Psychopathy Research Articles

Characterizing the role of unpredictability within different dimensions of early life adversity.

Dimensional models of early life adversity highlight the distinct roles of deprivation and threat in shaping neurocognitive development and mental health. However, relatively little is known about the role of unpredictability within each dimension. We estimated both the average levels of, and the temporal unpredictability of deprivation and threat exposure during adolescence in a high-risk, longitudinal sample of 1354 youth (Pathways to Desistance study). We then related these estimates to later life psychological distress, and Antisocial and Borderline personality traits, and tested whether any effects are mediated by future orientation. High average levels of both deprivation and threat exposure were found to be associated with worse mental health on all three outcomes, but only the effects on Antisocial and Borderline personality traits were mediated by decreased future orientation, a pattern consistent with evolutionary models of psychopathology. Unpredictability in deprivation exposure proved to be associated with increased psychological distress and a higher number of Borderline traits, but with increased future orientation. There was some evidence of unpredictability in threat exposure buffering against the detrimental developmental effects of average threat levels. Our results suggest that the effects of unpredictability are distinct within different dimensions of early life adversity.

Personality in Alcohol and Opioid Use Disorder: A Multiphasic Personality Questionnaire Study.

This study explored the relationship between personality attributes and substance use disorder (SUD). Research has identified specific personality dimensions, such as neuroticism, psychoticism, antisocial personality traits, paranoia, and anxiety, as contributing factors on the way to the initiation, continuation, and relapse of SUD. To explore this connection, we examined the personality profiles of subjects with alcohol use disorder (AUD) and opioid use disorder (OUD). A total of 928 subjects, 320 with AUD, 490 with OUD and 118 healthy controls (HC), in the age range of 16-65 years were recruited in the study. The Clinical Profile Sheet and the Multiphasic Personality Questionnaire (MPQ) were administered to HC and patients who fulfil the diagnostic criteria for substance dependence as defined by ICD-10 (WHO-1992). We found significant differences in personality profiles between individuals with OUD and AUD. Patients with AUD scored higher than OUD on the MPQ subscales for depression, mania, paranoia, and antisocial personality traits. All subscales of the MPQ showed elevated scores in subjects with SUD compared to HC. Elevated scores on the MPQ subscales suggest that personality factors may contribute to the pattern of substance use and misuse in this cohort.

Forensic Psychiatry Analysis and Methods for Assessing The Mental Health of A Serial Killer.

Psychosis is a mental illness that causes an alteration in the notion of reality, where a world of its own is formed in the mind of the psychotic, in other words, he lives in a delirium and suffers hallucinations, hearing voices and having bizarre visions. Objectives: To carry out a literature review on Forensic Psychiatry and how to assess the mental health of a serial killer. Method: The methodology used was a literature review. The research was carried out by means of an electronic search for scientific articles published on the Scielo (Scientific Electronic Library Online) and Lilacs (Latin American Health Sciences Literature) and Pubmed websites. The health terminologies consulted in the Health Sciences descriptors (DeCS/BIREME) were used; regarding Forensic Psychiatry and how to assess the mental health disorder of a serial killer.The inclusion criteria were: original article, published in Portuguese and English, freely accessible, in full, on the subject, in electronic format and published in the last years (2010 to 2024), totaling 26 articles. Results and Discussion: While antisocial personality disorder is a medical diagnosis, the term “psychopathy”, which belongs to the psychiatric-forensic sphere, can be understood as a “legal diagnosis”. There is still no effective treatment for so-called “serial killers”. Conclusion: Personality disorders, especially the antisocial type, still represent a real challenge for forensic psychiatry today. The most appropriate and fair place for its sufferers, as well as homogeneous treatment recommendations, are still unanswered questions.

Antisocial Personality Disorder as an Associated Precursor to the Development of Substance Use Disorder among Substance Users and Non Substance Users in Federal Neuropsychiatric Hospital, Kaduna, Nigeria

Antisocial Personality Disorder as an Associated Precursor to the Development of Substance Use Disorder among Substance Users and Non Substance Users in Federal Neuropsychiatric Hospital, Kaduna, Nigeria

Differences in natural standing posture are associated with antisocial and manipulative personality traits.

Differences in natural standing posture are associated with antisocial and manipulative personality traits.

