Credibility Ratings Research Articles

Safety instrumented system design with credible failure rates: The key to achieving plant safety

AbstractThe influence of the dangerous undetected failure rate, ƛdu, on safety instrumented system (SIS) design has evolved over last 30 years. Now, ƛdu has a significant impact on the SIS design. Using unrealistically low ƛdu can lead to an unsafe SIS design and thus compromise the plant safety. This paper explains some of the reasons why some published ƛdu could be unrealistically low. To address this challenge, ISA TR84 committee Working Group 02 has undertaken an effort to develop a failure rate credibility assessment tool. In this tool, the user will answer a series of questions, and the weighted score of answers will provide a credibility rank for the published device failure rate. This paper will explain the approach of this tool, its target users, and its benefits.

The credibility of subgroup analyses reported in stroke trials is low: A systematic review.

Subgroup analyses are widely used to evaluate the heterogeneity of treatment effects in randomized clinical trials. However, there is a limited investigation of the quality of prespecified and reported subgroup analyses in stroke trials. This study evaluated the credibility of subgroup analyses in stroke trials. We searched Medline/PubMed, Embase, the Cochrane Central Register of Controlled Trials, and the Web of Science from inception to 24 March 2021. Three reviewers screened, extracted, and analyzed the data from the publications. Primary publications of stroke trials that reported at least one subgroup effect and had published corresponding study protocols were included. The Instrument for Assessing the Credibility of Effect Modification Analyses (ICEMAN) was used to examine the quality of the subgroup effects reported, with each subgroup effect assigned a credibility rating ranging from very low to high. Subgroup effects with two or more "definitely no" responses received a low credibility rating. The risk of bias was assessed using the Cochrane Risk-of-Bias tool for randomized trials version 2. Seventy-four articles met the inclusion criteria and reported a combined total of 647 subgroup effects. The median sample size was 1264 (interquartile range (IQR): 380-3876), and the median number of subgroups prespecified in the protocol was 6 (IQR: 2-10). Sixty-one (82%) studies used the univariate test of interaction. Of the total 647 subgroup effects reported in these studies, 319 (49%) were reported in acute stroke trials, while 423 (65%) had low credibility. The quality of subgroup analysis reporting in stroke trials remains poor. More effort is needed to train trialists on the best methods for designing and performing subgroup analyses, and how to report the results. We prospectively registered the review with International Prospective Register for Systematic Reviews (registration number: CRD42020223133).

Effects of Informational Asymmetries on Job Seekers’ Ratings of Organizational Credibility

Recruiters need to develop successful recruitment strategies and techniques to attract new employees by examining the employment process from the job seeker’s point of view. This study aimed to examine the impact of additional information from an external source (Wall Street Journal) on the relationship between job previews used in recruitment and applicants' perceptions of corporate credibility. Results of an experimental study with 2 × 3 factorial design show that that while the presence of realistic job previews did not affect credibility ratings, additional information did moderate the relationship between job previews and perceived credibility. The findings suggest that providing consistent information in the job preview and external sources enhances perceived credibility. Practical implications and future research directions are discussed

A statistical approach for reducing misinformation propagation on twitter social media

Misinformation on Twitter has caused havoc all over the world, thus posing a prime cybersecurity concern. Hence, our research objective is to tackle the menace of infodemic by computing the credibility of Twitter users. Our proposed approach rates the Twitter users on a scale of credibility rating, obtained by analysing the pattern of growth rate statistics of the tweeting and following behaviour. Hence, our research provides two types of credibility computational frameworks that includes Twitter-user profile-centric activities and tweet-propagation features. Initially, we establish and justify the fact that there is a observable difference in the propagation pattern of rumored and non-rumored tweets by analysing the posts of 129,323 Twitter users. Later, the credibility score is devised based on tweet propagation pattern. It contains parameters that satisfies a statistical significance level of 99.99%. The second credibility score formula utilizes more profile centric features and almost all the parameters used for second formula satisfy a statistical significance level of 95%. Our research will significantly assist social media administrators to identify the rumor spreaders, thereby reducing the menace of misinformation.

