Perceptual Bias Research Articles

Does culture moderate the encoding and recognition of negative cues? Evidence from an eye-tracking study.

Cross-cultural research has elucidated many important differences between people from Western European and East Asian cultural backgrounds regarding how each group encodes and consolidates the contents of complex visual stimuli. While Western European groups typically demonstrate a perceptual bias towards centralised information, East Asian groups favour a perceptual bias towards background information. However, this research has largely focused on the perception of neutral cues and thus questions remain regarding cultural group differences in both the perception and recognition of negative, emotionally significant cues. The present study therefore compared Western European (n = 42) and East Asian (n = 40) participants on a free-viewing task and a subsequent memory task utilising negative and neutral social cues. Attentional deployment to the centralised versus background components of negative and neutral social cues was indexed via eye-tracking, and memory was assessed with a cued-recognition task two days later. While both groups demonstrated an attentional bias towards the centralised components of the neutral cues, only the Western European group demonstrated this bias in the case of the negative cues. There were no significant differences observed between Western European and East Asian groups in terms of memory accuracy, although the Western European group was unexpectedly less sensitive to the centralised components of the negative cues. These findings suggest that culture modulates low-level attentional deployment to negative information, however not higher-level recognition after a temporal interval. This paper is, to our knowledge, the first to concurrently consider the effect of culture on both attentional outcomes and memory for both negative and neutral cues.

ChatGPT and Perception Biases in Investments: An Experimental Study

ChatGPT and Perception Biases in Investments: An Experimental Study

My Model is Unfair, Do People Even Care? Visual Design Affects Trust and Perceived Bias in Machine Learning.

Machine learning technology has become ubiquitous, but, unfortunately, often exhibits bias. As a consequence, disparate stakeholders need to interact with and make informed decisions about using machine learning models in everyday systems. Visualization technology can support stakeholders in understanding and evaluating trade-offs between, for example, accuracy and fairness of models. This paper aims to empirically answer "Can visualization design choices affect a stakeholder's perception of model bias, trust in a model, and willingness to adopt a model?" Through a series of controlled, crowd-sourced experiments with more than 1,500 participants, we identify a set of strategies people follow in deciding which models to trust. Our results show that men and women prioritize fairness and performance differently and that visual design choices significantly affect that prioritization. For example, women trust fairer models more often than men do, participants value fairness more when it is explained using text than as a bar chart, and being explicitly told a model is biased has a bigger impact than showing past biased performance. We test the generalizability of our results by comparing the effect of multiple textual and visual design choices and offer potential explanations of the cognitive mechanisms behind the difference in fairness perception and trust. Our research guides design considerations to support future work developing visualization systems for machine learning.

Plastic Surgeon versus Orthopedic Surgeon: Where Would You go for Your Hand Injury? A Cross-Sectional Study in Saudi Arabia.

Background Hand surgery has become a well-established medical specialty in recent years, with many highly trained hand surgeons practicing in various cities throughout Saudi Arabia. It is crucial to assess the public's knowledge and awareness regarding hand surgery specialists and to identify the existence of bias in the public's perception of plastic and Orthopedic surgeons. Methods A self-administered questionnaire was designed and disseminated to adults in Saudi Arabia via Google Forms. The questionnaire addressed participants' knowledge about which type of surgeon they would consult for various hand-related issues. Results A total of 716 participants were surveyed. Most believed Orthopedic surgeons were more qualified for hand surgeries than plastic surgeons. Furthermore, the public seemed to feel safer with Orthopedic surgeons regarding complications. There was a misconception regarding plastic surgeons' qualifications, with only 24.4% recognizing that all plastic surgeons could perform hand surgery. The majority also held misconceptions regarding Orthopedic surgeons' qualifications for hand surgery. Gender and educational level influenced the responses, with females and those with bachelor's degrees or higher showing slightly more knowledge. Conclusion There is a need for increased public awareness and education regarding the qualifications and capabilities of both plastic and Orthopedic surgeons in hand surgeries. Both specialties are well-trained and competent in this area, and the choice should be based on the specific needs and circumstances of the patient.

Where Does Wastewater-Based Epidemiology Fall in Medical Student Education?

