SUPPORTING DECISION MAKING FOR THE PREVENTION OF CHILD MALTREATMENT IN NORTH CAROLINA

Child maltreatment is a distressingly prevalent problem in the United States, with over 674,000 children estimated to be witness to domestic violence or otherwise affected by abuse or neglect in federal fiscal year 2017. While evidence-based programs exist to prevent child maltreatment, only a small proportion of families receive such services. Tools are needed to support decision makers when they are assessing their local context and selecting discrete evidence-based programs to reduce child maltreatment. This research addresses three aims in order to support such decision making in North Carolina (NC): 1) To understand how county-level indicators of child and family well-being co-vary using data from the U.S. Census and RWJF County Health Rankings; 2) To collaboratively develop a systems informed hypothesis of child maltreatment risk and protective factors using a Group Model Building (GMB) approach with NC stakeholders, and structure an early quantitative system dynamics simulation model to compare the potential effects of three evidence-based child maltreatment prevention programs, and 3) To develop and pilot test a multi-criteria decision analysis (MCDA) tool to assess whether interventions are differentially ranked with a manual ranking compared to ranks calculated with the tool. In Aim 1, we find that latent profiles of North Carolina counties can be characterized by low, moderate, and high risk, but the moderate risk profile is also associated with the highest level of predicted drug overdose deaths and with highest mean of predicted child maltreatment reports. In Aim 2, stakeholders emphasized the role of parental trauma and access to peer supports, and the simulation model offered preliminary insights into the importance of system shocks such as newborns. In Aim 3, over half of decision makers (55%) ranked the three interventions differently with their manual ranking compared to rankings calculated with the MCDA tool. The results of this research suggest that stakeholders conceptualize of child maltreatment risk factors in a multi-level, interconnected manner, and that decision support tools such as the ones presented here can aid with facilitating, not replacing, community conversations around how best to address child maltreatment within the local context.Doctor of Philosoph

Simulating the Effect of Social Influence on Collective Decision-making: The Case of Educator Reporting of Child Abuse

The dissertation is directed toward a simulation study of social influence in small, task-oriented, groups composed of education professionals of differing status who hold differing beliefs about what constitutes the reportable physical abuse of elementary students by parents. It is asserted on philosophical grounds that simulation allows the development and refinement of computational, process-based, models that reflect the stratified nature of social and educational reality. More practically, simulation makes it possible to trace socio-cultural processes over time rather than simply settle for an input-output analysis. The possibility of more adequate explanation, and transformation, of social and educational systems makes simulation relatively superior to other research methods.Persons are modeled as computational objects that participate in social relations. The simulation is based on the social-psychological theory of expectation states and is expressly framed to allow comparison of: (1) a static model and process model of social influence and (2) the social theories of Giddens and Archer regarding the timing of social tie formation. National data are used to formulate models of professional belief concerning N = 111 cases of reported physical abuse. The chief findings are: (1) as applied to the group task of child abuse reporting, the collective decision outcomes obtained from the two models of social influence disagree by a number greater than that expected by chance alone, and (2) as modeled, there is essentially no difference in the simulated collective decision outcomes generated under each theory concerning the timing of social tie formation.Several refinements are needed. First, it is important to construct a more adequate characterization of the relevant beliefs of education professionals, best done via the construction of an ethnographic decision model for each professional type. Second, given the importance of social influence, the simulation should be extended to incorporate socio-linguistic, especially argumentative, behavior. Third, it is important to extend the model to take into account the constraining power of belief with respect to social action. These extensions would add believability to the model and its outputs, thus enhancing its power to inform social and educational theory and practice

Children exposed to intimate partner violence: Identifying differential effects of family environment on children\u27s trauma and psychopathology symptoms through regression mixture models

The majority of analytic approaches aimed at understanding the influence of environmental context on children\u27s socioemotional adjustment assume comparable effects of contextual risk and protective factors for all children. Using self-reported data from 289 maternal caregiver-child dyads, we examined the degree to which there are differential effects of severity of intimate partner violence (IPV) exposure, yearly household income, and number of children in the family on posttraumatic stress symptoms (PTS) and psychopathology symptoms (i.e., internalizing and externalizing problems) among school-age children between the ages of 7–12 years. A regression mixture model identified three latent classes that were primarily distinguished by differential effects of IPV exposure severity on PTS and psychopathology symptoms: (1) asymptomatic with low sensitivity to environmental factors (66% of children), (2) maladjusted with moderate sensitivity (24%), and (3) highly maladjusted with high sensitivity (10%). Children with mothers who had higher levels of education were more likely to be in the maladjusted with moderate sensitivity group than the asymptomatic with low sensitivity group. Latino children were less likely to be in both maladjusted groups compared to the asymptomatic group. Overall, the findings suggest differential effects of family environmental factors on PTS and psychopathology symptoms among children exposed to IPV. Implications for research and practice are discussed