A cost‐efficient and QoS‐aware adaptive placement of applications in fog computing

SummaryWith the rapid development of the Internet of Things (IoT), fog computing has emerged as a complementary solution to address the issues faced in cloud computing. However, it is a challenging issue to ensure both of the high Quality of Service (QoS) and low cost for different requests when dealing with computing resources. In this article, we propose a new approach on adaptive cost‐efficient and QoS‐aware application placement for fog computing called DATSS. Specifically, this approach consists of a QoS state driven strategy and a credibility rating mechanism. The algorithm divides the QoS into three different states by calculating the QoS violation rate and adaptively selects the best scheduling strategy. Then evaluates the stability of the node based on the task history, and prioritize the task on the node with a higher rating. Performance results show that the cost, delay and energy consumption of the proposed algorithm can be reduced by 20.9%, 15.7%, and 12.6% respectively compared with other algorithms at most. The proposed algorithm can effectively improve cost efficiency and stability under QoS constraints in fog computing environments.

Can Fighting Misinformation Have a Negative Spillover Effect? How Warnings for the Threat of Misinformation Can Decrease General News Credibility

ABSTRACT In the battle against misinformation, do negative spillover effects of communicative efforts intended to protect audiences from inaccurate information exist? Given the relatively limited prevalence of misinformation in people’s news diets, this study explores if the heightened salience of misinformation as a persistent societal threat can have an unintended spillover effect by decreasing the credibility of factually accurate news. Using an experimental design (N = 1305), we test whether credibility ratings of factually accurate news are subject to exposure to misinformation, corrective information, misinformation warnings, and news media literacy (NML) interventions relativizing the misinformation threat. Findings suggest that efforts like warning about the threat of misinformation can prime general distrust in authentic news, hinting toward a deception bias in the context of fear of misinformation being salient. Next, the successfulness of NML interventions is not straight forward if it comes to avoiding that the salience of misinformation distorts people’s creditability accuracy. We conclude that the threats of the misinformation order may not just be remedied by fighting false information, but also by reestablishing trust in legitimate news.

Undergraduate student perceptions of cognitive behavioral therapy, aerobic exercise, and their combination for depression

Objective Both aerobic exercise and Cognitive Behavioral Therapy (CBT) improve depression, but perceptions of their credibility and efficacy are underexplored. These perceptions can contribute to treatment seeking and outcome. A previous online sample ranging in age and education rated a combined treatment higher than individual components and underestimated their efficacy. The current study is a replication exclusively focused on college students. Participants Undergraduates (N = 260) participated during the 2021–2022 school year. Methods Students reported impressions of each treatment’s credibility, efficacy, difficulty, and recovery rate. Results Students viewed combined therapy as potentially better, but also more difficult, and underestimated recovery rates, replicating previous work. Their efficacy ratings significantly underestimated both meta-analytic estimates and the previous sample’s perceptions. Conclusions Consistent underestimation of treatment effectiveness suggests that realistic education could prove especially beneficial. Students might be more willing than the broader population to accept exercise as a treatment or adjunct for depression.

Examining the structure of credibility evaluation when sixth graders read online texts

AbstractBackgroundPrevious research indicates that students lack sufficient online credibility evaluation skills. However, the results are fragmented and difficult to compare as they are based on different types of measures and indicators. Consequently, there is no clear understanding of the structure of credibility evaluation.ObjectivesThe present study sought to establish the structure of credibility evaluation of online texts among 265 sixth graders.MethodsStudents' credibility evaluation skills were measured with a task in which they read four online texts, two more credible (a popular science text and a newspaper article) and two less credible (a layperson's blog text and a commercial text). Students read one text at a time and evaluated the author's expertise, the author's benevolence and the quality of the evidence before ranking the texts according to credibility. Four competing measurement models of students' credibility evaluations were assessed.ResultsThe model termed the Genre‐based Confirming‐Questioning Model reflected the structure of credibility evaluation best. The results suggest that credibility evaluation reflects the source texts and requires two latent skills: confirming the more credible texts and questioning the less credible texts. These latent skills of credibility evaluation were positively associated with students' abilities to rank the texts according to credibility.ImplicationsThe study revealed that the structure of credibility evaluation might be more complex than previously conceptualized. Consequently, students would benefit from activities that ask them to carefully analyse different credibility aspects of more and less credible texts, as well as the connections between these aspects.

