Bayesian nonparametric models for spatially indexed data of mixed type

We develop Bayesian nonparametric models for spatially indexed data of mixed type. Our work is motivated by challenges that occur in environmental epidemiology, where the usual presence of several confounding variables that exhibit complex interactions and high correlations makes it difficult to estimate and understand the effects of risk factors on health outcomes of interest. The modeling approach we adopt assumes that responses and confounding variables are manifestations of continuous latent variables, and uses multivariate Gaussians to jointly model these. Responses and confounding variables are not treated equally as relevant parameters of the distributions of the responses only are modeled in terms of explanatory variables or risk factors. Spatial dependence is introduced by allowing the weights of the nonparametric process priors to be location specific, obtained as probit transformations of Gaussian Markov random fields. Confounding variables and spatial configuration have a similar role in the model, in that they only influence, along with the responses, the allocation probabilities of the areas into the mixture components, thereby allowing for flexible adjustment of the effects of observed confounders, while allowing for the possibility of residual spatial structure, possibly occurring due to unmeasured or undiscovered spatially varying factors. Aspects of the model are illustrated in simulation studies and an application to a real data set

Home sampling for sexually transmitted infections and HIV in men who have sex with men: a prospective observational study

To determine uptake of home sampling kit (HSK) for STI/HIV compared to clinic-based testing, whether the availability of HSK would increase STI testing rates amongst HIV infected MSM, and those attending a community-based HIV testing clinic compared to historical control. Prospective observational study in three facilities providing STI/HIV testing services in Brighton, UK was conducted. Adult MSM attending/contacting a GUM clinic requesting an STI screen (group 1), HIV infected MSM attending routine outpatient clinic (group 2), and MSM attending a community-based rapid HIV testing service (group 3) were eligible. Participants were required to have no symptomatology consistent with STI and known to be immune to hepatitis A and B (group 1). Eligible men were offered a HSK to obtain self-collected specimens as an alternative to routine testing. HSK uptake compared to conventional clinic based STI/HIV testing in group 1, increase in STI testing rates due to availability of HSK compared to historical controls in group 2 and 3, and HSK return rates in all settings were calculated. Among the 128 eligible men in group 1, HSK acceptance was higher (62.5% (95%CI: 53.5–70.9)) compared to GUM clinic-based testing (37.5% (95% CI: 29.1–46.5)), (p = 0.0004). Two thirds of eligible MSM offered an HSK in all three groups accepted it, but HSK return rates varied (highest in group 1, 77.5%, lowest in group 3, 16%). HSK for HIV testing was acceptable to 81%of men in group 1. Compared to historical controls, availability of HSK increased the proportion of MSM testing for STIs in group 2 but not in group 3. HSK for STI/ HIV offers an alternative to conventional clinic-based testing for MSM seeking STI screening. It significantly increases STI testing uptake in HIV infected MSM. HSK could be considered as an adjunct to clinic-based services to further improve STI/HIV testing in MSM

Rapid Evidence Assessment: What can be learnt from other jurisdictions about preventing and responding to child sexual abuse

