.2019.1633932 Boumans, J. W., & Trilling, D. (2015). Taking stock of the toolkit: An overview of relevant automated content analysis approaches and techniques for digital journalism scholars. Digital Journalism,4(1), 8–23. Bornman, L., Haunschild, R. & Mutz, R. (2021). Growth rates of modern science: a latent piecewise growth curve approach to model numbers from established and new literature databases. Humanities and Social Sciences Communications,8(1), 1–15. https://doi.org/10.1057/s41599-021-00903-w Boyack, K. W., & Klavans, R. (2010). Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately? Journal of the American Society for Information Science and Technology,61(12), 2389–2404. Breakwell, G. M., Fino, E., & Jaspal, R. (2022). COVID-19 preventive behaviours in White British and Black, Asian and Minority Ethnic (BAME) people in the UK. Journal of Health Psychology,27(6), 1301–1317. https://doi.org/10. 1177/13591053211017208 Brown, R. C. H., de Barra, M., & Earp, B. D. (2022). Broad medical uncertainty and the ethical obligation for openness. Synthese,200(2), 121. https://doi.org/10.1007/s11229-02203666-2 Bucchi, M., Fattorini, E., & Saracino, B. (2022). Public perception of COVID-19 vaccination in Italy: The role of trust and experts’ communication. International Journal of Public Health, 67, 1604222. https://doi.org/10.3389/ijph.2022.1604222 Cadeddu, C., Daugbjerg, S., Ricciardi, W., & Rosano, A. (2020). Beliefs towards vaccination and trust in the scientific community in Italy. Vaccine,38(42), 6609–6617. https://doi. org/10.1016/j.vaccine.2020.07.076 Cadeddu, C., Sapienza, M., Castagna, C., Regazzi, L., Paladini, A., Ricciardi, W., & Rosano, A. (2021). Vaccine hesitancy and trust in the scientific community in Italy: Comparative analysis from two recent surveys. Vaccines,9(10), 1206. https://doi.org/10.3390/VACCINES9101206 Camic, C., Gross, N., & Lamont, M. (2011). Introduction. The study of social knowledge making. In C. Camic, N. Gross, & M. Lamont (Eds.), Social knowledge in the making (pp. 1– 40). University of Chicago Press. Capasso, M., Caso, D., & Zimet, G. D. (2022). The mediating roles of attitude toward COVID-19 vaccination, trust in science and trust in government in the relationship between anti-vaccine conspiracy beliefs and vaccination intention. Frontiers in Psychology,13, 936917. https://doi.org/10.3389/ fpsyg.2022.936917 Carrier, M. (2022). What does good science-based advice to politics look like? Journal for General Philosophy of Science, 53(1), 5–21. https://doi.org/10.1007/s10838-021-09574-2 Chinn, S., & Sol Hart, P. (2022). Can’t you all just get along? Effects of scientific disagreement and incivility on attention to and trust in science. Science Communication,44(1), 108–129. https://doi.org/10.1177/10755470211054446 Cologna, V., Mede, N. G., Berger, S., Besley, J., Brick, C., Joubert, M., Maibach, E. W., Mihelj, S., Oreskes, N., Scha ¨fer, M. S., van der Linden, S., Aziz, I. A., Abdulsalam, S., Shamsi, N. A., Aczel, B., Adinugroho, I., Alabrese, E., Aldoh, A., Alfano, M., & .Zwaan, R. A. (2025). Trust in scientists and their role in society across 68 countries. Nature Human Behaviour,9(4), 713–730. https://doi.org/10.1038/ s41562-024-02090-5 Corcoran, K. E., Scheitle, C. P., & DiGregorio, B. D. (2023). Paranormal beliefs, vaccine confidence, and COVID-19 vaccine uptake. Sociology of Religion,84(2), 111–143. https:// doi.org/10.1093/socrel/srac024 Critchley, C., Nicol, D., & Otlowski, M. (2015). The impact of commercialisation and genetic data sharing arrangements on public trust and the intention to participate in biobank research. Public Health Genomics,18(3), 160–172. https:// doi.org/10.1159/000375441 Critchley, C. R., Bruce, G., & Farrugia, M. (2013). The impact of commercialisation on public perceptions of stem cell research: Exploring differences across the use of induced pluripotent cells, human and animal embryos. Stem Cell Reviews and Reports,9(5), 541–554. https://doi.org/10.1007/ s12015-013-9445-4 Cunningham-Burley, S. (2006). Public knowledge and public trust. Community Genetics,9(3), 204–210. https://doi.org/10. 