Using Bayesian networks to guide the assessment of new evidence in an appeal case.

When new forensic evidence becomes available after a conviction there is no systematic framework to help lawyers to determine whether it raises sufficient questions about the verdict in order to launch an appeal. This paper presents such a framework driven by a recent case, in which a defendant was convicted primarily on the basis of audio evidence, but where subsequent analysis of the evidence revealed additional sounds that were not considered during the trial. The framework is intended to overcome the gap between what is generally known from scientific analyses and what is hypothesized in a legal setting. It is based on Bayesian networks (BNs) which have the potential to be a structured and understandable way to evaluate the evidence in a specific case context. However, BN methods suffered a setback with regards to the use in court due to the confusing way they have been used in some legal cases in the past. To address this concern, we show the extent to which the reasoning and decisions within the particular case can be made explicit and transparent. The BN approach enables us to clearly define the relevant propositions and evidence, and uses sensitivity analysis to assess the impact of the evidence under different assumptions. The results show that such a framework is suitable to identify information that is currently missing, yet clearly crucial for a valid and complete reasoning process. Furthermore, a method is provided whereby BNs can serve as a guide to not only reason with incomplete evidence in forensic cases, but also identify very specific research questions that should be addressed to extend the evidence base and solve similar issues in the future.This research was funded by the Engineering and Physical Sciences Research Council of the UK through the Security Science Doctoral Research Training Centre (UCL SECReT) based at University College London (EP/G037264/1), and the European Research Council (ERC-2013-AdG339182-BAYES_KNOWLEDGE)

Evidence maps and evidence gaps: evidence review mapping as a method for collating and appraising evidence reviews to inform research and policy

Evidence reviews are a key mechanism for incorporating extensive, complex and specialised evidence into policy and practice, and in guiding future research. However, evidence reviews vary in scope and methodological rigour, creating several risks for decision-makers: decisions may be informed by less reliable reviews; apparently conflicting interpretations of evidence may obfuscate decisions; and low quality reviews may create the perception that a topic has been adequately addressed, deterring new syntheses (cryptic evidence gaps). We present a new approach, evidence review mapping, designed to produce a visual representation and critical assessment of the review landscape for a particular environmental topic or question. By systematically selecting and describing the scope and rigour of each review, this helps guide non-specialists to the most relevant and methodologically reliable reviews. The map can also direct future research through the identification of evidence gaps (whether cryptic or otherwise) and redundancy (multiple reviews on similar questions). We consider evidence review mapping a complementary approach to systematic reviews and systematic maps of primary literature and an important tool for facilitating evidence-based decision-making and research efficiency

Evaluation of a risk-stratification strategy to improve primary care for low back pain: the MATCH cluster randomised trial protocol

Background Despite numerous options for treating back pain and the increasing healthcare resources devoted to this problem, the prevalence and impact of back pain-related disability has not improved. It is now recognized that psychosocial factors, as well as physical factors, are important predictors of poor outcomes for back pain. A promising new approach that matches treatments to the physical and psychosocial obstacles to recovery, the STarT Back risk stratification approach, improved patients’ physical function while reducing costs of care in the United Kingdom (UK). This trial evaluates implementation of this strategy in a United States (US) healthcare setting. Methods Six large primary care clinics in an integrated healthcare system in Washington State were block-randomized, three to receive an intensive quality improvement intervention for back pain and three to serve as controls for secular trends. The intervention included 6 one-hour training sessions for physicians, 5 days of training for physical therapists, individualized and group coaching of clinicians, and integration of the STarT Back tool into the electronic health record. This prognostic tool uses 9 questions to categorize patients at low, medium or high risk of persistent disabling pain with recommendations about evidence-based treatment options appropriate for each subgroup. Patients at least 18 years of age, receiving primary care for non-specific low back pain, were invited to provide data 1–3 weeks after their primary care visit and follow-up data 2 months and 6 months (primary endpoint) later. The primary outcomes are back-related physical function and pain severity. Using an intention to treat approach, intervention effects on patient outcomes will be estimated by comparing mean changes at the 2 and 6 month follow-up between the pre- and post-implementation periods. The inclusion of control clinics permits adjustment for secular trends. Differences in change scores by intervention group and time period will be estimated using linear mixed models with random effects. Secondary outcomes include healthcare utilization and adherence to clinical guidelines. Discussion This trial will provide the first randomized trial evidence of the clinical effectiveness of implementing risk stratification with matched treatment options for low back pain in a United States health care delivery system