Doctors are well-trained in the collection, analysis, and interpretation of individual stool or urine sample data; however, wastewater-based epidemiology (WBE) combines the excretion of many community members into an anonymous health sample tied to a geographic location. We advocate for the inclusion of WBE in medical education. WBE offers physicians an opportunity to better care for patients with diseases seen at health clinics and doctors' offices, customize and inform treatment, and accept positive results as true positives, backed by the contextual information provided by wastewater findings. It is also a tool to combat biased or misinformed risk perceptions. Medical education should include how to evaluate wastewater information presented, detect inconsistencies, and determine applicability; just as medical students are taught to do with data from other sources.

Neural signatures of emotional biases predict clinical outcomes in difficult-to-treat depression

Abstract Background: Neural predictors underlying variability in depression outcomes are poorly understood. Functional MRI measures of subgenual cortex connectivity, self-blaming and negative perceptual biases have shown prognostic potential in treatment-naïve, medication-free and fully remitting forms of major depressive disorder (MDD). However, their role in more chronic, difficult-to-treat forms of MDD is unknown. Methods: Forty-five participants (n = 38 meeting minimum data quality thresholds) fulfilled criteria for difficult-to-treat MDD. Clinical outcome was determined by computing percentage change at follow-up from baseline (four months) on the self-reported Quick Inventory of Depressive Symptomatology (16-item). Baseline measures included self-blame-selective connectivity of the right superior anterior temporal lobe with an a priori Brodmann Area 25 region-of-interest, blood-oxygen-level-dependent a priori bilateral amygdala activation for subliminal sad vs happy faces, and resting-state connectivity of the subgenual cortex with an a priori defined ventrolateral prefrontal cortex/insula region-of-interest. Findings: A linear regression model showed that baseline severity of depressive symptoms explained 3% of the variance in outcomes at follow-up (F[3,34] = .33, p = .81). In contrast, our three pre-registered neural measures combined, explained 32% of the variance in clinical outcomes (F[4,33] = 3.86, p = .01). Conclusion: These findings corroborate the pathophysiological relevance of neural signatures of emotional biases and their potential as predictors of outcomes in difficult-to-treat depression.

Pencirian Isyarat Data Muzik yang Terhasil dari Alat Muzik Tradisional Menggunakan Ciri Fraktal

Musical instruments are usually distinguished by their sound produced through human perception which may lead to misinterpretation due to auditory perception bias and other disturbances. Therefore, recognition using music signals is carried out to help characterize signals from different musical instruments. Fractal analysis is a mathematical tool used to study complex and irregular patterns in various systems. In this study, fractal analysis was used to study and analyze musical notes signal data from different instruments. The fractal analysis method used is the box counting method. The traditional musical instruments involved in this study are the seruling, cak lempong, kompang, and gambus. Matlab software was used to analyze the musical data signal. First, the fractal dimension of the music data signal in the form of time domain is calculated. Then, the mean and standard deviation of the fractal dimension values were determined to recognize different musical instruments. Additionally, different image resolutions and box sizes are also used to calculate the fractal dimension of musical instrument from the time domain data. The error of best fit line, E will also be calculated to ensure the reliability of box counting dimensions using leastsquares regression method. The results show that the value of the fractal dimension for all 18 data is between 1.2636 to 1.7543. In terms of musical instrument recognition, the recognition of seruling and kompang using mean fractal dimension is successful. However, this method is less suitable for identification for cak lempong and gambus due to the high standard deviation. By using different image resolutions and box sizes, the accuracy of fractal dimension values will be affected. Increasing these parameters increases the accuracy of the results. The results of the study show that an image with a resolution of 1024 x 1024 pixels and a scaling factor of 9 is suitable to analyze the fractal characteristics of musical instrument data signals by using the box counting method.

Optimism Bias in Firearm-Related Risk Perceptions

This survey study assesses the perceptions of California adults about the safety and risk of personal firearm use or access vs firearm use or access by others.

Müller-Lyer Illusion susceptibility is conditionally predicted by autistic trait expression.