1159/000092658 Kabakcxi et al. 17 Cvitanovic, C., Marshall, N. A., Wilson, S. K., Dobbs, K., & Hobday, A. J. (2014). Perceptions of Australian marine protected area managers regarding the role, importance, and achievability of adaptation for managing the risks of climate change. Ecology and Society,19(4), 33–42. https://doi.org/ 10.5751/ES-07019-190433 Denton, G., Chi, H., & Gursoy, D. (2022). An examination of critical determinants of carbon offsetting attitudes: The role of gender. Journal of Sustainable Tourism,30(7), 1539–1561. https://doi.org/10.1080/09669582.2021.1920966 Develaki, M. (2022). Trustworthiness of science in debate: Challenges, responses, and implications. Science & Education,31(5 Suppl), 1181–1208. https://doi.org/10.1007/ s11191-021-00300-4 Dietz, T. (2013). Bringing values and deliberation to science communication. Proceedings of the National Academy of Sciences of the United States of America,110(3), 14081–14087. https://doi.org/10.1073/pnas.1212740110 DiMaggio, P., Nag, M., & Blei, D. (2013). Exploiting affinities between topic modeling and the sociological perspective on culture: Application to newspaper coverage of U.S. government arts funding. Poetics,41(6), 570–606. https://doi.org/ 10.1016/j.poetic.2013.08.004 Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research,133, 285–296. Drummond, C., & Fischhoff, B. (2017). Individuals with greater science literacy and education have more polarized beliefs on controversial science topics. Proceedings of the National Academy of Sciences of the United States of America,114(36), 9587–9592. https://doi.org/10.1073/pnas. 1704882114 Eichengreen, B., Aksoy, C. G., & Saka, O. (2021). Revenge of the experts: Will COVID-19 renew or diminish public trust in science? Journal of Public Economics,193, 104343. https:// doi.org/10.1016/j.jpubeco.2020.104343 Elgesem, D., Steskal, L., & Diakopoulos, N. (2015). Structure and content of the discourse on climate change in the blogosphere: The big picture. Environmental Communication,9(2), 169–188. https://doi.org/10.1080/17524032.2014.983536 Engdahl, E., & Lidskog, R. (2014). Risk, communication and trust: Towards an emotional understanding of trust. Public Understanding of Science,23(6), 703–717. https://doi.org/10. 1177/0963662512460953 Falade, B. A., & Bauer, M. W. (2018). ‘‘I have faith in science and in God’’: Common sense, cognitive polyphasia and attitudes to science in Nigeria. Public Understanding of Science,27(1), 29–46. https://doi.org/10.1177/ 0963662517690293 Fensham, P. J. (2014). Scepticism and trust: Two counterpoint essentials in science education for complex socio-scientific issues. Cultural Studies of Science Education,9(3), 649–661. https://doi.org/10.1007/s11422-013-9560-1 Flynn, R., Ricci, M., & Bellaby, P. (2011). The mirage of citizen engagement in uncertain science: Public attitudes towards hydrogen energy. International Journal of Science Education Part B Communication and Public Engagement,1(2), 97–114. https://doi.org/10.1080/21548455.2011.585810 Furman, K. (2020). Emotions and distrust in science. International Journal of Philosophical Studies,28(5 Suppl), 713–730. https://doi.org/10.1080/09672559.2020.1846281 Gabel, M., Gooblar, J., Roe, C. M., Selsor, N. J., & Morris, J. C. (2018). Political ideology, confidence in science, and participation in Alzheimer disease research studies. Alzheimer Disease & Associated Disorders,32(3), 179–184. https://doi. org/10.1097/WAD.0000000000000244 Gauchat, G. (2012). Politicization of science in the public sphere: A study of public trust in the United States, 1974 to 2010. American Sociological Review,77(2), 167–187. https:// doi.org/10.1177/0003122412438225 Gesser-Edelsburg, A., Shir-Raz, Y., Hayek, S., & Lev, O. S.-B. (2015). What does the public know about Ebola? The public’s risk perceptions regarding the current Ebola outbreak in an as-yet unaffected country. American Control of Infection Control,43(7), 669–675. https://doi.org/10.1016/j.ajic. 2015.03.005 Gierth, L., & Bromme, R. (2020). Attacking science on social media: How user comments affect perceived trustworthiness and credibility. Public Understanding of Science,29(2), 230–247. https://doi.org/10.1177/0963662519889275 Gilfedder, M., Robinson, C. J., Watson, J. E. M., Campbell, T. G., Sullivan, B. L., & Possingham, H. P. (2019). Brokering trust in citizen science. Society & Natural Resources,32(3), 292–302. https://doi.org/10.1080/08941920.2018.1518507 Goldenberg M. J. (2023). Public trust in science. Interdisciplinary Science Reviews,48(2), 366–378. https://doi.org/10.1080/ 03080188.2022.2152243 Goldfinch, S., & Taplin, R. (2022). A cross-sectional international study shows confidence in public health scientists predicts use of COVID-19 non-pharmaceutical interventions. BMC Public Health,22(1), 662. https://doi.org/10.1186/ s12889-022-13074-3 Goud, S., Sheats, J. L., & Mertz, A. F. (2023). Building bridges, earning trust: The WHY and the HOW of public trust in science. Aspen Institute Science and Society Program. Granados Samayoa, J. A., Ruisch, B. C., Moore, C. A., Boggs, S. T., Ladanyi, J. T., & Fazio, R. H. (2021). When does knowing