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This article evaluated the effectiveness of using generative AI to simplify science communication and enhance the public's understanding of science. By comparing lay summaries of journal articles from PNAS, yoked to those generated by AI, this work first assessed linguistic simplicity differences across such summaries and public perceptions in follow-up experiments. Specifically, study 1a analyzed simplicity features of PNAS abstracts (scientific summaries) and significance statements (lay summaries), observing that lay summaries were indeed linguistically simpler, but effect size differences were small. Study 1b used a large language model, GPT-4, to create significance statements based on paper abstracts and this more than doubled the average effect size without fine-tuning. Study 2 experimentally demonstrated that simply-written generative pre-trained transformer (GPT) summaries facilitated more favorable perceptions of scientists (they were perceived as more credible and trustworthy, but less intelligent) than more complexly written human PNAS summaries. Crucially, study 3 experimentally demonstrated that participants comprehended scientific writing better after reading simple GPT summaries compared to complex PNAS summaries. In their own words, participants also summarized scientific papers in a more detailed and concrete manner after reading GPT summaries compared to PNAS summaries of the same article. AI has the potential to engage scientific communities and the public via a simple language heuristic, advocating for its integration into scientific dissemination for a more informed society.

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We discuss a relatively new meta-scientific research design: many-analyst studies that attempt to assess the replicability and credibility of research based on large-scale observational data. In these studies, a large number of analysts try to answer the same research question using the same data. The key idea is the greater the variation in results, the greater the uncertainty in answering the research question and, accordingly, the lower the credibility of any individual research finding. Compared to individual replications, the large crowd of analysts allows for a more systematic investigation of uncertainty and its sources. However, many-analyst studies are also resource-intensive, and there are some doubts about their potential to provide credible assessments. We identify three issues that any many-analyst study must address: 1) identifying the source of variation in the results; 2) providing an incentive structure similar to that of standard research; and 3) conducting a proper meta-analysis of the results. We argue that some recent many-analyst studies have failed to address these issues satisfactorily and have therefore provided an overly pessimistic assessment of the credibility of science. We also provide some concrete guidance on how future many-analyst studies could provide a more constructive assessment.

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IMF interventions are often associated with rising political discontent in countries where the Fund intervenes. Studies examining this relationship, however, face the challenge of disentangling the impact of the IMF from the impact of the crisis that triggered the intervention. To address this challenge, we conduct survey experiments in Greece, Ireland, Portugal, and Spain and directly assess how voters evaluate the costs and benefits of an IMF intervention. We find that voters believe that the crisis will more likely be solved when the IMF intervenes, but they are also critical of the corresponding loss of national sovereignty. Because the former consideration, on average, dominates their assessment, IMF interventions increase the support of voters for unpopular economic policies. Nonetheless, cross-country differences suggest that continued public support for intervention hinges on the IMF's ability to deliver on its promise to help resolve the crisis.

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Computational models of patients and medical devices can be combined to perform an in silico clinical trial (ISCT) to investigate questions related to device safety and/or effectiveness across the total product life cycle. ISCTs can potentially accelerate product development by more quickly informing device design and testing or they could be used to refine, reduce, or in some cases to completely replace human subjects in a clinical trial. There are numerous potential benefits of ISCTs. An important caveat, however, is that an ISCT is a virtual representation of the real world that has to be shown to be credible before being relied upon to make decisions that have the potential to cause patient harm. There are many challenges to establishing ISCT credibility. ISCTs can integrate many different submodels that potentially use different modeling types (e.g., physics-based, data-driven, rule-based) that necessitate different strategies and approaches for generating credibility evidence. ISCT submodels can include those for the medical device, the patient, the interaction of the device and patient, generating virtual patients, clinical decision making and simulating an intervention (e.g., device implantation), and translating acute physics-based simulation outputs to health-related clinical outcomes (e.g., device safety and/or effectiveness endpoints). Establishing the credibility of each ISCT submodel is challenging, but is nonetheless important because inaccurate output from a single submodel could potentially compromise the credibility of the entire ISCT. The objective of this study is to begin addressing some of these challenges and to identify general strategies for establishing ISCT credibility. Most notably, we propose a hierarchical approach for assessing the credibility of an ISCT that involves systematically gathering credibility evidence for each ISCT submodel in isolation before demonstrating credibility of the full ISCT. Also, following FDA Guidance for assessing computational model credibility, we provide suggestions for ways to clearly describe each of the ISCT submodels and the full ISCT, discuss considerations for performing an ISCT model risk assessment, identify common challenges to demonstrating ISCT credibility, and present strategies for addressing these challenges using our proposed hierarchical approach. Finally, in the Appendix we illustrate the many concepts described here using a hypothetical ISCT example.