Müller-Lyer (ML) figures bias size estimation consistently, yet different methods can lead to different degrees of illusory bias. Autistic individuals may also be less likely to perceive illusory biases with varying levels of autistic trait expression proposed to modulate reported illusory biases. The Autism-Spectrum Quotient (AQ) and Systemizing Quotient (SQ) are self-report measures that quantify autistic trait expression and systemizing ability in neurotypical individuals. The current study sought to determine if perceptions of illusory size bias negatively correlate with autistic trait expression and the extent to which varying methods of illusion presentation change the magnitude of illusory bias. Thirty neurotypical adults completed both questionnaires as well as four size estimation tasks. Two tasks involved perceptual discrimination of ML figures by concurrent and successive presentation, where participants selected the longer figure by keypress. For Tasks 3 and 4, participants adjusted the size of a non-illusory line (Task 3) or complementary illusory figure (Task 4) to match the perceived length. Overall, task performance was not correlated with autistic trait expression. One exception was a negative correlation with AQ when adjusting a complementary illusory ML figure in Task 4. Illusory biases were also stronger when two illusory figures were presented concurrently. Given these results, illusion susceptibility to the ML is suggested to be reduced with increases in AQ, but only when the method of illusion measurement is adjustment of concurrent illusory figures. Taken together the results provide evidence that traits associated with autism in a neurotypical population may systematically modulate perception.

Self-initiation enhances perceptual processing of auditory stimuli in an online study.

Understanding how the brain incorporates sensory and motor information will enable better theory building on human perception and behavior. In this study, we aimed to estimate the influence of predictive mechanisms on the magnitude and variability of sensory attenuation in two online samples. After the presentation of a visual cue stimulus, participants (Experiment 1: N = 224, Experiment 2: N = 84) compared the loudness of two consecutive tones in a two-alternative forced-choice task. In Experiment 1, the first tone was either self-initiated or not; in Experiment 2, the second tone was either self-initiated or not (active and passive condition, respectively). We further manipulated identity prediction (i.e., the congruence of pre-learned cue-sound combinations; congruent vs. incongruent), and the duration of the onset delay (to account for effects of attentional differences between the passive and active condition, 50 ms vs. 0 ms). We critically discuss our results within the framework of both classical (i.e., motor-based forward models) and contemporary approaches (i.e., predictive processing framework). Contrary to our preregistered hypothesis, we observed enhanced perceptual processing, instead of attenuation, for self-initiated auditory sensory input. Further, our results reveal an effect of fixed sound delays on the processing of motor and non-motor-based predictive information, and may point to according shifts in attention, leading to a perceptual bias. These results might best be captured by a hybrid explanatory model, combining predictions based on self-initiated motor action with a global predictive mechanism.

Top-down threat bias in pain perception is predicted by higher segregation between resting-state networks.

Top-down processes such as expectations have a strong influence on pain perception. Predicted threat of impending pain can affect perceived pain even more than the actual intensity of a noxious event. This type of threat bias in pain perception is associated with fear of pain and low pain tolerance, and hence the extent of bias varies between individuals. Large-scale patterns of functional brain connectivity are important for integrating expectations with sensory data. Greater integration is necessary for sensory integration; therefore, here we investigate the association between system segregation and top-down threat bias in healthy individuals. We show that top-down threat bias is predicted by less functional connectivity between resting-state networks. This effect was significant at a wide range of network thresholds and specifically in predefined parcellations of resting-state networks. Greater system segregation in brain networks also predicted higher anxiety and pain catastrophizing. These findings highlight the role of integration in brain networks in mediating threat bias in pain perception.

MATCHING DYADIC RESEARCH QUESTIONS WITH DYADIC ANALYTIC MODELS

Abstract Examining shared and common experiences between dyads affords opportunities to answer interesting research questions using dyadic data. Emerging dyadic methodology has expanded the types of research questions researchers can ask and answer. This session aims to equip researchers with knowledge and resources for grant writing, when planning new data collection projects, or when conducting secondary data analyses. Reviewing both cross-sectional and longitudinal methods, we will walk attendees through several types of research questions and match them with appropriate dyadic analytic strategies. These include the Actor-Partner Interdependence Model (APIM), the Common Fate Model, the Dyadic Growth Curve Model (and ALT Model), the Common Fate Growth Curve Model, the Random Intercept Cross-lagged Model, as well as various extensions. We will address accounting for non-independence in dyadic models, along with how to explore substantive dyadic processes. We will review ways that different approaches conceptualize, assess, and examine within and between dyad comparisons. We will also consider ways to address self and other reports of the same construct, such as health congruence/concordance or discordance/difference, as well as perceptions of accuracy or bias, enhancement, and idealization between dyads. Attendees will learn of resources available to learn more about the methods addressed in this session.

