Childhood and Race

Amongst the many social factors that impact upon children, race is arguably one of the largest. Race is an ever-present social category that governs many elements of a child’s interaction with others, and especially for racial minority children it exerts a deep influence on their understanding of themselves. In this chapter, we shall begin by examining what the concept of race really amounts to, emphasizing its status as a socially constructed concept, before examining in the following section how children first come to recognize the existence of race, and to understand their own racial identity.We will then look at two important areas that illustrate the profound impact that the social presence of race and the child’s developing understanding of racial identity have upon the social conditions of many children. First, we will examine how race and childhood intersect in matters of educational opportunity and achievement, before moving on to examine the issue of transracial adoption in the final section

Characterization of Time-variant and Time-invariant Assessment of Suicidality on Reddit using C-SSRS

Suicide is the 10th leading cause of death in the U.S (1999-2019). However, predicting when someone will attempt suicide has been nearly impossible. In the modern world, many individuals suffering from mental illness seek emotional support and advice on well-known and easily-accessible social media platforms such as Reddit. While prior artificial intelligence research has demonstrated the ability to extract valuable information from social media on suicidal thoughts and behaviors, these efforts have not considered both severity and temporality of risk. The insights made possible by access to such data have enormous clinical potential - most dramatically envisioned as a trigger to employ timely and targeted interventions (i.e., voluntary and involuntary psychiatric hospitalization) to save lives. In this work, we address this knowledge gap by developing deep learning algorithms to assess suicide risk in terms of severity and temporality from Reddit data based on the Columbia Suicide Severity Rating Scale (C-SSRS). In particular, we employ two deep learning approaches: time-variant and time-invariant modeling, for user-level suicide risk assessment, and evaluate their performance against a clinician-adjudicated gold standard Reddit corpus annotated based on the C-SSRS. Our results suggest that the time-variant approach outperforms the time-invariant method in the assessment of suicide-related ideations and supportive behaviors (AUC:0.78), while the time-invariant model performed better in predicting suicide-related behaviors and suicide attempt (AUC:0.64). The proposed approach can be integrated with clinical diagnostic interviews for improving suicide risk assessments.Comment: 24 Pages, 8 Tables, 6 Figures; Accepted by PLoS One ; One of the two mentioned Datasets in the manuscript has Closed Access. We will make it public after PLoS One produces the manuscrip

THE USE OF PERCUSSION IN THERAPY: A REALIST SYNTHESIS

Background: Percussion use is common in both music therapy clinical practice and in publications. However, no comprehensive review regarding the use of percussion instruments in music interventions appears to exist. The investigator examined the various literature review types available in order to address the complex and contextual nature of percussion-related interventions. The purpose of this study was to conduct a realist synthesis-type systematic review of the literature regarding the use of percussion in therapy in order to answer the following research questions. Research Questions: 1. When using published tools designed to evaluate quality of research, what was the outcome of this appraisal process when reviewing identified studies? 2. What are the context-mechanism-outcome configurations within percussion-related interventions as found through the systematic review process? Methods: Literature review types were examined in order to locate a systematic review type that best fit the research questions. The investigator used a prior database from Matney (in press), and employed inclusion/exclusion criteria to locate studies with reduced bias and increased study rigor. Eligible studies were examined using methodological evaluation tools, which were corroborated through inter-rater reliability. The investigator created evidence tables that included context-mechanism-outcome configurations (CMOC’s). These configurations were examined for larger patterns that may inform theory development. The investigator linked chains of evidence in accordance with the realist synthesis methodology, and offered CMOC propositions. Results: Results revealed that 30.91% of studies prior to eligibility screening did not report internal review board or consent procedures. Regarding experimental studies evaluated after screening, 34.79% did not report the type of randomization procedure used, and 43.48% were unclear regarding concealment of allocation. Reporting within qualitative and mixed-methods studies also lacked transparent reporting. The investigator presented CMOC’s for each individual study, and proposed evidence linkage that may promote theory development regarding percussion interventions. Conclusions: The percussion-related intervention literature that was evaluated demonstrates a lack of study rigor (internal review board and/or consent procedures, intention to treat principle), a lack of transparent and detailed reporting (randomization details, allocation concealment, treatment consistency amongst groups), as well as a lack of replication and transferability. While context-mechanism-outcome configurations can only provide tentative theory development due to the paucity of connections available, the literature suggests that particular mechanisms may promote effective outcomes in particular situations. The investigator provides implications for future research, clinical practice, and pedagogy