Cervelleite, Ag4TeS: solution and description of the crystal structure

Copyright: Springer-Verlag Wien 2015. This is the final, post refereeing version. You are advised to consult the publisher's version if you wish to cite from it, http://link.springer.com/article/10.1007%2Fs00710-015-0384-

The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning

Positive testing is characteristic of exploratory behavior, yet it seems to be at odds with the aim of information seeking. After all, repeated demonstrations of one’s current hypothesis often produce the same evidence and fail to distinguish it from potential alternatives. Research on the development of scientific reasoning and adult rule learning have both documented and attempted to explain this behavior. The current chapter reviews this prior work and introduces a novel theoretical account—the Search for Invariance (SI) hypothesis—which suggests that producing multiple positive examples serves the goals of causal learning. This hypothesis draws on the interventionist framework of causal reasoning, which suggests that causal learners are concerned with the invariance of candidate hypotheses. In a probabilistic and interdependent causal world, our primary goal is to determine whether, and in what contexts, our causal hypotheses provide accurate foundations for inference and intervention—not to disconfirm their alternatives. By recognizing the central role of invariance in causal learning, the phenomenon of positive testing may be reinterpreted as a rational information-seeking strategy

A systematic review and meta-synthesis of the impact of low back pain on people's lives

Copyright @ 2014 Froud et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.Background - Low back pain (LBP) is a common and costly problem that many interpret within a biopsychosocial model. There is renewed concern that core-sets of outcome measures do not capture what is important. To inform debate about the coverage of back pain outcome measure core-sets, and to suggest areas worthy of exploration within healthcare consultations, we have synthesised the qualitative literature on the impact of low back pain on people’s lives. Methods - Two reviewers searched CINAHL, Embase, PsycINFO, PEDro, and Medline, identifying qualitative studies of people’s experiences of non-specific LBP. Abstracted data were thematic coded and synthesised using a meta-ethnographic, and a meta-narrative approach. Results - We included 49 papers describing 42 studies. Patients are concerned with engagement in meaningful activities; but they also want to be believed and have their experiences and identity, as someone ‘doing battle’ with pain, validated. Patients seek diagnosis, treatment, and cure, but also reassurance of the absence of pathology. Some struggle to meet social expectations and obligations. When these are achieved, the credibility of their pain/disability claims can be jeopardised. Others withdraw, fearful of disapproval, or unable or unwilling to accommodate social demands. Patients generally seek to regain their pre-pain levels of health, and physical and emotional stability. After time, this can be perceived to become unrealistic and some adjust their expectations accordingly. Conclusions - The social component of the biopsychosocial model is not well represented in current core-sets of outcome measures. Clinicians should appreciate that the broader impact of low back pain includes social factors; this may be crucial to improving patients’ experiences of health care. Researchers should consider social factors to help develop a portfolio of more relevant outcome measures.Arthritis Research U

Risk measures for direct real estate investments with non-normal or unknown return distributions

The volatility of returns is probably the most widely used risk measure for real estate. This is rather surprising since a number of studies have cast doubts on the view that volatility can capture the manifold risks attached to properties and corresponds to the risk attitude of investors. A central issue in this discussion is the statistical properties of real estate returns—in contrast to neoclassical capital market theory they are mostly non-normal and often unknown, which render many statistical measures useless. Based on a literature review and an analysis of data from Germany we provide evidence that volatility alone is inappropriate for measuring the risk of direct real estate. We use a unique data sample by IPD, which includes the total returns of 939 properties across different usage types (56% office, 20% retail, 8% others and 16% residential properties) from 1996 to 2009, the German IPD Index, and the German Property Index. The analysis of the distributional characteristics shows that German real estate returns in this period were not normally distributed and that a logistic distribution would have been a better fit. This is in line with most of the current literature on this subject and leads to the question which indicators are more appropriate to measure real estate risks. We suggest that a combination of quantitative and qualitative risk measures more adequately captures real estate risks and conforms better with investor attitudes to risk. Furthermore, we present criteria for the purpose of risk classification

Health services changes: is a run-in period necessary before evaluation in randomised clinical trials?