COGNITIVE MISPERCEPTION, DISABILITY, AND MORTALITY AMONG OLDER ADULTS IN 25 COUNTRIES

Abstract Despite a large body of literature on cognitive ability and health, less is known about the health consequences of biased cognitive perception. Using harmonized and nationally representative longitudinal surveys from 25 countries spanning Asia, Europe and the Americas, we document the growing gap between actual and perceived cognitive ability that appears to increase with age, and construct a standardized measure of cognitive misperception. Linking this novel measure with mortality and disability, we model the cognitive misperception – health gradient. Results show that being in the upper quartile of cognitive misperception (i.e., showing heightened overconfidence in cognition) leads to higher mortality rates within 1 year, 3 years, and 5 years. Conditional on survival, being overconfident in cognition also greatly increases the risks of incident disability and frailty, especially for older adults receiving less family support. We identify two possible pathways inducing poorer outcomes: the first stemming from increased risk taking and financial vulnerability; the second associated with suboptimal use of preventive services and declines in health-promoting behaviors. Given the large and profound impacts of cognitive misperception on older adults’ health and well-being, more family and social supports, public investment in education and health literacy, and better healthcare access and affordability are needed to increase the timely awareness of cognitive decline.

Daily perceptions of romantic partner autonomy support and undermining of health behavior

Objective This study examined accuracy and bias in daily perceptions of a romantic partner’s autonomy support and undermining of health behaviors and the associations between misperceptions and both partners’ daily experiences. Design A sample of 106 cohabiting couples from the community completed daily reports (N = 2377) of their own and their partner’s autonomy support and undermining, and their daily experiences. Results We found tracking accuracy and projection in perceptions of provider’s autonomy support and undermining, and evidence of misperceptions: people over-perceived the provider’s undermining and under-perceived the provider’s autonomy support. Misperceptions were linked with more negative experiences, indicating support and undermining may have the most benefit and least harm when more accurately perceived. Conclusion Although there is some accuracy in daily perceptions of provider support and undermining of health behaviors, there are also biases at play in perceptions and misperceptions are linked with more negative experiences, indicating that support and undermining have the most benefit and least harm to both perceiving and providing partners when such behaviors are accurately perceived.

Missing a beam in thine own eye: Motivated perceptions of collective narcissism

This work examines lay beliefs about the societal implications of different forms of ingroup identity. While secure ingroup identity reflects a genuine attachment to one’s ingroup members, defensive forms of identity are aimed at satisfying individual enhancement motives through highlighting belongingness to an exceptional group. The latter can be exemplified by collective narcissism, a belief in ingroup greatness and entitlement to privileged treatment, which has been linked to undesirable intra- and intergroup outcomes. In three experiments (total N = 473), conducted in the context of national identities, we investigated how people perceive the manifestations of collective narcissism, contrasted with secure ingroup identity and low identity. Across all studies, participants expected the highest outgroup hostility and poorest intragroup relations from those high in collective narcissism. However, perceivers who were themselves high in collective narcissism were less likely to expect these undesirable manifestations, thus revealing a biased perception of similar others.

The Role of Media in Risk Management Processes—Analysis of the News Coverage of the Forest Fires in Spain

This paper focuses on the analysis of information on environmental catastrophes published in the digital editions of different national and regional newspapers, from a theoretical perspective that situates them as possible amplifiers of the social perception of risk or generators of alarm among the population in situations of risk or catastrophe. Within this framework, the general objective of the research was to find out to what extent the analysed media (a) transmit specialized, accurate, truthful and contrasted information that moves away from the characteristics of sensationalist news; (b) are useful sources of information for the public in the face of the possibility that they may act as generators of confusion and biased perceptions; and (c) show “communication gaps” in their news in relation to two cases of forest fires in Spain: the fires in Galicia in 2017 and those in Gran Canaria in 2019. The results obtained highlight the need for the media to make an effort to transmit truthful and useful communication for citizens in situations of crisis or catastrophe.

Perception and attitude toward the regulation of online video streaming (in South Korea)

Abstract As the production and consumption of live video streaming have increased, a general concern is that live video streaming might yield social problems. This paper investigated how people perceived the current status of live video streaming through a nationwide survey. The survey was conducted with 825 users and 335 non-users in South Korea. The results demonstrate that people perceived live video streaming has more impact on adolescents than themselves, which confirms that the previous study of third-person perception. Respondents also evaluated that the current self-regulatory system is not functioning properly and regulation of live video streaming is required. Especially non-users are more supportive of regulation than users. The perception bias, the difference between the perceived influence on self and adolescents, is the strongest predictor of the need for regulation. Because of the difference between users and non-users regarding the perception of live video streaming, this study recommends that the policymakers should consider the actual status of live video streaming and not perception-based biases in orienting regulation.

