Is it gossip or feedback? Surgical attendings' perceptions of gossip within residency

OBJECTIVE

Gossip-evaluative talk about an absent third party-exists in surgical residency programs. Attending surgeons may engage in gossip to provide residents with feedback on performance, which may contribute to bias. Nevertheless, the perspectives of attending surgeons on gossip has not been studied.

DESIGN

In this qualitative study, semi-structured interviews about gossip in surgical training were conducted with attending surgeons. We performed a reflexive thematic analysis of transcripts with a grounded theory approach to describe attendings' perceptions of their role in gossip within surgical residency.

SETTING

Interviews were conducted from September 23, 2023, to November 27, 2023 via Zoom™.

PARTICIPANTS

Eighteen surgery attendings associated with 7 surgical training programs were interviewed.

RESULTS

Six themes were developed: 1) Attendings typically view gossip with a negative lens; thus, well-intended conversations about resident performance that meet the academic definition of gossip are not perceived as gossip; 2) Gossip can damage attendings' reputations as surgeons and educators; 3) Mitigating the negative impacts of gossip by maintaining accurate and objective standards of honest communication is hard; 4) Attendings express concerns about hearing other attendings' impressions of residents prior to formulating their own opinion; 5) The surgical hierarchy restricts the volume and content of gossip that reaches attendings, which may limit their knowledge of program culture; and 6) It is very difficult to mitigate gossip at the program level. Ultimately, attendings utilize gossip (e.g. triangulating their experience) with the goal of providing residents feedback.

CONCLUSIONS

Defining important conversations about resident performance as gossip should not discourage these critically important conversations but rather underscore the importance of combating harmful gossip through 3 behaviors: 1) committing to objective communication; 2) limiting or reframing information about resident performance that is shared with attendings who have yet to formulate their own opinions; and 3) regulating gossip in particular high-stakes microenvironments (e.g. the operating room).

Demystifying unsupervised learning: how it helps and hurts

Humans and machines rarely have access to explicit external feedback or supervision, yet manage to learn. Most modern machine learning systems succeed because they benefit from unsupervised data. Humans are also expected to benefit and yet, mysteriously, empirical results are mixed. Does unsupervised learning help humans or not? Here, we argue that the mixed results are not conflicting answers to this question, but reflect that humans self-reinforce their predictions in the absence of supervision, which can help or hurt depending on whether predictions and task align. We use this framework to synthesize empirical results across various domains to clarify when unsupervised learning will help or hurt. This provides new insights into the fundamentals of learning with implications for instruction and lifelong learning.

Human hippocampus and dorsomedial prefrontal cortex infer and update latent causes during social interaction

Latent-cause inference is the process of identifying features of the environment that have caused an outcome. This problem is especially important in social settings where individuals may not make equal contributions to the outcomes they achieve together. Here, we designed a novel task in which participants inferred which of two characters was more likely to have been responsible for outcomes achieved by working together. Using computational modeling, univariate and multivariate analysis of human fMRI, and continuous theta-burst stimulation, we identified two brain regions that solved the task. Notably, as each outcome occurred, it was possible to decode the inference of its cause (the responsible character) from hippocampal activity. Activity in dorsomedial prefrontal cortex (dmPFC) updated estimates of association between cause-responsible character-and the outcome. Disruption of dmPFC activity impaired participants' ability to update their estimate as a function of inferred responsibility but spared their ability to infer responsibility.

Exploring the influence of historical storytelling on cultural heritage tourists' revisit intention: A case study of the Mogao Grottoes in Dunhuang

The revisit intention of tourists has long been a focal point of academic inquiry. However, there is still insufficient research on the antecedents of revisit intention from the perspectives of historical storytelling, destination image and perceived value. Taking the Mogao Grottoes in Dunhuang, a UNESCO World Heritage Site, as a case study, this paper, based on stimulus-organism-response (SOR) theory, examines the impact of historical storytelling on the destination image, perceived value, and revisit intention. Additionally, it further explores the mediating role of destination image and perceived value, as well as the moderating effect of place attachment in this chain. The research findings indicate that: (1) Historical storytelling significantly enhances tourists' perception of the tourism experience and revisit intention; (2) The study supports the mediating effect of destination image and perceived value; (3) Place attachment has a significant positive moderating effect between historical storytelling and revisit intention. Effective historical storytelling can significantly enhance destination image and perceived value, improve tourists' participation and satisfaction in tourism, stimulate revisit intention, and promote the sustainable development of tourist destinations. These findings enrich the research content of cultural heritage tourism, providing valuable suggestions for improving the management level of cultural heritage tourism attractions and increasing visitors' revisit intention.

Artificial intelligence-assisted interventions for perioperative anesthetic management: a systematic review and meta-analysis

BACKGROUND

Integration of artificial intelligence (AI) into medical practice has increased recently. Numerous AI models have been developed in the field of anesthesiology; however, their use in clinical settings remains limited. This study aimed to identify the gap between AI research and its implementation in anesthesiology via a systematic review of randomized controlled trials with meta-analysis (CRD42022353727).

METHODS

We searched the databases of Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica Database (Embase), Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), Institute of Electrical and Electronics Engineers Xplore (IEEE), and Google Scholar and retrieved randomized controlled trials comparing conventional and AI-assisted anesthetic management published between the date of inception of the database and August 31, 2023.

RESULTS

Eight randomized controlled trials were included in this systematic review (n = 568 patients), including 286 and 282 patients who underwent anesthetic management with and without AI-assisted interventions, respectively. AI-assisted interventions used in the studies included fuzzy logic control for gas concentrations (one study) and the Hypotension Prediction Index (seven studies; adding only one indicator). Seven studies had small sample sizes (n = 30 to 68, except for the largest), and meta-analysis including the study with the largest sample size (n = 213) showed no difference in a hypotension-related outcome (mean difference of the time-weighted average of the area under the threshold 0.22, 95% confidence interval -0.03 to 0.48, P = 0.215, I2 93.8%).

CONCLUSIONS

This systematic review and meta-analysis revealed that randomized controlled trials on AI-assisted interventions in anesthesiology are in their infancy, and approaches that take into account complex clinical practice should be investigated in the future.

TRIAL REGISTRATION

This study was registered with the International Prospective Register of Systematic Reviews (PROSPERO ID: CRD42022353727).

Artificial intelligence enables unified analysis of historical and landscape influences on genetic diversity

While genetic variation in any species is potentially shaped by a range of processes, phylogeography and landscape genetics are largely concerned with inferring how environmental conditions and landscape features impact neutral intraspecific diversity. However, even as both disciplines have come to utilize SNP data over the last decades, analytical approaches have remained for the most part focused on either broad-scale inferences of historical processes (phylogeography) or on more localized inferences about environmental and/or landscape features (landscape genetics). Here we demonstrate that an artificial intelligence model-based analytical framework can consider both deeper historical factors and landscape-level processes in an integrated analysis. We implement this framework using data collected from two Brazilian anurans, the Brazilian sibilator frog (Leptodactylus troglodytes) and granular toad (Rhinella granulosa). Our results indicate that historical demographic processes shape most the genetic variation in the sibulator frog, while landscape processes primarily influence variation in the granular toad. The machine learning framework used here allows both historical and landscape processes to be considered equally, rather than requiring researchers to make an a priori decision about which factors are important.

