Attribution Bias Research Articles

Research on similarity bias in dual objective visual search based on nuclear power human-machine interface icons

Using icons from nuclear power interface as the research object, this study explored how icon similarity affected the performance of dual objective visual search. Firstly, the process of generating similarity bias was described from the perspective of human cognitive processing. The feature attributes of nuclear power icons were extracted, and then associated and mapped with similarity bias attributes. Secondly, a total of 16 instruction icons, device icons, and component icons were selected to propose icon coding logic for different similarity dimensions, and similarity experimental materials were designed. Finally, a dual objective search experiment with a 4 × 4 matrix was conducted to explore the impact of graph similarity on search performance and to determine the priority of perceptual similarity, semantic similarity, and memory similarity. High-level (H) similarity between the two targets resulted in superior visual search performance (p = 0.01 between the response times of similarity high and medium/low). Improving experiential familiarity enhanced search performance in cases of low-level (L) (p = 0.021) and medium-level (M) (p ≤ 0.009) icon similarity, but had no significant impact on search performance in cases of high-level (H) similarity (p ≥ 0.269). Compared to semantic similarity, enhancing perceptual similarity was more likely to improve search performance(p = 0.024).

Blunted Cortisol Awakening Response Is Associated with External Attribution Bias Among Individuals with Personality Disorders.

The dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis has been associated with various mental disorders. One of the most commonly described parameters of HPA axis functioning is the cortisol awakening response (CAR). To date, few studies have been conducted on the relationship between personality disorders and CAR. The present study aimed to compare the CAR between individuals with personality disorders and healthy controls. Moreover, the study aimed to assess the association of CAR with cognitive biases and psychopathological symptoms in people with personality disorders. A total of 43 individuals with personality disorders and 45 healthy controls were enrolled. Participants completed questionnaires measuring the severity of depressive symptoms, anxiety, cognitive biases, and psychotic-like experiences. Cortisol levels were measured in four morning saliva samples: immediately after awakening, and after 15, 30, and 45 min. A significantly lower CAR was found among individuals with personality disorders, even after adjustment for age, sex, and the level of education. However, the receiver operating characteristic (ROC) curve analysis showed a relatively low area under the curve (AUC = 0.362). Furthermore, a significant negative correlation was observed between the CAR and the level of external attribution bias among individuals with personality disorders. No significant associations of the CAR with psychopathological symptoms and other cognitive biases were observed. Findings from this study indicate that the HPA axis activity might be altered in personality disorders. However, the clinical utility of this observation needs further studies in larger samples. External attribution might be related to the HPA axis alterations in this population.

Mandibular second molar impaction: introducing a novel and validated 3D classification system

BackgroundMandibular second molar (M2M) impaction is a clinically significant manifestation of eruption disturbance in dental development. The primary aim of this study was to investigate the impact of the three-dimensional (3D) characterization on clinical and therapeutic decisions for M2M impaction. The secondary aim was to introduce a validated 3D classification system incorporating both surgical and orthodontic parameters.MethodsBidimensional (2D) and 3D radiological records of 15 impacted M2M were collected and deidentified. Ten experienced clinicians (5 oral surgeons;5 orthodontists) categorized each case, first based on 2D records and then with 3D scans. The degree of orthodontic and surgical difficulty in treating impacted M2M was evaluated using a novel classification system based on anatomical and radiological features. The primary outcome variable was the assessment of differences in diagnosis and decision-making protocol using 2D or 3D records, where clinical relevance ranged from 0 to 4. The secondary outcome variable was the validation analysis of the proposed 3D classification system to determine the concordance among the clinicians. Descriptive statistics and multivariable inferential analysis based on Akaike information criterion (AIC) were performed (α = 0.05).Results3D examination allowed a better visualization of M2M impaction with higher clinical relevance for diagnosis of M2M root relationship to alveolar nerve and lingual plate, height to alveolar crest, depth, and inclination relative to the first molar and position relative to the third molar (range:2.69–3.43). The proposed 3D classification of M2M impaction changed clinical decisions regarding surgical-orthodontic approach, biomechanics, patient education, and treatment time estimate (range:2.59–3.33). In the validation analysis of the classification, no evidence of inter- or intra-group (surgeon/orthodontist) bias in score attribution occurred: the model with the minimum AIC was the null model (AIC = 718.04).Conclusion3D evaluation of impacted M2Ms could enhance diagnostic accuracy, and a classification system was proposed and validated by a group of experienced surgeons and orthodontists with high concordance.

