bluuebunny/crossref_metadata_2025_split huggingface dataset:
The politics of administrative data: A case study of school census data for children with SEND
Authors: Rempel Emily , Durrant Hannah , Barnett Julie 
Published: June 2018

BackgroundFrom 2016 to 2018 we collaborated on a programme of work with a local authority in the South West of England around understanding diagnosis trends for children with special educational needs and disabilities (SEND). Tracking SEND is a key issue for both local and national government due to the high cost of provision and perceived increases in diagnoses prior to 2010.
ObjectiveIn this presentation we explore the use of school census data for research and commissioning in local government.
MethodsWe supplement statistical reports of SEND diagnoses from 2011 to 2017 with semi-structured interviews with individuals who inform their decision making with these and similar data. We draw on theories of narrative and causal story-telling to understand how modern statistical analysis is used as a tool to develop commissioning decisions. This includes testing narratives using data as well as data being used to inform narratives.
Early Findings and ConclusionsWe add to a growing area of literature that discusses data and statistics as subjective policy tools. Early results include the use of data as a perceived objective tool in calming emotions during commissioning negotiations. We aim to describe how these decisions are made and what this means for service provision for children with SEND.
Social care and health outcomes in ageing: exploring measures of multimorbidity
Authors: Henery Paul 
Published: June 2018

BackgroundThe older population within developed countries is increasing, leading to increased pressure on health services. Most of this demographic have multiple conditions (multimorbidity), which is difficult to measure in a methodological context. In Scotland, efforts are being made to integrate health and social care under one body in order to provide a person-centred environment where older people with complex needs receive tailored care. In this context it is important to consider the effect of social care in conjunction with multimorbidity on health outcomes to target care provision.
ObjectivesThis study intends to determine which is the best tool for predicting both mortality and care uptake amongst older people. The effect of care on mortality in conjunction with multimorbidity is also considered. This study also attempts to derive the best predictive model for both mortality and care uptake, using additional explanatory variables such as deprivation.
MethodsThis quantitative longitudinal study uses a linked SMR admissions and social care census dataset from 2010-2015. It considers the impact of multiple measures of multimorbidity (such as ICD-10 flagged condition indices or prescription scores) on outcomes such as mortality, receipt of informal care or admissions using nested logistic regression models with summary statistics such as the AIC, BIC, R-squared and ROC curve.
Projected resultsBased on literature, it is hypothesised that diagnosis-based indices (such as the Charlson Index) will perform best at predicting mortality, whilst prescription-based scores (such as the Chronic Disease Score) will perform best at predicting admissions.
Predicting the use Literacy Interventions Using a Pre-School Health and Developmental Screen: Evidence from New Zealand’s Integrated Data Infrastructure (IDI)
Authors: Audas Richard 
Published: June 2018

Early literacy attainment is a key progression towards advanced learning. All New Zealand schools offer interventions for children who are farthest from standard in literacy, although these interventions typically do not commence until the child has been in school for one year. Considerable evidence demonstrates that literacy interventions can be effective, if implemented as early as possible. As such there is significant benefit in quickly identifying those most at risk of failing to meet the literacy standard.
In New Zealand all children are expected to get a Before School Check (B4SC) between their fourth birthday and prior to entering school. These checks are generally conducted by public health nurses, with children's health and developmental status being divided into seven categories.
Data linkage across government collected administrative data files can be conducted in the Statistics New Zealand Integrated Data Infrastructure (IDI). The IDI provides a whole of population inter-departmental architecture to link individuals. In this study, we link individual's B4SC records to school interventions data as well as to birth and census records.
Using a time-to-event approach, we find that there is significant predictive value in using B4SC to identify children who are at risk of requiring a literacy intervention.
The Inverse Care Law programme: evaluating a population based intervention in primary care within deprived communities in Wales.
Authors: Song Jiao , Akbari Ashley , Cox Caryn , May Leon , Watkins William , Aitken Sarah , Thomas Sarah , King William 
Published: June 2018