Background Most randomised clinical trials (RCTs) testing a new health service do not allow a run-in period of consolidation before evaluating the new approach. Consequently, health professionals involved may feel insufficiently familiar or confident, or that new processes or systems that are integral to the service are insufficiently embedded in routine care prior to definitive evaluation in a RCT. This study aimed to determine the optimal run-in period for a new physiotherapy-led telephone assessment and treatment service known as PhysioDirect and whether a run-in was needed prior to evaluating outcomes in an RCT. Methods The PhysioDirect trial assessed whether PhysioDirect was as effective as usual care. Prior to the main trial, a run-in of up to 12 weeks was permitted to facilitate physiotherapists to become confident in delivering the new service. Outcomes collected from the run-in and main trial were length of telephone calls within the PhysioDirect service and patients’ physical function (SF-36v2 questionnaire) and Measure Yourself Medical Outcome Profile v2 collected at baseline and six months. Joinpoint regression determined how long it had taken call times to stabilise. Analysis of covariance determined whether patients’ physical function at six months changed from the run-in to the main trial. Results Mean PhysioDirect call times (minutes) were higher in the run-in (31 (SD: 12.6)) than in the main trial (25 (SD: 11.6)). Each physiotherapist needed to answer 42 (95% CI: 20,56) calls for their mean call time to stabilise at 25 minutes per call; this took a minimum of seven weeks. For patients’ physical function, PhysioDirect was equally clinically effective as usual care during both the run-in (0.17 (95% CI: -0.91,1.24)) and main trial (-0.01 (95% CI: -0.80,0.79)). Conclusions A run-in was not needed in a large trial testing PhysioDirect services in terms of patient outcomes. A learning curve was evident in the process measure of telephone call length. This decreased during the run-in and stabilised prior to commencement of the main trial. Future trials should build in a run-in if it is anticipated that learning would have an effect on patient outcome

Observational Conditioning in Flower Choice Copying by Bumblebees (Bombus terrestris): Influence of Observer Distance and Demonstrator Movement

A. Avargues-Weber was funded by a postdoctoral fellowship from Fyssen fondation: http://www.fondationfyssen.fr/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Predictors of children's secondhand smoke exposure at home: a systematic review and narrative synthesis of the evidence

BACKGROUND: Children's exposure to secondhand smoke (SHS) has been causally linked to a number of childhood morbidities and mortalities. Over 50% of UK children whose parents are smokers are regularly exposed to SHS at home. No previous review has identified the factors associated with children's SHS exposure in the home. AIM: To identify by systematic review, the factors which are associated with children's SHS exposure in the home, determined by parent or child reports and/or biochemically validated measures including cotinine, carbon monoxide or home air particulate matter. METHODS: Electronic searches of MEDLINE, EMBASE, PsychINFO, CINAHL and Web of Knowledge to July 2014, and hand searches of reference lists from publications included in the review were conducted. FINDINGS: Forty one studies were included in the review. Parental smoking, low socioeconomic status and being less educated were all frequently and consistently found to be independently associated with children's SHS exposure in the home. Children whose parents held more negative attitudes towards SHS were less likely to be exposed. Associations were strongest for parental cigarette smoking status; compared to children of non-smokers, those whose mothers or both parents smoked were between two and 13 times more likely to be exposed to SHS. CONCLUSION: Multiple factors are associated with child SHS exposure in the home; the best way to reduce child SHS exposure in the home is for smoking parents to quit. If parents are unable or unwilling to stop smoking, they should instigate smoke-free homes. Interventions targeted towards the socially disadvantaged parents aiming to change attitudes to smoking in the presence of children and providing practical support to help parents smoke outside the home may be beneficial