Outcomes of the American Board of Dermatology focused Practice Improvement program 2016-2023

BackgroundBoard-certified dermatologists experience diverse practice gaps. ObjectiveIdentify the top self-selected focused Practice Improvement (fPI) modules completed over time by board-certified dermatologists during the program’s first 8 years. MethodsCohort study of dermatologists certified by American Board of Dermatology (ABD) completing fPI modules from 2016 to 2023. This descriptive analysis reports modules completed by topic, subspecialty, relevance, and self-reported changes to subsequent patient care related to modules. Results19143 fPI modules were completed by 7378 unique ABD diplomates, representing 48.8% of all current ABD-certified dermatologists (n = 15118). Modules were rated relevant by 18917 participants (99%). Care gaps requiring improvement efforts and performance remeasurement occurred in 2919 (15.2%) completed modules. Acne and medication-related laboratory monitoring were popular topics requiring improvement. Diplomates reported care improvements resulting from completing modules in 8397 instances (43.9%), and improved patient outcomes in at least one patient 5310 times (27.7%). Finally, diplomates stated they would recommend fPI modules to peers 18633 (97.3%) times. LimitationsDermatologists who started but did not complete modules would not have rated the module. Attribution bias on care impact is possible and potentially overestimated. ConclusionThe ABD fPI program is helping board-certified dermatologists identify and improve gaps in care with reported patient outcome improvements.

Bias Defended

Abstract In this paper, I clarify and defend some of the central ideas of Bias in response to commentators, with a special focus on the theme of skepticism. In response to Michael Veber, I defend the project of offering a modest as opposed to an ambitious response to the skeptic. In response to Jonathan Matheson, I defend my account of the way in which bias attributions function in contexts of interpersonal disagreement, as well as the claim that an unbiased believer will generally be in a stronger position to resist skeptical pressure from disagreement than a biased believer. In response to Brett Sherman, I clarify the way in which my account of bias accommodates the phenomenon of biased suspension of judgment, and I explore some of the connections between bias, suspension of judgment, and skepticism. In response to Jared Celinker and Nathan Ballantyne, I defend the possibility of emergent biases.

Disrupted basolateral amygdala circuits supports negative valence bias in depressive states

Negative bias is an essential characteristic of depressive episodes leading patients to attribute more negative valence to environmental cues. This negative bias affects all levels of information processing including emotional response, attention and memory, leading to the development and maintenance of depressive symptoms. In this context, pleasant stimuli become less attractive and unpleasant ones more aversive, yet the related neural circuits underlying this bias remain largely unknown. By studying a mice model for depression chronically receiving corticosterone (CORT), we showed a negative bias in valence attribution to olfactory stimuli that responds to antidepressant drug. This result paralleled the alterations in odor value assignment we observed in bipolar depressed patients. Given the crucial role of amygdala in valence coding and its strong link with depression, we hypothesized that basolateral amygdala (BLA) circuits alterations might support negative shift associated with depressive states. Contrary to humans, where limits in spatial resolution of imaging tools impair easy amygdala segmentation, recently unravelled specific BLA circuits implicated in negative and positive valence attribution could be studied in mice. Combining CTB and rabies-based tracing with ex vivo measurements of neuronal activity, we demonstrated that negative valence bias is supported by disrupted activity of specific BLA circuits during depressive states. Chronic CORT administration induced decreased recruitment of BLA-to-NAc neurons preferentially involved in positive valence encoding, while increasing recruitment of BLA-to-CeA neurons preferentially involved in negative valence encoding. Importantly, this dysfunction was dampened by chemogenetic hyperactivation of BLA-to-NAc neurons. Moreover, altered BLA activity correlated with durable presynaptic connectivity changes coming from the paraventricular nucleus of the thalamus, recently demonstrated as orchestrating valence assignment in the amygdala. Together, our findings suggest that specific BLA circuits alterations might support negative bias in depressive states and provide new avenues for translational research to understand the mechanisms underlying depression and treatment efficacy.

Beyond Blame: Fostering an Accountability Culture Through Shared Leadership

This article discusses how organizations can move beyond a toxic "blame culture" and instead foster an "accountability culture" where teams share responsibility for both successes and failures. It explains how attribution biases and a lack of psychological safety enable defensive behaviors in blame cultures. Strategies are provided for leaders to establish accountability, including distributing leadership through cross-functional teams, facilitating regular feedback sessions, promoting data-driven problem solving, framing failures in terms of customer impact, and role modeling transparency. Case studies of Toyota, IDEO product design, and patient safety initiatives demonstrate how accountability cultures prioritize continual learning and collaboration over fault-finding. When teams focus on understanding root causes and preventing future mistakes rather than assigning blame, organizations can sustain high performance through innovation and resilience.