Hyperthermic intraoperative peritoneal chemotherapy and cytoreductive surgery for people with peritoneal metastases: a systematic review and cost-effectiveness analysis

Background

We compared the relative benefits, harms and cost-effectiveness of hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery ± systemic chemotherapy versus cytoreductive surgery ± systemic chemotherapy or systemic chemotherapy alone in people with peritoneal metastases from colorectal, gastric or ovarian cancers by a systematic review, meta-analysis and model-based cost-utility analysis.

Methods

We searched MEDLINE, EMBASE, Cochrane Library and the Science Citation Index, ClinicalTrials.gov and WHO ICTRP trial registers until 14 April 2022. We included only randomised controlled trials addressing the research objectives. We used the Cochrane risk of bias tool version 2 to assess the risk of bias in randomised controlled trials. We used the random-effects model for data synthesis when applicable. For the cost-effectiveness analysis, we performed a model-based cost-utility analysis using methods recommended by The National Institute for Health and Care Excellence.

Results

The systematic review included a total of eight randomised controlled trials (seven randomised controlled trials, 955 participants included in the quantitative analysis). All comparisons other than those for stage III or greater epithelial ovarian cancer contained only one trial, indicating the paucity of randomised controlled trials that provided data. For colorectal cancer, hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy probably results in little to no difference in all-cause mortality (60.6% vs. 60.6%; hazard ratio 1.00, 95% confidence interval 0.63 to 1.58) and may increase the serious adverse event proportions compared to cytoreductive surgery ± systemic chemotherapy (25.6% vs. 15.2%; risk ratio 1.69, 95% confidence interval 1.03 to 2.77). Hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy probably decreases all-cause mortality compared to fluorouracil-based systemic chemotherapy alone (40.8% vs. 60.8%; hazard ratio 0.55, 95% confidence interval 0.32 to 0.95). For gastric cancer, there is high uncertainty about the effects of hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy versus cytoreductive surgery + systemic chemotherapy or systemic chemotherapy alone on all-cause mortality. For stage III or greater epithelial ovarian cancer undergoing interval cytoreductive surgery, hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy probably decreases all-cause mortality compared to cytoreductive surgery + systemic chemotherapy (46.3% vs. 57.4%; hazard ratio 0.73, 95% confidence interval 0.57 to 0.93). Hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy may not be cost-effective versus cytoreductive surgery + systemic chemotherapy for colorectal cancer but may be cost-effective for the remaining comparisons.

Limitations

We were unable to obtain individual participant data as planned. The limited number of randomised controlled trials for each comparison and the paucity of data on health-related quality of life mean that the recommendations may change as new evidence (from trials with a low risk of bias) emerges.

Conclusions

In people with peritoneal metastases from colorectal cancer with limited peritoneal metastases and who are likely to withstand major surgery, hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy should not be used in routine clinical practice (strong recommendation). There is considerable uncertainty as to whether hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy or cytoreductive surgery + systemic chemotherapy should be offered to patients with gastric cancer and peritoneal metastases (no recommendation). Hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy should be offered routinely to women with stage III or greater epithelial ovarian cancer and metastases confined to the abdomen requiring and likely to withstand interval cytoreductive surgery after chemotherapy (strong recommendation).

Future work

More randomised controlled trials are necessary.

Study registration

This study is registered as PROSPERO CRD42019130504.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 17/135/02) and is published in full in Health Technology Assessment; Vol. 28, No. 51. See the NIHR Funding and Awards website for further award information.

Processing of misinformation as motivational and cognitive biases

Misinformation can be broadly defined as false or inaccurate information created and spread with or without clear intent to cause harm. It travels fast and deep and persists despite debunking. It is well-documented that corrective messages and fact-checking efforts often fail to mitigate the effects or persistence of misinformation. In this article, we examine the persistence of misinformation as rooted in motivational and cognitive biases in information processing. While drawing on the frameworks of motivations that drive information seeking, sharing, and processing and various cognitive biases, we explicate mechanisms and processes that underlie the impact and persistence of misinformation. We conclude our article by discussing the potential utility of psychological inoculation as a prebunking strategy.

A veracity dissemination consistency-based few-shot fake news detection framework by synergizing adversarial and contrastive self-supervised learning

With the rapid growth of social media, fake news (rumors) are rampant online, seriously endangering the health of mainstream social consciousness. Fake news detection (FEND), as a machine learning solution for automatically identifying fake news on Internet, is increasingly gaining the attentions of academic community and researchers. Recently, the mainstream FEND approaches relying on deep learning primarily involves fully supervised fine-tuning paradigms based on pre-trained language models (PLMs), relying on large annotated datasets. In many real scenarios, obtaining high-quality annotated corpora are time-consuming, expertise-required, labor-intensive, and expensive, which presents challenges in obtaining a competitive automatic rumor detection system. Therefore, developing and enhancing FEND towards data-scarce scenarios is becoming increasingly essential. In this work, inspired by the superiority of semi-/self- supervised learning, we propose a novel few-shot rumor detection framework based on semi-supervised adversarial learning and self-supervised contrastive learning, named Detection Yet See Few (DetectYSF). DetectYSF synergizes contrastive self-supervised learning and adversarial semi-supervised learning to achieve accurate and efficient FEND capabilities with limited supervised data. DetectYSF uses Transformer-based PLMs (e.g., BERT, RoBERTa) as its backbone and employs a Masked LM-based pseudo prompt learning paradigm for model tuning (prompt-tuning). Specifically, during DetectYSF training, the enhancement measures for DetectYSF are as follows: (1) We design a simple but efficient self-supervised contrastive learning strategy to optimize sentence-level semantic embedding representations obtained from PLMs; (2) We construct a Generation Adversarial Network (GAN), utilizing random noises and negative fake news samples as inputs, and employing Multi-Layer Perceptrons (MLPs) and an extra independent PLM encoder to generate abundant adversarial embeddings. Then, incorporated with the adversarial embeddings, we utilize semi-supervised adversarial learning to further optimize the output embeddings of DetectYSF during its prompt-tuning procedure. From the news veracity dissemination perspective, we found that the authenticity of the news shared by these collectives tends to remain consistent, either mostly genuine or predominantly fake, a theory we refer to as "news veracity dissemination consistency". By employing an adjacent sub-graph feature aggregation algorithm, we infuse the authenticity characteristics from neighboring news nodes of the constructed veracity dissemination network during DetectYSF inference. It integrates the external supervisory signals from "news veracity dissemination consistency" to further refine the news authenticity detection results of PLM prompt-tuning, thereby enhancing the accuracy of fake news detection. Furthermore, extensive baseline comparisons and ablated experiments on three widely-used benchmarks demonstrate the effectiveness and superiority of DetectYSF for few-shot fake new detection under low-resource scenarios.