BackgroundThe Inverse Care Law (ICL) programme was set up in South Wales valleys and aiming to achieve a measurable closing of the gap in health outcomes between the most and least deprived areas.
ObjectivesPeople in deprived communities in Wales were invited for health checks to identify risks of cardiovascular disease followed by targeted interventions towards lifestyle risk factors, e.g. poor diet, physical inactivity, smoking and high alcohol intake, under the ICL programme piloted in Aneurin Bevan (AB) and Cwm Taf (CT) University Health Boards.
MethodsWelsh Longitudinal General Practice (WLGP) data held in Secure Anonymised Information Linkage (SAIL) databank was utilised to evaluate outcomes through project-specified clinical codes and uptake of the programme, linked with the Welsh Demographic Service Dataset (WDSD) providing demographic characteristics.
FindingsThere were 7,094 people completing health checks in AB and CT University Health Boards between February 2015 and November 2016. 96% of these were in the three most deprived Welsh Index of Multiple Deprivation (WIMD) quintiles. 51% were referred within primary care for follow-up based on their health check results, 71% were overweight/obese, and 20% were identified as current smokers of within which 28% were referred to smoking sensation services, with further analyses to follow.
ConclusionsImplementations and effectiveness of the interventions and impact of health checks will be evaluated longitudinally on a scheduled basis with repeated analyses. Challenges and results will help refining the programme to be delivered across Wales.
Measuring Active Living Environments: An international comparison between Canada and Wales
Authors: Fry Richard , Akbari Ashley , Mah Sarah , Ross Nancy 
Published: June 2018

BackgroundThe impacts of the built environment on health is a widely studied international area of research. One area of research is how urban morphology (e.g. active living environments, also known as neighbourhood walkability) may promote healthy behaviour within a population. However urban morphology and data relating to the built environment varies across different countries.
ObjectivesOne of the challenges in international studies is producing consistent, comparable measures of the built environment, in this case active living environments. As part of a study which compares the impact of neighbourhood environments on health outcomes for patients with type 2 diabetes (T2D), neighbourhood-level measures for walkable environments were derived for Canada and Wales using Geographic Information Systems (GIS).
MethodsUsing method based upon the Canadian Active Living Environments Database (Can-ALE) we created walkability indicators for Wales, UK. We created GIS models using OpenStreetMap and Office for National Statistics (ONS) Open Data to produce walkability metrics for each Lower Layer Super Output Area (LSOA) in Wales for linkage into the SAIL databank. We compared the GIS generated walkability metrics for Wales with those produced for Canada to evaluate whether the GIS methods are internationally transferable in the context of generating walkability indictors and associations with T2D.
FindingsThis work highlights the challenges in creating internationally comparable environmental exposure metrics. The differences in urban morphology and scale in Canada and Wales are significant, however this work demonstrates how with considered methodological choices these differences can be overcome to generate comparable built environment indicators.
ConclusionsThe generation of comparable walkability indicators for the built environment has allowed subsequent analysis into hospital admissions for people living with T2D in Caranda and Wales. This study has wider implications for international research into the impacts of the built environment on population health and are reproducible on future studies.
Estimating the causal effects of academisation of English schools with the data from the National Pupil Database
Authors: Liu Yi , Bessudnov Alexey , Norwich Brahm , Black Alison 
Published: June 2018

BackgroundOver the last 30 years there have been two key policy initiatives in schooling in England. First, there was a move to raise academic standards with a market-oriented model of schooling and the introduction of Academies with higher levels of autonomy. Second, there has been a lesser though nevertheless important trend to providing for more pupils with special educational needs (SEN) in ordinary rather than special schools, what has been called the inclusive education movement.
ObjectivesWe explore causal effects of converting English schools into academies on educational inclusiveness in England. Specifically we investigate the implications of a school’s academisation event in converting to a Sponsored Academy or a Converter Academy on the inclusion of pupils with SEN and the impacts on the education trajectory of these pupils.
Methods (including data)Using administrative data from the National Pupil Database and combining it with publicly available data on school institutional history, we are able to construct extensive longitudinal samples of pupil cohorts and academisation school cohorts from 2003 to 2015. Utilising both from aggregate school level and individual level features, we study the various aspects of academisation on educational inclusiveness by modelling the admissions, re-classifications and potential exclusions on pupils with SEN from the contemporaneous and follow-up effects of academisation events. In addition, we examine the adequacy and effectiveness in causality modelling in a educational context under various regimes of modelling frameworks.
Findings and conclusionsThe analysis to date suggests that academisation events have small negative impacts in educational inclusiveness. Specifically, we find that pupils with SEN are more likely to register with non-SEN in academised schools in the treatment group. In addition, these negative effects are found to remain statistically significant several periods after occurrence of the event.
Exploiting the coverage of administrative data to understand changing criminal careers and the causes of the crime drop: changing conviction patterns in the Scottish Offenders Index, 1989-2011
Authors: Matthews Ben , McVie Susan , Dibben Chris 
Published: June 2018