The theory, process, and outcomes of culturally adapted psychotherapy and psychosocial interventions

Massive demographic changes have coincided with rise of the importance of evidence-based treatment among the health sciences and widespread awareness of the failure of psychology to address and serve the mental health needs of historically underrepresented groups. Researchers, theorists, and clinicians demand that empirically supported treatments be adapted to better address and better fit clinical needs. Based on existing approaches in the literature, this dissertation presents a four-part model of cultural adaptation of psychological interventions and reviews 101 current culturally adapted empirically supported treatments through the lens of this model. The dissertation project comprehensively describes the current state of the field in terms of the theoretical bases, processes, and outcomes of culturally adapted psychotherapy and psychosocial interventions in the context of evidence-based practice, provides suggestions, and illuminates implications for future research and practice

Knowledge engineering with semantic web technologies for decision support systems based on psychological models of expertise

Machines that provide decision support have traditionally used either a representation of human expertise or used mathematical algorithms. Each approach has its own limitations. This study helps to combine both types of decision support system for a single system. However, the focus is on how the machines can formalise and manipulate the human representation of expertise rather than on data processing or machine learning algorithms. It will be based on a system that represents human expertise in a psychological format. The particular decision support system for testing the approach is based on a psychological model of classification that is called the Galatean model of classification. The simple classification problems only require one XML structure to represent each class and the objects to be assigned to it. However, when the classification system is implemented as a decision support system within more complex realworld domains, there may be many variations of the class specification for different types of object to be assigned to the class in different circumstances and by different types of user making the classification decision. All these XML structures will be related to each other in formal ways, based on the original class specification, but managing their relationships and evolution becomes very difficult when the specifications for the XML variants are text-based documents. For dealing with these complexities a knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. The aim is to explore how semantic web technologies can be employed to help the knowledge engineering process for decision support systems based on human expertise, but deployed in complex domains with variable circumstances. The research evaluated OWL as a suitable vehicle for representing psychological expertise. The task was to see how well it can provide a machine formalism for the knowledge without losing its psychological validity or transparency: that is, the ability of end users to understand the knowledge representation intuitively despite its OWL format. The OWL Galatea model is designed in this study to help in automatic knowledge maintenance, reducing the replication of knowledge with variant uncertainties and support in knowledge engineering processes. The OWL-based approaches used in this model also aid in the adaptive knowledge management. An adaptive assessment questionnaire is an example of it, which is dynamically derived using the users age as the seed for creating the alternative questionnaires. The credibility of the OWL Galatea model is tested by applying it on two extremely different assessment domains (i.e. GRiST and ADVANCE). The conclusions are that OWLbased specifications provide the complementary structures for managing complex knowledge based on human expertise without impeding the end users’ understanding of the knowledgebase. The generic classification model is applicable to many domains and the accompanying OWL specification facilitates its implementations

Social Media for the Promotion of Holistic Self-Participatory Care: An Evidence Based Approach

Objectives: As health information is becoming increasingly accessible, social media offers ample opportunities to track, be informed, share and promote health. These authors explore how social media and holistic care may work together; more specifically however, our objective is to document, from different perspectives, how social networks have impacted, supported and helped sustain holistic self-participatory care. Methods: A literature review was performed to investigate the use of social media for promoting health in general and complementary alternative care in particular. We also explore a case study of an intervention for improving the health of Greek senior citizens through digital and other means. Results: The Health Belief Model provides a framework for assessing the benefits of social media interventions in promoting comprehensive participatory self-care. Some interventions are particularly effective when integrating social media with real-world encounters. Yet not all social media tools are evidence-based and efficacious. Interestingly, social media is also used to elicit patient ratings of treatments (e.g., for depression), often demonstrating the effectiveness of complementary treatments, such as yoga and mindfulness meditation. Conclusions: To facilitate the use of social media for the promotion of complementary alternative medicine through self-quantification, social connectedness and sharing of experiences, exploration of concrete and abstract ideas are presented herewithin. The main mechanisms by which social support may help improve health - emotional support, an ability to share experiences, and non-hierarchal roles, emphasizing reciprocity in giving and receiving support – are integral to social media and provide great hope for its effective us