Marginal debiased network for fair visual recognition

Deep neural networks (DNNs) are often prone to learn the spurious correlations between target classes and bias attributes, like gender and race, inherent in a major portion of training data (bias-aligned samples), thus showing unfair behavior and arising controversy in the modern pluralistic and egalitarian society. In this paper, we propose a novel marginal debiased network (MDN) to learn debiased representations. More specifically, a marginal softmax loss (MSL) is designed by introducing the idea of margin penalty into the fairness problem, which assigns a larger margin for bias-conflicting samples (data without spurious correlations) than for bias-aligned ones, so as to deemphasize the spurious correlations and improve generalization on unbiased test criteria. To determine the margins, our MDN is optimized through a meta learning framework. We propose a meta equalized loss (MEL) to perceive the model fairness, and adaptively update the margin parameters by meta-optimization which requires the trained model guided by the optimal margins should minimize MEL computed on an unbiased meta-validation set. Extensive experiments on BiasedMNIST, Corrupted CIFAR-10, CelebA and UTK-Face datasets demonstrate that our MDN can achieve a remarkable performance on under-represented samples and obtain superior debiased results against the previous approaches.

Perception of emotional facial expressions in aggression and psychopathy.

Altered affective state recognition is assumed to be a root cause of aggressive behavior, a hallmark of psychopathologies such as psychopathy and antisocial personality disorder. However, the two most influential models make markedly different predictions regarding the underlying mechanism. According to the integrated emotion system theory (IES), aggression reflects impaired processing of social distress cues such as fearful faces. In contrast, the hostile attribution bias (HAB) model explains aggression with a bias to interpret ambiguous expressions as angry. In a set of four experiments, we measured processing of fearful and angry facial expressions (compared to neutral and other expressions) in a sample of 65 male imprisoned violent offenders rated using the Hare Psychopathy Checklist-Revised (PCL-R, Hare, R. D. (1991). The psychopathy checklist-revised. Toronto, ON: Multi-Health Systems) and in 60 age-matched control participants. There was no evidence for a fear deficit in violent offenders or for an association of psychopathy or aggression with impaired processing of fearful faces. Similarly, there was no evidence for a perceptual bias for angry faces linked to psychopathy or aggression. However, using highly ambiguous stimuli and requiring explicit labeling of emotions, violent offenders showed a categorization bias for anger and this anger bias correlated with self-reported trait aggression (but not with psychopathy). These results add to a growing literature casting doubt on the notion that fear processing is impaired in aggressive individuals and in psychopathy and provide support for the idea that aggression is related to a hostile attribution bias that emerges from later cognitive, post-perceptual processing stages.

How Attribution Theory Helps to Explain Psychiatric Nosology

By exposing the assumptions made about dysfunctional behaviors, treatment options can be better understood. Belief in the cause of a disorder determines what is done to alleviate it. By applying attribution theory to psychiatric nosology—categorization of psychiatry dysfunctions—attributional bias of clinicians can be shown. Primarily clinicians are biased to diagnose a patient’s dysfunction as internal, stable and uncontrollable. In reality most dysfunctions are periodic/cyclical and therefore unstable and through behavioral therapy, most are controllable. By changing the attributions, a different meaning of mental illness emerges. Historical evidence illustrates how the attribution of aberrant behaviors has changed which consequently resulted in different theories and treatments. From ‘spirits that invade the body’ of the Middle Ages to the ‘imbalance in the nervous energy’ of the Enlightenment, beliefs dictated how people were treated. From the punitive treatments of the Middle Ages to the ‘Moral Treatment’ of the Enlightenment. With the attribution of biological determinism, a new age of psychopharmacology was ushered in. All these treatment fads rely on different attributions rather than on scientific evidence. With Mad Studies promoting the perspective of the patients who use the mental health care system, the attribution of disease changes again, and a greater emphasis is placed on the external, unstable, and controllable aspects of madness. According to the theory ‘Power Threat Meaning Framework,’ madness is a mental strategy that has become mismatched with its current context. The context determines the expression of dysfunction. Future treatment requires a population-based approach that offers social prescribing, short-term respite programs, and broad community-based cognitive-behavioral therapies. The objective is to focus on alleviating the anxiety and distress experienced by the individual and to aim for personal and functional recovery rather than to aim for a purely clinical recovery.