BackgroundThe status of the Scottish Offenders Index (SOI) as a census (n=all) of conviction proceedings in Scotland allows the adoption of research designs that would be prohibitively costly and time consuming to implement with more traditional survey approaches. This paper argues that this flexibility, combined with the large time span covered by the SOI (1989-current), provides a way to bridge the typical individual (micro-) focus of developmental criminology and the (macro-) analysis of aggregate crime rates.
ObjectivesBy examining conviction patterns for multiple cohorts across multiple years, we can infer whether recent falls in aggregate conviction rates are most plausibly explained by period or cohort effects. In turn, this distinction between period and cohort effects can both suggest which potential explanations for these recent falls in conviction rates in Scotland are most feasible - thus helping to refine explanations for the recent ’crime drop’ - and help us understand the factors leading to change in criminal careers over time.
Methods and FindingsTo support these claims, this paper presents the results of an exploratory analysis of change in convictions patterns in the SOI between 1989 and 2011, drawing on demographic information to account for change in population structure. Results show a complex pattern of change over time, with differences in convictions trends for young and old, for men and women and in different periods. Explanations of the crime drop must be able to account for these complex trends.
ConclusionsAdministrative data provide a unique window into the recent crime drop, and we encourage similar studies on comparable datasets where possible.
Which best predicts suicides in Northern Ireland - self-rated mental health or medication record?
Authors: Onyeka Ifeoma , Maguire Aideen , O’Reilly Dermot 
Published: June 2018

BackgroundOver 800,000 suicides occur annually worldwide, and approximately 300 suicides in Northern Ireland (NI) each year. Studies from elsewhere have highlighted the role of mental health in the risk of death by suicide, but such studies are scarce in NI.
ObjectivesThis project seeks to: (1) examine the association between mental health and death by suicide during 2011–2015, and (2) assess if self-rated mental health, medication record, or both better predict risk of death by suicide.
MethodsDe-identified information will be drawn from 2011 Census on NI’s 1.8 million residents, linked to the Business Service Organisation’s Health Card Registration data, the Enhanced Prescribing Database (EPD) and death registrations. Subjects’ mental health will be ascertained through single-item self-rated mental health question from the Census and/or record of psychotropic medication in the EPD. Data captures over 1,100 suicides over 5 years (main causes of death defined as ICD- 10 codes X60–X84, Y10–Y34, Y87). Cox proportional hazard models will be used to examine the association between mental health and death by suicide (adjusting for age, gender, comorbid physical disorders, socio-economic status). The performance of prediction models of death by suicide, including self-rated mental health or prescribed medication record or both, will be compared. Data are with the Administrative Data Research Centre – NI, with data analysis underway.
FindingsThis study will yield information beneficial for policy-making regarding suicide prevention and identifying “at risk” groups. Understanding which measures of mental health (self-rated versus medication record) best predict risk of death by suicide could be used to inform future studies on suicide risk and to identify groups for targeted interventions.
Is commercial/private sector access to administrative data inevitable?
Authors: Porteous Carol 
Published: June 2018