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This systematic review aims to report on the use of Statement Validity Analysis (SVA) with minors involved in criminal justice proceedings. We conducted a literature search of six bibliographic databases up to March 2024. Additional searches were performed using citation tracing strategies. Nineteen studies published between 1991 and 2023 were retained. Most were published between 1991 and 2000, mainly in the USA. A scientific gap was observed for 10 years before studies resumed between 2011 and 2022. These 19 studies involved 2931 children; most were girls (n = 2080; 71%). The mean age was 9.4 years (SD = 2.40; min = 2; max = 17.5). Most studies did not mention the nature of the relationship between the child and the alleged perpetrator of sexual violence, three studies involved intra-family violence and six studies involved victims of intra- and extra-family violence. Nearly 75% of the interviewers were trained with SVA methods. Most were mental health professionals (52.6%) or police officers (15.8%). No study used the SVA as a whole, 10 studies used 19 criteria of the Criteria-Based Content Analysis (CBCA), and no study used the Validity Check List (VCL). Most studies performed SVA on interview transcripts (n = 8), and two studies performed their analysis on both verbatims and video. The conclusion of our literature review highlights the methodological weaknesses of these studies and encourages more research about the use of SVA in the judicial field to reduce the risk of misleading the judiciary.

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INTRODUCTION: The assessment of online health-related information presents a significant challenge for today's youth. Using the Processing of Commercial Media Content (PCMC) model, we investigated the impact of advertising on the perceived credibility of informational content concerning fitness (in boys) and dietary supplements (in girls). METHODS: In a survey-based preregistered experiment, 681 Czech adolescents (aged 13-18, 52% girls) were randomly assigned to three groups and exposed to websites with a banner ad, a native ad, or simple informational text without an ad. RESULTS: The presence of ads on websites diminishes the perceived credibility of informational content. While we did not observe the difference between banner and native advertising, we found one gender-specific difference. Specifically, boys perceive informational content linked with native ads as more credible compared to girls. Additionally, no difference was found between younger and older adolescents. Adolescents demonstrated success in identifying both types of advertisements, irrespective of their age. CONCLUSIONS: The findings are discussed in light of individual differences and various approaches to processing online content. It appears that adolescents are accustomed to native advertising, which seamlessly integrates with traditional banner ads. Moreover, it is plausible that boys assess advertising texts more heuristically and less systematically than girls. Contrary to PCMC expectations, even younger adolescents seem to possess sufficient skills to identify the advertisements.

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Medicine regulators need to judge whether a drug's favorable effects outweigh its unfavorable effects based on a dossier submitted by an applicant, such as a pharmaceutical company. Because scientific knowledge is inherently uncertain, regulators also need to judge the credibility of these effects by identifying and evaluating uncertainties. We performed an ethnographic study of assessment procedures at the Dutch Medicines Evaluation Board (MEB) and describe how regulators evaluate the credibility of an applicant's claims about the benefits and risks of a drug in practice. Our analysis shows that regulators use an investigative approach, which illustrates the effort required to identify uncertainties. Moreover, we show that regulators' expectations about the presentation, the design, and the results of studies can shape how they perceive a medicine's dossier. We highlight the importance of regulatory experience and expertise in the identification and evaluation of uncertainties. In light of our observations, we provide two recommendations to reduce avoidable uncertainty: less reliance on evidence generated by the applicant; and better communication about, and enforcement of, regulatory frameworks toward drug developers.

