Easy-fix attentional focus manipulation boosts the intuitive and deliberate use of base-rate information.

In addressing human reasoning biases, "easy-fix" attentional focus interventions have shown that we can prompt reasoners to align responses with logico-mathematical principles. The current study aimed to test the impact of such interventions on both intuitive and deliberate responses on base-rate items. Using a two-response paradigm, participants provided initial intuitive responses under time constraints and cognitive load, followed by deliberate responses. During the intervention, we used attentional focus manipulations with base-rate items that aimed to redirect participants' attention toward the "logical" base-rate cue (i.e., the logical intervention) or toward the "heuristic" descriptive cue (i.e., the heuristic intervention). The results indicate that the logical intervention led to improved alignment with logico-mathematical principles in both intuitive and deliberate responses, albeit with a modest effect size. Conversely, the heuristic intervention had no discernible impact on accuracy. This indicates that our attentional focus manipulation is more effective at getting reasoners to respect rather than to override base-rates.

Social-cognitive biases underlying the development of ableism.

Disabled people are the largest minority group in the world. Like members of many minority groups, they face considerable prejudice and discrimination-known as ableism. Ableism reflects entrenched beliefs about what human bodies and minds should be like and a devaluation of individuals who deviate from that ideal. There is surprisingly little psychological science about ableism, and even less about its development. This chapter considers how social-cognitive biases evident in early childhood could contribute to its development. The chapter is structured around four biases: Prescriptive reasoning, promiscuous teleology, psychological essentialism, and the positivity bias. For each bias, we review foundational research about how it manifests in early childhood, speculate about its connection to ableism, and outline avenues for additional research. Understanding how social-cognitive biases contribute to the development of ableism is an important first step in efforts to equip children (and adults) with the tools to reject it.

Cognitive vulnerabilities and depressed mood in acquired brain injury.

ABSTRACTAcquired Brain Injury (ABI), an important cause of long-term disability, is associated with increased rates of depression in addition to common cognitive and physical consequences. Past research has linked post-ABI depression to injury severity (e.g., extent of physical or cognitive impairment) and premorbid mood problems. In the general (non-ABI) population, depression is associated with cognitive vulnerabilities that have informed the development of psychological interventions. In this observational study in a heterogeneous sample of individuals with chronic stage ABI, we examine two cognitive vulnerabilities - dysfunctional attitudes (DAs) and autobiographical memory specificity - and explore whether these are linked to depression symptoms and ongoing cognitive difficulties as in the general population. Compared to control participants, individuals with an ABI demonstrated increased endorsement of DAs and reduced specificity of autobiographical memory recall. Within the ABI group, cognitive vulnerability-depression symptom correlations were detected for an explicit measure of DAs, but not for a more implicit DA measure or for autobiographical memory specificity. While individual differences in injury severity and other factors likely obscured subtle relationships between mood and cognitive vulnerabilities, evidence of these vulnerabilities may be relevant to changes in identity and psychological interventions that target low mood in ABI.

Artistic turns: laterality in paintings of kisses and embraces.

Many lateral biases exist in human behavior, often implicit and not deliberated. Romantic kissing and embracing received experimental attention in the last three decades. We investigated laterality in paintings depicting these social interactions using two methodologies to assess whether painters depicted such biases and whether these biases could be due to observers' aesthetic preferences or painters' ability in portraying naturalistic interactions. In Study 1, we inspected about 190,000 artworks available online to classify leftward and rightward biases in romantic kisses and embraces. The comparison of 103 paintings depicting clearly lateralized interactions revealed a significant rightward bias in romantic kissing (66%) and a trend toward a leftward bias (62%) for embraces, aligning with naturalistic studies of human interactions. In Study 2, 128 participants expressed their aesthetic preference between the paintings selected in Study 1 and their vertically mirrored versions. A preference for the original paintings over their mirrored versions emerged, especially when presented in the upper portion of the screen, but no significant preference for the typical lateralization of kissing and embracing was found. These findings suggest that artists' alignment with naturalistic biases could be due to familiarity and exposure to asymmetric interactions rather than observers' aesthetic preferences.