Hesitancy toward Childhood and Influenza Vaccines: Experiences from Highly Educated Jordanian Parents

We aimed to examine vaccine hesitancy and knowledge towards influenza vaccines among Jordanian parents. Data were collected via an online questionnaire distributed between October 2023 and March 2024. They included sections on demographics, parental attitudes towards childhood vaccines (PACVs), and knowledge and practices towards influenza vaccines. Associations were examined using the chi-squared test. A binary logistic regression model was utilized to determine predictors of vaccine usage. A total of 3208 participants were included, of which 9.3% were vaccine hesitant per the PACV categorization. Fathers were more likely to be vaccine hesitant (OR: 1.40; 95CI: 1.07-1.85). Similarly, divorced parents (OR: 1.80; 95CI: 1.05-3.12) were significantly more vaccine hesitant compared to their married counterparts. Conversely, higher monthly income (OR: 0.66; 95CI: 0.48-0.92), working in healthcare settings (OR: 0.71; 95CI: 0.51-0.98), and adherence to national vaccination policies (OR: 0.07; 95CI: 0.04-0.13) were significantly associated with a lower likelihood of vaccine hesitancy. Multivariate analysis shows that a healthcare-related occupation (OR: 0.62; 95CI: 0.44-0.87), semi-compliance (OR: 0.37; 95CI: 0.22-0.64), full compliance (OR: 0.08; 95CI: 0.05-0.13) with national vaccine guidelines, and knowledge scores of influenza and vaccines (OR: 0.79; 95CI: 0.75-0.84) were the only independent factors influencing vaccine hesitancy. Finally, non-hesitant participants were significantly more likely to give the influenza vaccine to their children at the present or future time (OR: 2.07; 95CI: 1.53-2.80). Our findings highlight the complexity of vaccine hesitancy and underscore the importance of tailored interventions. Cultural, socioeconomic, and individual factors play significant roles in shaping attitudes toward vaccination. An understanding of the aforementioned among Jordanian parents provides insights for public health initiatives. Compliance with national vaccination guidelines and addressing concerns about vaccine safety are essential for improving childhood vaccination rates in Jordan.

Encountering Bias: Examining Biases and Stereotypes in the Evaluation Process Among Expert Psychologists During Specialization Exams

The study of cognitive biases in job interviews has garnered significant attention due to its far-reaching implications for the economy and society. However, little research has focused on the biases exhibited by expert psychologists serving on psychology specialization examination committees. As such, this study has conducted a comprehensive examination of biases within the specialization exam in Israel. One additional objective of the research is to assess the levels of distress experienced by examinees following the examination. Questionnaires were administered to 418 psychologists participating in the clinical and educational psychology specialization exams. The findings unveiled several noteworthy outcomes. Firstly, several biases were identified, including ethnic stereotypes, biases stemming from cognitive load, and more. Secondly, examinees who presented a cognitive-behavioral therapy (CBT) case experienced a higher failure rate. Thirdly, a positive association was found between exam failure and personal distress and this effect was stronger for educational examinees compared to clinical examinees. The most intriguing discovery was that all biases, without exception, occurred among clinical psychologists, whereas educational psychologists displayed no biases. This outcome contrasted with initial expectations. Consequently, the present study aims to expand the existing knowledge about psychological biases and stereotypes by elucidate the reasons behind this discrepancy between the two disciplines while considering the advantages and disadvantages associated with a sense of "expertise" in the realm of adult diagnostics.

A Multidimensional Approach for Evaluating Reality in Social Media: Mixed Methods Study

BACKGROUND

Misinformation is a threat to public health. The effective countering of misinformation may require moving beyond the binary classification of fake versus fact to capture the range of schemas that users employ to evaluate social media content. A more comprehensive understanding of user evaluation schemas is necessary.

OBJECTIVE

The goal of this research was to advance the current understanding of user evaluations of social media information and to develop and validate a measurement instrument for assessing social media realism.

METHODS

This research involved a sequence of 2 studies. First, we used qualitative focus groups (n=48). Second, building on the first study, we surveyed a national sample of social media users (n=442). The focus group data were analyzed using the constant comparison approach. The survey data were analyzed using confirmatory factor analyses and ordinary least squares regression.

RESULTS

The findings showed that social media reality evaluation involves 5 dimensions: falsity, naturality, authenticity, resonance, and social assurance. These dimensions were differentially mapped onto patterns of social media use. Authenticity was strongly associated with the existing global measure of social media realism (P<.001). Naturality, or the willingness to accept artificiality and engineered aspects of social media representations, was linked to hedonic enjoyment (P<.001). Resonance predicted reflective thinking (P<.001), while social assurance was strongly related to addictive use (P<.001). Falsity, the general belief that much of what is on social media is not real, showed a positive association with both frequency (P<.001) and engagement with (P=.003) social media. These results provide preliminary validity data for a social media reality measure that encompasses multiple evaluation schemas for social media content.

CONCLUSIONS

The identification of divergent schemas expands the current focus beyond fake versus fact, while the goals, contexts, and outcomes of social media use associated with these schemas can guide future digital media literacy efforts. Specifically, the social media reality measure can be used to develop tailored digital media literacy interventions for addressing diverse public health issues.

There Is no Universal Standard of Beauty

This article discusses the various factors that contribute to facial beauty and the different contexts in which they are significant. The authors examine the roles of the golden ratio, ideal proportions, symmetry, and specific facial features in what constitutes an attractive face. They also investigate the influence of cultural and evolutionary perspectives on facial beauty and the impact of social media on our perception of beauty. The article provides a comprehensive overview of the topic and emphasises the significance of facial beauty and its impact on our lives. The authors acknowledge that the concept of beauty is difficult to define with absolute precision, and that the objective-subjective argument regarding facial beauty remains unsolved. However, they argue that physical attributes undoubtedly influence perceptions of attractiveness, but beauty extends beyond surface-level features. They also suggest that embracing diversity in beauty standards fosters a more inclusive society that celebrates the unique qualities of every person.Level of Evidence V This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The limited memory of value following value directed encoding

Items associated with higher values during encoding are later recognized and recalled better than are lower valued items. During recall paradigms, these value directed encoding (VDE) effects heavily depend upon learned strategies acquired during repeated testing with earnings feedback. However, because VDE effects also occur in single test recognition designs, precluding such learning, it has been suggested that high value may automatically induce good encoding. We tested this by manipulating encoding instructions (Experiments 1a and 1b) and manipulating concurrent levels of processing (LOP) requirements during encoding (Experiment 2a and 2b). Two main findings emerged. First, subject initiated strategies played a dominant role in VDE effects with little evidence for automaticity. This was demonstrated in Experiment 1 by a more than three-fold increase in the VDE recognition effect when instructions specifically encouraged selective elaboration of high-value items. It was also shown by the complete elimination of VDE recognition effects in Experiment 2 when LOP tasks were concurrently performed during encoding. Critically, the blocking of VDE effects occurred even though a catch trial procedure verified that value was being processed during encoding and remained even when subjects had unlimited time to process the materials during encoding. Second, the data showed, for the first time, that when subjects attempted to specify the value of recognized items, they heavily depended upon a recognition heuristic in which increases in recognition strength, even when nondiagnostic, were inferred to reflect high encoding value. The tendency for subjects to conflate recognition strength and value may have important implications for behavioral economics.

