2,876 research outputs found
Improving the Institutional Behaviour of Prisoners: Challenges and Opportunities for Behaviour Analysis
Prisoner misconduct presents a significant issue to correctional administrators, disrupting the orderly running of regimes, endangering safety, and negatively impacting the health and well-being of both prisoners and frontline staff. While an extensive literature has emerged around rehabilitative intervention with offenders, research efforts have been more commonly directed towards reducing post-release recidivism, resulting in a relatively sparse literature concerning the in-prison behaviour of prisoners. Persistent and rising levels of violent and disruptive behaviour in prisons highlight the need for greater research attention to be devoted to this issue. The field of applied behaviour analysis may be well placed to address this research deficit, with historical work in prisons and more recent efforts in juvenile justice settings suggesting that approaches derived from behaviour analysis may hold promise in correctional settings. This includes an emerging literature relating to the adaptation of school-wide Positive Behavioural Interventions and Supports (PBIS) to juvenile justice facilities. PBIS offers a framework within which to integrate a continuum of evidencebased practices to address the needs of the population to which it is applied. Preliminary evidence suggests that the approach is feasible, is viewed positively by residents and staff, and can be efficacious in improving resident behaviour in these settings. However, addressing prisoner misconduct within adult prisons may present distinct challenges to that of juvenile forensic settings, given differences in their size, staffing ratios, and focus on education and rehabilitation. This thesis aimed to contribute to the literature on identifying effective behavioural interventions for use with adult prisoners. First, a comprehensive systematic review was conducted to explore the range of interventions directed towards reducing prisoner misconduct and identify âwhat worksâ in reducing institutional infractions (Chapter 2). Findings suggested that cognitive behavioural approaches reduced violent infractions but not overall misconduct, while therapeutic community interventions and educational approaches reduced overall misconduct. Second, focus groups were conducted with prisoners and frontline staff (prison officers) to assess valued intervention outcomes and explore potential barriers for PBIS implementation (Chapter 3). Three overarching values were identified: a need for rehabilitation, consistency, and respect. Potential barriers to PBIS included pessimistic views towards rehabilitative approaches and perceptions of limited resources. Third, the intervention design process of a universal (Tier 1) intervention strategy was described that incorporated evidence-based practices, stakeholder values, and institutional data on prisoner behaviour, whilst also operating within available resources (Chapter 4). The resulting intervention was a peer-led approach that focussed on increasing prisoner engagement in purposeful activity. Fourth, a feasibility study was conducted to establish the viability of the intervention as well as the feasibility of research procedures in the setting (Chapter 5). The intervention successfully promoted prisoner engagement, with prisoners reporting beneficial effects on behaviour, social relationships, and well-being. Staff perceptions of the approach were more tempered but generally positive. Institutional records did not appear sufficiently sensitive to detect changes in prisoner misconduct, suggesting that alternative measurement approaches may need to be identified. Finally, opportunities and barriers to behaviour analytic research in adult prisons were explored (Chapter 6), highlighting the continued relevance of the seven dimensions of behaviour analysis to prisonbased research.<br/
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Mistreatment in Childbirth: A mixed-methods approach to understand the mental health sequelae of mistreatment in maternity care among a diverse cohort of birthing persons in New York City
The present study aimed to explore the objective and subjective experiences of âmistreatmentâ in maternity care in a diverse cohort of women who gave birth in New York City hospitals to identify the prevalence and risk factors of mistreatment and measure the relationship between mistreatment and mental health (Bohren et al., 2015). The study utilized a mixed-methods cross-sectional approach. To collect the quantitative data, 109 participants <1 year postpartum completed an anonymous online survey comprising a self-report measure of demographic, health and mental health information, several mental health questionnaires and two measures of mistreatment in maternity care. 8 of these participants were interviewed about their childbirth experience. The quantitative data was analyzed utilizing linear regression, moderation analysis and path analysis, and the qualitative data was thematically coded then analyzed using Reflexive Thematic (RT) analysis. These data were then triangulated using a mixed-methods model of mistreatment.
In total, 10-15% of the sample experienced mistreatment in the form of Low to Very Low respect and/or autonomy in decision making in their maternity care. Forms of mistreatment included unwanted procedures, provider pressure to undergo procedures, dismissal of womenâs concerns, racial discrimination, abandonment, and medical neglect. Approximately 25% of respondents received an unwanted intervention; this was the most significant predictor of mistreatment. This relationship was moderated by race, parity and birth plan. Black, Latinx and Hispanic women experienced the lowest levels of respect in maternity care. Mistreatment in maternity care was correlated with increased risk for postpartum mental illness: decreased respect and autonomy in childbirth was associated with increased postpartum depression and PTSD symptoms.
Eight themes were identified in the qualitative analysis: Discrimination and Unfair Treatment, Confusion and Abandonment, Disregard for Patient Autonomy, Hospital-Level Drivers of Mistreatment, Women Treated as Passive, Normalization of Mistreatment, Self-Advocacy and Vulnerability and, Reclaiming Power through Knowledge. Together, the triangulated mixed- methods data were fit to render a comprehensive âmodel of mistreatmentâ to illustrate direct and indirect relationships between mistreatment, mental health, race, trauma history, and childbirth preparation. These findings demonstrate that mistreatment is a multi-determined phenomenon that is interdependent with mental health and requires systematic measurement in healthcare treatment, the integration of anti-racist and patient-centered care and improved childbirth education for patients
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
Multidisciplinary perspectives on Artificial Intelligence and the law
This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (âAIâ) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics â and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the CatĂłlica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio
UMSL Bulletin 2022-2023
The 2022-2023 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1087/thumbnail.jp
Current and Future Challenges in Knowledge Representation and Reasoning
Knowledge Representation and Reasoning is a central, longstanding, and active
area of Artificial Intelligence. Over the years it has evolved significantly;
more recently it has been challenged and complemented by research in areas such
as machine learning and reasoning under uncertainty. In July 2022 a Dagstuhl
Perspectives workshop was held on Knowledge Representation and Reasoning. The
goal of the workshop was to describe the state of the art in the field,
including its relation with other areas, its shortcomings and strengths,
together with recommendations for future progress. We developed this manifesto
based on the presentations, panels, working groups, and discussions that took
place at the Dagstuhl Workshop. It is a declaration of our views on Knowledge
Representation: its origins, goals, milestones, and current foci; its relation
to other disciplines, especially to Artificial Intelligence; and on its
challenges, along with key priorities for the next decade
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