Is there an intergenerational discrepancy in the comprehension and aesthetic preference regarding emoji usage? Evidence from WeChat.

Emojis are widely used on social media, blogs, and instant messaging to express users' feelings. However, in everyday interactions, the same emoji often has different interpretations and aesthetic preferences among different age groups. This can lead to communication barriers and misunderstandings. Based on social identity theory, this study uses WeChat, a social platform popular in China, to analyze intergenerational differences in emoji understanding and preferences through a questionnaire survey. The results indicate: (1) There are significant intergenerational differences in the usage habits, interpretation, and aesthetic preferences of emojis. (2) Middle-aged and elderly tend to interpret goodbye emoji symbols as simple emotional expressions, such as "goodbye" or "see you later," while younger-age groups lean towards more complex emotions and social intentions, such as "speechlessness" and "end of friendship." (3) Younger-age groups use emojis frequently and with a wide variety, whereas middle-aged and elderly groups use emojis less frequently and with limited variety. Younger individuals' aesthetic preferences for emojis lean towards humor, conflict, and narrative, whereas middle-aged and elderly groups prefer emojis with bright colors and everyday greetings typical of their generation. Based on research findings, we believe that social identity theory provides a framework for understanding how individuals establish their identities through interactions with specific social groups. This study is beneficial for identifying the comprehension and aesthetic biases in emoji usage across generations, sheds light on the broader implications of social identity theory in digital communication contexts, and promotes friendly social interactions in real-time communication applications.

The Role of Self-Compassion and Social Anxiety in the Relationship Between Cognitive Distortions and Emotional Eating.

This study aimed to examine the mediating role of self-compassion and social anxiety in the relationship between cognitive distortions and emotional eating. The research was carried out on 406 adult individuals between the ages of 18-25 living in different regions of Turkey. To measure research variables, Liebowitz social anxiety, thought types, self-sensitivity, and Turkish emotional eating scale were used. The scales were distributed to the participants online. The data were analyzed through the SPSS program. In the study, it was determined that self-compassion predicted emotional eating negatively and social anxiety predicted emotional eating positively. According to the results of the serial mediation analysis, it was determined that self-compassion and social anxiety mediated the relationship between cognitive distortions and emotional eating separately.

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.

Critical appraisal of the CLSI guideline EP09c "measurement procedure comparison and bias estimation using patient samples".

BACKGROUND: In laboratory setting evaluating the agreement between two measurement methods is a very frequent practice. Unfortunately, the guidelines to refer to are not free from criticisms from a statistical methodological point of view. We reviewed the Clinical and Laboratory Standards Institute guideline EP09c, 3rd ed. pointing out some drawbacks and some aspects that have not been well defined, leaving situations of uncertainty and/or of excessive subjectivity in the judgement. CONTENT: We have stressed the need of having replicates to estimate the systematic and the proportional biases of the measurement methods to be compared. Indeed, unequal variance of the two measurement methods gives a slope and intercept of the regression between the difference and the mean of the two values of the measurement methods to be compared that can be absolutely calculated from their means, their variances and their correlation coefficient. So, it is not possible to disentangle true from spurious biases. For laboratory professionals we have developed a worked exemplification of an agreement assessment. SUMMARY: We have stressed the need of other approaches than the classic Bland and Altman method to calculate the systematic and proportional biases of two measurement methods compared for their agreement in a study with replicates.

Race norming and biases in surgical oncology care.

Disparities in surgical oncology care may be due to race/ethnicity. Race norming, defined as the adjustment of medical assessments based on an individual's race/ethnicity, and implicit bias are specifically explored in this focused systematic review. We aim to examine how race norming and bias impact oncologic care and postsurgical outcomes, particularly in Black patient populations, while providing potential strategies to improve equitable and inclusive care.