Judgement and Decision Making in Clinical and Return-to-Sports Decision Making: A Narrative Review

Making return-to-sport decisions can be complex and multi-faceted, as it requires an evaluation of an individual's physical, psychological, and social well-being. Specifically, the timing of progression, regression, or return to sport can be difficult to determine due to the multitude of information that needs to be considered by clinicians. With the advent of new sports technology, the increasing volume of data poses a challenge to clinicians in effectively processing and utilising it to enhance the quality of their decisions. To gain a deeper understanding of the mechanisms underlying human decision making and associated biases, this narrative review provides a brief overview of different decision-making models that are relevant to sports rehabilitation settings. Accordingly, decisions can be made intuitively, analytically, and/or with heuristics. This narrative review demonstrates how the decision-making models can be applied in the context of return-to-sport decisions and shed light on strategies that may help clinicians improve decision quality.

Overcoming confusion and stigma in habitat fragmentation research

Anthropogenic habitat loss is widely recognized as a primary environmental concern. By contrast, debates on the effects of habitat fragmentation persist. To facilitate overcoming these debates, here we: (i) review the state of the literature on habitat fragmentation, finding widespread confusion and stigma; (ii) identify consequences of this for biodiversity conservation and ecosystem management; and (iii) suggest ways in which research can move forward to resolve these problems. Confusion is evident from the 25 most-cited fragmentation articles published between 2017 and 2021. These articles use five distinct concepts of habitat fragmentation, only one of which clearly distinguishes habitat fragmentation from habitat area and other factors ('fragmentation per se'). Stigmatization is evident from our new findings that fragmentation papers are more charged with negative sentiments when compared to papers from other subfields in the environmental sciences, and that fragmentation papers with more negative sentiments are cited more. While most empirical studies of habitat fragmentation per se find neutral or positive effects on species and biodiversity outcomes, which implies that small habitat patches have a high cumulative value, confusion and stigma in reporting and discussing such results have led to suboptimal habitat protection policy. For example, government agencies, conservation organizations, and land trusts impose minimum habitat patch sizes on habitat protection. Given the high cumulative value of small patches, such policies mean that many opportunities for conservation are being missed. Our review highlights the importance of reducing confusion and stigma in habitat fragmentation research. To this end, we propose implementing study designs in which multiple sample landscapes are selected across independent gradients of habitat amount and fragmentation, measured as patch density. We show that such designs are possible for forest habitat across Earth's biomes. As such study designs are adopted, and as language becomes more precise, we expect that confusion and stigma in habitat fragmentation research will dissipate. We also expect important breakthroughs in understanding the situations where effects of habitat fragmentation per se are neutral, positive, or negative, and the reasons for these differences. Ultimately this will improve efficacy of area-based conservation policies, to the benefit of biodiversity and people.

AI and XAI second opinion: the danger of false confirmation in human-AI collaboration

Can AI substitute a human physician's second opinion? Recently the Journal of Medical Ethics published two contrasting views: Kempt and Nagel advocate for using artificial intelligence (AI) for a second opinion except when its conclusions significantly diverge from the initial physician's while Jongsma and Sand argue for a second human opinion irrespective of AI's concurrence or dissent. The crux of this debate hinges on the prevalence and impact of 'false confirmation'-a scenario where AI erroneously validates an incorrect human decision. These errors seem exceedingly difficult to detect, reminiscent of heuristics akin to confirmation bias. However, this debate has yet to engage with the emergence of explainable AI (XAI), which elaborates on why the AI tool reaches its diagnosis. To progress this debate, we outline a framework for conceptualising decision-making errors in physician-AI collaborations. We then review emerging evidence on the magnitude of false confirmation errors. Our simulations show that they are likely to be pervasive in clinical practice, decreasing diagnostic accuracy to between 5% and 30%. We conclude with a pragmatic approach to employing AI as a second opinion, emphasising the need for physicians to make clinical decisions before consulting AI; employing nudges to increase awareness of false confirmations and critically engaging with XAI explanations. This approach underscores the necessity for a cautious, evidence-based methodology when integrating AI into clinical decision-making.

Response to discussant comments on "NMA, the first 20 years"

We respond to discussant comments on our paper "Twenty years of network meta-analysis: Continuing controversies and recent developments" (https://doi.org/10.1002/jrsm.1700) and raise some additional points for consideration, including: the way in which methodological guidance is generated; integration of the estimand framework with evidence synthesis; and implications of the European Joint Clinical Assessment. We ask: what properties are required of population adjustment methods to enable transparent and consistent decision-making? We also ask why individual patient data is not routinely made available to re-imbursement authorities and clinical guideline developers.

Unnecessary care in orthopaedic surgery

Unnecessary care, where the potential for harm exceeds the potential for benefit, is widespread in medical care. Orthopaedic surgery is no exception. This has significant implications for patient safety and health care expenditure. This narrative review explores unnecessary care in orthopaedic surgery. There is wide geographic variation in orthopaedic surgical practice that cannot be explained by differences in local patient populations. Furthermore, many orthopaedic interventions lack adequate low-bias evidence to support their use. Quantifying the size of the problem is difficult, but the economic burden and morbidity associated with unnecessary care is likely to be significant. An evidence gap, evidence-practice gap, cognitive biases, and health system factors all contribute to unnecessary care in orthopaedic surgery. Unnecessary care is harming patients and incurring high costs. Solutions include increasing awareness of the problem, aligning financial incentives to high value care and away from low value care, and demanding low bias evidence where none exists.

Navigating persuasive strategies in online health misinformation: An interview study with older adults on misinformation management

Online health misinformation commonly includes persuasive strategies that can easily deceive lay people. Yet, it is not well understood how individuals respond to misinformation with persuasive strategies at the moment of exposure. This study aims to address the research gap by exploring how and why older adults fall into the persuasive trap of online health misinformation and how they manage their encounters of online health misinformation. Using a think-aloud protocol, semi-structured interviews were conducted with twenty-nine older adults who were exposed to articles employing twelve groups of common persuasive strategies in online health misinformation. Thematic analysis of the transcripts revealed that some participants fell for the persuasive strategies, yet the same strategies were detected by others as cues to pin down misinformation. Based on the participants' own words, informational and individual factors as well as the interplay of these factors were identified as contributors to susceptibility to misinformation. Participants' strategies to manage misinformation for themselves and others were categorized. Implications of the findings are discussed.

A second chance for first impressions: evidence for altered impression updating in borderline personality disorder

BACKGROUND

Individuals with borderline personality disorder (BPD) frequently alter between idealizing and devaluing other persons, which has been linked to an increased tendency to update self-relevant beliefs and impressions. We hypothesized that increased impression updating could stem from reduced attitude contextualization, i.e., a process in which impression-disconfirming information is linked to contextual cues.

METHODS

Individuals diagnosed with BPD and controls (recruited online, with unknown diagnostic status) completed an impression formation paradigm. They first learned about the positive or negative behaviors of others in one Context A (e.g., Person 1 is helpful), followed by learning about behaviors of the opposite valence in a second Context B (Person 1 is rude). We also manipulated between participants whether the observed behaviors were directed toward the study participants (self-relevant) or, more generally, at other people (other-relevant). The contexts were marked by differently-colored backgrounds (e.g., yellow vs. blue), to avoid influences of prior knowledge or experiences. After exposure to information in both contexts, participants rated their impressions of the persons in Context A, Context B, and, crucially, a previously unknown Context C (white background). We examined whether the initial or an updated impression (re-)emerged in Context C.

