Non-accidental Trauma in Infants: a Review of Evidence-Based Strategies for Diagnosis, Management, and Prevention

Purpose of Review To provide a resource for providers that may be involved in the diagnosis and management of infant non-accidental trauma (NAT). Recent Findings Infants are more likely to both suffer from physical abuse and die from their subsequent injuries. There are missed opportunities among providers for recognizing sentinel injuries. Minority children are overrepresented in the reporting of child maltreatment, and there is systemic bias in the evaluation and treatment of minority victims of child abuse. Summary Unfortunately, no single, primary preventative intervention has been conclusively shown to reduce the incidence of child maltreatment. Standardized algorithms for NAT screening have been shown to increase the bias-free utilization of NAT evaluations. Every healthcare provider that interacts with children has a responsibility to recognize warning signs of NAT, be able to initiate the evaluation for suspected NAT, and understand their role as a mandatory reporter.

Physical Intimate Partner Violence, Childhood Physical Abuse and Mental Health of U.S. Caribbean Women: The Interrelationship of Social, Contextual, and Migratory Influences

The literature has shown an increased risk for mental health conditions among victims of domestic violence. Few studies have examined the relationship between mental health disorders and domestic violence among Caribbean women, and how the association might be influenced by migratory and contextual factors. This study addresses the mental well-being of U.S. Caribbean Black women victims of domestic violence, and the relationships between acculturation, discrimination, and demographic influences. An analysis of data from the 2001–2003 National Survey of American Life (NSAL) re-interview, the first and most complete study on U.S. Caribbean Blacks, was conducted. Bivariate analysis revealed an association between acts of physical domestic violence and mental health conditions, with generally higher risk among women who reported both severe physical intimate partner violence and childhood physical abuse. Multivariate logistic regression indicates an association between specific mental disorders and acts of domestic violence. Acculturation, length of residence in the United States, age, education, poverty, and country of origin were also associated with mental health. The study highlights future directions for exploration including additional investigation of the influence of acculturation on the physical health of victims of domestic violence.

A Meta-Analysis of Childhood Maltreatment in Relation to Psychopathic Traits

Psychopathy is a personality disorder characterized by a mix of traits belonging to four facets: affective (e.g., callous/lack of empathy), interpersonal (e.g., grandiosity), behavioral instability (e.g., impulsivity, poor behavioral controls), and social deviance (e.g., juvenile delinquency, criminal versatility). Several scholars have argued that early childhood maltreatment impacts the development of psychopathy, although views regarding its role in the four facets differ. We conducted a meta-analysis including 47 studies comprising a total of 349 effect sizes and 12,737 participants, to investigate the association between the four psychopathy facets and four types of child maltreatment: physical abuse, emotional abuse, neglect, and sexual abuse.We found support for a moderate link between overall psychopathy and childhood physical abuse, emotional abuse, and neglect, as well as overall childhood maltreatment. The link between psychopathy and childhood sexual abuse was small, but still significant. These associations were stronger for the behavioral and antisocial facets than for the affective and interpersonal facets of psychopathy, but nearly all associations were significant. Our findings are consistent with recently developed theories on the role of complex trauma in the development of severe personality disorders. Trauma-focused preventive and therapeutic interventions can provide further tests of the trauma-psychopathy hypothesis.

Identification of Intimate Partner Violence from Free Text Descriptions in Social Media

Intimate Partner Violence (IPV) is a significant public health problem that adversely affects the well-being of victims. IPV is often under-reported and non-physical forms of violence may not be recognized as IPV, even by victims. With the increasing popularity of social media and due to the anonymity provided by some of these platforms, people feel comfortable sharing descriptions of their relationship problems in social media. The content generated in these platforms can be useful in identifying IPV and characterizing the prevalence, causes, consequences, and correlates of IPV in broad populations. However, these descriptions are in the form of free text and no corpus of labeled data is available to perform large-scale computational and statistical analyses. Here, we use data from established questionnaires that are used to collect self-report data on IPV to train machine learning models to predict IPV from free text. Using Universal Sentence Encoder (USE) along with multiple machine learning algorithms (Random Forest, SVM, Logistic Regression, Naive Bayes), we develop DETECTIPV, a tool for detecting IPV in free text. Using DETECTIPV, we comprehensively characterize the predictability of different types of violence (Physical Abuse, Emotional Abuse, Sexual Abuse) from free text. Our results show that a general model that is trained using examples of all violence types can identify IPV from free text with area under the ROC curve (AUROC) 89%. We also train type-specific models and observe that Physical Abuse can be identified with greatest accuracy (AUROC 98%), while Sexual Abuse can be identified with high precision but relatively low recall. While our results indicate that the prediction of Emotional Abuse is the most challenging, DETECTIPV can identify Emotional Abuse with AUROC above 80%. These results establish DETECTIPV as a tool that can be used to reliably detect IPV in the context of various applications, ranging from flagging social media posts to detecting IPV in large text corpuses for research purposes. DETECTIPV is available as a web service at https://ipvlab.case.edu/ipvdetect/.