Exploring the Interplay of Dataset Size and Imbalance on CNN Performance in Healthcare: Using X-rays to Identify COVID-19 Patients.

INTRODUCTION: Convolutional Neural Network (CNN) systems in healthcare are influenced by unbalanced datasets and varying sizes. This article delves into the impact of dataset size, class imbalance, and their interplay on CNN systems, focusing on the size of the training set versus imbalance-a unique perspective compared to the prevailing literature. Furthermore, it addresses scenarios with more than two classification groups, often overlooked but prevalent in practical settings. METHODS: Initially, a CNN was developed to classify lung diseases using X-ray images, distinguishing between healthy individuals and COVID-19 patients. Later, the model was expanded to include pneumonia patients. To evaluate performance, numerous experiments were conducted with varied data sizes and imbalance ratios for both binary and ternary classifications, measuring various indices to validate the model's efficacy. RESULTS: The study revealed that increasing dataset size positively impacts CNN performance, but this improvement saturates beyond a certain size. A novel finding is that the data balance ratio influences performance more significantly than dataset size. The behavior of three-class classification mirrored that of binary classification, underscoring the importance of balanced datasets for accurate classification. CONCLUSIONS: This study emphasizes the fact that achieving balanced representation in datasets is crucial for optimal CNN performance in healthcare, challenging the conventional focus on dataset size. Balanced datasets improve classification accuracy, both in two-class and three-class scenarios, highlighting the need for data-balancing techniques to improve model reliability and effectiveness. MOTIVATION: Our study is motivated by a scenario with 100 patient samples, offering two options: a balanced dataset with 200 samples and an unbalanced dataset with 500 samples (400 healthy individuals). We aim to provide insights into the optimal choice based on the interplay between dataset size and imbalance, enriching the discourse for stakeholders interested in achieving optimal model performance. LIMITATIONS: Recognizing a single model's generalizability limitations, we assert that further studies on diverse datasets are needed.

The relationship between morningness-eveningness and naturalness bias.

The naturalness bias in which people perceive natural items to be safer, healthier, and better than synthetic alternatives has been found to be associated with numerous individual difference variables (e.g. connectedness to nature and religiosity). However, no research has examined the role of morningness-eveningness in influencing preferences for naturalness. Here, we propose that evening individuals may exhibit a weaker preference for naturalness compared to morning individuals due to their greater exposure to artificial lighting, technology, and stimuli. To systematically test our theoretical perspective, we conducted three complementary and high-powered studies. In an online survey (Study 1), student participants with a stronger evening orientation displayed a diminished preference for natural drugs compared to those with a morning orientation. Using a sample of community adults, Study 2 replicated the findings of Study 1 in a real-world, behavioral context. Study 3 examined the relationship between morningness-eveningness and preference for naturalness within the domain of beverages. The results revealed that individuals with an evening-orientation had decreased odds of selecting natural water without minerals. Taken together, the findings suggest that an individual's diurnal preference toward eveningness may have implications for their bias toward and perception of naturalness across various domains.

Quantitative bias analysis methods for summary level epidemiologic data in the peer-reviewed literature: a systematic review.

OBJECTIVE: Quantitative bias analysis (QBA) methods evaluate the impact of biases arising from systematic errors on observational study results. This systematic review aimed to summarize the range and characteristics of quantitative bias analysis (QBA) methods for summary level data published in the peer-reviewed literature. STUDY DESIGN AND SETTING: We searched MEDLINE, Embase, Scopus, and Web of Science for English-language articles describing QBA methods. For each QBA method, we recorded key characteristics, including applicable study designs, bias(es) addressed; bias parameters, and publicly available software. The study protocol was pre-registered on the Open Science Framework (https://osf.io/ue6vm/). RESULTS: Our search identified 10,249 records, of which 53 were articles describing 57 QBA methods for summary level data. Of the 57 QBA methods, 53 (93%) were explicitly designed for observational studies, and 4 (7%) for meta-analyses. There were 29 (51%) QBA methods that addressed unmeasured confounding, 19 (33%) misclassification bias, 6 (11%) selection bias, and 3 (5%) multiple biases. 38 (67%) QBA methods were designed to generate bias-adjusted effect estimates and 18 (32%) were designed to describe how bias could explain away observed findings. 22 (39%) articles provided code or online tools to implement the QBA methods. CONCLUSION: In this systematic review, we identified a total of 57 QBA methods for summary level epidemiologic data published in the peer-reviewed literature. Future investigators can use this systematic review to identify different QBA methods for summary level epidemiologic data.

