Self-Hatred: The Unaddressed Symptom of Borderline Personality Disorder.

Individuals with borderline personality disorder (BPD) often report chronic, severe self-hatred. It is frequently experienced as immutable, seen as a barrier to recovery, and is associated with risk for self-injury and suicide attempts. Yet self-hatred remains a poorly understood, underdiagnosed, and undertreated presentation of BPD. In this concept article and review, we describe the nature of self-hatred in BPD and related disorders, propose a theory as to the development of self-hatred in BPD, review the assessments of and interventions for self-hatred, and consider next steps in the research, assessment, and treatment of self-hatred in BPD. Through increased awareness, understanding, and measures of self-hatred in BPD, new treatment paradigms can be developed to ensure more comprehensive recovery.

A case report of an atypical severe case of skin picking disorder managed by a multidisciplinary team.

BACKGROUND: While skin picking disorder remains relatively common, it often does not present to psychiatry until significant morbidity or comorbidities are reached. It is described as recurrent picking of skin leading to skin lesions, with repeated attempts to decrease or stop skin picking. It is also often associated with significant distress or functional impairment. There has been limited research in this specific disorder and treatment efficacy has often been poor in severe cases. For various reasons, only a small amount of patients with this disorder present to care, and often to a multidisciplinary team prior to psychiatry. CASE PRESENTATION: This is a case presentation of a 44 year old male with a complex past psychiatric history, ultimately untreated for an underlying skin picking disorder. He presented for urgent medical care following a self-inflicted wound through the central frontal bone and dura over the course of 2 years. He was treated with current psychiatric evidence based medicine, including an SSRI, antipsychotic augmentation and NAC, along with habit reversal techniques during the admission. He was concurrently managed with the neurosurgery team, initially with a poor prognosis due to the severity of his presentation. He required debriding of the devitalized bone within the adjacent brain to cover the dural defect, IV antibiotics for 6 weeks, and an initial skin graft on his initial admission. CONCLUSIONS: This case in particular highlighted the importance of urgent treatment via a multidisciplinary approach to avoid mortality. It highlights the importance of increasing awareness about the disorder and that treatment with SSRI's, along with antipsychotic and NAC adjuncts remains the mainstay of acute treatment.

Measurement properties of tools used to assess self-harm in autistic and general population adults.

Autistic people are at increased risk of experiencing self-harm compared to the general population. However, it is unclear which tools are being used to assess self-harm in autistic people, or whether existing tools need to be adapted for this group. This two-stage systematic review aimed to identify tools used to assess self-harm in autistic and general population adults, evaluate these tools on their measurement properties, and make recommendations for their appropriate use in research and clinical practice. Four databases were systematically searched (PsycINFO, Embase, MEDLINE and Web of Science). Eight frequently used self-harm assessment tools were identified and assessed for risk of bias, criteria for good measurement properties, and quality of evidence using the COSMIN checklist. Of these, two tools had sufficient evidence of internal consistency (ISAS, QNSSI), and one had been frequently used with autistic adults (NSSI-AT). These three tools may have potential for use with autistic adults but require further investigation for content validity and measurement properties in the autistic population. More research and potential adaptations to current self-harm assessment tools are recommended in order to better conceptualise and understand self-harm and its measurement in autism.

Developing a clinical decision support system software prototype that assists in the management of patients with self-harm in the emergency department: protocol of the PERMANENS project.

