Big Data and Causality

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Causality analysis continues to remain one of the fundamental research questions and the ultimate objective for a tremendous amount of scientific studies. In line with the rapid progress of science and technology, the age of big data has significantly influenced the causality analysis on various disciplines especially for the last decade due to the fact that the complexity and difficulty on identifying causality among big data has dramatically increased. Data mining, the process of uncovering hidden information from big data is now an important tool for causality analysis, and has been extensively exploited by scholars around the world. The primary aim of this paper is to provide a concise review of the causality analysis in big data. To this end the paper reviews recent significant applications of data mining techniques in causality analysis covering a substantial quantity of research to date, presented in chronological order with an overview table of data mining applications in causality analysis domain as a reference directory

Understanding prognosis independent of treatment for adults with depression in primary care

This thesis details the rationale and methods for compiling a large individual patient data (IPD) dataset of adults treated for depression in primary care, for the purpose of identifying predictors of prognosis independent of treatment. I present a narrative review of the knowledge of factors associated with prognosis for adults with depression, a narrative review of the merits and difficulties of utilising IPD data, and a protocol for a series of systematic reviews with IPD meta-analyses seeking to meet the above aim. I then present three such IPD meta-analyses. These focus on the associations between depressed patient’s pre-treatment characteristics, and i) prognosis independent of a range of treatments for depression in primary care, and ii) attrition from treatment. The first of these IPD meta-analyses is centred on depressive symptom severity and a group of factors that are associated with the degree of severity of a patient’s experience of depression, but which are separate from depressive symptoms, (I refer to these as indicators of depressive ‘disorder severity’). The second is centred on perceived social support. The third is centred on adverse life events in the six months prior to starting treatment, socio-demographics (age, gender, ethnicity, marital status, employment status, financial wellbeing, housing tenancy, and the highest level of educational attainment), and comorbid long-term physical health conditions. The thesis finishes with a critical review of the implications of these analyses, consideration of future directions and implications for clinical practice

Violent and non-violent crime against people with severe mental illness

Introduction: There is emerging evidence that people with severe mental illness (SMI) are at increased risk of being victims of violence and other crimes, but little is known about the extent, impact and reporting of violence against people with SMI compared with the general population. This thesis aimed to address key evidence gaps on victimisation among people with SMI. Methods: Work reported in this thesis includes: (a) A systematic review (on prevalence, relative risks and risk factors for violent victimisation among people with SMI), (b) Analysis of national survey data (from the British Crime Survey and the Adult Psychiatric Morbidity Survey), investigating violence against people with self-reported chronic mental illness (CMI) and (c) A new patient survey, based on modified national crime survey methods, investigating recent crime against patients with SMI compared with the general population. Results: Past-year physical or sexual violence was experienced by around 30% of people with SMI, 12% of those with self-reported CMI and 5-7% of the general population. After adjusting for socio-demographic differences, and compared to the general population, people with CMI had two to three-fold higher odds of being victims of any past-year violence, whilst those with SMI had five to 12-fold higher odds. Victims with pre-existing mental illness were more likely to experience adverse psychosocial effects following violent incidents than general population victims. There is preliminary evidence that risk profiles for community and domestic violence are distinct, and that power imbalance and targeted violence are important interpersonal contexts for violence against people with SMI. Conclusions: Compared to the general population, people with pre-existing mental illness are at increased risk of being victims of all types of violence, and of experiencing adverse psychosocial effects once victimised. Psychiatric services, and public health and criminal justice policies, need to address violence in this at-risk group

Evaluation of Syringe Markers Distributed Through Community Pharmacy Needle Exchanges