Artificial Intelligence for e-Government: A View on Children’ Welfare

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThis thesis aims to perform a holistic investigation concerning the use of artificial intelligence advance techniques in predicting children in danger of abuse or neglect. A dataset containing over 55322 cases from the Portuguese National Commission for the Promotion of the Rights and Protection of Children and Youth (CNPCJ) was collected and trained to uncover the patterns and additional findings. This research uses machine learning classification models to unveil the model with highest accuracy and robustness in the use predictive analytics in the children’s’ welfare field. This approach will allow social security services to understand the impact of underlying factors for further improvement of their services. Finally, this study develops a random forest predictive model to forecast children in risk, with an accuracy of 84.5%

Who Uses Community-Based Youth Shelters? An Inter-Group And Intra-Group Analysis

Community-based youth shelters are the primary method of intervention designed to meet the complex needs of at-risk youth who leave home before they have developed the skills to live independently. This research examines shelter users\u27 patterns of cross-sector service use to better understand the needs and resources of shelter residents. The aims of this study are 1) to perform an inter-group analysis, comparing sheltered youth with status offense runaways and foster care runaways, and 2) to explore the population of emergency shelter residents using an intra-group analysis, determining whether distinct profiles of sheltered youth exist, based on individual characteristics and service use patterns over time. The study samples were drawn from a larger longitudinal study of services and outcomes. The samples included subjects born between 1981 and 1992 who were reported for child maltreatment and/or lived in families receiving Aid to Families with Dependent Children during childhood. For the first Aim, the sample included subjects identified as runaway by the court system: status offense runaways), foster care runaways, and sheltered youth. The sample for the second aim included only sheltered youth. Bivariate analyses found differences between runaway groups in terms of poverty, maltreatment history, school-identified disability, report of neglect, receipt of family services, delinquent offenses, truancy, ethnicity, and parent mental health or substance abuse treatment. Controlling for covariates in the multinomial logistic regression, only age discriminated between all three groups. Just 20% of the sheltered youth ran away from their previous residence or spent time living on the street. Latent class analysis suggests sheltered youth fall into four clearly distinct categories, clearly defined by connection to school and family. These include: 1) a parent time-out group: attending school and living with family), 2) a school/behavior problem group: not attending school and living with family), 3) youth in DFS custody placed at the shelter: disconnected from family but attending school), and 4) multi-problem youth: disconnected from both school and family)

Trauma Violence Abuse

In this article, the authors critically review the literature testing the cycle of maltreatment hypothesis which posits continuity in maltreatment across adjacent generations. That is, the authors examine whether a history of maltreatment victimization is a significant risk factor for the later perpetration of maltreatment. The authors begin by establishing 11 methodological criteria that studies testing this hypothesis should meet. They include such basic standards as using representative samples, valid and reliable measures, prospective designs, and different reporters for each generation. The authors identify 47 studies that investigated this issue and then evaluate them with regard to the 11 methodological criteria. Overall, most of these studies report findings consistent with the cycle of maltreatment hypothesis. Unfortunately, at the same time, few of them satisfy the basic methodological criteria that the authors established; indeed, even the stronger studies in this area only meet about half of them. Moreover, the methodologically stronger studies present mixed support for the hypothesis. As a result, the positive association often reported in the literature appears to be based largely on the methodologically weaker designs. Based on this systematic methodological review, the authors conclude that this small and methodologically weak body of literature does not provide a definitive test of the cycle of maltreatment hypothesis. The authors conclude that it is imperative to develop more robust and methodologically adequate assessments of this hypothesis to more accurately inform the development of prevention and treatment programs.R01 CE001572/CE/NCIPC CDC HHS/United StatesR01 DA020195/DA/NIDA NIH HHS/United StatesR01CE001572/CE/NCIPC CDC HHS/United States2014-05-27T00:00:00Z22673145PMC403502

Towards AI-governance in psychosocial care: A systematic literature review analysis