BACKGROUND: Self-harm presents a significant public health challenge. Emergency departments (EDs) are crucial healthcare settings in managing self-harm, but clinician uncertainty in risk assessment may contribute to ineffective care. Clinical Decision Support Systems (CDSSs) show promise in enhancing care processes, but their effective implementation in self-harm management remains unexplored. METHODS: PERMANENS comprises a combination of methodologies and study designs aimed at developing a CDSS prototype that assists clinicians in the personalized assessment and management of ED patients presenting with self-harm. Ensemble prediction models will be constructed by applying machine learning techniques on electronic registry data from four sites, i.e., Catalonia (Spain), Ireland, Norway, and Sweden. These models will predict key adverse outcomes including self-harm repetition, suicide, premature death, and lack of post-discharge care. Available registry data include routinely collected electronic health record data, mortality data, and administrative data, and will be harmonized using the OMOP Common Data Model, ensuring consistency in terminologies, vocabularies and coding schemes. A clinical knowledge base of effective suicide prevention interventions will be developed rooted in a systematic review of clinical practice guidelines, including quality assessment of guidelines using the AGREE II tool. The CDSS software prototype will include a backend that integrates the prediction models and the clinical knowledge base to enable accurate patient risk stratification and subsequent intervention allocation. The CDSS frontend will enable personalized risk assessment and will provide tailored treatment plans, following a tiered evidence-based approach. Implementation research will ensure the CDSS' practical functionality and feasibility, and will include periodic meetings with user-advisory groups, mixed-methods research to identify currently unmet needs in self-harm risk assessment, and small-scale usability testing of the CDSS prototype software. DISCUSSION: Through the development of the proposed CDSS software prototype, PERMANENS aims to standardize care, enhance clinician confidence, improve patient satisfaction, and increase treatment compliance. The routine integration of CDSS for self-harm risk assessment within healthcare systems holds significant potential in effectively reducing suicide mortality rates by facilitating personalized and timely delivery of effective interventions on a large scale for individuals at risk of suicide.

[Prevalence and risk factors of non-suicidal self-injury behavior]. / Rasprostranennost' i faktory riska nesuitsidal'nogo samopovrezhdayushchego povedeniya.

The prevalence of non-suicidal self-injury (NSSI) behavior in adolescents has increased significantly in the early 21st century. The phenomenon of NSSI behavior has become one of the key health problems in the field of adolescent psychiatry and psychology over the past decade worldwide. However, the social characteristics and factors influencing NSSI are very different in different regions of the world. Studies of self-harming behavior indicate that the upward trend is almost equally relevant for developing and developed countries. To date, the methodological basis for the diagnosis of NSSI has not been sufficiently developed in the Russian Federation, there are only some studies of NSSI both from an empirical perspective and in the context of the search for risk factors, causes and functions, models of comorbidity with mental disorders.

Factors within the clinical encounter that impact upon risk assessment within child and adolescent mental health services: a rapid realist synthesis.

Background: Risk assessment is a key process when a child or adolescent presents at risk for self-harm or suicide in a mental health crisis or emergency. Risk assessment by a healthcare professional should be included within a biopsychosocial assessment. However, the predictive value of risk-screening tools for self-harm and suicide in children and adolescents is consistently challenged. A review is needed to explore how best to undertake risk assessment and the appropriate role for tools/checklists within the assessment pathway. Aims: To map research relating to risk assessment for child and adolescent mental health and to identify features that relate to a successful risk assessment. Objectives: To review factors within the clinical encounter that impact upon risk assessments for self-harm and suicide in children and adolescents: i. to conduct a realist synthesis to understand mechanisms for risk assessment, why they occur and how they vary by context ii. to conduct a mapping review of primary studies/reviews to describe available tools of applicability to the UK. Data sources: Databases, including MEDLINE, PsycINFO®, EMBASE, CINAHL, HMIC, Science and Social Sciences Citation Index and the Cochrane Library, were searched (September 2021). Searches were also conducted for reports from websites. Review methods: A resource-constrained realist synthesis was conducted exploring factors that impact upon risk assessments for self-harm and suicide. This was accompanied by a mapping review of primary studies/reviews describing risk-assessment tools and approaches used in UK child and adolescent mental health. Following piloting, four reviewers screened retrieved records. Items were coded for the mapping and/or for inclusion in the realist synthesis. The review team examined the validity and limitations of risk-screening tools. In addition, the team identified structured approaches to risk assessment. Reporting of the realist synthesis followed RAMESES guidelines. Results: From 4084 unique citations, 249 papers were reviewed and 41 studies (49 tools) were included in the mapping review. Eight reviews were identified following full-text screening. Fifty-seven papers were identified for the realist review. Findings highlight 14 explanations (programme theories) for a successful risk assessment for self-harm and suicide. Forty-nine individual assessment tools/approaches were identified. Few tools were developed in the UK, specifically for children and adolescents. These lacked formal independent evaluation. No risk-screening tool is suitable for risk prediction; optimal approaches incorporate a relationship of trust, involvement of the family, where appropriate, and a patient-centred holistic approach. The objective of risk assessment should be elicitation of information to direct a risk formulation and care plan. Limitations: Many identified tools are well-established but lack scientific validity, particularly predictive validity, or clinical utility. Programme theories were generated rapidly from a survey of risk assessment. Conclusions: No single checklist/approach meets the needs of risk assessment for self-harm and suicide. A whole-system approach is required, informed by structured clinical judgement. Useful components include a holistic assessment within a climate of trust, facilitated by family involvement. Study registration: This study is registered as PROSPERO CRD42021276671. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR135079) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 1. See the NIHR Funding and Awards website for further award information.