RESULTS

Initial impressions remained stable and dominated the ratings of controls across contexts A, B, and C for both self-relevant and other-relevant behaviors, consistent with contextualizing impression-disconfirming information. As expected, however, individuals with BPD only showed updated impression ratings in Context C for self-relevant behaviors, consistent with the assumed reduced tendency to contextualize impression-disconfirming self-relevant information. Further exploratory analyses suggest that more severe BPD symptoms predicted more pronounced impression updating in the self-relevant condition.

CONCLUSIONS

The findings help to illuminate the mechanisms underlying interpersonal problems in individuals with BPD. People with BPD are not just more inclined to discard positive first impressions but to re-evaluate disliked others when they behave positively, contributing to the volatility of interactions with others. Contextualization has known and modifiable antecedents, and the study may thus provide potential targets for therapeutic intervention. Future studies will need to replicate the findings with specified controls.

A global survey of the attitudes and perspectives of cognitive bias in forensic anthropology

It is now well established that decision making can be susceptible to cognitive bias in a broad range of fields, with forensic science being no exception. Previously published research has revealed a bias blind spot in forensic science where examiners do not recognise bias within their own domain. A survey of 101 forensic anthropology practitioners (n = 52) and students (n = 38) was undertaken to assess their level of awareness of cognitive bias and investigate their attitudes towards cognitive bias within forensic anthropology. The results revealed that the forensic anthropology community (∼90%) had a high level of awareness of cognitive bias. Overall ∼89% expressed concerns about cognitive bias in the broad discipline of forensic science, their own domain of forensic anthropology, and in the evaluative judgments they made in reconstruction activities, identifying a significant reduction in the bias blind spot. However, more than half of the participants believed that bias can be reduced by sheer force of will, and there was a lack of consensus about implementing blinding procedures or context management. These findings highlight the need to investigate empirically the feasibility of proposed mitigating strategies within the workflow of forensic anthropologists and their capabilities for increasing the transparency in decision making.

Ethical Challenges for Plastic Surgery in Treating Internationally Adopted Children With Cleft Lip and Palate

A large number of children with cleft lip and palate (CLP) were adopted to Sweden in the last decade, mainly from China. Most of the children arrived with unoperated palates and at later ages than earlier years. This article aims to present an overview of ethical challenges within the practice of international adoption of children with CLP from the perspective of plastic surgery in a welfare health care system. An overview of CLP treatment is presented, followed by a normative discussion and ethical analysis using the 4 principles of Beauchamp and Childress: non-maleficence, beneficence, autonomy, and justice. The following themes and subthemes were analyzed: the search for normality and the potential challenge of being adopted and having CLP-treatment autonomy of the child and future preferences, adoptive parents' expectations of plastic surgery, the journey of the adoptee and the adoptive parents; and general issues-reconstructive possibilities and consequences of CLP in the country of origin, information to the adoptive parents, health care needs, and reconstructive possibilities for children with CLP in the receiving country. Clinical implications are discussed, and suggestions for future research are provided.

The perceived guilt and innocence of adults with developmental language disorder and adults with typical language during a mock interrogation

PURPOSE

This study examined if there were differences in the guilty and not guilty judgments of adults with developmental language disorder (DLD) and those with typical language (TL) functioning.

METHOD

Twenty-four adults (12 DLD, 12 TL) were assigned to either the guilty or not guilty conditions. Those in the guilty condition engaged in a mock crime while those in the not guilty condition were informed that a crime had been committed. Peer jurors were presented with video interrogations of the DLD (6 guilty, 6 not guilty) and TL (6 guilty, 6 not guilty) participants and were asked to make categorical judgments of guilty and not guilty and to indicate confidence in their judgments.

RESULTS

In general, peer jurors were not accurate in their judgments of the accused, and were more likely to judge individuals with DLD as guilty relative to accused individuals with TL. Peer jurors were particularly poor at judging innocent adults with DLD as not guilty and guilty adults with TL as guilty. Despite this, peer jurors were more confident than not in their guilty and not guilty determinations.

CONCLUSIONS

Peer jurors are confident in their judgments of the guilt of the accused when they should not be, particularly in the case of accused adults with DLD. Implications are discussed.

Quantifying the vulnerabilities of the online public square to adversarial manipulation tactics

Social media, seen by some as the modern public square, is vulnerable to manipulation. By controlling inauthentic accounts impersonating humans, malicious actors can amplify disinformation within target communities. The consequences of such operations are difficult to evaluate due to the challenges posed by collecting data and carrying out ethical experiments that would influence online communities. Here we use a social media model that simulates information diffusion in an empirical network to quantify the impacts of adversarial manipulation tactics on the quality of content. We find that the presence of hub accounts, a hallmark of social media, exacerbates the vulnerabilities of online communities to manipulation. Among the explored tactics that bad actors can employ, infiltrating a community is the most likely to make low-quality content go viral. Such harm can be further compounded by inauthentic agents flooding the network with low-quality, yet appealing content, but is mitigated when bad actors focus on specific targets, such as influential or vulnerable individuals. These insights suggest countermeasures that platforms could employ to increase the resilience of social media users to manipulation.

Understanding Responses to Conflicting Advice on COVID-19

This survey study tested a two-level model of responses to conflicting advice about COVID-19 and examined the underlying emotional and cognitive mechanisms and the moderating role of advice source. Results showed that at the individual message level, advice evaluation was associated with advice outcomes. At the message group level, advice evaluation and outcomes were linked to perceived contradiction in content among the advice and the quantity of conflicting messages received, both directly and indirectly via recipients' emotions. Features of conflicting advice received primarily from impersonal sources had particularly strong associations with advice evaluation and outcomes. Implications for health communication were discussed.

Effects of task structure and confirmation bias in alternative hypotheses evaluation

We empirically examined the effectiveness of how the Analysis of Competing Hypotheses (ACH) technique structures task information to help reduce confirmation bias (Study 1) and the portrayal of intelligence analysts as suffering from such bias (Study 2). Study 1 (N = 161) showed that individuals presented with hypotheses in rows and evidence items in columns were significantly less likely to demonstrate confirmation bias, whereas those presented with the ACH-style matrix (with hypotheses in columns and evidence items in rows) or a paragraph of text (listing the evidence for each hypothesis) were not less likely to demonstrate bias. The ACH-style matrix also did not confer any benefits regarding increasing sensitivity to evidence credibility. Study 2 showed that the majority of 62 Dutch military analysts did not suffer from confirmation bias and were sensitive to evidence credibility. Finally, neither judgmental coherence nor cognitive reflection differentiated between better or worse performers in the hypotheses evaluation tasks.

Falling into the trap: A study of the cognitive neural mechanisms of immediate rewards impact on consumer attitudes toward forwarding perk advertisements

In the context of digital marketing, consumers often express aversion to perk advertisements yet find it challenging to resist the temptation and forward it, resulting in inconsistent attitudes and behaviors. This study, based on the Associative Propositional Evaluation model and the Confirmation Bias theory, utilizes event-related potential experiments to identify the interactive impacts of immediate rewards and information diagnosticity in advertisements on consumer attitude change in specific contexts. The research findings indicate that when rewards were present, information diagnosticity positively influences attitude change and the willingness to forward. However, when rewards were absent, the impact of information diagnosticity on attitude change and the willingness to forward is not significant, and neuroscientific evidence supports these findings. Theoretically, this study extends the research perspective on attitude change in online advertising contexts and broadens the application of the Associative Propositional Evaluation model in the field of consumer attitude change towards advertisements. In practice, this research holds significant guiding value for constraining platform manipulation of consumer cognitive behaviors, guiding the healthy development of platform economics, and promoting digital technology ethics.