This Rapid Evidence Assessment was commissioned by the Independent Inquiry into Child Sexual Abuse in England and Wales which is investigating whether public bodies and other non-state institutions have taken seriously their duties to care for and protect children and young people from child sexual abuse and exploitation. The question for the review was: What can be learnt from jurisdictions, outside of England and Wales, about the role of institutions, including accountable state and non-state organisations with responsibility for children in preventing and responding to child sexual abuse and exploitation? Key messages ● No jurisdiction has everything ‘right’. While overall robust research on what is effective is limited, there is plenty of promising evidence that can be developed further to inform work in England and Wales. ● Adequately resourced, comprehensive, multi sector approaches that aim to prevent and respond to child sexual abuse and exploitation are likely to be the most effective approaches. ● Effective responses are those able to meet the complexity and diversity of the needs of children and young people who are vulnerable or affected. ● Work with sexual offenders could broaden out to include earlier intervention to prevent offending by adults and adolescents who have not been convicted. Findings Primary prevention None of the jurisdictions1 included in the review had a comprehensive approach combining primary prevention and response but we found more evidence of prevention efforts in Australia, Finland, Norway, Sweden and the USA. Changing attitudes and behaviour by education or awareness raising - There is moderately good evidence from Canada and the USA that pre-school and school based education programmes on child sexual abuse are effective at teaching children to recognise inappropriate behaviour and improving their knowledge of self protection. Research in Australia and the USA supports whole school approaches and involving parents, faith and community groups. Public education and social marketing campaigns to prevent abuse are commonly used but poorly evaluated. 1 Wales, Scotland, Northern Ireland, Ireland, EU 28 countries, Norway, Iceland, USA, Canada, Australia, New Zealand Situational prevention – The UK has led primary prevention and early identification efforts online and there is evidence of successful take-down, site blocking, extensive take up of online safety resources and considerable international collaboration through the work of CEOP, the National Crime Agency, and participation in the Global Alliance and WePROTECT. In other organisational contexts, efforts have been more limited covering pre-employment checks, vetting and barring. While important, these only exclude the minority of offenders already known or convicted. Inquiries in the USA, Germany, the Netherlands, Belgium and Ireland on institutional child abuse in churches show we need a wider focus on organisational safety and the opportunities for unmonitored contact. Reducing vulnerabilities - Very little evidence could be found on the best approaches to reduce the vulnerabilities of children to sexual abuse and exploitation in the jurisdictions covered. Some promising evidence from the UK, Canada and the Netherlands was found from Stop It Now which aims to reduce offending among those not previously identified as offenders. Disclosure, identification, reporting and response Professionals need to be aware of the barriers children face in disclosing abuse and trained to recognise signs of abuse other than the child’s disclosure. Identification in children’s social services, education and health particularly needs to be recognised as a process of proactively asking, building a relationship with a vulnerable child or young person and collecting information from a range of sources over time. Research in Australia confirms that mandatory reporting can increase reports of child sexual abuse but that resources are needed to manage these. The number of cases investigated but not then substantiated also increased. From Australia and the USA, there is evidence that training, proactive identification and promoting expertise and good practice through specialist mobile teams or task forces in health, justice and child protection can have a positive impact. For health, use of new technologies such as telemedicine can give access to specialist skills. Also in Australia, proactive approaches to involve the wider community in identification and reporting had a positive impact on reporting rates, arrests, prosecution and convictions for child sexual abuse cases. Support for children through prosecution and the court process is generally poor but there is promising evidence on the effectiveness of co-located multi-disciplinary services such as the National Children’s Advocacy Centers in the USA and the Children’s Houses (or Barnahus) in Iceland and other parts of Europe. Managing offenders Management of offenders has focused largely on those high risk sexual offenders against children already convicted. In the UK, Germany and Sweden, attention is shifting to look at offenders at lower levels of assessed risk, including those not convicted. More work is needed on effective responses for health, education and social work; on managing peer abusers; on improving prosecution and the use of appropriate sanctions for offenders in organisations such as churches and faith groups. Commonly used policies such as sexual