better mean doing better? Trust in President Trump and in scientists moderates the relation between COVID-19 knowledge and social distancing. Journal of Elections, Public Opinion and Parties,31(Suppl 1), 218–231. https://doi.org/ 10.1080/17457289.2021.1924744 Graso, M., Henwood, A., Aquino, K., Dolan, P., & Chen, F. X. (2022). The dark side of belief in Covid-19 scientists and scientific evidence. Personality and Individual Differences, 193, 111594. https://doi.org/10.1016/j.paid.2022.111594 Gray, S., Shwom, R., & Jordan, R. (2012). Understanding factors that influence stakeholder trust of Natural Resource Science and Institutions. Environmental Management,49(3), 663–674. https://doi.org/10.1007/s00267-011-9800-7 Grimmer, J. (2010). A Bayesian hierarchical topic model for political texts: Measuring expressed agendas in Senate Press Releases. Political Analysis,18(1), 1–35. https://doi.org/10. 1093/pan/mpp034 Grimmer, J., Roberts, M. E., & Stewart, B. M. (2022). Text as data: A new framework for machine learning and the social sciences. Princeton University Press. 18 SAGE Open Gundersen, T., Alinejad, D., Branch, T. Y., Duffy, B., Hewlett, K., Holst, C., Owens, S., Panizza, F., Tellmann, S. M., van Dijck, J., & Baghramian, M. (2022). A new dark age? Truth, trust, and environmental science. Annual Review of Environment and Resources,47, 5–29. https://doi.org/10.1146/ annurev-environ-120920-015909 Gundersen, T., & Holst, C. (2022). Science advice in an environment of trust: Trusted, but not trustworthy? Social Epistemology,36(5 Suppl), 629–640. https://doi.org/10.1080/ 02691728.2022.2101564 Gustafsson, K., & Lidskog, R. (2012). Acknowledging risk, trusting expertise, and coping with uncertainty: Citizens’ deliberations on spraying an insect population. Society & Natural Resources,25(6), 587–601. https://doi.org/10.1080/ 08941920.2011.620598 Hamilton, L. C., Hartter, J., & Saito, K. (2015). Trust in scientists on climate change and vaccines. Sage Open,5(3). https://doi.org/10.1177/2158244015602752 Han, H. (2022). Trust in the scientific research community predicts intent to comply with COVID-19 prevention measures: An analysis of a large-scale international survey dataset. Epidemiology and Infection,150, e36. https://doi.org/10.1017/ S0950268822000255 Hegland, A., Zhang, A. L., Zichettella, B., & Pasek, J. (2022). A Partisan pandemic: How COVID-19 was primed for polarization. Annals of the American Academy of Political and Social Science,700(1), 55–72. https://doi.org/10.1177/ 00027162221083686 Hendriks, F., & Jucks, R. (2020). Does scientific uncertainty in news articles affect readers’ trust and decision-making? Media and Communication,8(2), 401–412. https://doi.org/ 10.17645/mac.v8i2.2824 Hendriks, F., Kienhues, D., & Bromme, R. (2016a). Evoking vigilance: Would you (dis)trust a scientist who discusses ethical implications of research in a science blog? Public Understanding of Science,25(8 Suppl), 992–1008. https://doi.org/ 10.1177/0963662516646048 Hendriks, F., Kienhues, D., & Bromme, R. (2016b). Trust in science and the science of trust. In B. Blo ¨baum (ed.). Trust and communication in a digitized world: Models and concepts of trust research, (pp. 143–159). Springer International Publishing. Hendriks, F., Kienhues, D., & Bromme, R. (2020). Replication crisis = trust crisis? The effect of successful vs failed replications on laypeople’s trust in researchers and research. Public Understanding of Science,29(3), 270–288. https://doi.org/10. 1177/0963662520902383 Hilgard, J., & Jamieson, K. H. (2017). Does a scientific breakthrough increase confidence in science? News of a Zika vaccine and trust in science. Science Communication,39(4), 548–560. https://doi.org/10.1177/1075547017719075 Hornsey, M. J., Lobera, J., & Dı ´az-Catala ´n, C. (2020). Vaccine hesitancy is strongly associated with distrust of conventional medicine, and only weakly associated with trust in alternative medicine. Social Science and Medicine,255, 113019. https://doi.org/10.1016/j.socscimed.2020.113019 Hromatko, I., Tonkovic ´, M., & Vranic, A. (2021). Trust in science, perceived vulnerability to disease, and adherence to pharmacological and non-pharmacological COVID-19 recommendations. Frontiers in Psychology,12, 664554. https://doi.org/10.3389/fpsyg.2021.664554 Huang, Y., & Green, M. C. (2023). Reducing COVID-19 vaccine hesitancy among African Americans: The effects of narratives, character’s self-persuasion, and trust in science. Journal of Behavioral Medicine,46, 290–302. https://doi.org/ 10.1007/s10865-022-00303-8 Huber, B., Barnidge, M., de Zuniga, H., & Liu, J. (2019). Fostering public