When young people up to 18 years of age present to health services, having tried to poison themselves, take an overdose or injure themselves, a health professional needs to work out whether this is likely to happen again (risk assessment). Lists of questions or things to look for (risk screening) have proved unreliable. Thorough discussion with the child or teenager may be helpful but takes much time. How can a health professional best use time spent with a young person to prevent further harm and make sure that they get the treatment that they need? This review focuses on young persons who use health services in the UK. Included studies report how health professionals work out whether young people are likely to harm themselves; either how to handle the overall discussion or to use memory aids or checklists (known as tools) to help the discussion. Tools developed in the USA many years ago have not been tested well enough with UK populations. Recent approaches within the UK are used inconsistently. Young persons do not like how they are assessed. Health professionals may use methods that have not been shown to work or use tools differently from how they were designed. This review identified 14 ways to help a young person have valued discussions with a health professional. Health professionals should not simply 'tick boxes'; tools should help them gain a full picture, including input from other family members. Health professionals should create a trusted relationship where the young person feels respected and heard. Tools should not label someone 'at risk' but should support care that reduces the risk of further harm. Health professionals should gather good-quality information that includes asking about thoughts of suicide. Staff should be supported by training, guidance and feedback from experienced colleagues.

Prediction of non-suicidal self-injury in adolescents at the family level using regression methods and machine learning.

BACKGROUND: Adolescent non-suicidal self-injury (NSSI) is a major public health issue. Family factors are significantly associated with NSSI in adolescents, while studies on forecasting NSSI at the family level are still limited. In addition to regression methods, machine learning (ML) techniques have been recommended to improve the accuracy of family-level risk prediction for NSSI. METHODS: Using a dataset of 7967 students and their primary caregivers from a cross-sectional study, logistic regression model and random forest model were used to test the forecasting accuracy of NSSI predictions at the family level. Cross-validation was used to assess model prediction performance, including the area under the receiver operator curve (AUC), precision, Brier score, accuracy, sensitivity, specificity, positive predictive value and negative predictive value. RESULTS: The top three important family-related predictors within the random forest algorithm included family function (importance:42.66), family conflict (importance:42.18), and parental depression (importance:27.21). The most significant family-related risk predictors and protective predictors identified by the logistic regression model were family history of mental illness (OR:2.25) and help-seeking behaviors of mental distress from parents (OR:0.65), respectively. The AUCs of the two models, logistic regression and random forest, were 0.852 and 0.835, respectively. LIMITATIONS: The key limitation is that this cross-sectional survey only enabled the authors to examine predictors that were considered to be proximal rather than distal. CONCLUSIONS: These findings highlight the significance of family-related factors in forecasting NSSI in adolescents. Combining both conventional statistical methods and ML methods to improve risk assessment of NSSI at the family level deserves attention.

Evaluation and management of suicidal ideation and self-harm in children in the emergency department.

Suicide is a leading cause of death among youth, and the emergency department (ED) serves as the primary point of healthcare contact for many with suicidal ideation. As suicide-related presentations to the ED continue to rise, the implementation of time- and cost-effective care pathways becomes ever more critical. Evidence-based tools for the identification and stratification of suicide risk can aid in clinical decision-making and care linkage. This issue reviews best practices for suicide risk assessment of youth to guide evaluation, management, and disposition planning within the ED setting.

Depression and posttraumatic stress disorder in adolescents with nonsuicidal self-injury: comparisons of the psychological correlates and suicidal presentations across diagnostic subgroups.