The aim of this study is to evaluate the supply of markers for the identification of syringes distributed by pharmacy needle exchanges and to determine if this product and service delivery offers a feasible method of marking syringes to promote the reduction of accidental sharing of syringes and needles amongst injecting drug users (IDU) and thereby reduce the risk of transmission of blood borne viruses (BBVs) and other related infections. This study involves the assessment, implementation and evaluation of syringe markers as a pilot study within three community pharmacy sites in Glasgow. The secondary aims of the study were to identify whether the supply of syringe markers from community pharmacy needle exchanges was acceptable to IDU and if it enabled them to mark their syringes. The literature review demonstrates that providing a means of identification of personal injecting equipment has been proposed as a viable option that should be promoted to prevent the inadvertent accidental sharing of syringes within a group setting. Needle exchanges (NEX) are important component parts of the harm reduction responses designed to reduce the physical health harms caused to individuals through injecting drug use. The literature is reviewed on BBV transmission and the historical, legal and policy context associated with the development of NEXs. Community pharmacies act as a source of health advice and can help to facilitate access to treatment services for those attending the NEX. However the specific aim of this study is not to investigate the totality of the benefits of a NEX but to examine the supply of a potential means of reducing accidental and unintentional sharing of all injecting equipment and thereby contribute to minimising some of the health harms linked to injecting drug use. Three established community pharmacies were identified as suitable sites to pilot the supply of syringe markers. A number of criteria were used to select the sites. These included an assessment of the geographic locations, staffing arrangements, NEX attendances and transactional activity and the availability of private consultation facilities. The health board central database which holds records on a range of factors including, the characteristics of those who attend NEX and detailed information on all transactions, was used to identify the most suitable sites to pilot the new intervention. This indicated that the characteristics of those who attended the three chosen sites were broadly similar to the wider NEX attending population. The evaluation was conducted in two separate periods. The first 4 week period was the supply phase where markers were distributed over this period to all patients receiving NEX packs from the 3 pharmacies. The second data collection phase was undertaken in the following 4 week period. Data was collected by means of a structured questionnaire. In order to reduce the potential interviewer bias it was decided to incorporate the use of peer researchers in the administration of the questionnaire. The Scottish Drugs Forum (SDF) was approached and agreement was reached to use members of the Service User Involvement Group (SUIG) to assist with the design and administration of the questionnaire. A submission was made to the health board Research Ethics Committee (REC) and approval was given to enable the study and the research evaluation to proceed. Before the start of the study, joint briefing and training sessions were held for pharmacy staff from the 3 sites and the 6 participating SUIG members. A total of 177 questionnaires were completed during the second data collection phase of the evaluation. Information was collected on personal details and injecting behaviours (including deliberate and accidental sharing), any current means of syringe identification, use of the markers and on the usefulness of the instruction card. Most individuals (75%, n=132) had been supplied with the markers to trial during the first supply phase of the study with 63% of the 132 (n=83) of those individuals reporting use of the markers. The results of the evaluation and subsequent analysis of the findings indicated that the syringe marker supply could be successfully implemented using pharmacy NEXs. The product and the supply method were acceptable to both staff and service users. Initial bivariate analysis was conducted using a number of dependent and independent variables identified within the questionnaire. These findings highlighted a number of areas worthy of further exploration, including emerging differences between male and female respondents, and indicated specific target groups for future developments in syringe identification. The contribution of the peer researchers was found to be a significant factor in successfully completing the evaluation. However it is not possible to make any definitive statements on how effective the intervention is in terms of reducing the transmission of BBVs and other related infections. The findings of the evaluation indicated a number of potential areas of work that could be usefully explored to investigate the effectiveness of the markers in reducing the transmission of infections. The limitations of the evaluation became apparent during the course of the study and the implications of these limitations are discussed

Methods to Improve the Prediction Accuracy and Performance of Ensemble Models

The application of ensemble predictive models has been an important research area in predicting medical diagnostics, engineering diagnostics, and other related smart devices and related technologies. Most of the current predictive models are complex and not reliable despite numerous efforts in the past by the research community. The performance accuracy of the predictive models have not always been realised due to many factors such as complexity and class imbalance. Therefore there is a need to improve the predictive accuracy of current ensemble models and to enhance their applications and reliability and non-visual predictive tools. The research work presented in this thesis has adopted a pragmatic phased approach to propose and develop new ensemble models using multiple methods and validated the methods through rigorous testing and implementation in different phases. The first phase comprises of empirical investigations on standalone and ensemble algorithms that were carried out to ascertain their performance effects on complexity and simplicity of the classifiers. The second phase comprises of an improved ensemble model based on the integration of Extended Kalman Filter (EKF), Radial Basis Function Network (RBFN) and AdaBoost algorithms. The third phase comprises of an extended model based on early stop concepts, AdaBoost algorithm, and statistical performance of the training samples to minimize overfitting performance of the proposed model. The fourth phase comprises of an enhanced analytical multivariate logistic regression predictive model developed to minimize the complexity and improve prediction accuracy of logistic regression model. To facilitate the practical application of the proposed models; an ensemble non-invasive analytical tool is proposed and developed. The tool links the gap between theoretical concepts and practical application of theories to predict breast cancer survivability. The empirical findings suggested that: (1) increasing the complexity and topology of algorithms does not necessarily lead to a better algorithmic performance, (2) boosting by resampling performs slightly better than boosting by reweighting, (3) the prediction accuracy of the proposed ensemble EKF-RBFN-AdaBoost model performed better than several established ensemble models, (4) the proposed early stopped model converges faster and minimizes overfitting better compare with other models, (5) the proposed multivariate logistic regression concept minimizes the complexity models (6) the performance of the proposed analytical non-invasive tool performed comparatively better than many of the benchmark analytical tools used in predicting breast cancers and diabetics ailments. The research contributions to ensemble practice are: (1) the integration and development of EKF, RBFN and AdaBoost algorithms as an ensemble model, (2) the development and validation of ensemble model based on early stop concepts, AdaBoost, and statistical concepts of the training samples, (3) the development and validation of predictive logistic regression model based on breast cancer, and (4) the development and validation of a non-invasive breast cancer analytic tools based on the proposed and developed predictive models in this thesis. To validate prediction accuracy of ensemble models, in this thesis the proposed models were applied in modelling breast cancer survivability and diabetics’ diagnostic tasks. In comparison with other established models the simulation results of the models showed improved predictive accuracy. The research outlines the benefits of the proposed models, whilst proposes new directions for future work that could further extend and improve the proposed models discussed in this thesis

Healthy people healthy places evidence tool: Evidence and practical linkage for design, planning and health

This project was commissioned by Public Health England to address the need for a UK centric evidence review which analyses and demonstrates the links between health and the built and natural environment. This umbrella review attempts to provide an overview, based on umbrella review methodology outlined in this document, of the strength of the evidence of the impacts on health of the built and natural environment with the purpose to inform action and policy