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Predictions and estimates are sometimes qualified as certain. This epistemic marker occupies a privileged position at the top of scales of verbal probability expressions, reflecting probabilities close to 1. But such statements have rarely been compared to plain, unqualified statements in which certainty is not mentioned. We examined in nine studies (N = 2784) whether statements explicitly claimed to be certain are perceived as (1) more (or less) credible, (2) more (or less) precise, and (3) more (or less) strongly based upon evidence, compared to plain, unmarked declarative statements. We find, in apparent contrast with assumptions made by the standard scales, that "certain" are often judged to be less trustworthy, less reliable, and held with lower confidence than unmarked statements. Plain, declarative statements are further assumed to be more precise, while certainty implies that more extreme outcomes are possible. When it is certain that Henry made four errors, it is clear he did not commit less than four, but he might have committed five errors or more. Thus certainty can indicate lower bounds of an interval whose upper bounds are not defined, and certainty statements are consequently more ambiguous than estimates that do not mention certainty. At least-interpretations of certainty affect the interpretation of options in risky choice problems, where "200 lives will be saved" was deemed by a majority to mean exactly 200, while "it is certain that 200 will be saved", could mean 200-600 lives. We also find that credibility is affected by type of certainty, with impersonal certainty ("it is certain") perceived to be more accurate and persuasive than personal certainty ("I am certain"), especially in predictions of future events. Moreover, mentions of certainty can reveal that that a speaker's estimate is based on subjective judgments and guesswork rather than upon objective evidence. These findings have implications for communication. Estimates can appear more consensual when claims of certainty are omitted. To convey certainty it may be better not to mention that one is certain.

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BACKGROUND: Recruiting participants for clinical trials poses challenges. Major barriers to participation include psychological factors (eg, fear and mistrust) and logistical constraints (eg, transportation, cost, and scheduling). The strategic design of clinical trial messaging can help overcome these barriers. While strategic communication can be done through various channels (eg, recruitment advertisements), health care providers on the internet have been found to be key sources for communicating clinical trial information to US adults in the social media era. OBJECTIVE: This study aims to examine how communication source (ie, medical doctors and peers) and message framing of TikTok videos (ie, psychological and logistical framing) influence clinical trial-related attitudes, perceptions, and sign-up behaviors under the guidance of the integrated behavioral model. METHODS: This study used a 2 (source: doctor vs peer) × 2 (framing: psychological vs logistical) between-participant factorial design web-based experiment targeting adults in the United States who had never participated in clinical trials (ie, newcomers). A Qualtrics panel was used to recruit and compensate the study respondents (n=561). Participants viewed short-form videos with doctors or peers, using psychological or logistical framing. The main outcome measures included perceived source credibility, self-efficacy, attitude toward clinical trial participation, behavioral intention, and sign-up behavior. Structural equation modeling was used to analyze the direct and indirect effects of message factors on the outcome variables. Source (doctor=1; peer=0) and framing (psychological=1; logistical=0) were dummy-coded. RESULTS: Doctor-featured messages led to greater perceived source credibility (ß=.31, P<.001), leading to greater self-efficacy (95% CI 0.13-0.30), which in turn enhanced behavioral intention (95% CI 0.12-0.29) and clinical trial sign-up behavior (95% CI 0.02-0.04). Logistical barrier-framed messages led to greater self-efficacy (ß=-.09, P=.02), resulting in higher intention to participate in clinical trials (95% CI -0.38 to -0.03) and improved sign-up behavior (95% CI -0.06 to -0.004). Logistical barrier-framed messages were also directly associated with an increased likelihood of signing up for a clinical trial (ß=-.08, P=.03). The model accounted for 21% of the variance in clinical trial sign-up behavior. Attitude did not significantly affect behavioral intention in this study (ß=.08, P=.14), and psychological and logistical barrier-framed messages did not significantly differ in attitudes toward clinical trial participation (ß=-.04, P=.09). CONCLUSIONS: These findings advance our understanding of how people process popular message characteristics in short-form videos and lend practical guidance for communicators. We encourage medical professionals to consider short-form video sites (eg, TikTok and Instagram Reels) as effective tools for discussing clinical trials and participation opportunities. Specifically, featuring doctors discussing efforts to reduce logistical barriers is recommended. Our measuring of actual behavior as an outcome is a rare and noteworthy contribution to this research.