BACKGROUND: Nonsuicidal self-injury (NSSI) combined with suicide ideation increases the risk of suicidal behaviors. Depression and posttraumatic stress disorder (PTSD) are comorbidities of NSSI compounding this relationship. The present study compared diagnostic subgroups of NSSI based on current depression and PTSD on psychological correlates (i.e., vulnerabilities and impairment) and suicidal presentations (i.e., suicidal cognitions and behaviors) in a psychiatric sample of adolescents. METHODS: Eighty-seven adolescents meeting DSM-5 criteria for NSSI and 104 age-range-matched nonclinical controls (NC) participated. Participants completed self-report measures on psychological vulnerabilities and impairment (e.g., emotion regulation difficulties, negative cognitions). Adolescents with NSSI also completed clinical interviews on psychiatric diagnoses and a recent self-injurious behavior (SIB). Scores on the psychological correlates of NSSI were compared between adolescents with NSSI and NC, and across three diagnostic subgroups of NSSI (A: NSSI+/depression-/PTSD-, n = 14; B: NSSI+/depression+/PTSD-, n = 57; C: NSSI+/depression+/PTSD+, n = 14). Differences between NSSI diagnostic subgroups were tested on the motives for SIB and accompanying suicidal presentations (e.g., desire, intent, motive, lethality). RESULTS: Common comorbidities of NSSI included depression, panic disorder, generalized anxiety disorder, and PTSD. The NSSI subgroup classification was significantly associated with panic disorder, which was controlled for in the subsequent group comparisons. Overall, adolescents who engage in NSSI with vs. without depression reported more psychological vulnerabilities and impairment and a greater degree of suicidal thoughts/desire in SIB (i.e., groups B, C >A), which remained significant after controlling for panic disorder. An increased odds of the suicidal motive for SIB was found in adolescents with all three conditions (i.e., group C: NSSI+/depression+/PTSD+) compared to those with NSSI but neither depression nor PTSD (i.e., group A: NSSI+/depression-/PTSD-); however, this was not significant after controlling for panic disorder. CONCLUSIONS: Psychological underpinnings of adolescent NSSI in clinical contexts may be largely associated with concurrent depression. Suicidal motives in adolescents who engage in NSSI in the presence of depression and PTSD may be confounded by the co-occurrence of panic disorder. This study warrants the importance of attending to the comorbid depression with NSSI in adolescents as it is related to an increase in suicidal desire accompanying SIB.

Association between sports-related concussions and the risk of self-injury thoughts and behaviors: Who, and under what circumstances?

BACKGROUND: Understanding the association between sport-related concussions and the risk of suicidal and non-suicidal self-injury thoughts and behaviors (SITBs), including non-suicidal self-injury (NSSI), suicidal ideation (SI), suicidal plan (SP), and suicidal attempt (SA), is crucial for suicide prevention. We aimed to identify the circumstances in which individuals with or without a concussion are vulnerable to SITBs. METHODS: The cross-sectional study included 85,469 students from 63 Chinese university with a mean age of 19.6 years. Firstly, propensity score matching, and inverse probability of treatment weighting (IPTW) were used to match the concussion and non-concussion group based on a range of biological, social, and psychological factors. Subsequently, multivariable logistic regression and a decision tree algorithm were employed to evaluate the interaction and cumulative impact of these risk factors and concussion on the probability of SITBs. RESULTS: In the unmatched sample, concussion exposures were associated with all SITBs, with NSSI (OR, 1.41), SI (OR, 1.10), SP (OR, 1.23), and SA (OR, 1.28). However, the matched and weighted sample only had a significant association with NSSI and SI. The decision tree model revealed that, in the unmatched sample, among individuals without depressive symptoms or childhood emotional abuse, the risk of concussion on SITBs increased from 45.5 % to 65.2 % (χ2, 9.370; adjusted P = .002) after experiencing sexual abuse and verbal bullying. In the matched sample, the risk increased from 46.2 % to 64.6 % (χ2, 6.848; adjusted P = .009). CONCLUSION: Our study revealed that individuals who suffered concussions exhibited a significantly higher risk of SITBs.

What are the Key Phenomenological Clues to Diagnose Functional Tic-Like Behaviors in the Pandemic Era?