Using network analysis to illuminate the intergenerational transmission of adversity in the ALSPAC cohort

Objective: The effects of maternal exposure to adverse childhood experiences (ACEs) may be transmitted to subsequent generations through various biopsychosocial mechanisms. However, studies tend to focus on exploring one or two focal pathways with less attention paid to links between different pathways. Using a network approach, this paper explores a range of core prenatal risk factors that may link maternal ACEs to infant preterm birth (PTB) and low birthweight (LBW). Methods: We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 8 379) to estimate two mixed graphical network models: Model 1 was constructed using adverse infant outcomes, biopsychosocial and environmental risk factors, forms of ACEs, and sociodemographic factors. In Model 2, ACEs were combined to represent a threshold ACEs score (≥ 4). Network indices were estimated to determine the shortest pathway from ACEs to infant outcomes, and to identify the risk factors that are most vital in bridging these variables. Results: In both models, childhood and prenatal risk factors were highly interrelated. Childhood physical abuse, but not threshold ACEs, was directly linked to LBW. Further, exposure to second-hand smoke, developing gestational hypertension, prenatal smoking, first time pregnancy, not being White, and older age were directly linked to LBW, while developing gestational diabetes, having previous pregnanc(ies), and lower educational attainment were associated with PTB. Only pre-eclampsia was directly linked to both outcomes. Network indices and shortest pathways plots indicate that sexual abuse played a central role in bridging ACEs to other risks and poor infant outcomes. Overall, prenatal smoking was determined as the most influential bridge node. Conclusions: As child physical abuse was directly linked to low birthweight, and child sexual abuse and prenatal smoking were the most influential bridge nodes, they can be considered priority candidate targets for interventions to disrupt intergenerational risk transmission. Further, our study demonstrates the promise of network analysis as an approach for illuminating the intergenerational transmission of adversity in its full complexity.

The Kreutzer Sonata

Women's inferiority persists, particularly in patriarchal societies. In Russia, women have always been treated as second-class citize (Placeholder1)ns to men. As a result, because it is a system that already exists in society, women's inferiority is the fundamental problem of inequality for women in Russia. The novel The Kreutzer Sonata explores the inferiority of female characters in nineteenth-century Russia, where the church's influence is still strong. The aims of the research were to examine about women inferiority and struggle in patriarchal society as portrayed in the novel The Kreutzer Sonata by Leo Tolstoy. The data was collected using the following methods: 1) attentively reading the novel to determine which sections featured inferiority and struggle, and 2) collecting notes and marking the facts of inferiority in the marriage and society. 3) categorizing; and 4) analyzing. Based on the research, it was discovered that there were two major forms of women's inferiority: 1) the feeling of powerlessness in decision of marriages. This powerlessness happens to both the mother and the daughters. 2) being subjected to discriminatory treatment, such as a lack of freedom and mobility based only on sexuality, as well as physical abuse and loss of inheritance.

Incidence and Risk Factors of Elder Mistreatment in the Community: A Longitudinal Population-Based Study

Prior population-based elder mistreatment (EM) risk factor research has focused on problem prevalence using cross-sectional designs, which cannot make causal inferences between proposed risk factors and EM or discern existing cases from new cases entering the population. This study sought to estimate the incidence of EM and identify risk factors for new cases. It is a ten-year prospective, population-based cohort study with data collected between 2009 (Wave 1) and 2019 (Wave 2). Based on Wave 1 random, stratified sampling to recruit English/Spanish-speaking, cognitively intact, community-dwelling older adults (age ≥ 60) across New York State, this study conducted computer assisted telephone interviews (CATI) with 628 respondents participating in both Wave 1 and Wave 2 interviews (response rate=60.7%). Ten-year EM incidence was regressed on factors related to physical vulnerability, living arrangement, and socio-cultural characteristics using logistic regression. Ten-year incidence rates included overall EM (11.4%), financial abuse (8.5%), emotional abuse (4.1%), physical abuse (2.3%), and neglect (1.0%). Poor self-rated health at Wave 1 significantly predicted increased risk of new Wave 2 overall EM (odds ratio [OR]=2.8), emotional abuse (OR=3.67), physical abuse (OR=4.21), and financial abuse (OR=2.8). Black older adults were at significantly heightened risk of overall EM (OR=2.61), specifically financial abuse (OR=2.8). Change from co-residence (Wave 1) toward living alone (Wave 2) significantly predicted financial abuse (OR=2.74). Healthcare visits represent important opportunities to detect at-risk older adults. Race is highlighted as an important social determinant for EM requiring urgent attention. This study represents the first longitudinal, population-based EM incidence study.