Measuring Unipolar Traits With Continuous Response Items: Some Methodological and Substantive Developments

In recent years, some models for binary and graded format responses have been proposed to assess unipolar variables or "quasi-traits." These studies have mainly focused on clinical variables that have traditionally been treated as bipolar traits. In the present study, we have made a proposal for unipolar traits measured with continuous response items. The proposed log-logistic continuous unipolar model (LL-C) is remarkably simple and is more similar to the original binary formulation than the graded extensions, which is an advantage. Furthermore, considering that irrational, extreme, or polarizing beliefs could be another domain of unipolar variables, we have applied this proposal to an empirical example of superstitious beliefs. The results suggest that, in certain cases, the standard linear model can be a good approximation to the LL-C model in terms of parameter estimation and goodness of fit, but not trait estimates and their accuracy. The results also show the importance of considering the unipolar nature of this kind of trait when predicting criterion variables, since the validity results were clearly different.

Trust but verify: The biasing effects of witness opinions and background knowledge in workplace investigations

INTRODUCTION

A unique feature of workplace investigations is the familiarity that investigators and witnesses have with the factors involved in the adverse incident. Familiarity creates expectations that can shape investigators' and witnesses' assumptions and opinions. The current research examined the biasing effect of non-factual witness claims on investigators' judgments. These claims, which we call 'uncheckable,' included opinions about factors involved in the event and the future. We also examined how participants' a priori knowledge of an employee's history influenced their judgments.

METHOD

This experiment used a 2 (background information: control or unsafe) × 2 (uncheckable content: neutral or unsafe) between-subjects design. Participants were provided with background information about a worker (control or unsafe history) and a witness statement about a workplace event that contained uncheckable claims (neutral or worker as unsafe). We tested how our manipulations biased participants' judgments of: (i) the cause of the event, (ii) the witness's confidence and credibility, and (iii) the diagnosticity of the witness's account. We also tested if biasing background information affected how factual participants found the witness's statement.

RESULTS

Biasing uncheckable information (i.e., opinions) affected participants' judgments of event cause (ηp2 = 0.033) and increased their ratings of witness confidence (ηp2 = 0.074). Biasing background information about a worker affected participants' judgments of the cause of the event (ηp2 = 0.088), the diagnostic value of the witness statement (ηp2 = 0.054), and the number of factual claims in the witness statement, resulting in more uncheckable claims being misclassified as potential facts (ηp2 = 0.18).

CONCLUSION

This experiment demonstrated the significant effect that non-factual witness statements and irrelevant background information can have on the interpretation of evidence and judgments about the cause of events.

PRACTICAL APPLICATION

Understanding how contextual information can bias investigative judgment helps workplace investigators manage its influence in their judgment practices.

People see what they want to see: an EEG study

This study explored selective exposure and confirmation bias in the choices participants made about which political videos to watch, and whether their political positions changed after they watched videos that either agreed with or opposed their positions on two controversial issues in South Korea: North Korea policy and social welfare policy. The participants completed questionnaires before and after they watched the videos, were asked to select thumbnails of videos before they watched any, and had their brain wave activity measured through electroencephalogram (EEG) as they watched both types of videos. The participants demonstrated selective exposure as they primarily selected video thumbnails with content that matched their political orientations, and they demonstrated confirmation bias as their questionnaire responses after they watched the videos indicated that their positions had hardened. There were also statistically significant differences in alpha, beta, sensory motor rhythm, low beta, mid beta, and fast alpha activity depending on the political orientation consistency between the participants and the videos. Future studies could expand this line of research beyond college students and beyond Asia, and longitudinal work could also be conducted to determine if the obtained patterns remain constant over time.

Who Do I (Not) Ask to Play my Lottery? Effects of Perceived Positive and Negative Agency, Communion and Luck on the Illusion of Control by Proxy

The paper investigates the illusion of control by proxy in games of chance - an attempt to exert control by assigning it to others who are perceived as more capable, communable or luckier. Following up on research by Wohl & Enzle, who showed participants' preference to ask lucky others to play a lottery instead of doing it themselves, we included proxies with positive and negative qualities in the domains of agency and communion, as well good and bad luck. In three experiments (total N = 249) we tested participants' choices between these proxies and a random number generator in a task consisting of obtaining lottery numbers. We obtained consistent preventative illusions of control (i.e. avoidance of proxies with strictly negative qualities, as well as proxies with positive communion but negative agency), however we observed indifference between proxies with positive qualities and random number generators.

Genetic structure and landscape effects on gene flow in the Neotropical lizard Norops brasiliensis (Squamata: Dactyloidae)

One key research goal of evolutionary biology is to understand the origin and maintenance of genetic variation. In the Cerrado, the South American savanna located primarily in the Central Brazilian Plateau, many hypotheses have been proposed to explain how landscape features (e.g., geographic distance, river barriers, topographic compartmentalization, and historical climatic fluctuations) have promoted genetic structure by mediating gene flow. Here, we asked whether these landscape features have influenced the genetic structure and differentiation in the lizard species Norops brasiliensis (Squamata: Dactyloidae). To achieve our goal, we used a genetic clustering analysis and estimate an effective migration surface to assess genetic structure in the focal species. Optimized isolation-by-resistance models and a simulation-based approach combined with machine learning (convolutional neural network; CNN) were then used to infer current and historical effects on population genetic structure through 12 unique landscape models. We recovered five geographically distributed populations that are separated by regions of lower-than-expected gene flow. The results of the CNN showed that geographic distance is the sole predictor of genetic variation in N. brasiliensis, and that slope, rivers, and historical climate had no discernible influence on gene flow. Our novel CNN approach was accurate (89.5%) in differentiating each landscape model. CNN and other machine learning approaches are still largely unexplored in landscape genetics studies, representing promising avenues for future research with increasingly accessible genomic datasets.

Privacy Barriers in Health Monitoring: Scoping Review

BACKGROUND

Health monitoring technologies help patients and older adults live better and stay longer in their own homes. However, there are many factors influencing their adoption of these technologies. Privacy is one of them.

OBJECTIVE

The aim of this study was to provide an overview of the privacy barriers in health monitoring from current research, analyze the factors that influence patients to adopt assisted living technologies, provide a social psychological explanation, and propose suggestions for mitigating these barriers in future research.

METHODS

A scoping review was conducted, and web-based literature databases were searched for published studies to explore the available research on privacy barriers in a health monitoring environment.

RESULTS

In total, 65 articles met the inclusion criteria and were selected and analyzed. Contradictory findings and results were found in some of the included articles. We analyzed the contradictory findings and provided possible explanations for current barriers, such as demographic differences, information asymmetry, researchers' conceptual confusion, inducible experiment design and its psychological impacts on participants, researchers' confirmation bias, and a lack of distinction among different user roles. We found that few exploratory studies have been conducted so far to collect privacy-related legal norms in a health monitoring environment. Four research questions related to privacy barriers were raised, and an attempt was made to provide answers.