BACKGROUND: Functional tic-like behaviors (FTLBs) can be difficult to distinguish from tics. OBJECTIVES: To describe the phenomenology of FTLBs in youth and assess the movements and vocalizations most suggestive of the diagnosis. METHODS: We compared the phenomenology of tics between youth (<20 yr) with FTLBs and with primary tics from our Registry in Calgary, Canada. RESULTS: Two hundred and thirty-six youths were included: 195 with primary tics (75% males; mean age: 10.8 yr) and 41 with FTLBs (98% females; 16.1 yr). In the bivariate models, FTLBs were most associated with copropraxia (OR = 15.5), saying words (OR = 14.5), coprolalia (OR = 13.1), popping (OR = 11.0), whistling (OR = 9.8), simple head movements (OR = 8.6), and self-injurious behaviors (OR = 6.9). In the multivariable model, FTLBs were still associated with saying words (OR = 13.5) and simple head movements (OR = 6.3). Only 12.2% of youth with FTLBs had throat clearing tics (OR = 0.2). CONCLUSIONS: This study shall help physicians diagnose youth with FTLBs according to the presence/association of specific movements and vocalizations.

Mapping clinical interactions in an Australian tertiary hospital emergency department for patients presenting with risk of suicide or self-harm: Network modeling from observational data.

BACKGROUND: Reliable assessment of suicide and self-harm risk in emergency medicine is critical for effective intervention and treatment of patients affected by mental health disorders. Teams of clinicians face the challenge of rapidly integrating medical history, wide-ranging psychosocial factors, and real-time patient observations to inform diagnosis, treatment, and referral decisions. Patient outcomes therefore depend on the reliable flow of information through networks of clinical staff and information systems. This study aimed to develop a quantitative data-driven research framework for the analysis of information flow in emergency healthcare settings to evaluate clinical practice and operational models for emergency psychiatric care. METHODS AND FINDINGS: We deployed 2 observers in a tertiary hospital emergency department during 2018 for a total of 118.5 h to record clinical interactions along patient trajectories for presentations with risk of self-harm or suicide (n = 272 interactions for n = 43 patient trajectories). The study population was reflective of a naturalistic sample of patients presenting to a tertiary emergency department in a metropolitan Australian city. Using the observational data, we constructed a clinical interaction network to model the flow of clinical information at a systems level. Community detection via modularity maximization revealed communities in the network closely aligned with the underlying clinical team structure. The Psychiatric Liaison Nurse (PLN) was identified as the most important agent in the network as quantified by node degree, closeness centrality, and betweenness centrality. Betweenness centrality of the PLN was significantly higher than expected by chance (>95th percentile compared with randomly shuffled networks) and removing the PLN from the network reduced both the global efficiency of the model and the closeness centrality of all doctors. This indicated a potential vulnerability in the system that could negatively impact patient care if the function of the PLN was compromised. We developed an algorithmic strategy to mitigate this risk by targeted strengthening of links between clinical teams using greedy cumulative addition of network edges in the model. Finally, we identified specific interactions along patient trajectories which were most likely to precipitate a psychiatric referral using a machine learning model trained on features from dynamically constructed clinical interaction networks. The main limitation of this study is the use of nonclinical information only (i.e., modeling is based on timing of interactions and agents involved, but not the content or quantity of information transferred during interactions). CONCLUSIONS: This study demonstrates a data-driven research framework, new to the best of our knowledge, to assess and reinforce important information pathways that guide clinical decision processes and provide complementary insights for improving clinical practice and operational models in emergency medicine for patients at risk of suicide or self-harm. Our findings suggest that PLNs can play a crucial role in clinical communication, but overreliance on PLNs may pose risks to reliable information flow. Operational models that utilize PLNs may be made more robust to these risks by improving interdisciplinary communication between doctors. Our research framework could also be applied more broadly to investigate service delivery in different healthcare settings or for other medical specialties, patient groups, or demographics.

Identifying high-risk subgroups for self-harm in adolescents and young adults: A longitudinal latent class analysis of risk factors.