Unraveling the patterns of marginalization:Four quantitative studies on students' experience of social marginalization in Danish public schools

Empirical research suggests that children who experience social marginalization in school (i.e., feel left out, excluded, or that they simply do not belong) generally experience lower well-being and have lower-quality relationships with both teachers and peers. Unfortunately, there is scant knowledge on the complex patterns of marginalization, making it difficult to develop general strategies to tackle the issue. To fill this knowledge gap, this dissertation presents four quantitative studies that utilize survey data from Program for Learning Management (PLM; 2015–2019), which to date is the largest school development program in Danish educational history. By conducting state-of-the-art multivariate analyses (incl. structural equation modeling), an instrument for measuring the construct is developed, resulting in quantitative knowledge on the intricate patterns of marginalization. As a result, this dissertation points to some key mechanisms underlying social marginalization. In addition, it provides theoretical and methodological directions for future research

Approches transcriptionelles dans des modèles animaux de stress et de dépression majeure

La dépression majeure (DM) est la principale cause d'invalidité depuis trois décennies, avec plus de 300 millions de personnes touchées dans le monde. En effet, elle contribue largement à la charge économique mondiale globale des maladies. Malgré son impact sociétal important, les mécanismes biologiques de la dépression restent mal compris. Malheureusement, seuls 30 % environ des patients traités pour la dépression présentent une amélioration complète de leurs symptômes. Étant donné le taux d’échec élevé des essais cliniques d’antidépresseurs, récemment, un examen plus minutieux de leur utilisation a eu lieu, notamment pour investiguer la neurobiologie de la dépression et dans le design de potentiels traitements. Étant donné que la plupart de nos connaissances dans ce domaine proviennent de modèles animaux, ces modèles reproduisent en effet certains aspects de la DM humaine, mais on ne sait pas dans quelle mesure. Ce travail a pour but d'élucider dans quelle mesure ils récapitulent la pathologie moléculaire du trouble humain. Dans cette thèse, nous nous sommes appuyés sur des analyses de réseaux d'expression différentielle et de co-expression pour cataloguer le chevauchement entre la DM humaine et 3 modèles murins de stress, à savoir le stress variable chronique, l'isolement social et le stress par défaite sociale chronique, et avons évalué leur capacité à reproduire les profils transcriptionnels associés à la DM humaine dans deux régions du cerveau, le mPFC et le NAc, largement impliquées dans la dépression. Nos résultats montrent que chaque modèle reproduit efficacement les caractéristiques transcriptionnelles communes mais aussi uniques du syndrome humain. Dans l'ensemble, en identifiant des groupes de gènes fortement co-exprimés, partagés entre l'homme et la souris, nos résultats suggèrent que ces signatures transcriptionnelles sont impliquées de manière similaire dans le contrôle des voies fonctionnelles chez les deux espèces et confèrent un fort soutien à l'utilisation de ces modèles de souris pour l'étude des altérations moléculaires observées dans la DM tout en fournissant des implications importantes pour la recherche future et les applications cliniques.Major depressive disorder (MDD) is the leading cause of disability for three decades with over 300 million affected worldwide. Indeed, it is a major contributor to the overall global economic burden of disease. Despite its significant societal impact, the biological mechanisms of depression remain poorly understood. Unfortunately, only around 30% of patients treated for depression show complete improvement in their symptoms. Given, the high failure rate of antidepressant clinical trials, there has been increased scrutiny recently regarding their use for deciphering the neurobiology of depression and to design potential treatment interventions. Given the fact that most of our knowledge of the field comes from animal models, indeed, these models reproduce some aspects of human MDD but to what degree remains unknown. This work elucidates the extent to which they recapitulate the molecular pathology of the human disorder. In this thesis, we leveraged differential expression and co-expression network analyses to catalogue the overlap between human MDD and 3 mouse model of stress, namely chronic variable stress, social isolation and chronic social defeat stress, and evaluated their capacity of reproducing the transcriptional profiles associated with human MDD in two brain regions, mPFC and NAc, widely implicated in depression. Our results show that each model efficiently reproduces common but also unique transcriptional features of the human syndrome.Overall, by identifying strongly co-expressed groups of genes shared between humans and mice, our results suggest that these transcriptional signatures are similarly involved in the control of functional pathways in both species and confer strong support for the use of these mouse models for the study of the molecular alterations seen in MDD while providing important implications for future research and clinical applications