1,173 research outputs found

    Improving the Institutional Behaviour of Prisoners: Challenges and Opportunities for Behaviour Analysis

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    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 “what works” 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/

    Understanding and improving the applicability of randomised controlled trials: subgroup reporting and the statistical calibration of trials to real-world populations

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    Context and objective Randomised controlled trials (hereafter, trials) are widely regarded as the gold standard for evaluating treatment efficacy in medical interventions. They employ strict study designs, rigorous eligibility criteria, standardised protocols, and close participant monitoring under controlled conditions, contributing to high internal validity. However, these stringent criteria and procedures may limit the generalisability of trial findings to real-world situations, which often involve diverse patient populations such as multimorbidity and frailty patients. Consequently, there is growing interest in the applicability of trials to real-world clinical practice. In this thesis I will 1) evaluate how well major trials report on variation in treatment effects and 2) examine the use of trial calibration methods to test trial applicability. Methods 1) A comprehensive and consistent subgroup reporting description was presented, which contributes to the exploration of subgroup effects and treatment heterogeneity for informed decision-making in tailored subgroup populations within routine practice. The study evaluated 2,235 trials from clinicaltrial.gov that involve multiple chronic medical conditions, assessing the presence of subgroup reporting in corresponding publications and extracting subgroup terms. These terms were then standardised and summarised using Medical Subject Headings and WHO Anatomical Therapeutic Chemical codes. Logistic and Poisson regression models were employed to identify independent predictors of subgroup reporting patterns. 2) Two calibration models, namely the regression-based model and inverse odds of sampling weights (IOSW) were implemented. These models were utilised to apply the findings from two influential heart failure (HF) trials - COMET and DIG - to a real-world HF registry in Scotland consisting of 8,012 HF patients mainly with reduced ejection fraction, using individual participant data (IPD) from both datasets. Additionally, calibration was conducted within the subgroup population (lowest and highest risk group) of the real-world Scottish HF registry for exploratory analyses. The study provided comparisons of baseline characteristics and calibrated and uncalibrated results between the trial and registry. Furthermore, it assessed the impact of calibration on the results with the focus on overall effects and precision. Results The subgroup reporting study showed that among 2,235 eligible trials, 48% (1,082 trials) reported overall results and 23% (524 trials) reported subgroups. Age (51%), gender (45%), racial group (28%) and geographical locations (17%) were the most frequently reported subgroups among 524 trials. Characteristics related to the index condition (severity/duration/types, etc.) were somewhat commonly reported. However, reporting on metrics of comorbidity or frailty and mental health were rare. Follow-up time, enrolment size, trial starting year and specific index conditions (e.g., hypercholesterolemia, hypertension etc.) were significant predictors for any subgroup reporting after adjusting for enrolment size and index conditions while funding source and number of arms were not associated with subgroup reporting. The trial calibration study showed that registry patients were, on average, older, had poorer renal function and received higher-doses of loop diuretics than trial participants. The key findings from two HF trials remained consistent after calibration in the registry, with a tolerable decrease in precision (larger confidence intervals) for the effect estimates. Treatment-effect estimates were also similar when trials were calibrated to high-risk and low-risk registry patients, albeit with a greater reduction in precision. Conclusion Variations in subgroup reporting among different trials limited the feasibility to evaluate subgroup effects and examine heterogeneity of treatment effects. If IPD or IPD alternative summarised data is available from trials and the registry, trial applicability can be assessed by performing calibration

    Regional variation in diagnosis, prognosis and treatment of Guillain-Barré syndrome

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    Regional variation in diagnosis, prognosis and treatment of Guillain-Barré syndrome

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    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) 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 – 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 Católica 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

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This ïŹfth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different ïŹelds of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modiïŹed Proportional ConïŹ‚ict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classiïŹers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identiïŹcation of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classiïŹcation. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classiïŹcation, and hybrid techniques mixing deep learning with belief functions as well

    Cardiovascular health, orthostatic hypotension, and cognitive aging

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    Cardiovascular health (CVH) plays an important role in dementia development. Ideal CVH, defined by Life’s Simple 7 (LS7), has been associated with a lower risk of dementia in older adults. Orthostatic hypotension (OH) may be a novel cardiovascular risk factor that can affect dementia development. In this thesis, population-based cohort studies were conducted to investigate the role of LS7-defined CVH and OH in cognitive aging in people aged ≄60 years using data from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K). Study I investigated LS7-defined CVH in relation to transitions between normal cognition, cognitive impairment, no dementia (CIND), and dementia. The study found that people with better CVH had a lower hazard of transitioning directly from normal cognition to CIND (HR = 0.76, 95% CI = 0.61-0.95) and dementia (HR = 0.42, 95% CI = 0.21-0.82) in people aged <78 years. In addition, people aged <78 years with better CVH had two to three more years of life living with normal cognition. However, CVH, defined by LS7, was not related to transitions between cognitive states in people aged ≄78 years. Study II evaluated the associations between OH and dementia. Of the 2532 people who were initially free of dementia, 615 (24.3%) people had OH. People with OH had higher hazards of developing dementia (HR = 1.40, 95% CI = 1.10–1.76) and Alzheimer’s disease (HR = 1.39, 95% CI = 1.04–1.86). In addition, OH was related to a higher hazard of progression from CIND to dementia in people with CIND (HR = 1.54, 95% CI = 1.05–2.25) but not with incident CIND in those without CIND and dementia (HR = 1.15, 95% CI = 0.94–1.40). Study III investigated the impact of OH on the development of CVDs and dementia in people initially free of CVDs as well as the impact of OH on dementia development in people with CVDs. The study found that in people who were initially free of CVDs, individuals who had OH at baseline had a higher hazard of developing CVDs (HR = 1.33, 95% CI = 1.12-1.59) but not dementia (HR = 1.22, 95% CI = 0.83-1.81) compared to those without OH. Among those with CVDs, persons with OH also had a higher hazard of dementia (HR = 1.54, 95% CI = 1.06-2.23) compared to those without OH. Study IV assessed the associations of OH, in the presence or absence of frailty, with dementia and mortality. This study found that individuals who had OH at baseline had a higher hazard of dementia in the presence (HR = 2.73, 95% CI = 1.82-4.10) and absence (HR = 2.28, 95% CI = 1.47-3.54) of frailty than robust persons without OH. However, OH was only associated with a higher hazard of death without dementia when accompanied by frailty (HR = 1.56, 95% CI = 1.25-1.96). Conclusions. Maintaining ideal CVH may protect against cognitive dysfunction and reduce years of life with cognitive dysfunction in younger old age. OH may be a potential modifiable risk factor for dementia, and the intermediate development of CVDs may help explain the association between OH and dementia
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