Dressing the part: The influence of police attire on outcomes in a simulated traffic violation case

Consistently outlined in juror decision-making research is that seemingly irrelevant variables (e.g., the appearance of defendants or plaintiffs) can impact judicial proceedings. Although police officers frequently appear in courtrooms, limited literature exists that assesses the impact of officer attire in this setting. The current study exposed participants to a mock-trial transcript outlining a traffic violation case in which officer gender and attire were manipulated. Participants then rendered a verdict, before providing ratings of officer credibility and police legitimacy, using the Police Legitimacy Scale (PLS). The female officer was viewed as significantly more credible than the male officer and participants’ PLS scores predicted their verdicts. Although no attire differences were found, findings might have implications for uniform policies.

Hybrid Feature Selection Method for Predicting Alzheimer’s Disease Using Gene Expression Data

Gene expression (GE) classification is a research trend as it has been used to diagnose and prognosis many diseases. Employing machine learning (ML) in the prediction of many diseases based on GE data has been a flourishing research area. However, some diseases, like Alzheimer’s disease (AD), have not received considerable attention, probably owing to data scarcity obstacles. In this work, we shed light on the prediction of AD from GE data accurately using ML. Our approach consists of four phases: preprocessing, gene selection (GS), classification, and performance validation. In the preprocessing phase, gene columns are preprocessed identically. In the GS phase, a hybrid filtering method and embedded method are used. In the classification phase, three ML models are implemented using the bare minimum of the chosen genes obtained from the previous phase. The final phase is to validate the performance of these classifiers using different metrics. The crux of this article is to select the most informative genes from the hybrid method, and the best ML technique to predict AD using this minimal set of genes. Five different datasets are used to achieve our goal. We predict AD with impressive values for MultiLayer Perceptron (MLP) classifier which has the best performance metrics in four datasets, and the Support Vector Machine (SVM) achieves the highest performance values in only one dataset. We assessed the classifiers using seven metrics; and received impressive results, allowing for a credible performance rating. The metrics values we obtain in our study lie in the range [.97, .99] for the accuracy (Acc), [.97, .99] for F1-score, [.94, .98] for kappa index, [.97, .99] for area under curve (AUC), [.95, 1] for precision, [.98, .99] for sensitivity (recall), and [.98, 1] for specificity. With these results, the proposed approach outperforms recent interesting results. With these results, the proposed approach outperforms recent interesting results.

Management of the 4th of August explosion in an orthopedics department

Abstract Mass casualty incidents (MCI) are rare, large-scale events that result in heavy damage to people and infrastructure. These types of incidents result in a high influx of patients in local hospitals. In Beirut, this was witnessed on the 4th of August. A massive explosion took place in Lebanon’s capital city Beirut. Although Hotel-Dieu de France Hospital was damaged, it played a crucial role in the management of numerous injured, especially in the orthopedics department. Six months later, the hospital contacted all patients that had been hospitalized during that night and the following 2 days for musculoskeletal injuries. The contact was done for feedback purposes as the event was considered one of the largest non-nuclear explosions in international history. Accordingly, most of the patients that were contacted gave a credible and positive rating. There were few who had suggestions for management improvement. MCIs are rare, but it is crucial to be prepared to face any edging situation. Having effective communication and an organized plan in any risk management process are essential tools to foster for the well of the community and to scale down the losses of the locals in the area.

Fake news by any other name: phrases for false content and effects on public perceptions of U.S. news media

ABSTRACT The term ‘fake news’ aims to delegitimize news and is weaponized by political leaders and partisan media. Research has noted the negative impact of the phrase ‘fake news’ yet little work has investigated alternative discourse. We explore whether the phrase ‘fake news’ is distinct from alternative phrases such as ‘misinformation’ and ‘false news.’ Using two experiments, we compare effects of these phrases on evaluations of trust and credibility regarding U.S. news media. Results indicate that ‘fake news’ exerts disproportionate negative effects on perceptions of news and journalists, when controlling for political ideology, compared to ‘misinformation.’ Effects are pronounced when the phrase is used by a politician. Findings challenge research to address the communicative underpinnings of the fake news phenomenon rather than focus on “fake news” as a varietal of misinformation. Insights are discussed for news organizations seeking to distance themselves from the term while providing audiences with accurate information.