With increased digitalization and e-government services, Artificial Intelligence (AI) gained momentum. This paper focuses on AI-governance in Child Social Care field, exploring how aspects of individual, family/community factors are embedded in organizational level, especially when dealing with children resilience and wellbeing. A three-level based review has been conducted. In the first part we explored the interlink between individual factors associated to either resilience or wellbeing are connected to community and governance level where a new conceptual model is provided. In the second phase, we conducted an in-depth systematic literature review using PRISMA review protocol where new categorizations of identified literature with respect to individual, family and community levels in child social care field were suggested, while in the third phase, a review of relevant AI-initiatives in Europe and USA was performed. Finally, a comprehensive discussion of the literature review outcomes was carried out and a new updated conceptual model was provided.© 2023 The Author(s). Published by Elsevier Ltd on behalf of Prof JinHyo Joseph Yun. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

African American Women’s Experiences of Parental Discipline Post Residential Substance Abuse Treatment

Substance use amongst African American mothers has been linked to a number of adverse effects in parental practices, including higher levels of maltreatment, strained family dynamics, delays with the child’s development, and harsh forms of discipline. There is an abundance of literature on how parenting styles affect children, yet little is known about the influence of parental discipline post discharge from a substance use residential treatment facility, specifically among African American mothers. Examining the impact of substance use on African American mothers’ parenting is important as experts in the field such as behavioral health therapists can tailor therapeutic interventions to improve their parenting skills after discharge from treatment to maintain sobriety. Guided by social cognitive theory, the purpose of this generic qualitative study was to explore the lived experiences of African American women post treatment from a residential facility who completed parenting classes and the outcome of implementing learned discipline practices. Experiential anecdotes of data collected from semistructured interviews with eight participants were hand coded for emergent themes; analysis generated four essential themes and 10 subthemes of experience. This study’s implications for positive social change include contributing to the knowledge base about the process of amending parental discipline experienced by African American mothers who completed substance use treatment at a residential facility. Findings may improve support services to prevent adverse long-term effects of substance use, develop culturally relevant interventions, and promote resilience to avoid relapse

A Data-Driven Simulation of the New York State Foster Care System

We introduce an analytic pipeline to model and simulate youth trajectories through the New York state foster care system. Our goal in doing so is to forecast how proposed interventions may impact the foster care system’s ability to achieve it’s stated goals before these interventions are actually implemented and impact the lives of thousands of youth. Here, we focus on two specific stated goals of the system: racial equity, and, as codified most recently by the 2018 Family First Prevention Services Act (FFPSA), a focus on keeping all youth out of foster care. We also focus on one specific potential intervention— a predictive model, proposed in prior work and implemented elsewhere in the U.S., which aims to determine whether or not a youth is in need of care. We use our method to explore how the implementation of this predictive model in New York would impact racial equity and the number of youth in care. While our findings, as in any simulation model, ultimately rely on modeling assumptions, we find evidence that the model would not necessarily achieve either goal. Primarily, then, we aim to further promote the use of data-driven simulation to help understand the ramifications of algorithmic interventions in public systems

Childhood Adversity and Systemic Inflammation in Preschool-Aged Children: The Role of Family Cohesion

Systemic inflammation is a critical physiological mechanism that appears to link exposure to early childhood adversity to later disease. However, some children exposed to adversity have low levels of inflammatory proteins and do not go on to develop health problems. Thus, understanding what factors contribute to less inflammation in some (but not in others) is key to environmental effects on youth health. Family cohesion is one potential contributor to the differences in inflammation levels among adversity-exposed children. This study aimed to test the association between adversity and systemic inflammation, and the role of family cohesion as a moderator of this relation in 145 3- to 6-year-old children recruited from Head Start and the state Department of Social Services. Parents completed the Childhood Experiences Measure and the Cohesion subscale of the Family Environment Scale. Biomarkers linked to systemic inflammation (i.e., IL-6, IL-1β, IL-8, TNF-α, and CRP) were collected via saliva. Using path modeling, the results indicated that increases in adversity exposure were associated with increases in inflammation; adversity explained 27% of the variance in inflammation. The model testing family cohesion as a moderator was nonsignificant. Although family cohesion did not serve as a buffer as expected, dosage and frequency of adversity emerged as important factors influencing systemic inflammation in young children. These findings may suggest a need for a sharpened awareness of early adversity’s impact on biology among professionals who work with families exposed to adversity. Otherwise, the presence of these potential future disease indicators may go unnoticed in young children