trust in science: The role of social media. Public Understanding of Science,28(7), 759–777. https://doi.org/ 10.1177/0963662519869097 Intemann, K. (2022). Understanding the problem of ‘‘Hype’’: Exaggeration, values, and trust in science. Canadian Journal of Philosophy,52(3 Suppl), 279–294. https://doi.org/10.1017/ can.2020.45 Irzik, G., & Kurtulmus, F. (2021). Well-ordered science and public trust in science. Synthese,198(Suppl 19), 4731–4748. https://doi.org/10.1007/s11229-018-02022-7 Ivani, S., & Novaes, C. D. (2022). Public engagement and argumentation in science. European Journal for Philosophy of Science,12(3), 54. https://doi.org/10.1007/s13194-02200480-y Jacob, M., & Hellstrom, T. (2000). Policy understanding of science, public trust and the BSE-CJD crisis. Journal of Hazardous Materials,78(1–3 Suppl), 303–317. https://doi.org/10. 1016/S0304-3894(00)00228-4 Jamieson, K. H., McNutt, M., Kiermer, V., & Sever, R. (2019). Signaling the trustworthiness of science. Proceedings of the National Academy of Sciences,116(39), 19231–19236. Janssen, I., Hendriks, F., & Jucks, R. (2021). Face masks might protect you from COVID-19: The communication of scientific uncertainty by scientists versus politicians in the context of policy in the making. Journal of Language and Social Psychology,40(5–6 Suppl), 602–626. https://doi.org/10.1177/ 0261927X211044512 Jaspal, R., Gardner, S., Zwach, P., Green, M., & Breakwell, G. M. (2022). Trust in science, homonegativity, and HIV stigma: Experimental data from the United Kingdom and Germany. Stigma and Health,7(4), 471–480. https://doi.org/ 10.1037/sah0000401 Jensen, K. K. (2004). BSE in the UK: Why the risk communication strategy failed. Journal of Agricultural & Environmental Ethics,17(4–5), 405–423. https://doi.org/10.1007/s10806004-5186-3 Kelly, R., Fleming, A., & Pecl, G. T. (2019). Citizen science and social licence: Improving perceptions and connecting marine user groups. Ocean & Coastal Management,178, 104855. https://doi.org/10.1016/j.ocecoaman.2019.104855 Kerr, J. R., & Wilson, M. S. (2021). Right-wing authoritarianism and social dominance orientation predict rejection of science and scientists. Group Processes and Intergroup Relations, 24(4), 550–567. https://doi.org/10.1177/1368430221992126 Kitcher, P. (2001). Science, Truth, and Democracy. Oxford University Press. Koetke, J., Schumann, K., & Porter, T. (2021). Trust in science increases conservative support for social distancing. Group Processes and Intergroup Relations,24(4), 680–697. https:// doi.org/10.1177/1368430220985918 Kabakcxi et al. 19 Koltsova, O., & Koltcov, S. (2013). Mapping the public agenda with topic modeling: The case of the Russian livejournal. Policy & Internet,5(2), 207–227. https://doi.org/10.1002/ 1944-2866.POI331 Ko ¨nig, L., & Jucks, R. (2019a). Hot topics in science communication: Aggressive language decreases trustworthiness and credibility in scientific debates. Public Understanding of Science, 28(4), 401–416. https://doi.org/10.1177/0963662519833903 Ko ¨nig, L., & Jucks, R. (2019b). When do information seekers trust scientific information? Insights from recipients’ evaluations of online video lectures. International Journal of Educational Technology in Higher Education,16(1), 1. https://doi. org/10.1186/s41239-019-0132-7 Kossowska, M., Szwed, P., & Czarnek, G. (2021). Ideology shapes trust in scientists and attitudes towards vaccines during the COVID-19 pandemic. Group Processes and Intergroup Relations,24(5), 720–737. https://doi.org/10.1177/ 13684302211001946 Kotcher, J. E., Myers, T. A., Vraga, E. K., Stenhouse, N., & Maibach, E. W. (2017). Does engagement in advocacy hurt the credibility of scientists? Results from a Randomized National Survey Experiment. Environmental Communication—A Journal of Nature and Culture,11(3), 415–429. https://doi.org/10.1080/17524032.2016.1275736 Kuroki, M., Yamamoto, K., & Goldfinch, S. (2022). Factors influencing the adoption of voluntary nonpharmaceutical interventions to control COVID-19 in Japan: Cross-sectional study. JMIR Formative Research,6(8), e34268. https://doi.org/10.2196/34268 Kwon, S. A., Kim, S., & Lee, J. E. (2019). Analyzing the determinants of individual action on climate change by specifying the roles of six values in South Korea. Sustainability (Switzerland),11(7), 1834. https://doi.org/10.3390/su11071834 Lamot, M., Kerman, K., & Kirbis ˇ, A. (2022). Distrustful, dissatisfied, and conspiratorial: A latent profile analysis of COVID-19 vaccination rejection. International Journal of Environmental Research and Public Health,19(16), 10096. https://doi.org/10.3390/ijerph191610096 