offender registration, notification schemes and residency restrictions evaluated in the USA found these have not been effective in reducing recidivism and may work against efforts to rehabilitate offenders. Sex offender treatment responses are more likely to be effective if they can address the type of offence and level of risk, the offender’s criminogenic needs, learning style and abilities. Restorative justice approaches to sex offender treatment such as Circles of Support and Accountability show promising results from Australia and the US, but have high levels of programme drop out. Treatment responses developed for adults are less relevant for young people who present with harmful sexual behaviour. There is more evidence to support the use of MST than CBT based treatment approaches for young people who present with harmful sexual behaviour. Supporting victims and survivors There are significant gaps in the availability of relevant support and therapeutic services for child victims of sexual abuse in the UK and funding for services addressing significant risks such as domestic abuse has declined. Research from Scotland on guardianship schemes shows positive results improving support for trafficked young people. Advocacy schemes do not prevent sexually exploited young people from going missing, but can ensure there is a coordinated response should this happen. The evidence on victim support and recovery focuses mostly on child sexual abuse, while needs of those who have been sexually exploited may differ. Best evidence on therapeutic treatment for children exists for trauma focused CBT although a variety of therapeutic methods, for example those using drama or EMDR, also show promise. Therapy approaches may be more effective when tailored to the individual needs of the child or young person, taking into account their specific symptom constellation, development, context, and background. Evidence from other jurisdictions on the effectiveness of victim redress, compensation schemes, no fault insurance, publicly available insurance registers and the structure and source of different funding streams could not be found. Implications ● A wider focus on prevention and response is needed, with prevention moving beyond teaching children to protect themselves and beyond the regulation of convicted sexual offenders to focus on wider prevention efforts targeting risks and vulnerabilities. ● Prevention and response needs to be comprehensive, cover the complexity and diversity of children’s experiences and be guided by leadership promoting an outcome focused theory of change. ● Responsibility for preventing and responding to child sexual abuse and exploitation needs to extend beyond specialist and child protection services to include the wider range of organisations, particularly faith groups, industry, the private sector, sport and leisure. The National Response Unit and proposed Centre for Excellence (in the UK) could play an important role in partnerships. ● Research from the USA and Canada provides evidence for prevention delivered in schools to increase children’s knowledge and awareness and starting to change the attitudes and environments that contribute to abuse. A strong argument could be made for compulsory PSHE for all schools and academies on safety and respectful relationships. ● Additional resources will be needed to deal with increased reports and additional screening procedures that will result if mandatory reporting is introduced. ● The gaps in knowledge identified in this review could be used to inform priorities for future funding. Approach The project was desk based using recognised methods for rapid evidence assessment. Rapid evidence assessments, like systematic reviews, aim to thoroughly and transparently identify and assess the evidence on a particular topic but within a more limited time frame and with restrictions on the breadth of literature included. Using agreed search terms, we searched online databases (Embase, ASSIA, PsychInfo, Social Work Abstracts and Criminal Justice Abstracts) and websites for relevant peer reviewed articles and research reports on effective responses delivered by different institutions from jurisdictions outside of, but similar to, those in England and Wales. Grey literature and references in publications included were additionally searched. We rated 1,460 relevant studies for quality and included 88 high quality studies in the review. To address gaps in the research, we were asked to identify examples of responses where the evidence was promising but did not yet meet quality standards. We were also asked to discuss the findings with reference to the current context of research, policy and practice in England and Wales. This meant reading a large body of additional materials which we included in the report bibliography. A full description of the methods are in the research report. Limitations The scope of the Rapid Evidence Assessment was narrow and might not have identified all the relevant evidence. The search was limited to articles published in English, between 2004- 2016, in peer reviewed journals and online in ‘grey literature’ research reports. We were unable to consult with international academic or practice experts to check whether all significant research evidence had been covered, but the draft report was reviewed by the IICSA advisory groups, including academic experts, who made suggestions on research to include (mostly from the UK)