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Expert witness credentials and gender have independently been shown to influence jurors' perceptions of expert witness credibility and legal decision-making. This study examined how manipulations of expert witness gender (Male/Female) and profession (Consultant Clinical Psychologist/Consultant Psychiatrist) together affected mock jurors' perceptions of expert witness credibility, judgements, and decision-making. Mock jurors (N = 182; 80.9 % were White) were recruited from England and Wales and were randomly assigned to watch a video-recorded mock expert witness testimony. Participants rated the expert witness using the Witness Credibility Scale and reported the likelihood of assigning the defendant to a guilty verdict. Results showed significant interaction effects of expert witness gender and profession on jurors' perceptions of their likeability, trustworthiness, knowledge, and total credibility. Male psychiatrists, followed by female clinical psychologists, received the highest scores in most credibility variables. Varied main effects of expert witness gender and profession on credibility were also found. Overall, jurors' ratings of expert witness credibility, when controlled by the expert's gender and profession, predicted jurors' determination of guilt. This study provides evidence of a potential interaction effect between profession and gender in expert witness credibility and supports existing research linking credibility with ultimate decision-making. More research is needed to understand jurors' unconscious biases and cognitive processes in making legal decisions.

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BACKGROUND: Green space is an important part of the human living environment, with many epidemiological studies estimating its impact on human health. However, no study has quantitatively assessed the credibility of the existing evidence, impeding their translations into policy decisions and hindering researchers from identifying new research gaps. This overview aims to evaluate and rank such evidence credibility. METHODS: Following the PRISMA guideline, we systematically searched PubMed, Web of Science, and Embase databases for systematic reviews with meta-analyses concerning green spaces and health outcomes published up to January 15, 2024. We categorized the credibility of meta-analytical evidence from interventional studies into four levels (i.e., high, moderate, low, and very low) using the Grading of Recommendation, Assessment, Development and Evaluations framework, based on five domains including risk of bias, inconsistency, indirectness, imprecision, and publication bias. Further, we recalculated all the meta-analyses from observational studies and classified evidence into five levels (i.e., convincing, highly suggestive, suggestive, weak, and non-significant) by considering stringent thresholds for P-values, sample size, robustness, heterogeneity, and testing for biases. FINDINGS: In total, 154 meta-analysed associations (interventional = 44, observational = 110) between green spaces and health outcomes were graded. Among meta-analyses from interventional studies, zero, four (wellbeing, systolic blood pressure, negative affect, and positive affect), 20, and 20 associations between green spaces and health outcomes were graded as high, moderate, low, and very low credibility evidence, respectively. Among meta-analyses from observational studies, one (cardiovascular disease mortality), four (prevalence/incidence of diabetes mellitus, preterm birth, and small for gestational age infant, and all-cause mortality), 12, 22, and 71 associations were categorized as convincing, highly suggestive, suggestive, weak, and non-significant evidence, respectively. INTERPRETATION: The current evidence largely confirms beneficial associations between green spaces and human health. However, only a small subset of these associations can be deemed to have a high or convincing credibility. Hence, future better designed primary studies and meta-analyses are still needed to provide higher quality evidence for informing health promotion strategies. FUNDING: The National Natural Science Foundation of China of China; the Guangzhou Science and Technology Program; the Guangdong Medical Science and Technology Research Fund; the Research Grant Council of the Hong Kong SAR; and Sino-German mobility program.