Leith, P., Ogier, E., & Haward, M. (2014). Science and social license: Defining environmental sustainability of Atlantic Salmon Aquaculture in South-Eastern Tasmania, Australia. Social Epistemology,28(3–4 Suppl), 277–296. https://doi. org/10.1080/02691728.2014.922641 Lewis, S. C., Zamith, R., & Hermida, A. (2013). Content analysis in an era of big data: A hybrid approach to computational and manual methods. Journal of Broadcasting & Electronic Media,57(1), 34–52. Love, B., Mackert, M., & Silk, K. (2013). Consumer trust in information sources: Testing an interdisciplinary model. Sage Open, 3(2). https://doi.org/10.1177/2158244013492782 Majid, U., Ahmad, M., Zain, S., Akande, A., & Ikhlaq, F. (2022). COVID-19 vaccine hesitancy and acceptance: A comprehensive scoping review of global literature. Health Promotion International,37(3), daac078. https://doi.org/10. 1093/heapro/daac078 Marques, M. D., Critchley, C. R., & Walshe, J. (2015). Attitudes to genetically modified food over time: How trust in organizations and the media cycle predict support. Public Understanding of Science,24(5), 601–618. https://doi.org/10. 1177/0963662514542372 Matta, S., Rogova, N., & Luna-Corte ´s, G. (2022). Investigating tolerance of uncertainty, COVID-19 concern, and compliance with recommended behavior in four countries: The moderating role of mindfulness, trust in scientists, and power distance. Personality and Individual Differences,186, 111352. https://doi.org/10.1016/j.paid.2021.111352 McCright, A. M., Dentzman, K., Charters, M., & Dietz, T. (2013). The influence of political ideology on trust in science. Environmental Research Letters,8(4), 4029. https:// doi.org/10.1088/1748-9326/8/4/044029 Mede, N. G., Schaefer, M. S., Ziegler, R., & Weisskopf, M. (2021). The ‘‘replication crisis’’ in the public eye: Germans’ awareness and perceptions of the (ir)reproducibility of scientific research. Public Understanding of Science,30(1), 91–102. https://doi.org/10.1177/0963662520954370 Metzen, H. (2024). Objectivity, shared values, and trust. Synthese,203(1), 60. https://doi.org/10.1007/s11229-024-04493-3 Meyer, G. (2006). Journalism and science: How to erode the idea of knowledge. Journal of Agricultural & Environmental Ethics,19(3), 239–252. https://doi.org/10.1007/s10806-0056163-1 Mheidly, N., & Fares, J. (2020). Leveraging media and health communication strategies to overcome the COVID-19 infodemic. Journal of Public Health Policy,41, 410–420. https:// doi.org/10.1057/s41271-020-00247-w Millar, E., Melles, S., Klug, J. L., & Rees, T. (2023). Stewarding relations of trust: Citizen scientist perspectives on fostering community trust in science. Environmental Sociology,9(1), 31–50. https://doi.org/10.1080/23251042.2022.2112888 Milos ˇevic ´ord  evic ´, J., Mari, S., Vdovic ´, M., & Milos ˇevic ´,A. (2021). Links between conspiracy beliefs, vaccine knowledge, and trust: Anti-vaccine behavior of Serbian adults. Social Science and Medicine,277, 113930. https://doi.org/10. 1016/j.socscimed.2021.113930 Milos ˇevic ´-ord  evic ´, J., Kljajic ´, D., Sladojevic ´Matic ´, J., & uric ´, Z ˇ. (2022). Predictors and effects of scientific knowledge. International Journal of Sociology and Social Policy,42(9–10), 865–876. https://doi.org/10.1108/IJSSP-06-2021-0159 Myers, T. A., Kotcher, J., Stenhouse, N., Anderson, A. A., Maibach, E., Beall, L., & Leiserowitz, A. (2017). Predictors of trust in the general science and climate science research of US federal agencies. Public Understanding of Science,26(7), 843–860. https://doi.org/10.1177/0963662516636040 Myhr, A. I., & Traavik, T. (2003). Genetically modified (GM) crops: Precautionary science and conflicts of interests. Journal of Agricultural & Environmental Ethics,16(3), 227–247. https://doi.org/10.1023/A:1023686900879 Nerlich, B. (2013). Moderation impossible? On hype, honesty and trust in the context of modern academic life. Sociological Review,61(2 Suppl), 43–57. https://doi.org/10.1111/ 1467-954X.12099 Neureiter, A., Stubenvoll, M., Kaskeleviciute, R., & Matthes, J. (2021). Trust in science, perceived media exaggeration about COVID-19, and social distancing behavior. Frontiers in Public Health,9, 670485. https://doi.org/10.3389/fpubh.2021. 