Supplemental Material for Psychopathy and Interpersonal Functioning in a University Sample: A Hierarchical Perspective Using the Comprehensive Assessment of Psychopathic Personality: A Registered Report

Supplemental Material for Psychopathy and Interpersonal Functioning in a University Sample: A Hierarchical Perspective Using the Comprehensive Assessment of Psychopathic Personality: A Registered Report

Associations of Reversal Learning Performance With Personality Disorder Profile and Drug Abuse History in a Sample of Prison Inmates.

Prison inmate samples present a high prevalence of impulsivity- and compulsivity-related behavioral problems. The Probabilistic Reversal Learning Task (PRLT) is a useful tool to assess decision-making, and we explore its associations with inmates' personality disorder (antisocial personality disorder, APD; obsessive-compulsive personality disorder, OCPD; or both) and history of drug abuse. Mixed-effects methods were used to model acquisition and reacquisition curves across PRLT, in a sample of 275 prison inmates diagnosed with OCPD, APD, or both. Two aspects were assessed: general discrimination learning and decision-making inflexibility. Participants with a mixed personality disorder profile showed a clear pattern of decisional inflexibility. A history of drug abuse was associated with a general poorer performance but not with decision-making inflexibility. Inability to adapt to changing contingencies, and thus to adverse consequences of previously rewarded choices, was not linked to compulsivity, as hypothesized to be present in OCPD and substance use disorders, but to the mixed APD/OCPD profile.

Coarse-Fine Nested Network for Weakly Supervised Group Activity Recognition.

Weakly supervised group activity recognition (WSGAR) aims at identifying the overall behavior of multiple persons without any fine-grained supervision information (including individual position and action label). Traditional methods usually adopt a person-to-whole way: detect persons via off-the-shelf detectors, obtain person-level features, and integrate into the group-level features for training the classifier. However, these methods are unflexible due to serious reliance on the quality of detectors. To get rid of the detector, recent works learn several prototype tokens from noisy grid features with learnable weights directly, which treat all the local visual information equally and bring in redundant and ambiguous information to some extent. To this end, we propose a novel coarse-fine nested network (CFNN) to coarsely localize the key visual patches of activity and further finely learn the local features, as well as the global features. Specifically, we design a nested interactor (NI) to progressively model the spatiotemporal interactions of the learnable global token. According to the cue of spatial interaction in NI, we localize several key visual patches via a new coarse-grained spatial localizer (CSL). Then, we finally encode these localized visual patches with the help of global spatiotemporal dependency via a new fine-grained spatiotemporal selector (FSS). Extensive experiments on Volleyball and NBA datasets demonstrate the effectiveness of the proposed CFNN compared with the existing competitive methods. Code is available at: https://github.com/gexiaojingshelby/CFNN.

Clinical characteristics of adults with alcohol dependence syndrome comorbid with antisocial personality disorder: a cross-sectional study.

Antisocial Personality Disorder (ASPD) is characterized by a pervasive pattern of disregard for and violation of the rights of others, typically emerging by age 15 years and involving behaviors such as deceitfulness, impulsivity, and aggressiveness. The present study sought to examine the prevalence of the comorbid ASPD in adult people with Alcohol Dependence Syndrome (ADS) and identify clinical characteristics associated with ASPD. A cross-sectional study of 100 consecutive subjects diagnosed with ADS was conducted. Subjects were examined between August 2023 and September 2023. Various assessments and questionnaires were employed, including the Montreal Cognitive Assessment (MoCA), Alcohol Use Disorders Identification Test (AUDIT), and Structured Clinical Interview for DSM-IV (SCID-II). A computed tomography (CT) scan of the brain was performed on 47.5% participants. Out of the 100 individuals screened for the study, 20 were excluded. The study found that 35% of the examined study participants had a comorbid ASPD. Individuals with both ADS and ASPD were more likely to be younger, started drinking at an earlier age, had higher hospitalization rates, and scored higher on the AUDIT test (all P < 0.05%). Also, they had lower education levels, higher rates of unemployment, and lower marriage rates (all P < 0.05%). In addition, they reported more family members with ADS, incarceration, or mental illness and a higher frequency of traumatic experiences (all P < 0.05%). Depression, anxiety, stress (all P < 0.05%), and sleep problems (P = 0.058) were correlated with ASPD. Participants with the comorbid ASPD had lower MoCA scores (P = 0.046) and struggled with attention and linguistic subtests compared to subjects with ADS only. The study highlights the high prevalence of comorbid ASPD in participants with ADS, shedding light on their demographic and psychometric characteristics. Individuals with the comorbid ASPD are more likely to face cognitive deficits, especially in linguistic and attention-related tasks. The findings underline the importance of considering the comorbidity of ASPD in ADS subjects. The study implies that the understanding of the associated risk factors can aid in developing more targeted treatment interventions.