Hostile Attribution Bias and Working Memory in the Link Between Trauma Exposure and Violence in Justice-Involved Youth

Background Youth involved with the justice system are more vulnerable to trauma exposure and engaging in violent behavior. Trauma exposure is linked to increases in youth violence, however, the pathway from trauma to violence, including neurocognitive and neuropsychological mechanisms, is not well understood. The current study sought to test the influence of hostile attribution bias (HAB) and working memory on violence and whether these factors play a role in the link between trauma and violence among justice-involved youth. Methods Participants included 237 detained youth (Male = 81.0%, Mage = 15.22) who completed self-report surveys and working memory tasks. Results Trauma was significantly associated with violent behavior. HAB was related to physical violence; however, when trauma exposure was entered into subsequent models, HAB was no longer associated with violence. Lower levels of working memory were found to interact with HAB to increase the risk of physical violence. Mediation was not supported. Implications The current study supports universal trauma screening and trauma-informed care in justice facilities and suggests that neurocognitive functioning assessment and remediation are important to consider in treatment programming.

Understanding Romantic Relational Aggression in Emerging Adults Using Latent Profile Analysis of Jealousy and Hostile Attribution Bias.

The present study sought to identify profiles of 753 emerging adults (62.5% females) with different levels of hostile attribution bias (HAB) and jealousy dimensions (i.e., cognitive, emotional, behavioral) and examined differences in their levels of romantic relational aggression (RoRAgg) across profiles. Participants were recruited from Greek universities and completed and online survey. Using a person-centered approach, Latent Profile Analysis indicated the presence of three profiles of participants: a) jealous and hostile intent attributers who had high scores on jealousy dimensions and HAB, b) low risk who scored low on jealousy and HAB, and c) emotionally jealous and moderate hostile intent attributers with moderate cognitive and behavioral jealousy as well as HAB, and high emotional jealousy. As predicted, jealous and hostile intent attributers scored higher on RoRAgg compared with emotionally jealous and moderate hostile intent attributers and low risk. The findings confirm previous research and are discussed in terms of their implications. Interventions targeting relational aggressor's hostile attributions, cognitive suspicions, and negative thoughts should be implemented to reduce RoRAgg.

The relationship between trait anger and reactive aggressive behavior in middle school students: the mediating role and intervention of hostile attribution bias

BackgroundThe reactive aggressive behavior in individuals typically shows a rapid growth trend as individuals enter adolescence, and peaks during middle-school period. According to the Comprehensive Cognitive Model of Trait Anger, trait anger and hostile attribution bias play important roles in the development of reactive aggressive behavior. Based on this, current study explored the relationship between trait anger and reactive aggressive behavior in middle school students, as well as the mediating role of hostile attribution bias and interventions.MethodsThe current study consisted of three sub-studies. Study 1 recruited 87 middle school students with an average age of 12.367 ± 0.889 years, investigated the relationship between trait anger and reactive aggressive behavior, as well as the mediating role of trait hostile attribution bias. Study 2 recruited 62 middle school students with an average age of 13.376 ± 0.963 years, investigated the relationship between trait anger and reactive aggressive behavior, as well as the mediating role of state hostile attribution bias. Study 3 recruited 80 middle school students with an average age of 13.392 ± 0.977 years, implemented an intervention targeting trait hostile attribution bias in middle school students with high trait anger to reduce their reactive aggressive behavior. In current study, data management was performed using SPSS 22.0. Descriptive statistics, independent samples t-test, paired samples t-test, repeated measures analysis of variance (ANOVA), and path analysis were used for statistical analysis.FindingsThe results of Study 1 showed that trait anger predicted reactive aggressive behavior through trait hostile attribution bias. The results of Study 2 indicated that trait and state hostile attribution bias played mediating role intermediary, and trait hostile attribution bias had a stronger mediating effect than state hostile attribution bias. The results of Study 3 suggested that the intervention effectively decreased trait hostile attribution bias and reactive aggressive behavior.ConclusionsTrait anger can predict the reactive aggressive behavior of junior high school students, with trait hostility attribution bias and state hostility attribution bias mediating this relationship. Intervening in the hostility attribution bias of high-anger junior high school students can effectively reduce their reactive aggressive behavior.

Diversity-aware Population Models: Quantifying Associations between Socio-Spatial Factors and Cognitive Development in the ABCD Cohort.