670485 20 SAGE Open Nisbet, E. C., Cooper, K. E., & Garrett, R. K. (2015). The Partisan brain: How dissonant science messages lead conservatives and liberals to (dis)trust science. Annals of the American Academy of Political and Social Science,658(1), 36–66. https://doi.org/10.1177/0002716214555474 O’Brien, T. C., Palmer, R., & Albarracin, D. (2021). Misplaced trust: When trust in science fosters belief in pseudoscience and the benefits of critical evaluation. Journal of Experimental Social Psychology,96, 104184. https://doi.org/10.1016/j. jesp.2021.104184 O’Brien, T. L., & Noy, S. (2018), Cultural authority in comparative context: A multilevel analysis of trust in science and religion. Journal for the Scientific Study of Religion,57, 495–513. https://doi.org/10.1111/jssr.12537 O’Doherty, K. C. (2022). Trust, trustworthiness, and relationships: Ontological reflections on public trust in science. Journal of Responsible Innovation,10, 1–22. O’Neill, O. (2002). A question of trust: The BBC reith lectures 2002. Cambridge University Press. Ophir, Y., & Jamieson, K. H. (2021). The effects of media narratives about failures and discoveries in science on beliefs about and support for science. Public Understanding of Science,30(8), 1008–1023. https://doi.org/10.1177/ 09636625211012630 Oreskes, N. (2019). Why trust science?Princeton University Press. Oude Groeniger, J., Noordzij, K., van der Waal, J., & de Koster, W. (2021). Dutch COVID-19 lockdown measures increased trust in government and trust in science: A difference-in-differences analysis. Social Science and Medicine,275, 113819. https://doi.org/10.1016/j.socscimed.2021. 113819 Palamenghi, L., Barello, S., Boccia, S., & Graffigna, G. (2020). Mistrust in biomedical research and vaccine hesitancy: The forefront challenge in the battle against COVID-19 in Italy. European Journal of Epidemiology,35(8), 785–788. https:// doi.org/10.1007/s10654-020-00675-8 Pardo, R., & Calvo, F. (2008). Attitudes toward embryo research, worldviews, and the moral status of the embryo frame. Science Communication,30(1), 8–47. https://doi.org/ 10.1177/1075547008319432 Patwa, P., Sharma, S., Pykl, S., Guptha, V., Kumari, G., Akhtar, S., Ekbal, A., Das, A., & Chakraborty, T. (2021). Fighting an infodemic: COVID-19 fake news dataset. In T. Chakraborty, K. Shu, H. R. Bernard, H. Liu, & M. S. Akhtar (Eds.), Combating online hostile posts in regional languages during emergency situation. CONSTRAINT 2021. Communications in Computer and Information Science (Vol. 1402). Springer. https://doi.org/10.1007/978-3-03073696-5_3 Pechar, E., Bernauer, T., & Mayer, F. (2018). Beyond political ideology: The impact of attitudes towards government and corporations on trust in science. Science Communication,40(3), 291–313. https://doi.org/10.1177/10755470187 63970 Pivetti, M., Di Battista, S., Paleari, F. G., & Hakoko ¨nga ¨s, E. (2021). Conspiracy beliefs and attitudes toward COVID-19 vaccinations: A conceptual replication study in Finland. Journal of Pacific Rim Psychology,15. https://doi.org/10. 1177/18344909211039893 Plohl, N., & Musil, B. (2021). Modeling compliance with COVID-19 prevention guidelines: The critical role of trust in science. Psychology, Health and Medicine,26(1), 1–12. https://doi.org/10.1080/13548506.2020.1772988 Plohl, N., & Musil, B. (2022). Understanding, trusting, and applying scientific insights to improve your health: A latent profile analysis approach. International Journal of Environmental Research and Public Health,19(16), 9967. https://doi. org/10.3390/ijerph19169967 Proctor, J. (2006). Religion as trust in authority: Theocracy and ecology in the United States. Annals of the Association of American Geographers,96(1), 188–196. https://doi.org/10. 1111/j.1467-8306.2006.00508.x Qiao, S., Friedman, D. B., Tam, C. C., Zeng, C., & Li, X. (2022). COVID-19 vaccine acceptance among college students in South Carolina: Do information sources and trust in information matter? Journal of American College Health,72(3), 859–868. https://doi.org/10.1080/07448481.2022.2059375 Rabinovich, A., Morton, T. A., & Birney, M. E. (2012). Communicating climate science: The role of perceived communicator’s motives. Journal of Environmental Psychology,32(1), 11–18. https://doi.org/10.1016/j.jenvp.2011.09.002 Reif, A., & Guenther, L. (2021). How representative surveys measure public (dis)trust in science: A systematisation and analysis of survey items and open-ended questions. Journal of Trust Research,11(2), 94–118. https://doi.org/10.1080/ 21515581.2022.2075373 Reif, A., Kneisel, T., Schaefer, M., & Taddicken, M. (2020). Why are scientific experts perceived as trustworthy? Emotional assessment within TV and YouTube videos. Media and Communication,8(1), 191–205. https://doi.org/10.17645/ mac.v8i1.2536 Resnik, D. B. (2011). Scientific research and the public trust. Science and Engineering Ethics,17(3), 399–409. https://doi. org/10.1007/s11948-010-9210-x Roberts, M. E., Stewart, B. M., & Tingley, D. (2019). Stm: An R package for structural topic models. Journal of Statistical Software,91, 1–40. Roberts, M. R., Reid, G., Schroeder, M., & Norris, S. P. (2013). Causal or spurious? The relationship of knowledge and attitudes to trust in science and technology. Public Understanding of Science,22(5), 624–641. https://doi.org/10. 