CONCLUSIONS

This review highlights the problems of some research, summarizes patients' privacy concerns and legal concerns from the studies conducted, and lists the factors that should be considered when gathering and analyzing people's privacy attitudes.

Contingency inferences from base rates: A parsimonious strategy?

The pseudocontingency framework provides a parsimonious strategy for inferring the contingency between two variables by assessing the base rates. Frequently occurring levels are associated, as are rarely occurring levels. However, this strategy can lead to different contingency inferences in different contexts, depending on how the base rates vary across contexts. Here, we examine how base-rate consistency influences base-rate learning and reliance by contrasting consistent with inconsistent base rates. We hypothesized that base-rate learning is facilitated, and that people rely more on base rates if base rates are consistent. In Experiment 1, the base rates across four contexts implied the same (consistent) or different (inconsistent) contingencies. Base rates were learned equally accurately, and participants inferred contingencies that followed the base rates but deviated from the genuine contingencies within contexts, regardless of consistency. In Experiment 2, we additionally manipulated whether the context was a plausible moderator of the contingency. While we replicated the first experiment's results when the context was a plausible moderator, base-rate inferences were stronger for consistent base rates when the context was an implausible moderator. Possibly, when a moderation-by-context was implausible, participants also relied on the base-rate correlation across contexts, which implied the same contingency when base rates were consistent but was zero when the base rates were inconsistent. Thus, our findings suggest that contingency inferences from base rates involve top-down processes in which people decide how to use base-rate information.

Driver Expectations of a Partial Driving Automation System in Relation to Branding and Training

OBJECTIVE

The current study examined whether differences in the branding and description or mode of training materials influence drivers' understanding and expectations of a partial driving automation system.

BACKGROUND

How technology is described might influence consumers' understanding and expectations, even if all information is accurate.

METHOD

Ninety drivers received training about a real partial driving automation system with a fictitious name. Participants were randomly assigned to a branding condition (system named AutonoDrive, training emphasized capabilities; or system named DriveAssist, training emphasized limitations) and training mode (quick-start brochure; video; or in-person demonstration). No safety-critical information was withheld nor deliberately misleading information provided. After training, participants drove a vehicle equipped with the system. Associations of drivers' expectations with branding condition and training mode were assessed using between-subjects comparisons of questionnaire responses obtained pre- and post-drive.

RESULTS

Immediately after training, those who received information emphasizing the system's capabilities had greater expectations of the system's function and crash avoidance capability in a variety of driving scenarios, including many in which the system would not work, as well as greater willingness to utilize the system's workload reduction benefits to take more risks. Most but not all differences persisted after driving the vehicle. Expectations about collision avoidance differed by training mode pre-drive but not post-drive.

CONCLUSION

Training that emphasizes a partial driving automation system's capabilities and downplays its limitations can foster overconfidence.

APPLICATION

Accuracy of technical information does not guarantee understanding; training should provide a balanced view of a system's limitations as well as capabilities.

Pseudodiagnosticity and preference hierarchy in a search-only inference paradigm

Bayes' Theorem provides a rationality-standard for information search when there are two mutually exclusive hypotheses and one or more statistical cues pertaining to the likelihoods of the hypotheses. Prior research shows that when people already have a cue pertaining to a hypothesis and are asked to seek additional information to help decide which hypothesis is correct, they tend to exhibit a specific form of pseudodiagnosticity: Rather than seek information that would assess the same cue relative to an alternative hypothesis, they tend to seek information about how a second cue would pertain to the first hypothesis. For example, if people are told that 70% of genuine paintings are landscapes, they then seek to know the percentage of genuine paintings that are watercolor rather than the percentage of fake paintings that are landscapes. However, this response pattern has sometimes been violated in a way that may depend on the cues' numerical values (e.g., 70% vs. 30%), thus raising a question as to the nature of the bias: Does the selection bias characterize the search process per se, or does it reflect the manner in which people utilize already-obtained percentage information? To address these issues, we employed a novel, search-only judgment paradigm in which people were asked to search for cues and to select them without ever obtaining the cues' percentage values. The results confirmed a tendency toward same-hypothesis pseudodiagnosticity both in primary (i.e., most-preferred) and secondary preference, and supported a model in which pseudodiagnosticity can proceed with or without numerical cue data.

Entropy-based detection of Twitter echo chambers

Echo chambers, i.e. clusters of users exposed to news and opinions in line with their previous beliefs, were observed in many online debates on social platforms. We propose a completely unbiased entropy-based method for detecting echo chambers. The method is completely agnostic to the nature of the data. In the Italian Twitter debate about the Covid-19 vaccination, we find a limited presence of users in echo chambers (about 0.35% of all users). Nevertheless, their impact on the formation of a common discourse is strong, as users in echo chambers are responsible for nearly a third of the retweets in the original dataset. Moreover, in the case study observed, echo chambers appear to be a receptacle for disinformative content.

Thinking about Believing: Can Metacognitive Reflection Encourage Belief Updating?

People often cling to their beliefs even in the face of counterevidence. The current study explored metacognitive reflection as a potential driver for belief updating. In a randomized controlled experiment (n = 155), participants rated their degree of agreement with a statement regarding genetic modification in humans. Following this, participants were presented with a passage containing an argument counter to their indicated belief. Participants in the metacognition condition were asked to deeply reflect on the ways in which the passage was similar to or different from their current beliefs. Participants in the control condition were asked to engage in more shallow reflection on the composition of the passage. After reflecting on the counterevidence, participants were asked to again rate their agreement with the statement regarding human gene modification. Both groups updated their initial beliefs to be more consistent with the presented counterevidence. Although greater belief updating was observed in those who metacognitively reflected on the passage, this effect did not reach significance (p = .055). These findings suggest that reflecting on counterevidence has the potential to encourage belief updating, regardless of whether that reflection is metacognitive in nature, and provide promise for future work investigating the role of metacognition in belief updating.

The choice-wide behavioral association study: data-driven identification of interpretable behavioral components

Behavior contains rich structure across many timescales, but there is a dearth of methods to identify relevant components, especially over the longer periods required for learning and decision-making. Inspired by the goals and techniques of genome-wide association studies, we present a data-driven method-the choice-wide behavioral association study: CBAS-that systematically identifies such behavioral features. CBAS uses a powerful, resampling-based, method of multiple comparisons correction to identify sequences of actions or choices that either differ significantly between groups or significantly correlate with a covariate of interest. We apply CBAS to different tasks and species (flies, rats, and humans) and find, in all instances, that it provides interpretable information about each behavioral task.

How Can Debiasing Research Aid Efforts to Reduce Discrimination?

PUBLIC ABSTRACT

Scientists studying intergroup biases are often concerned with lessening discrimination (unequal treatment of one social group versus another), but many interventions for reducing such biased behavior have weak or limited evidence. In this review article, we argue one productive avenue for reducing discrimination comes from adapting interventions in a separate field-judgment and decision-making-that has historically studied "debiasing": the ways people can lessen the unwanted influence of irrelevant information on decision-making. While debiasing research shares several commonalities with research on reducing intergroup discrimination, many debiasing interventions have relied on methods that differ from those deployed in the intergroup bias literature. We review several instances where debiasing principles have been successfully applied toward reducing intergroup biases in behavior and introduce other debiasing techniques that may be well-suited for future efforts in lessening discrimination.