Psychometric validation of the Italian Self-Report Symptoms inventory (SRSI): Factor structure, construct validity, and diagnostic accuracy

The Self-Report Symptom Inventory (SRSI) is a novel tool designed to detect symptom overreporting and other forms of noncredible responding. Unlike existing scales, the SRSI includes genuine and pseudosymptoms scales covering cognitive, affective, motor, pain, and post-traumatic stress disorder domains. The present study aims to investigate the psychometric properties of the Italian Version of the SRSI (SRSI-It), in particular, its factor structure, reliability, convergent and discriminant validity, and diagnostic accuracy. Data from 1180 healthy participants showed a hierarchical structure with higher-order constructs for genuine symptoms and pseudosymptoms, each comprising five subscales. The SRSI-It showed a strong convergent validity with the Structured Inventory of Malingered Symptomatology and discriminant validity through low correlations with the Psychopathic Personality Inventory-Revised. Receiver operating characteristic analysis determined cut scores of 6 (95% specificity) and 9 (98% specificity) for pseudosymptoms, with a Ratio Index score of 0.289 (82% specificity). In summary, the SRSI-It appears to be a promising tool for identifying symptom exaggeration in clinical and forensic contexts, ultimately enhancing the quality and reliability of evaluations in these contexts.

AI-Enabled Sensor Fusion of Time-of-Flight Imaging and mmWave for Concealed Metal Detection.

In the field of detection and ranging, multiple complementary sensing modalities may be used to enrich information obtained from a dynamic scene. One application of this sensor fusion is in public security and surveillance, where efficacy and privacy protection measures must be continually evaluated. We present a novel deployment of sensor fusion for the discrete detection of concealed metal objects on persons whilst preserving their privacy. This is achieved by coupling off-the-shelf mmWave radar and depth camera technology with a novel neural network architecture that processes radar signals using convolutional Long Short-Term Memory (LSTM) blocks and depth signals using convolutional operations. The combined latent features are then magnified using deep feature magnification to reveal cross-modality dependencies in the data. We further propose a decoder, based on the feature extraction and embedding block, to learn an efficient upsampling of the latent space to locate the concealed object in the spatial domain through radar feature guidance. We demonstrate the ability to detect the presence and infer the 3D location of concealed metal objects. We achieve accuracies of up to 95% using a technique that is robust to multiple persons. This work provides a demonstration of the potential for cost-effective and portable sensor fusion with strong opportunities for further development.

Update on Antisocial Personality Disorder.

Antisocial personality disorder (ASPD) is a characterized by lifelong or recurrent behavioral problems that begin in childhood or early adolescence. This communication provides an overview on ASPD including findings from recent reviews and new research. With regard to DSM-5's Section III Alternative Model of Personality Disorder criteria for ASPD, advocates point to the broader symptom coverage and harmonization with ICD-11; yet critics point to the lack of evidence for improved outcomes. A new report shows that antisocial individuals age faster than non-antisocial peers. ASPD has high heritability and newer molecular studies have found intriguing linkages to genes associated with crucial brain regions. A mentalization-based therapy model has been developed and early work shows promise. ASPD is common, widespread, and disruptive to individuals, families, and society. Chronic and lifelong, ASPD typically lessens in severity with advancing age. Assessment rests on the individual's history because there are no diagnostic tests. ASPD likely results from an interplay ofgenetic and environmental factors. Brain imaging studies have linked cortical dysfunction to antisocial behavior in crucial brain regions. Medication is sometimes targeted at the individual's aggression and irritability, but a more rational approach is to target co-occurring disorders. Cognitive-behavioral therapy and mentalization-based therapy models have been developed and are being studied.