1177/0963662511420511 Rolin, K. H. (2020). Trust in science. In J. Simon (ed.), The Routledge Handbook of Trust and Philosophy, pp. 354– 366. Rolin, K. H. (2021). Objectivity, trust and social responsibility. Synthese,199(1–2), 513–533. https://doi.org/10.1007/s11229020-02669-1 Rosman, T., Bosnjak, M., Silber, H., Koßmann, J., & Heycke, T. (2022). Open science and public trust in science: Results from two studies. Public Understanding of Science (Bristol, England),31(8), 1046–1062. https://doi.org/10.1177/ 09636625221100686 Saarinen, A., Koivula, A., & Keipi, T. (2020). Political trust, political party preference and trust in knowledge-based Kabakcxi et al. 21 institutions. International Journal of Sociology and Social Policy,40(1–2), 154–168. https://doi.org/10.1108/IJSSP-06-20190113 Safford, T. G., Whitmore, E. H., & Hamilton, L. C. (2020). Questioning scientific practice: Linking beliefs about scientists, science agencies, and climate change. Environmental Sociology,6(2), 194–206. https://doi.org/10.1080/23251042. 2019.1696008 Sailer, M., Stadler, M., Botes, E., Fischer, F., & Greiff, S. (2022). Science knowledge and trust in medicine affect individuals’ behavior in pandemic crises. European Journal of Psychology of Education,37(1), 279–292. https://doi.org/10. 1007/s10212-021-00529-1 Sankare, I. C., Bross, R., Brown, A. F., del Pino, H. E., Jones, L. F., Morris, D. M., Porter, C., Lucas-Wright, A., Vargas, R., Forge, N., Norris, K. C., & Kahn, K. L. (2015). Strategies to build trust and recruit African American and Latino Community Residents for health research: A cohort study. CTS-Clinical and Translational Science,8(5), 412–420. https://doi.org/10.1111/cts.12273 Sanz-Menendez, L., & Cruz-Castro, L. (2019). The credibility of scientific communication sources regarding climate change: A population-based survey experiment. Public Understanding of Science,28(5), 534–553. https://doi.org/10. 1177/0963662519840946 Sarathchandra, D., & Haltinner, K. (2021). A survey instrument to measure skeptics’ (Dis)trust in climate science. Climate,9(2), 1–11. https://doi.org/10.3390/cli9020018 Sarathchandra, D., Navin, M. C., Largent, M. A., & McCright, A. M. (2018). A survey instrument for measuring vaccine acceptance. Preventive Medicine,109, 1–7. https://doi.org/ 10.1016/j.ypmed.2018.01.006 Scheufele, D. A. (2014). Science communication as political communication. Proceedings of the National Academy of Sciences of the United States of America,111 (Suppl 4), 13585–13592, https://doi.org/10.1073/pnas.1317516111 Scheufele, D. A. (2022). Thirty years of science–society interfaces: What’s next? Public Understanding of Science,31(3), 297–304. https://doi.org/10.1177/09636625221075947 Schnepf, J., Lux, A., Jin, Z., & Formanowicz, M. (2021). Left out-feelings of social exclusion incite individuals with high conspiracy mentality to reject complex scientific messages. Journal of Language and Social Psychology,40(5–6 Suppl), 627–652. https://doi.org/10.1177/0261927X211044789 Shahani, R., Chu, J., Rufai, O. H., Zawar, A., Muhideen, S., Dilawar, S., & Amosun, T. S. (2022). Understanding the role of psychosocial factors in Pakistani parents’ hesitancy to vaccinate their kids: The mediating role of knowledge and mistrust of science about the COVID-19 vaccine. Vaccines,10(8), 1260. https://doi.org/10.3390/vaccines10081260 Sibley, C. G., Greaves, L. M., Satherley, N., Wilson, M. S., Overall, N. C., Lee, C. H. J., Milojev, P., Bulbulia, J., Osborne, D., Milfont, T. L., Houkamau, C. A., Duck, I. M., Vickers-Jones, R., & Barlow, F. K. (2020). Effects of the COVID-19 pandemic and nationwide lockdown on trust, attitudes toward government, and well-being. American Psychologist,75(5), 618–630. https://doi.org/10.1037/ amp0000662 Slater, M. H., Scholfield, E. R., & Moore, J. C. (2021). Reporting on science as an ongoing process (or not). Frontiers in Communication,5. https://doi.org/10.3389/fcomm.2020. 535474 Smith, D. V. (2022). The problem of trust without intimacy: Education for handling expert knowledge in a neoliberal marketplace. Science & Education,31(6), 1449–1474. Solomon, M. (2021). Trust: The need for public understanding of how science works. Hastings Center Report,51(1 Suppl), S36–S39. https://doi.org/10.1002/hast.1227 Song, H, Markowitz, D. M., & Taylor, S. H. (2022). Trusting on the shoulders of open giants? Open science increases trust in science for the public and academics, Journal of Communication,72(4), 497–510. https://doi.org/10.1093/joc/jqac017 Stasiuk, K., Polak, M., Dolinski, D., & Maciuszek, J. (2021). The credibility of health information sources as predictors of attitudes toward vaccination—The results from a longitudinal study in poland. Vaccines,9(8), 933. https://doi.org/10. 