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The complex-enhanced hierarchical relationship among multiple stakeholders in the water-environment-agriculture interactive system has been overlooked. This study develops a leader-follower-enhanced framework (named as FCMLP) that integrates variable-weight combination prediction model, multi-level programming, and fuzzy credibility constrained programming, which can effectively address the above problems under uncertainties. Five water ecological carrying capacity (WECC) statuses are treated as a critical constraint into the modeling framework to improve the accuracy of decision-making. An interactive fuzzy satisfaction algorithm is advanced for solving this multi-level problem, in which COD discharge minimization, economic benefits maximization, and grain yield maximization are taken as the upper-, middle-, and lower-level goals, respectively. The framework is applied to plan the cross-regional water-environment-agriculture interactive system in the Beijing-Tianjin-Hebei and Yangtze River Economic Belt. Solutions reveal that increased WECC status and credibility level would decrease 1.40%-1.74%, 0.71%-9.61%, and 1.63%-2.26% of water resources allocation, COD emissions, and economic benefits, respectively. Crop area and grain yield would dramatically decline by 4.13%-4.46% and 4.03%-4.67% when a credibility level increases from 0.8 to 1, respectively. The overall satisfactory degree would range from 0.58 to 0.70, which illustrates interactive decision-making process of multiple stakeholders. Significant differences can be observed in the optimized schemes of water resources allocation and environmental-economic-agricultural performances among various models. The amounts of allocated water resources, pollutant discharge, and economic output from the FCMLP model would be respectively 11.30%-13.45%, 14.90%-15.21%, and 73.12%-73.48% higher than those from the environment- and agriculture-oriented schemes, yet 13.81%, 32.05%, and 15.29% lower than those from the economy-oriented scheme. Some water adaptability countermeasures are given for ensuring the scientific operation of the South-to-North Water Transfer Project and alleviating conflicts between water source and receiving areas. Further exploration of the optimization scheme of water-environment-energy-agriculture system driven by climate change is still required for guaranteeing the dynamic balance of regional resources.

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High-intensity interval training (HIIT) has been shown to benefit stroke patients when implemented three months post-stroke. This study examined HIIT's feasibility and clinical effectiveness in the early post-stroke stage in Benin. This was a prospective interventional study comprising an HIIT programme executed on a recumbent bike, three times/week, 20-30 min/session for 6 weeks, added to a conventional physiotherapy. The primary outcomes were feasibility, credibility and expectancy assessed with credibility and expectancy questionnaire. A maximal exercise test, 6-min walking test (6MWT), 10-m walking test (10mWT), Berg balance scale (BBS) and five repetitions sit-to-stand test (5 R-STS) were performed before and after the training programme. Ten outpatients, with a median age [P25-P75]: 63.5[56.7-71.2] years; time since stroke: 15.0[9.7-21.0] days, started and completed all training sessions without serious adverse events. High scores were observed on the Credibility subscale at admission (27.0[25.7-27.0]), which remained so after intervention (26.5[25.7-27.0]). Expectancy subscale scores were high at admission (25.5[24.0-27.0]) and post-training (25.5[24.5-27.0]). Peak workload (p < 0.001), BBS (p < 0.001), 6MWT (p < 0.001), 10mWT (p < 0.001) and 5 R-STS (p = 0.004) were all improved. HIIT is feasible and safe in the early subacute post-stroke stage and is perceived by patients as highly credible, meeting their expectations of recovery.