Emergence of simple and complex contagion dynamics from weighted belief networks

Social contagion is a ubiquitous and fundamental process that drives individual and social changes. Although social contagion arises as a result of cognitive processes and biases, the integration of cognitive mechanisms with the theory of social contagion remains an open challenge. In particular, studies on social phenomena usually assume contagion dynamics to be either simple or complex, rather than allowing it to emerge from cognitive mechanisms, despite empirical evidence indicating that a social system can exhibit a spectrum of contagion dynamics-from simple to complex-simultaneously. Here, we propose a model of interacting beliefs, from which both simple and complex contagion dynamics can organically arise. Our model also elucidates how a fundamental mechanism of complex contagion-resistance-can come about from cognitive mechanisms.

Scientific figures interpreted by ChatGPT: strengths in plot recognition and limits in color perception

Emerging studies underscore the promising capabilities of large language model-based chatbots in conducting basic bioinformatics data analyses. The recent feature of accepting image inputs by ChatGPT, also known as GPT-4V(ision), motivated us to explore its efficacy in deciphering bioinformatics scientific figures. Our evaluation with examples in cancer research, including sequencing data analysis, multimodal network-based drug repositioning, and tumor clonal evolution, revealed that ChatGPT can proficiently explain different plot types and apply biological knowledge to enrich interpretations. However, it struggled to provide accurate interpretations when color perception and quantitative analysis of visual elements were involved. Furthermore, while the chatbot can draft figure legends and summarize findings from the figures, stringent proofreading is imperative to ensure the accuracy and reliability of the content.

Adaptation and application of the Parent Attitudes About Childhood Vaccines survey tool in the Vietnamese language: a cross-sectional study

BACKGROUND

Parental vaccine hesitancy could lead to outbreaks of vaccine-preventable diseases. Although parental vaccine hesitancy exists in the Vietnamese community, no research has directly investigated this social phenomenon in Vietnam. Among the validated measures, the 15-item Parent Attitudes About Childhood Vaccines survey tool (PACV) was reliable for predicting vaccine-hesitant parents. However, the PACV was not available in Vietnamese. This study aimed to develop a Vietnamese version of the PACV and examine factors associated with parental vaccine hesitancy in Hue city, Vietnam.

METHODS

This study was a cross-sectional study. The English PACV was translated into Vietnamese with content and face validation. Self-administered questionnaires were distributed to 400 parents at ten commune health centres in Hue city, Vietnam. The parents were asked to answer the questionnaire again after two weeks for the test-retest reliability. The Vietnamese PACV reliability was assessed using Cronbach's alpha and McDonald's omega, and the intra-class correlation (ICC) coefficients were used for the test-retest reliability. The construct validity was tested by the hypothesis that parental vaccine hesitancy would be related to the intention of getting the children vaccinated. Exploratory factor analysis was also undertaken to determine the construct validity. Bivariate and multivariable logistic regression were used to identify the factors associated with parental vaccine hesitancy.

RESULTS

The Vietnamese PACV final version (PACV-Viet) contained 14 items. Three hundred and fifteen parents returned completed questionnaires, giving a response rate of 78.8%. The Cronbach's alpha and McDonald's omega were 0.72 and 0.70, respectively. Out of 315 parents, 84 responses were returned for test-retest reliability. All ICCs were good to excellent, ranging from 0.81 to 0.99. The PACV-Viet was confirmed to have construct validity. Using the PACV-Viet, 8.9% of the parents were found hesitant to childhood vaccination. Being unemployed and having seen the news about adverse events following immunisation were associated with parental vaccine hesitancy, with AOR = 3.2 (95% CI 1.3-8.0) and AOR = 4.5 (95% CI 1.2-16.7), respectively.

CONCLUSIONS

The PACV-Viet is a valid and reliable tool. Community outreach is necessary to alleviate parents' concerns about childhood vaccination.

Avoidance of causality outside experiments: Hypotheses from cognitive dissonance reduction

The avoidance of causality in the design, analysis and interpretation of non-experimental studies has often been criticised as an untenable scientific stance, because theories are based on causal relations (and not associations) and a rich set of methodological tools for causal analysis has been developed in recent decades. Psychology researchers (n = 106 with complete data) participated in an online study presenting a causal statement about the results of a fictitious paper on the potential effect of drinking clear water for years on the risk of dementia. Two randomised groups of participants were then asked to reflect on the conflict between the goal of approaching a causal answer and the prevailing norm of avoiding doing so. One of the two groups was also instructed to think about possible benefits of addressing causality. Both groups then responded to a list of 19 items about attitudes to causal questions in science. A control group did this without reflecting on conflict or benefits. Free-text assessments were also collected during reflection, giving some indication of how and why causality is avoided. We condense the exploratory findings of this study into five new hypotheses about the how and why, filtered through what can be explained by cognitive dissonance reduction theory. These concern the cost of addressing causality, the variety of ways in which dissonance can be reduced, the need for profound intervention through teaching and social aspects. Predictions are derived from the hypotheses for confirmation trials in future studies and recommendations for teaching causality. Open data are provided for researchers' own analyses.

Conspiracy Theory as Individual and Group Behavior: Observations from the Flat Earth International Conference

Conspiratorial thinking has been with humanity for a long time but has recently grown as a source of societal concern and as a subject of research in the cognitive and social sciences. We propose a three-tiered framework for the study of conspiracy theories: (1) cognitive processes, (2) the individual, and (3) social processes and communities of knowledge. At the level of cognitive processes, we identify explanatory coherence and faulty belief updating as critical ideas. At the level of the community of knowledge, we explore how conspiracy communities facilitate false belief by promoting a contagious sense of understanding, and how community norms catalyze the biased assimilation of evidence. We review recent research on conspiracy theories and explain how conspiratorial thinking emerges from the interaction of individual and group processes. As a case study, we describe observations the first author made while attending the Flat Earth International Conference, a meeting of conspiracy theorists who believe the Earth is flat. Rather than treating conspiracy belief as pathological, we take the perspective that is an extreme outcome of common cognitive processes.

Confirmation bias emerges from an approximation to Bayesian reasoning

Confirmation bias is defined as searching for and assimilating information in a way that favours existing beliefs. We show that confirmation bias emerges as a natural consequence of boundedly rational belief updating by presenting the BIASR model (Bayesian updating with an Independence Approximation and Source Reliability). In this model, an individual's beliefs about a hypothesis and the source reliability form a Bayesian network. Upon receiving information, an individual simultaneously updates beliefs about the hypothesis in question and the reliability of the information source. If the individual updates rationally then this introduces numerous dependencies between beliefs, the tracking of which represents an unrealistic demand on memory. We propose that human cognition overcomes this memory limitation by assuming independence between beliefs, evidence for which is provided in prior research. We show how a Bayesian belief updating model incorporating this independence approximation generates many types of confirmation bias, including biased evaluation, biased assimilation, attitude polarisation, belief perseverance and confirmation bias in the selection of sources.