3390/vaccines9080933 Steijaert, M. J., Schaap, G., & Riet, J. V. (2021). Two-sided science: Communicating scientific uncertainty increases trust in scientists and donation intention by decreasing attribution of communicator bias. Communications,46(2), 297–316. https://doi.org/10.1515/commun-2019-0123 Sulik, J., Deroy, O., Dezecache, G., Newson, M., Zhao, Y., El Zein, M., & Tuncxgencx, B. (2021). Facing the pandemic with trust in science. Humanities and Social Sciences Communications,8, 301. https://doi.org/10.1057/s41599-021-00982-9 Sztompka, P. (2007). Trust in science Robert K. Merton’s inspirations. Journal of Classical Sociology,7(2), 211–220. https://doi.org/10.1177/1468795X07078038 Thornton, T., & Leahy, J. (2012). Trust in citizen science research: A case study of the groundwater education through Water Evaluation & Testing Program, Journal of the American Water Resources Association,48(5), 1032–1040. https:// doi.org/10.1111/j.1752-1688.2012.00670.x Tonkovic ´, M., Dumanc ˇic ´, F., Jelic ´,M.,&C ˇorkalo Birus ˇki, D. (2021). Who believes in COVID-19 conspiracy theories in Croatia? Prevalence and predictors of conspiracy beliefs. Frontiers in Psychology,12. https://doi.org/10.3389/fpsyg. 2021.643568 van Stekelenburg, A., Schaap, G., Veling, H., & Buijzen, M. (2021). Investigating and improving the accuracy of US citizens’ beliefs about the COVID-19 pandemic: Longitudinal survey study. Journal of Medical Internet Research,23(1), e24069. https://doi.org/10.2196/24069 Varda, C., Iordanou, K., Antoniou, J., Barrios, M. M. Z., Yalaz, E., Gurzawska, A., Sz€ udi, G., Bartar, P., & Ha ¨berlein, L. (2025). The Role of stewards of trust in facilitating trust in Scsence: A Multistakeholder View. Journal of Academic Ethics.23, 463–483. https://doi.org/10.1007/s10805024-09583-y Viswanath, K., Bekalu, M., Dhawan, D., Pinnamaneni, R., Lang, J., & McLoud, R. (2021). Individual and social determinants of COVID-19 vaccine uptake. BMC Public Health, 21(1), 818. https://doi.org/10.1186/s12889-021-10862-1 Vranic, A., Hromatko, I., & Tonkovic ´, M. (2022). ‘‘I did my own research’’: Overconfidence, (dis)trust in science, and 22 SAGE Open endorsement of conspiracy theories. Frontiers in Psychology, 13, 931865. https://doi.org/10.3389/fpsyg.2022.931865 Walther, J., PytlikZillig, L., Detweiler, C., & Houston, A. (2019). How people make sense of drones used for atmospheric science (and other purposes): Hopes, concerns, and recommendations. Journal of Unmanned Vehicle Systems, 7(3), 219–234. https://doi.org/10.1139/juvs-2019-0003 Weingart, P. (2022). Trust or attention? Medialization of science revisited. Public Understanding of Science,31(3 Suppl), 288–296. https://doi.org/10.1177/09636625211070888 Whyte, K. P., & Crease, R. P. (2010). Trust, expertise, and the philosophy of science. Synthese,177(3), 411–425. Wiedemann, P. M., Thalmann, A. T., Grutsch, M. A., & Sch€ utz, H. (2006). The impacts of precautionary measures and the disclosure of scientific uncertainty on EMF risk perception and trust. Journal of Risk Research,9(4), 361–372. https://doi.org/10.1080/13669870600802111 Wingen, T., Berkessel, J. B., & Englich, B. (2020). No replication, no trust? How low replicability influences trust in psychology. Social Psychological and Personality Science, 11(4), 454–463. https://doi.org/10.1177/1948550619877412 Winter, T., Riordan, B. C., Scarf, D., & Jose, P. E. (2022). Conspiracy beliefs and distrust of science predicts reluctance of vaccine uptake of politically right-wing citizens. Vaccine, 40(12), 1896–1903. https://doi.org/10.1016/j.vaccine.2022.01. 039 Wintterlin, F., Hendriks, F., Mede, N. G., Bromme, R., Metag, J., & Scha ¨fer, M. S. (2021). Predicting public trust in science: The role of basic orientations toward science, perceived trustworthiness of scientists, and experiences with science. Frontiers in Communication,6. https://doi.org/10. 3389/fcomm.2021.822757 Zapp, M. (2022). The legitimacy of science and the populist backlash: Cross-national and longitudinal trends and determinants of attitudes toward science. Public Understanding of Science, 31(7), 885–902. https://doi.org/10.1177/09636625221093897 Ziman, J. (2002). The continuing need for disinterested research. Science and Engineering Ethics,8, 397–399. Kabakcxi et al. 23