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Over the last years computer modelling and simulation has emerged as an effective tool to support the total product life cycle of cardiovascular devices, particularly in the device preclinical evaluation and post-market assessment. Computational modelling is particularly relevant for heart valve prostheses, which require an extensive assessment of their hydrodynamic performance and of risks of hemolysis and thromboembolic complications associated with mechanically-induced blood damage. These biomechanical aspects are typically evaluated through a fluid-structure interaction (FSI) approach, which enables valve fluid dynamics evaluation accounting for leaflets movement. In this context, the present narrative review focuses on the computational modelling of bileaflet mechanical aortic valves through FSI approach, aiming to foster and guide the use of simulations in device total product life cycle. The state of the art of FSI simulation of heart valve prostheses is reviewed to highlight the variety of modelling strategies adopted in the literature. Furthermore, the integration of FSI simulations in the total product life cycle of bileaflet aortic valves is discussed, with particular emphasis on the role of simulations in complementing and potentially replacing the experimental tests suggested by international standards. Simulations credibility assessment is also discussed in the light of recently published guidelines, thus paving the way for a broader inclusion of in silico evidence in regulatory submissions. The present narrative review highlights that FSI simulations can be successfully framed within the total product life cycle of bileaflet mechanical aortic valves, emphasizing that credible in silico models evaluating the performance of implantable devices can (at least) partially replace preclinical in vitro experimentation and support post-market biomechanical evaluation, leading to a reduction in both time and cost required for device development.

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The high value placed on forensic information in the criminal justice process is demonstrated by the fallout resulting when questions are raised as to the validity of methods used, deficiencies in the understanding of the limitations of results, or uncertainties around the professional expertise or ethical practices of the provider of the information. To effectively act as the "speaker" for the scientific evidence in court, forensic science needs to have credibility. The workshop "Rethinking scientific communication in courts" held at the Australian National University College of Law in November 2023 explored the subject of science communication in the legal context through the lens of philosophy, law, forensic service provision and meta-science, demonstrating the unique challenges placed on the field of forensic science as a scientific profession confined and defined within a non-scientific system. Stemming from the discussions at the workshop, this paper examines the notion of credibility in science, how forensic science aligns with the hallmarks of a credible scientific community and the influence this has on our understandings of scientific communication in courts.

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In the era of social media, the influence of food exploration bloggers is increasingly apparent. Sharing their culinary experiences stimulates the audience's interest in visiting and consuming food destinations. This paper seeks to understand how the characteristics of food exploration bloggers on the Douyin platform influence audience perceptions of food and locations and how these perceptions may relate to visiting intentions, using the stimulus-organism-response (SOR) model. A cross-sectional online survey analyzed responses from 437 individuals interested in food exploration videos on Douyin. The results indicate that source credibility is significantly associated with the stimulation of taste desires and the formation of taste awareness. The audience's taste desire and taste awareness are positively linked to the intention to visit. This study contributes to the expansion of the SOR model's application in digital media, underscoring the substantial role of social media in influencing audience consumption intentions. It highlights that as an effective communication tool, social media can significantly impact users' behavioral responses and consumption decisions.

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We investigated whether adding hypnosis to CBT (CBTH) improved treatment outcomes for MDD with a two-armed, parallel-treated, randomized-controlled trial using anonymous self-report and clinician-blinded assessments. Expectancy, credibility, and attitude to hypnosis were also examined. Participants (n = 66) were randomly allocated to 10-weekly sessions of group-based CBT or CBTH. LMM analyses of ITT and Completer data at post-treatment, six-month and 12-month follow-up showed that both treatments were probably efficacious but we did not find significant differences between them. Analyses of remission and response to treatment data revealed that the CBTH Completer group significantly outperformed CBT at 12-month follow-up (p = .011). CBTH also displayed significantly higher associations between credibility, expectancy and mood outcomes up to 12-month follow-up (all p < .05 or better), while attitude to hypnosis showed one significant association (r = -0.57, p < .05). These results suggest that hypnosis shows promise as an adjunct in the treatment of MDD but a larger sample size is required to fully test its merits.