Challenging biases in delivery mode decisions for women with pelvic fracture history: a call for evidence-based practices and patient-centered care.

Pelvic fractures significantly impact young individuals, with a prevalence of 20 per 100,000, leading to long-term complications such as chronic pain and genitourinary dysfunction. Notably, women with a history of pelvic fractures face increased cesarean section (C-sections) rates during childbirth. This editorial investigates the factors contributing to higher C-section rates in these women, including provider assumptions about delivery complications and systemic hospital biases. Despite these trends, evidence suggests that vaginal delivery can be successful, especially when considering factors like pelvic displacement and the timing of delivery post-fracture. We advocate for education programs to challenge provider biases, transparent patient communication, and evidence-based practices prioritizing patient-centered care. Addressing these issues can enhance maternal and fetal outcomes, supporting women in making informed decisions about their delivery options.

The influence of emotional intelligence and behavioural biases on mutual fund churning frequency: Evidence from India.

Behavioural finance invalidates the rationalistic assumptions of the efficient market hypothesis by proposing a realistic explanation for overreaction and underreaction. These phenomena are caused by investors making financial decisions based on their emotions without realizing them. This study attempts to establish the effect of investors' emotional intelligence on behavioural biases, namely, herding, overconfidence bias, and disposition effects, and its consequences for the churning frequency of mutual fund portfolios. This quantitative cross-sectional study was undertaken to collect data from 499 mutual fund investors using a self-administered questionnaire. We found that the disposition effect has a negative impact and that overconfidence bias positively affects the churning frequency of mutual fund portfolios. Furthermore, emotional intelligence, particularly its subconstructs, affects herding bias and overconfidence bias, ultimately impacting the churning frequency of investors. An investor with a higher level of self-motivation is likely to have a disposition effect and herding bias. Investors with disposition impact may be encouraged to reorganize their portfolio if there are any schemes that have been providing negative returns for more than two years or that are not projected to offer significant returns in the future. By understanding how they stack up on each emotional intelligence metric, investors and financial advisors may focus on avoiding the biases that could jeopardize long-term portfolio returns.

Biases in Ecoacoustics Analysis: A Protocol to Equalize Audio Recorders.

Eco-acoustic indices allow us to rapidly evaluate habitats and ecosystems and derive information about anthropophonic impacts. However, it is proven that indices' values and trends are not comparable between studies. These incongruences may be caused by the availability on the market of recorders with different characteristics and costs. Thus, there is a need to reduce these biases and incongruences to ensure an accurate analysis and comparison between soundscape ecology studies and habitat assessments. In this study, we propose and validate an audio recording equalization protocol to reduce eco-acoustic indices' biases, by testing three soundscape recorder models: Song Meter Micro, Soundscape Explorer Terrestrial and Audiomoth. The equalization process aligns the signal amplitude and frequency response of the soundscape recorders to those of a type 1 level meter. The adjustment was made in MATLAB R2023a using a filter curve generated comparing a reference signal (white noise); the measurements were performed in an anechoic chamber using 11 audio sensors and a type 1 sound level meter (able to produce a .WAV file). The statistical validation of the procedure was performed on recordings obtained in an urban and Regional Park (Italy) assessing a significant reduction in indices' biases on the Song Meter Micro and Audiomoth.

Investigating a bias account of emotional false memories using a criterion warning and force choice restrictions at retrieval.