Examining the Influence of Algorithmic Message Personalization on Source Credibility and Reputation

Digital technologies such as AI (Artificial Intelligence) and big data analytics are altering public relations practices such as scanning social media and posting during crises. Crisis scholarship found these practices could potentially yield positive crisis outcomes such as increased reputational measures. However, research has not yet fully outlined the potential risks associated with using these tactics in crisis communication. Guided by situational crisis communication theory (SCCT), this study utilized a 2 (reputation repair strategy: Deny/Apology) x 2 (presence vs. absence of message personalization notification) factorial design experiment to determine how the utilization of algorithmic message personalization might influence reputational and source credibility evaluations during an athlete reputational crisis (ARC). Results revealed that reputation repair strategy selection indirectly influenced stakeholders’ reputation evaluations via source credibility. This relationship was moderated by a notification of personalization. Theoretical and practical insights elucidate how the increased usage of algorithmic-based message personalization influences crisis communication outcomes.

The impact of developmental language disorder in a defendant's description on mock jurors' perceptions and judgements.

While it has been posited that young people with language needs may be viewed more negatively (e.g., as more rude, less cooperative) than those without language needs, the impact of knowing about a person's language needs on others' perceptions has yet to experimentally tested. To examine whether the presence of a developmental language disorder (DLD) diagnosis in a defendant's information would affect mock juror ratings of guilt, sentence length, credibility and blameworthiness. A total of 143 jury eligible participants read a vignette of a non-violent crime. Half of the participants (N = 73) were told the defendant has a diagnosis of DLD, while half (N = 70) were not told. Preregistered analyses found that DLD information affected ratings of credibility and blameworthiness, though not judgements of guilt or sentence length. Unregistered content analyses were applied to the justifications participants gave for their ratings: these suggested that participants who did not have the DLD information judged the defendant more on his personality and attitude, and drew more links to his (perceived) background, while participants who received the DLD information condition made more reference to him having cognitive problems. Unlike in previous studies of the impact of autism information, information about a defendant's DLD did not affect mock jurors' likelihood of finding them guilty, or lead participants to give longer sentences. However, our findings suggest knowing a person has DLD does affect others' perceptions of credibility and blameworthiness. What is already known on the subject There is already evidence that some conditions that affect communication, specifically autism, also affect juror perceptions. Research also shows that knowing whether or not a defendant has autism influences how jurors rate defendants. However, autism is not the only condition that is relevant to juror perceptions, as we also know that a high rate of young offenders have language needs, and many have language profiles like DLD. What this paper adds to existing knowledge There is little research on how behaviours associated with DLD impact others' perceptions. This study reports the impact of knowing about a defendant's DLD on juror perceptions, investigating whether knowing about DLD improves judgements on guilt, sentencing lengths, credibility and culpability. Beyond the content of youth offending, this study suggests behaviours associated with DLD lead people to form more negative judgements about youth with DLD. This is important because there is still a lack of awareness of DLD both in- and outside the criminal justice system. What are the potential or actual clinical implications of this work? This study shows that knowing about a person's DLD has largely positive effects on others' perceptions of them. This implies that recognizing undetected language needs in young offenders, and supporting colleagues and members of the public to know what DLD is and how it affects people, is critical for youth with DLD to be judged fairly. This study will support the case for raising awareness of vulnerability within the youth justice population, and will assist in clinicians evidencing the need for our roles in justice settings.

Battling bias: can two implicit bias remedies reduce juror racial bias?

ABSTRACT Two studies examined the effectiveness of the Unconscious Bias Juror (UBJ) video and instructions at reducing racial bias in Black and White mock-jurors’ decisions, perceptions, and counterfactual endorsement in a murder (Study 1; N = 554) and battery (Study 2; N = 539) trial. Participants viewed the UBJ video or not, then read pretrial instructions (general or UBJ), a trial summary, and posttrial instructions (general or UBJ). In Study 1, juror race moderated the effect of defendant race on verdicts, culpability, and credibility. White, but not Black, jurors demonstrated greater leniency toward Black defendants for verdicts, culpability, and credibility. The UBJ video moderated the effect of defendant race on murder counterfactual endorsement. Only when the video was absent was jurors’ counterfactual endorsement higher for the White versus Black defendant, which mediated the effect of defendant race on White jurors’ verdicts. In Study 2, White jurors were more lenient regardless of defendant race. Instructions and juror race moderated the video’s effect on credibility ratings. The video only influenced Black jurors’ credibility ratings. In conclusion, the debiasing interventions were ineffective in reducing racial bias in jurors’ verdicts. However, they do impact aspects of juror attribution and may be effective with modification.