Impulsivity in antisocial personality disorder and obsessive-compulsive personality disorder in prison population

This study examined impulsivity in antisocial personality disorder (ASPD) and obsessive-compulsive personality disorder (OCPD) in the context of criminal offending. Participants completed the Demographic, Criminal, and Institutional Behavior Interview, the International Personality Disorder Examination, the Symptom Checklist-90-Revised, and the Impulsive Behavior Scale, that the APD and OCPD groups can commit the same crimes (against people and against objects). The results revealed that ASPD and OCPD groups can commit the same crimes (against human and against objects), although they differ in terms of impulsivity [Negative Urgency (UN), Sensation Seeking (BS) and Positive Urgency (UP)], with the OCPD group scoring lower on these dimensions. In the ASPD group, those who had committed crimes against human scored higher in UN, BS and UP than those who had committed crimes against objects. In the OCPD group, those who had committed crimes against human scored higher on UN and lower on BS and UP than those who had committed crimes against objects. The importance of analyzing personality disorder profiles for a better understanding of criminal behavior is emphasized.

Exploring teachers' experiences in teaching learners with Dissociative identity disorder at rural schools in the Amajuba district KwaZulu-Natal

This study aims to investigate how Dissociative Identity Disorder (DID) affects learners’ academic achievements, engagements, and overall school experience. The objectives were to identify the prevalence of DID among learners in rural KwaZulu-Natal schools, examine the impact of DID on their academic performance, and explore interventions that could support affected learners. The study gained qualitative insight from interviews and focus groups involving learners, teachers, and psychologists. This comprehensive method facilitated a nuanced understanding of DID's effects on learning and academic outcomes. Results indicated a significant correlation between learners with DID and lower academic performance when compared to their peers without DID. Qualitative findings revealed that dissociative episodes, memory lapse, and the psychological stress associated with Dissociative Identity DID adversely affected learners’ participation in class, homework completion, and exam performance. The study further found a general lack of awareness and resources in rural schools to effectively support learners with DID, compounding the challenges they face. The study concludes with several key findings: the need for targeted training for educators in identifying and supporting learners with DID, the importance of integrating psychological support within the school system, and the potential benefits of personalized learning plans for affected learners. The focus should not merely be on academic performance but on creating a holistic experience where every learner, regardless of their challenges, feels included and valued. The study calls for further research and strategies to identify and address dissociative symptoms in learners.

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.

The Community of Ella: A young woman with multiple personalities gets better without losing her "parts." Instead they learn to work as a team.

The Community of Ella: A young woman with multiple personalities gets better without losing her "parts." Instead they learn to work as a team.

Multiple Personality Disorder- A Case Study

This study presents an overview of Multiple Personality Disorder, its development, epidemiology, etiology and nursing management. It also presents a study of a case. The paper also stresses the criteria for diagnosis so professionalscan identify cases at an early stage. Different treatment approaches are discussed.

Association between pathogenic beliefs and personality disorders

Background and objectivesPersonality disorders are significant entities in the field of psychiatry and serve as predisposing factors for Axis I clinical disorder. The Treatment of choice is psychotherapy, and one specific approach is Control Mastery Therapy, which emphasizes addressing Pathogenic beliefs (PB). This study aimed to investigate whether there is a relationship between PB and specific personality disorders and whether these beliefs align with the core features specified in the Diagnostic and Statistical Manual of Mental Disorders (DSM) for that personality disorder. Materials and methodsThis study employed a retrospective cross-sectional design and included 319 participants, comprising individuals receiving treatment at the Psychotherapy Clinic at Maharaj Nakorn Chiang Mai Hospital, Faculty of Medicine, Chiang Mai University between 2007 and 2023. All participants were assessed and completed the Structured Clinical Interview for DSM-IV Axis II - Personality Disorders Questionnaire (SCID-II-PQ), Pathogenic Beliefs Scale, and Outcome-Inventory (depression). A generalized linear model (binary logistic regression) was employed, and the predictors included personality disorders. The outcome was the pathogenic belief, and covariates encompassed age, sex, education, clinical diagnosis, and depression score. A sensitivity analysis was conducted to examine the effect on the model when outliers of depressive scores were present. ResultsAfter adjusting for depression, ten personality disorders were found to predict 16 pathogenic beliefs out of the 27 outcomes examined. Notably, histrionic and obsessive-compulsive personality disorders showed no association with specific pathogenic beliefs. Furthermore, certain pathogenic beliefs were predicted by multiple personality disorders, while conversely, some personality disorders were associated with multiple pathogenic beliefs as well. Sensitivity analysis revealed that outliers influenced the relationships between certain disorders and pathogenic beliefs, particularly those with small effect sizes. ConclusionsThe profound impact of pathogenic beliefs intertwined with personality disorders, particularly influenced by childhood trauma and evident in Cluster B and schizotypal disorders, underscores the critical need for targeted psychotherapeutic interventions. Addressing these beliefs directly is key to enhancing treatment efficacy and patient outcomes. Pathogenic belief should be elicited in clinical settings regardless of personality disorder, especially those who experienced depression. Moving forward, rigorous research is imperative to validate and refine therapeutic approaches aimed at reshaping pathogenic beliefs, ensuring they become pivotal in transforming clinical practice and advancing mental health care.