Suicidal students' use of and attitudes to primary care prevention services

Aim The aims of this study were to improve responses to students in distress and who are feeling suicidal, to help practitioners to increase their responsiveness to those at high risk of suicide and to develop effective responses to those affected by their deaths. The study sought to build a detailed picture of students’ patterns of service use. Background National suicide prevention strategies emphasise that suicide prevention requires the collaboration of a wide range of organisations. Among these, primary care services play a key role in relation to suicide prevention for young people in crisis. Methods This study, undertaken between 2004 and 2007, focused on 20 case studies of student suicide that took place in the United Kingdom between May 2000 and June 2005. It adopted a psychological autopsy approach to learn from a wide range of informants, including parents, friends, university staff and the records of coroners or procurator fiscals. Twenty families gave permission for their son’s or daughter’s death to be included in the study and agreed to participate in the study. Informants were interviewed in person and the data were analysed thematically. Analysis of the case study data suggested that in a number of cases students had failed to engage with services sufficiently early or in sufficient depth. Primary care practitioners need to be proactive in communicating concerns about vulnerable students to student support services. At local levels, collaboration between student support and National Health Service practitioners varied considerably and channels of communication need to be developed

Interpreting Posterior Relative Risk Estimates in Disease-Mapping Studies

There is currently much interest in conducting spatial analyses of health outcomes at the small-area scale. This requires sophisticated statistical techniques, usually involving Bayesian models, to smooth the underlying risk estimates because the data are typically sparse. However, questions have been raised about the performance of these models for recovering the “true” risk surface, about the influence of the prior structure specified, and about the amount of smoothing of the risks that is actually performed. We describe a comprehensive simulation study designed to address these questions. Our results show that Bayesian disease-mapping models are essentially conservative, with high specificity even in situations with very sparse data but low sensitivity if the raised-risk areas have only a moderate (< 2-fold) excess or are not based on substantial expected counts (> 50 per area). Semiparametric spatial mixture models typically produce less smoothing than their conditional autoregressive counterpart when there is sufficient information in the data (moderate-size expected count and/or high true excess risk). Sensitivity may be improved by exploiting the whole posterior distribution to try to detect true raised-risk areas rather than just reporting and mapping the mean posterior relative risk. For the widely used conditional autoregressive model, we show that a decision rule based on computing the probability that the relative risk is above 1 with a cutoff between 70 and 80% gives a specific rule with reasonable sensitivity for a range of scenarios having moderate expected counts (~ 20) and excess risks (~1.5- to 2-fold). Larger (3-fold) excess risks are detected almost certainly using this rule, even when based on small expected counts, although the mean of the posterior distribution is typically smoothed to about half the true value

Using DIC to compare selection models with non-ignorable missing responses

Data with missing responses generated by a non-ignorable missingness mechanism can be analysed by jointly modelling the response and a binary variable indicating whether the response is observed or missing. Using a selection model factorisation, the resulting joint model consists of a model of interest and a model of missingness. In the case of non-ignorable missingness, model choice is difficult because the assumptions about the missingness model are never verifiable from the data at hand. For complete data, the Deviance Information Criterion (DIC) is routinely used for Bayesian model comparison. However, when an analysis includes missing data, DIC can be constructed in different ways and its use and interpretation are not straightforward. In this paper, we present a strategy for comparing selection models by combining information from two measures taken from different constructions of the DIC. A DIC based on the observed data likelihood is used to compare joint models with different models of interest but the same model of missingness, and a comparison of models with the same model of interest but different models of missingness is carried out using the model of missingness part of a conditional DIC. This strategy is intended for use within a sensitivity analysis that explores the impact of different assumptions about the two parts of the model, and is illustrated by examples with simulated missingness and an application which compares three treatments for depression using data from a clinical trial. We also examine issues relating to the calculation of the DIC based on the observed data likelihood

Propensity Score Adjustment for Unmeasured Confounding in Observational Studies

Adjusting for several unmeasured confounders is a challenging problem in the analysis of observational data. Information about unmeasured confounders is sometimes available from external validation data, such as surveys or secondary samples drawn from the same source population. In principal, the validation permits us to recover information about the missing data, but the difficulty is in eliciting a valid model for nuisance distribution of the unmeasured confounders. Motivated by a British study of the effects of trihalomethane exposure on full-term low birthweight, we describe a flexible Bayesian procedure for adjusting for a vector of unmeasured confounders using external validation data. We summarize the unmeasured confounders with a scalar summary score using the propensity score methodology of Rosenbaum and Rubin. The score has the property that it breaks the dependence between the exposure and unmeasured confounders within levels of measured confounders. To adjust for unmeasured confounding in a Bayesian analysis, we need only update and adjust for the summary score during Markov chain Monte Carlo simulation. We demonstrate that trihalomethane exposure is associated with increased risk of full-term low birthweight, and this association persists even after adjusting for eight unmeasured confounders. Empirical results from simulation illustrate that our proposed method eliminates bias from several unmeasured confounders, even in small samples

Adjustment for Missing Confounders Using External Validation Data and Propensity Scores

Reducing bias from missing confounders is a challenging problem in the analysis of observational data. Information about missing variables is sometimes available from external validation data, such as surveys or secondary samples drawn from the same source population. In principle, the validation data permits us to recover information about the missing data, but the di�culty is in eliciting a valid model for nuisance distribution of the missing confounders. Motivated by a British study of the e�ects of trihalomethane exposure on risk of full-term low birthweight, we describe a exible Bayesian procedure for adjusting for a vector of missing confounders using external validation data. We summarize the missing confounders with a scalar summary score using the propensity score methodology of Rosenbaum and Rubin. The score has the property that it induces conditional independence between the exposure and the missing confounders given the measured confounders. It balances the unmeasured confounders across exposure groups, within levels of measured covariates. To adjust for bias, we need only model and adjust for the summary score during Markov chain Monte Carlo simulation. Simulation results illustrate that the proposed method reduces bias from several missing confounders over a range of di�erent sample sizes for the validation data