BACKGROUND: Self-harm is a major public health concern in young people and is governed by a complex interaction of different risk factors. While many studies have identified these risk factors, less is known about how they tend to co-occur together. METHODS: A latent class analysis was conducted using risk factors for self-harm from two waves at ages 13 and 17 from the Growing Up in Ireland (GUI) study their associations with self-harm were examined longitudinally at ages 17 and 20, respectively. RESULTS: At age 13, there was a 'peer problems' group with higher probabilities of bullying, being unpopular and internalising problems and a 'school and substance use problems' group with higher probabilities of substance use, truancy or excessive absence from school and violence. Both of these two groups had over a two-fold risk of self-harm at age 17 in comparison to the low risk factor group. At age 17, there was a group with depression that was diagnosed by a medical professional with the highest relative risk (RR:13.9 (95 % CI 10.2-19.0)) of self-harm at age 20. Two other groups with undiagnosed depression had high probabilities of being bullied, and either high or low probabilities of substance use that had a 9.4 (95 % CI 6.8-13.1) and 7.4 (95 % CI 5.5-10.0) relative risk of self-harm at age 20, respectively. CONCLUSIONS: Identifying hidden sub-groups using risk factors for self-harm in young people can inform potential public health interventions by clinicians and other professionals who work with young people.

The Effect of Gender on Identification and Interpretation of Non-Suicidal Self-Injury.

INTRODUCTION: Reported rates of non-suicidal self-injury (NSSI) differ by gender but may be under-reported and under-recognised in men. People engaging in NSSI rarely seek professional help without encouragement, so others play a key role in its identification and potential intervention. The current research investigated others' interpretations of NSSI, examining whether gender affects the likelihood of NSSI identification and views of how common and acceptable NSSI is. METHOD: Participants (N = 429; 74.1% female, 23.3% male; please see below for further demographic information) responded to two vignettes describing a person self-injuring by punching a wall or by cutting themselves. The person's gender in each vignette was manipulated. Following each vignette, the participants rated the level to which they agreed the behaviour was common for the gender of the person described, as well as the level to which they agreed the behaviour was acceptable for the gender of the person described, on a 5-point Likert scale. Following both vignettes, participants were presented with a definition of NSSI and rated the level to which they agreed cutting and wall-punching were forms of NSSI on 5-point Likert scales. Independent-samples t tests and goodness of fit χ2 tests were conducted as appropriate. RESULTS: Participants were more likely to identify wall-punching as common for men and cutting as common for women. However, there was no significant difference in whether wall-punching was identified as NSSI or considered to be an acceptable behaviour, regardless of the gender of the person engaging in it. That is, although research suggests that men are far more likely to engage in wall-punching as a form of NSSI than women, participants did not recognise this. Overall, the results indicated a gender-dependent difference in how acceptable and common NSSI is thought to be, but no noticeable difference in identification of a behaviour as NSSI. Wall-punching, typically a form of NSSI engaged in by males, tended not to be identified as such. CONCLUSION: There is an effect of gender on how NSSI is interpreted, and it seems that men's NSSI is, and will continue to be, under-recognised. This has important implications for the treatment of men's NSSI, which is more likely to be seen as aggression and therefore deserving of punishment than an attempt at emotion regulation.

Association of Four Medication Classes and Non-suicidal Self-injury in Adolescents with Affective Disorders - A Retrospective Chart Review.

BACKGROUND: Non-suicidal self-injury (NSSI) behaviour is frequently observed in children and adolescents with psychiatric conditions. Affected individuals are regularly treated with psychotropic drugs, although the impact of these agents on NSSI behaviour remains elusive. METHODS: We performed a retrospective chart review from clinical routine data in a large cohort (N=1140) of adolescent inpatients with primary affective and non-affective psychiatric disorders according to ICD-10 (mean age=15.3±1.3 years; 72.6% female). Four separate mixed regression models compared the frequency of NSSI between treatment periods without any medication and four medication categories (benzodiazepines, selective serotonin reuptake inhibitors (SSRIs), high- and low-potency antipsychotics). RESULTS: In those individuals with affective disorders as the primary diagnosis, periods without medication were associated with significantly lower NSSI/day compared to all four other medication conditions (benzodiazepines p<10-8, antidepressants/SSRIs p=0.0004, high-potency antipsychotics p=0.0009, low-potency antipsychotics p<10 -4). In individuals with a primary diagnosis other than an affective disorder, NSSI was significantly lower during the period without medication compared to the treatment periods with benzodiazepines (p=0.005) and antidepressants/SSRIs (p=0.01). However, NSSI rates in the no-medication condition were comparable to NSSI rates under high-potency (p=0.89) and low-potency antipsychotics (p=0.53). CONCLUSIONS: The occurrence of NSSI correlates with the treatment with a psychotropic drug in children and adolescents with psychiatric disorders. Due to the retrospective design, it remains elusive to what extent psychotropic drugs might alter the frequency of NSSI in adolescents or if NSSI might indicate a transdiagnostic feature of more pronounced disease severity.