Association patterns of antisocial personality disorder across substance use disorders

There is a high prevalence of antisocial personality disorder (ASPD) in individuals affected by substance use disorders (SUD). However, there is limited information on the specific patterns of association of ASPD with SUD severity and specific SUD diagnostic criteria. We investigated the association of alcohol, cannabis, cocaine, opioid, and tobacco use disorders (AUD, CanUD, CocUD, OUD, and TUD, respectively) in 1660 individuals with ASPD and 6640 controls matched by sex (24% female), age, and racial/ethnic background in a sample ascertained for addiction-related traits. Generalized linear regressions were used to test ASPD with respect to the five DSM-5 SUD diagnoses, their severity (i.e., mild, moderate, severe), and their diagnostic criteria. We found that ASPD is associated with the diagnosis and severity of AUD (Odds Ratio, ORs = 1.89 and 1.25), CanUD (ORs = 2.13 and 1.32), and TUD (ORs = 1.50 and 1.21) (ps < 0.003). Of the specific diagnostic criteria, the “hazardous use” criterion showed the strongest association with ASPD across the five SUDs investigated (from ORTUD = 1.88 to ORCanUD = 1.37). However, when criteria of different SUDs were included in the same model, ASPD was independently associated only with TUD “hazardous use” and CocUD “attempts to quit”. Attempting to quit cocaine was inversely related to the presence of ASPD and remained significant (OR = 0.57, 95% confidence interval = 0.36–0.89) after controlling for interactive effects with sex. The current work provides novel insights into ASPD-SUD comorbidity, supporting the existence of different SUD patterns among individuals affected by ASPD.

AI can see you: Machiavellianism and extraversion are reflected in eye-movements.

Recent studies showed an association between personality traits and individual patterns of visual behaviour in laboratory and other settings. The current study extends previous research by measuring multiple personality traits in natural settings; and by comparing accuracy of prediction of multiple machine learning algorithms. Adolescent participants (N = 35) completed personality questionnaires (Big Five Inventory and Short Dark Triad Questionnaire) and visited an interactive museum while their eye movements were recorded with head-mounted eye tracking. To predict personality traits the eye-movement data was analysed using eight machine-learning methods: Random Forest, Adaboost, Naive Bayes, Support Vector Machine, Logistic Regression, k Nearest Neighbours, Decision Tree and a three-layer Perceptron. Extracted eye movement features introduced to machine learning algorithms predicted personality traits with above 33% chance accuracy (34%-48%). This result is comparable to previous ecologically valid studies, but lower than in laboratory-based research. Better prediction was achieved for Machiavellianism and Extraversion compared to other traits (10 and 9 predictions above the chance level by different algorithms from different parts of the recording). Conscientiousness, Narcissism and Psychopathy were not reliably predicted from eye movements. These differences in predictability across traits might be explained by differential activation of different traits in different situations, such as new vs. familiar, exciting vs. boring, and complex vs. simple settings. In turn, different machine learning approaches seem to be better at capturing specific gaze patterns (e.g. saccades), associated with specific traits evoked by the situation. Further research is needed to gain better insights into trait-situation-algorithm interactions.