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Physiological closed-loop controlled (PCLC) medical devices, such as those designed for blood pressure regulation, can be tested for safety and efficacy in real-world clinical settings. However, relying solely on limited animal and clinical studies may not capture the diverse range of physiological conditions. Credible mathematical models can complement these studies by allowing the testing of the device against simulated patient scenarios. This research involves the development and validation of a low-order lumped-parameter mathematical model of the cardiovascular system's response to fluid perturbation. The model takes rates of hemorrhage and fluid infusion as inputs and provides hematocrit and blood volume, heart rate, stroke volume, cardiac output and mean arterial blood pressure as outputs. The model was calibrated using data from 27 sheep subjects, and its predictive capability was evaluated through a leave-one-out cross-validation procedure, followed by independent validation using 12 swine subjects. Our findings showed small model calibration error against the training dataset, with the normalized root-mean-square error (NRMSE) less than 10% across all variables. The mathematical model and virtual patient cohort generation tool demonstrated a high level of predictive capability and successfully generated a sufficient number of subjects that closely resembled the test dataset. The average NRMSE for the best virtual subject, across two distinct samples of virtual subjects, was below 12.7% and 11.9% for the leave-one-out cross-validation and independent validation dataset. These findings suggest that the model and virtual cohort generator are suitable for simulating patient populations under fluid perturbation, indicating their potential value in PCLC medical device evaluation.

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Introduction: To enhance the precision of evaluating the impact of urban environments on resident health, this study introduces a novel fuzzy intelligent computing model designed to address health risk concerns using multi-media environmental monitoring data. Methods: Three cities were selected for the study: Beijing (B City), Kunming (K City), and Wuxi (W City), representing high, low, and moderate pollution levels, respectively. The study employs a Fuzzy Inference System (FIS) as the chosen fuzzy intelligent computing model, synthesizing multi-media environmental monitoring data for the purpose of urban health risk assessment. Results: (1) The model reliably estimates health risks across diverse cities and environmental conditions. (2) There is a positive correlation between PM2.5 concentrations and health risks, though the impact of noise levels varies by city. In cities B, K, and W, the respective correlation coefficients are 0.65, 0.55, and 0.7. (3) The Root Mean Square Error (RMSE) values for cities B, K, and W, are 0.0132, 0.0125, and 0.0118, respectively, indicating that the model has high accuracy. The R2 values for the three cities are 0.8963, 0.9127, and 0.9254, respectively, demonstrating the model's high explanatory power. The residual values for the three cities are 0.0087, 0.0075, and 0.0069, respectively, indicating small residuals and demonstrating robustness and adaptability. (4) The model's p-values for the Indoor Air Quality Index (IAQI), Thermal Comfort Index (TCI), and Noise Pollution Index (NPI) all satisfy p < 0.05 for the three cities, affirming the model's credibility in estimating health risks under varied urban environments. Discussion: These results showcase the model's ability to adapt to diverse geographical conditions and aid in the accurate assessment of existing risks in urban settings. This study significantly advances environmental health risk assessment by integrating multidimensional data, enhancing the formulation of comprehensive environmental protection and health management strategies, and providing scientific support for sustainable urban planning.

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Introduction: Official endorsement, distinct from celebrity, expertise, and peer endorsement, introduces a new paradigm where local government officials use online platforms, particularly live streaming, to promote local products and brands. Methods: This study examines the influence of official endorsement on consumer responses using the source credibility and source attractiveness models. We developed a framework that considers official credibility and attractiveness attributes as antecedents, and consumer perceived security and enjoyment as mediators, affecting purchase intention and local brand awareness. The study also incorporates variables such as consumer region and power distance belief. Results: Data from 594 responses obtained through an online survey were analyzed using structural equation modeling. The results indicate that official credibility attributes (expertise, trustworthiness, government credibility) enhances consumer perceived security, while official attractiveness attributes (physical attractiveness, interaction friendliness, and similarity with consumers) increases consumer enjoyment. Both perceived security and enjoyment positively influence purchase intention and local brand awareness. These relationships are partially moderated by consumer region and power distance belief. Discussion: This research pioneers the study of official endorsements, expanding the endorsement literature. It also provides practical insights for marketing professionals and government officials on leveraging official endorsements to enhance the value of local products and brands..