Here, we add to the debate as to whether false recognition of emotional stimuli is more memory-based or more bias-based. Emotional false memory findings using the DRM paradigm have been marked by higher false alarms to negatively arousing compared to neutral critical lure items. Explanation for these findings has mainly focused on false memory-based accounts. However, here we address the question of whether a response bias for emotional stimuli can, at least in part, explain this phenomenon. In Experiment 1, we used a criterion warning, previously shown to increase more conservative responding and reduce false recognition. Experiment 2, we employed a two-alternative-forced choice test, which minimises the role of criterion setting. In both experiments, we compared false alarms to negative and neutral critical lures. We observed a significant decrease in false recognition rates for both negative and neutral critical lures under the conditions of forced choice restriction and criterion warning. However, despite these conditions, negative items, compared to their neutral counterparts, still consistently provoked a higher degree of false recognition. The discussion that follows presents an exploration of both memory-based accounts and criterion-setting explanations for the enhanced emotional false memory finding.

Emergent perceptual biases from state-space geometry in trained spiking recurrent neural networks.

A stimulus held in working memory is perceived as contracted toward the average stimulus. This contraction bias has been extensively studied in psychophysics, but little is known about its origin from neural activity. By training recurrent networks of spiking neurons to discriminate temporal intervals, we explored the causes of this bias and how behavior relates to population firing activity. We found that the trained networks exhibited animal-like behavior. Various geometric features of neural trajectories in state space encoded warped representations of the durations of the first interval modulated by sensory history. Formulating a normative model, we showed that these representations conveyed a Bayesian estimate of the interval durations, thus relating activity and behavior. Importantly, our findings demonstrate that Bayesian computations already occur during the sensory phase of the first stimulus and persist throughout its maintenance in working memory, until the time of stimulus comparison.

Serial dependence: A matter of memory load.

In serial dependence, perceptual decisions are biased towards stimuli encountered in the recent past. Here, we investigate whether and how serial dependence is affected by the availability of visual working memory (VWM) resources. In two experiments, participants reproduced the orientation of a series of stimuli. On alternating trials, we included an additional VWM task with randomly varying levels of load. Serial dependence was not only affected by the additional load task but also clearly modulated by the level of load: a high load in the previous trial reduced serial dependence while a high load in the present increased it. These results were independent of the effects of VWM load on the precision of reproduction responses. Our findings provide new insights into the mechanisms that may regulate serial dependence, revealing its intimate link with VWM resources. Significance statement: Our perception, thoughts, and behavior are continuously influenced by recent events. For instance, the way we process and understand current visual information depends on what we have seen in the preceding seconds, a phenomenon known as serial dependence. The precise mechanisms and factors involved in serial dependence are still unclear. Here, we demonstrated that working memory resources are a crucial component. Specifically, when we are currently experiencing a heavy memory load, the influence of prior stimuli becomes stronger. Conversely, when prior stimuli were shown under a high memory load, their influence was reduced. These findings highlight the importance of working memory resources in shaping our interpretation of the present based on the recent past.

How School Burnout Affects Depression Symptoms Among Chinese Adolescents: Evidence from Individual and Peer Clique Level.

The impact of peer clique school burnout norms on adolescents' emotional adaptation is becoming increasingly prominent, but its underlying mechanisms remain unclear, especially in China where academic achievement is highly valued. The present study examined how clique burnout norms impact the relationship between school burnout, negative cognitive bias, and depressive symptoms. A total of 904 Chinese adolescents (57% boys; Mage = 12.73, SD = 0.43) participated in a two-wave longitudinal study (initiated in 2015, with approximately a 2-year interval). The results of multilevel models indicated that only in low clique burnout norms, adolescents with high school burnout at T1 would exhibit more negative cognitive bias and suffer from more depressive symptoms at T2, whereas the moderating effect was only observed in all-boys cliques. These findings reflect that a decrease in the overall level of burnout within a peer clique does not necessarily benefit every student, and the adaptation issues of students experiencing burnout still require attention even in a relatively healthy context.