Population-level analyses are inherently complex due to a myriad of latent confounding effects that underlie the interdisciplinary topics of research interest. Despite the mounting demand for generative population models, the limited generalizability to underrepresented groups hinders their widespread adoption in downstream applications. Interpretability and reliability are essential for clinicians and policymakers, while accuracy and precision are prioritized from an engineering standpoint. Thus, in domains such as population neuroscience, the challenge lies in determining a suitable approach to model population data effectively. Notably, the traditional strata-agnostic nature of existing methods in this field reveals a pertinent gap in quantitative techniques that directly capture major sources of population stratification. The emergence of population-scale cohorts, like the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study, provides unparalleled opportunities to explore and characterize neurobehavioral and sociodemographic relationships comprehensively. We propose diversity-aware population modeling, a framework poised to standardize systematic incorporation of diverse attributes, structured with respect to intrinsic population stratification to obtain holistic insights. Here, we leverage Bayesian multilevel regression and poststratification, to elucidate inter-individual differences in the relationships between socioeconomic status (SES) and cognitive development. We constructed 14 varying-intercepts and varying-slopes models to investigate 3 cognitive phenotypes and 5 sociodemographic variables (SDV), across 17 US states and 5 race subgroups. SDVs exhibited systemic socio-spatial effects that served as fundamental drivers of variation in cognitive outcomes. Low SES was disproportionately associated with cognitive development among Black and Hispanic children, while high SES was a robust predictor of cognitive development only among White and Asian children, consistent with the minorities' diminished returns (MDRs) theory. Notably, adversity-susceptible subgroups demonstrated an expressive association with fluid cognition compared to crystallized cognition. Poststratification proved effective in correcting group attribution biases, particularly in Pennsylvania, highlighting sampling discrepancies in US states with the highest percentage of marginalized participants in the ABCD Study©. Our collective analyses underscore the inextricable link between race and geographic location within the US. We emphasize the importance of diversity-aware population models that consider the intersectional composition of society to derive precise and interpretable insights across applicable domains.

Is high exposure to antisocial media content associated with increased participation in malicious online trolling? exploring the moderated mediation model of hostile attribution bias and empathy

Malicious online trolling is prevalent among Chinese college students and has recently garnered extensive attention from researchers due to the substantial harm it causes to the victims and the damage it inflicts on the online environment. Most previous studies have focused on examining how personal traits related to malicious online trolling. Further comprehensive research is needed to explore the mechanisms linking external environmental factors (antisocial media exposure) and malicious online trolling. A total of 1259 Chinese college students completed questionnaires regarding malicious online trolling, antisocial media exposure, hostile attribution bias, and empathy. The results indicated a positive association between antisocial media exposure and malicious online trolling among Chinese college students, with hostile attribution bias serving as a mediating factor. Furthermore, the direct and mediated paths between antisocial media exposure and malicious online trolling were moderated by empathy. Specifically, as the level of empathy increased among college students, the relations between the variables all weakened. Excessive exposure to antisocial media content among college students may trigger hostile attribution bias and lead to more malicious online trolling behavior. However, the relation between antisocial media exposure and malicious online trolling, hostile attribution bias and malicious online trolling, was attenuated when college students’ empathy levels were high.

Evidence of a self-serving bias in people's attributions for their food intake

People often fail to acknowledge external influences on their food intake, but there might be some circumstances in which people are willing to report that those external factors influenced their behavior. This study examined whether participants who believed that they had overeaten would indicate that the portion size they were served influenced their food intake. Participants (119 women) ate a pasta lunch at two separate sessions, one week apart. At the second session, participants were randomly assigned to receive either a regular portion of pasta (the same portion as the first session) or a large portion of pasta (a portion that was twice the size), and to receive false feedback about their food intake indicating that they had either eaten about the same as or substantially more than they had at the previous session. Participants were then asked to indicate the extent to which the amount of food served influenced how much they ate at that second session. Compared to participants who were informed that they had eaten the same amount across the two sessions, those who were informed that they ate more at the second session reported a stronger influence of the amount of food served if they also received a large portion of pasta, but not if they received a regular portion of pasta. These findings suggest that the willingness to implicate external influences (e.g., portion size) on one's food intake may be driven by a self-serving bias, providing an “excuse” for overeating. However, the external cue must be salient enough to be a plausible explanation for one's behavior.