Kesetaraan Gender Egalitarianisme dalam Narasi Film Barbie melalui Perspektif Konstruktivisme

The issue of gender equality is not something new today. This issue has been widely discussed in a series of interesting stories full of meaning, one of which is in the form of a film. This research explores the representation of gender equality in the Barbie film released in 2023 and directed by Greta Gerwig from a constructivist perspective. The Barbie film is mass media that influences people's perceptions of gender bias. In the context of constructivism, films are considered the result of construction by media professionals, which can strengthen or change gender stereotypes that already exist in society. The research method used is a qualitative approach with Roland Barthes' semiotic analysis. The constructivism paradigm is used to understand how reality is understood and constructed by research subjects. The research subject is the representation of gender equality in the Barbie film narrative, while the research object is the dialogues in the film that will be analyzed. The results of the analysis show that the Barbie film depicts excessive expectations placed on women and criticizes views that trivialize or simplify issues of gender equality. The conclusion of this research is that the Barbie film as part of mass media depicts gender equality issues in a complex way and triggers critical thinking about gender stereotypes in society.

Medical Trainees' Knowledge and Attitudes Towards Electronic Cigarettes and Hookah: A Multinational Survey Study.

The rising prevalence of electronic cigarette (e-cigarette) and hookah use among youth raises questions about medical trainees' views of these products. We aimed to investigate medical trainees' knowledge and attitudes toward e-cigarette and hookah use. We used data from a large cross-sectional survey of medical trainees in Brazil, the United States, and India. We investigated demographic and mental health aspects, history of e-cigarettes and tobacco use, knowledge and attitudes toward e-cigarettes and hookah, and sources of information on e-cigarettes and hookah. Although all medical trainees were eligible for the original study, only senior students and physicians-in-training were included in the present analysis. Of 2,036 senior students and physicians-in-training, 27.4% believed e-cigarette use to be less harmful than tobacco smoking. As for hookah use, 14.9% believed it posed a lower risk than cigarettes. More than a third of trainees did not acknowledge the risks of passive e-cigarette use (42.9%) or hookah smoking (35.1%). Also, 32.4% endorsed e-cigarettes to quit smoking, whereas 22.5% felt ill equipped to discuss these tobacco products with patients. Fewer than half recalled attending lectures on these topics, and their most common sources of information were social media (54.5%), Google (40.8%), and friends and relatives (40.3%). Medical trainees often reported incorrect or biased perceptions of e-cigarettes and hookah, resorted to unreliable sources of information, and lacked the confidence to discuss the topic with patients. An expanded curriculum emphasis on e-cigarette and hookah use might be necessary because failing to address these educational gaps could risk years of efforts against smoking normalization.

Improving Text-Independent Forced Alignment to Support Speech-Language Pathologists with Phonetic Transcription.

Problem: Phonetic transcription is crucial in diagnosing speech sound disorders (SSDs) but is susceptible to transcriber experience and perceptual bias. Current forced alignment (FA) tools, which annotate audio files to determine spoken content and its placement, often require manual transcription, limiting their effectiveness. Method: We introduce a novel, text-independent forced alignment model that autonomously recognises individual phonemes and their boundaries, addressing these limitations. Our approach leverages an advanced, pre-trained wav2vec 2.0 model to segment speech into tokens and recognise them automatically. To accurately identify phoneme boundaries, we utilise an unsupervised segmentation tool, UnsupSeg. Labelling of segments employs nearest-neighbour classification with wav2vec 2.0 labels, before connectionist temporal classification (CTC) collapse, determining class labels based on maximum overlap. Additional post-processing, including overfitting cleaning and voice activity detection, is implemented to enhance segmentation. Results: We benchmarked our model against existing methods using the TIMIT dataset for normal speakers and, for the first time, evaluated its performance on the TORGO dataset containing SSD speakers. Our model demonstrated competitive performance, achieving a harmonic mean score of 76.88% on TIMIT and 70.31% on TORGO. Implications: This research presents a significant advancement in the assessment and diagnosis of SSDs, offering a more objective and less biased approach than traditional methods. Our model's effectiveness, particularly with SSD speakers, opens new avenues for research and clinical application in speech pathology.