THE CREDIBILITY OF CONSUMER REVIEWS ON THREE E-COMMERCE IN INDONESIA: MIXED METHOD APPROACH

Online stores with more than 3000 reviews have made it difficult for consumers to find reviews that can be used as the main source of information to decide on a purchase. This research aims to investigate the credibility of reviews that consumers can be trusted. This research used mixed methods (quantitative and qualitative) through sequential explanation. In this quantitative study, 300 respondents were collected using a voluntary sampling technique, and 900 reviews from three e-commerce sites in Indonesia were selected purposely. The qualitative approach used in-depth interviews with three consumers and a selected seller using a purposive sampling technique. The data was processed by multiple linear regression and descriptive using SPSS 25.0 and Nvivo 12. Research results confirmed that the motivation to read reviews and consumer attitudes toward reviews significantly affect online purchasing decisions, but a third of consumers still rarely provide reviews. Furthermore, based on source credibility, E-WOM quality, and recommendation rating, in the three e-commerce sites, almost half of the reviews studied were hard to be trusted. Based on these findings, this research summarizes the policy implications for consumers and governments and suggests future research.

How Personal Values Count in Misleading News Sharing with Moral Content.

The present study investigates the personal factors underlying online sharing of moral misleading news by observing the interaction between personal values, communication bias, credibility evaluations, and moral emotions. Specifically, we hypothesized that self-transcendence and conservation values may differently influence the sharing of misleading news depending on which moral domain is activated and that these are more likely to be shared when moral emotions and perceived credibility increase. In a sample of 132 participants (65% female), we tested SEMs on misleading news regarding violations in five different moral domains. The results suggest that self-transcendence values hinder online sharing of misleading news, while conservation values promote it; moreover, news written with a less blatantly biased linguistic frame are consistently rated as more credible. Lastly, more credible and emotionally activating news is more likely to be shared online.

Credibility, Inflation Targets and Interest Rate: Long-Term Results for Brazil

This study carried out an empirical investigation into the relationship between the credibility of monetary policy – measured based on seven indicators – and the necessary variation of interest rates to control inflation, replicating the methods proposed by Mendonça and Souza (2007), extending them for the period 1999-2020. The results obtained confirm the hypothesis that higher levels of credibility allow the Central Bank to control inflation with lower interest rate increases. Furthermore, evidence was found that, although the credibility indicators show a better adjustment relative to the data – indicating a forward-looking nature in the conduction of basic interest rates –, among the reputation indicators, short-run inflationary results have a stronger weight in the decisions of monetary policy, suggesting that public expectations with short-memory remain relevant in the sample period.

Age and neurocognition are associated with credibility evaluations of health websites

The internet has become a common means by which many older adults seek out health information. The prevalence of misinformation on the internet makes the search for accurate online health information a more complex and evaluative process. This study examined the role of age and neurocognition in credibility evaluations of credible and non-credible health websites. Forty-one older adults and fifty younger adults completed a structured credibility rating task in which they evaluated a series of webpages displaying health information about migraine treatments. Participants also completed measures of neurocognition, internet use, and health literacy. Results suggested that older adults rated non-credible health websites as more credible than younger adults, but the age groups did not differ in their ratings of credible sites. Within the full sample, neurocognition was associated with credibility ratings for non-credible health websites, whereas health literacy was related to the ratings of credible sites. Findings indicate that older adults may be more likely to trust non-credible health websites than younger adults, which may be related to differences in higher-order neurocognitive functions. Future work might examine whether cognitive-based supports for credibility training in older adults can be used to improve the accuracy with which they evaluate online health information.

A robust reputation iterative algorithm based on Z-statistics in a rating system with thorny objects

With the explosive growth of online alternative objects, the availability of a credible rating system could play a valuable role for users who are evaluating and/or choosing items. Due to the existence of spammers, many methods have been proposed that employ a reputation-based mechanism in the last few years. However, these methods only consider spammers’ behaviours but neglect the effect of thorny objects, which are difficult to evaluate because of their intrinsic uncertainty and complexity with respect to the problem context, knowledge gaps, and various user criteria. To solve this problem, we propose a new reputation iterative algorithm based on Z-statistics (ZS), which eliminates the effect of thorny objects and strengthens the ability to deal with spammers. In this article, the proposed method makes effectiveness comparisons with other typical methods using a rating example and a simulated rating system, and presents additional effectiveness and complexity analyses of these results. Finally, the experimental results also demonstrate that the ZS algorithm outperforms other methods in simultaneously dealing with the effects of spammers and thorny objects.