Disorders of impulsivity in trichotillomania and skin picking disorder.

Trichotillomania and skin picking disorder are often classified as body-focused repetitive behaviors (BFRBs) as they are characterized by repetitive hair-pulling and skin picking, respectively. They were initially considered to be impulse control disorders despite little research scrutiny. The objective of this study was to examine the relationship of these two conditions to other disorders with impulsive features. Adults with trichotillomania (n = 104) and skin picking (n = 178) or both (n = 96) were recruited from the general community using advertisements and online support groups and completed an online survey. Participants undertook a structured clinical interview and completion of self-report instruments to characterize clinical profiles and associated characteristics. In addition, each participant completed the Minnesota Impulse Disorders Interview to screen for disorders with impulsive features. Of the 378 adults with BFRBs, 134 (35.4%) screened positive for at least one disorder with features of impulsivity with the most common being compulsive buying (18.3%) and problematic use of the internet (17.5%). Participants with a co-occurring disorder of impulsivity reported significantly worse pulling and picking symptoms (p < .001), were more likely to have co-occurring alcohol problems (p < .001) and PTSD (p < .001), and scored higher regarding dissociative symptoms (p < .001). BFRBs are associated with a range of impulsive disorders and the comorbidity may have important treatment implications.

Transdiagnostic inflammatory and oxidative biomarkers with predictive capacity of self-injurious behavior in impulsive and unstable disorders.

INTRODUCTION: Alterations in inflammatory processes have previously been reported in impulsive and unstable disorders, as well as in other psychiatric conditions. In order to investigate transdiagnostic biomarkers associated with various phenotypic features of these disorders, this study is designed to identify biomarkers of inflammatory and oxidative endophenotypes related to autolytic behavior. METHODS: Peripheral blood mononuclear cells were collected from 35 patients with borderline personality disorder (BPD), 29 patients with restrictive eating disorder (rED), 21 patients with purging eating disorder (pED) and 23 control subjects. Plasma levels of different inflammatory and oxidative factors were measured by ELISA and the expression of selected proteins was by Western Blot. Principal component analysis (PCA) was performed to categorize the different inflammatory factors. Additionally, Ancova was performed to observe the differences in the principal components among the different groups and logistic regression analysis was conducted to assess the predictive capacity of these components for autolytic behaviors. RESULTS: We found two inflammatory/oxidative components were associated with BPD, characterized by high levels of JNK and ERK and low levels of GPx, SOD and Keap1; and two other inflammatory/oxidative components were linked to pED, associated with more JNK, TBARS and TNF-α and less GPx and SOD. Two components, with more JNK and ERK and less GPx, SOD and Keap1, predicted non-suicidal self-injury and three components, with higher JNK, TBARS and TNF-α levels and lower GPx, SOD and iNOS levels, predicted suicide attempts. CONCLUSIONS: These results strongly support the endophenotypic characterization of impulsivity and the identification of transdiagnostic inflammatory/oxidative biomarkers relevant to autolytic behavior in impulsive and unstable disorders. These dates lay the groundwork for developing of screening tests for these biomarker components to rapidly detect biological risk factors for specific impulse control disorders and future self-injurious behaviors.

[Psychopathological correlates of depression with non-suicidal self-harm in non-psychotic mental illnesses of adolescence]. / Psikhopatologicheskie korrelyaty depressii s nesuitsidal'nymi samopovrezhdeniyami pri nepsikhoticheskikh psikhicheskikh zabolevaniyakh yunosheskogo vozrasta.