Loneliness and psychotic-like experiences in middle-aged and older adults: the mediating role of selective attention to threat and external attribution biases

Objectives Loneliness has been associated with psychotic-like experiences (PLEs) in the general population, but the mechanisms underlying this association are poorly understood. Theoretical models, corroborated by empirical findings, signify the key role of biased cognition in both loneliness and psychosis. This study tested whether two cognitive biases – Selective Attention to Threat (ATB) and External Attribution Bias (EAB) – account for the association between loneliness and PLEs. Method A convenience sample (n = 357) of middle-aged and older adults (aged 40+) was recruited online from the UK population. The parallel mediation model with two the aforementioned cognitive biases as mediators was tested. Results A mediation effect between loneliness and PLEs via ATB (ab1 = 0.441, 95% CI = [0.264, 0.646]) and EAB (ab2 = 0.354, 95% CI [0.124, 0.627] was established. This model remained significant after controlling for the current symptoms of anxiety and depression. Conclusion Greater loneliness was associated with a higher rate of PLEs in the sample of middle-aged and older adults. This association was fully explained by ATB and EAB, independent of the current symptoms of anxiety and depression.

Bearing the burden of peace: Intergroup attribution bias and public support for peace provisions

AbstractWhat drives public support for peace provisions? Based on intergroup attribution theory, we argue that public support for peace provisions depends on “who bears the burden of peace,” with people wanting to protect their ingroup while holding the outgroup accountable. To examine this claim, we conducted a series of question‐wording experiments with more than 1650 Azerbaijani participants shortly after a deadly resurgence of the Nagorno‐Karabakh war. Our initial findings confirm that support for war crime punishments and monetary reparations decreases when the ingroup stands trial or must pay. Conversely, support increases when these same burdens fall on the outgroup. A follow‐up study shows that these patterns persist for at least 6 months but also reveals a more nuanced perspective. Public support for peace provisions does not automatically decrease when the ingroup bears the cost or increase when the outgroup bears it; rather, it depends on the group‐based implications of the provision under consideration. Taken together, our results underscore the importance of crafting and communicating peace provisions in a tailored manner and the potential of emphasizing burden sharing as an effective strategy for addressing intergroup hostilities and fostering sustainable peace.

Predictors of clinical insight in first-episode psychosis: Different patterns in men and women

BackgroundWe aimed to explore gender-related differences in the associations of insight impairment with clinical symptoms, metacognition, and social cognition in psychosis. MethodsRegression analysis of several clinical insight dimensions was conducted on the data from 116 men and 56 women with first-episode psychosis. Various clinical symptoms and measures of metacognition and social cognition were entered as predictors. ResultsIn both men and women, delusions emerged as a strong predictor of all insight dimensions, and verbal hallucinations as a strong predictor of symptom relabelling. In men, certain negative symptoms as well as self-certainty, lack of self-reflectiveness, impaired theory of mind, attributional biases, and a jumping-to-conclusions bias were additional predictors of poor insight, while good insight was associated with depression, anxiety, avolition, blunted affect, and impaired emotional recognition. In women, poor insight was associated with a self-serving/externalising bias, impaired emotional recognition, and attention disorders. ConclusionsPoor insight in first-episode psychosis is strongly linked to deficits in metacognition and social cognition, with marked differences between men and women with respect to the specific skills involved in the impairment. Meanwhile, good insight is linked to a variety of affective manifestations in men. These findings suggest new avenues for more targeted cognitive interventions to improve clinical insight in psychosis.

Emotional Invalidation and Relationship Quality: A Mediational Model Through a Social Learning Lens.

While we know childhood experiences are influential on a child's later socioemotional awareness and behavior, we are still searching for specific mechanisms that influence the transferability of childhood experiences and adult relationship functioning. In this study, we seek to further this area of investigation by examining the interpretation of ambiguous social interactions and perceptions of emotional invalidation as potential mediators of the relationship between perceptions of childhood emotional invalidation and current relationship quality. Participants completed online measures of hostile intent attributions, perceptions of childhood emotional invalidation, and current relationship quality with a significant other. They read emotionally provocative interpersonal scenarios and then reported likely emotionally invalidating reactions from their significant other to measure current perceptions of emotional invalidation. Results supported our hypotheses that perceptions of current emotional invalidation in a close, personal relationship would mediate the relationship between perceptions of childhood maternal emotional invalidation and both current relationship support and relationship conflict. Furthermore, the strength of this mediational pathway outweighed the influence of a more general hostile attribution bias. These findings have implications for prevention and intervention strategies designed to enhance interpersonal functioning.