OBJECTIVE: To determine the main clinical and psychopathological features of the relationship between depressive states and non-suicidal self-injury (NSSI) in mental illnesses of the non-psychotic register in adolescence. MATERIAL AND METHODS: Clinical data of 128 patients (77 males and 51 females), who presented with depressive states and NSSI in non-psychotic mental disorders during adolescence, were analyzed. The patients were examined at the Clinic of the Mental Health Research Center during the period 2020-2023. The mean age of the patients was 19±4.1 years. RESULTS: Based on the data from studying depression and NSSI in adolescence, we developed a typology, identifying three variants of affect and auto-aggressive activity interactions. The affect-dominant type (25.8%) was characterized by a predominance of affective pathology (p<.05), with the occurrence of impulsive NSSI (45.5%) and demonstrative NSSI (30.3%) (p<0.05). The personality-dominant type (43.0%) was based on pathocharacterological abnormalities (60.0%), where NSSI were represented by impulsive (25.5%), depersonalizing (27.3%), and addictive variants (32.7%) (p<0.05). The reciprocal type (31.3%) exhibited pronounced polymorphism, combining high affect variability with a tendency towards auto-aggressive behavior of varying severity and manifestations of NSSI (p<0.05). In terms of nosological distribution, schizotypal disorder predominated (45.0%) followed by predominantly borderline personality disorder (30.0%) and bipolar affective disorder (25.0%) (p<0.05). In terms of nosological distribution, schizotypal disorder predominated (45.0%), followed by predominantly borderline personality disorder (30.0%) and bipolar affective disorder (25.0%) (p<0.05). CONCLUSION: Three types of correlation between depression and NSSI were identified, the formation of which was due to the pathoplastic influence of the age factor, nosological affiliation and a certain, including pathological personality structure. Statistically significant regularities between variants of NSSI and types of their interrelation were revealed. The results can be considered as differential diagnostic and prognostic markers of their further trajectories and, therefore, contribute to the creation of new therapeutic strategies, timely diagnosis and earlier intervention.

Wearable Biosensing to Predict Imminent Aggressive Behavior in Psychiatric Inpatient Youths With Autism.

Importance: Aggressive behavior is a prevalent and challenging issue in individuals with autism. Objective: To investigate whether changes in peripheral physiology recorded by a wearable biosensor and machine learning can be used to predict imminent aggressive behavior before it occurs in inpatient youths with autism. Design, Setting, and Participants: This noninterventional prognostic study used data collected from March 2019 to March 2020 from 4 primary care psychiatric inpatient hospitals. Enrolled participants were 86 psychiatric inpatients with confirmed diagnoses of autism exhibiting operationally defined self-injurious behavior, emotion dysregulation, or aggression toward others; 16 individuals were not included (18.6%) because they would not wear the biosensor (8 individuals) or were discharged before an observation could be made (8 individuals). Data were analyzed from March 2020 through October 2023. Main Outcomes and Measures: Research staff performed live behavioral coding of aggressive behavior while inpatient study participants wore a commercially available biosensor that recorded peripheral physiological signals (cardiovascular activity, electrodermal activity, and motion). Logistic regression, support vector machines, neural networks, and domain adaptation were used to analyze time-series features extracted from biosensor data. Area under the receiver operating characteristic curve (AUROC) values were used to evaluate the performance of population- and person-dependent models. Results: There were 70 study participants (mean [range; SD] age, 11.9 [5-19; 3.5] years; 62 males [88.6%]; 1 Asian [1.4%], 5 Black [7.1%], 1 Native Hawaiian or Other Pacific Islander [1.4%], and 63 White [90.0%]; 5 Hispanic [7.5%] and 62 non-Hispanic [92.5%] among 67 individuals with ethnicity data). Nearly half of the population (32 individuals [45.7%]) was minimally verbal, and 30 individuals (42.8%) had an intellectual disability. Participant length of inpatient hospital stay ranged from 8 to 201 days, and the mean (SD) length was 37.28 (33.95) days. A total of 429 naturalistic observational coding sessions were recorded, totaling 497 hours, wherein 6665 aggressive behaviors were documented, including self-injury (3983 behaviors [59.8%]), emotion dysregulation (2063 behaviors [31.0%]), and aggression toward others (619 behaviors [9.3%]). Logistic regression was the best-performing overall classifier across all experiments; for example, it predicted aggressive behavior 3 minutes before onset with a mean AUROC of 0.80 (95% CI, 0.79-0.81). Conclusions and Relevance: This study replicated and extended previous findings suggesting that machine learning analyses of preceding changes in peripheral physiology may be used to predict imminent aggressive behaviors before they occur in inpatient youths with autism. Further research will explore clinical implications and the potential for personalized interventions.