BackgroundCurrently in the UK, access to publicly collected administrative data for use in research, is only available to accredited researchers. However, administrative data may be of interest to commercial or private sector organisations, some of whom have already controversially been partnering with universities and health researchers in the recent case of an NHS Trust partnering with Google Deep Mind.
ObjectivesHow do we deal with the issue of commercial/private sector access openly and critically as a society?
MethodThis work will present the current landscape of commercial access to administrative data use and the results of a focus group with members of the public. Presented will be the views of the focus group in relation to different categories of commercial organisations and whether they should or should not be allowed access to administrative data and what conditions (if any) should be in place.
FindingsInitial findings indicate commercial access may be acceptable, but this raises new issues for society to consider about the role and extent of commercial/private sector reach.
Cognitive development Respiratory Tract Illness and Effects of eXposure (CORTEX) project: Data processing challenges in combining high spatial resolution pollution level data with individual level health and education data
Authors: Lyons Jane , Mizen Amy , Rodgers Sarah , Berridge Damon , Akbari Ashley , Wilkinson Paul , Milojevic Ai , Doherty Ruth , Dearden Lorraine , Lake Iain , Carruthers David , Strickland Sarah , Mavrogianni Anna , Davies Gwyneth 
Published: June 2018

Background and ObjectivesThere is a lack of evidence of the adverse effects of air pollution and pollen on cognition for people with air quality-related health conditions. The CORTEX project combined routinely collected health and education data, high spatial resolution air pollution modelling, and daily pollen measurements for 18,241 pupils living in Cardiff, UK, between 2009 and 2015, to investigate the acute effects of air quality and respiratory conditions on education attainment.
DatasetsAir pollutants PM2.5, PM10, NO2, and ozone levels were modelled for 157,361 home and school locations, anonymised into the Secure Anonymised Information Linkage (SAIL) Databank, and summarised into minimum, average and maximum readings for 4 daily time periods reflecting pupil home/school exposure. Adding a unique Residential Anonymised Linking Field (RALF) allowed linkage of pollution estimates to individual level data. Annual pollution datasets contained 369 columns and 472,083-rows, with one column per location, pollutant, daily time-period and day of year. Dataset transformation produced a 5 column, 3,446,205,900-row matrix per year.
Methods and ConclusionsAn algorithm using Structured Query Language (SQL) to manage data held within a relational database management system, was designed to reduce dimensionality from 24 billion to 18,241 rows of data. The algorithm calculated average means for each pollutant (PM2.5, PM10, NO2, and ozone levels) over the revision and examination periods, and summarised data into one row per pupil. The algorithm adjusted for weekends, school, and bank holidays, it calculated daily pollutant exposure for each pupil, and successfully linked 95% of pupil pollution exposures to their health and education data.
Finding and Counting Difficult to Reach Population Groups in the UK (and other Developed Countries)
Authors: Carr-Hill Roy 
Published: June 2018

BackgroundCensuses are meant to provide a complete count and basic information about all households and individuals in a country. After decades of complacency, it has begun to be realised that this can no longer be guaranteed. Several of the presentations at the Edinburgh in March 2018 demonstrated methods which the ONS were developing to resolve many of the problems; but those methods do not solve the problem of those who, for a variety of reasons, cannot or do not want to be counted.
ObjectivesThis paper sets out to document the possible size of the ‘hidden’ populations in the UK and demonstrate that they are predominantly poor.
Methods (including data)Estimates of the numbers are provided (globally and in the UK) in difficult-to-reach categories: homeless/street children, care homes/hospitals, military, prisons, refugees and illegal immigrants, gypsies/travellers, urban slums.With the exception of the military, the majority in each group are poor.
FindingsThe paper then reviews approaches to counting and describing the various categories:

grosso modo, those in institutions can already be headcounted but apart from relevant institutional status, gender and perhaps age, we have no other information about them; but the main problem is that, in many cases, there is potential double counting with their (temporarily) broken household.
for both Refugees/ Illegal immigrants and Gypsy/ Traveller Population, the main problem is the reluctance of the former to complete forms or be interviewed and of the latter to acknowledge their own ethnic identity
in high rise blocks where lifts are not always working, there will certainly be some unsurveyed and uncensored people; and the Grenfell Towers experience shows that there is not always a secure count of the numbers

ConclusionsThe issue of ‘hidden’ or missing populations in the UK has to be taken much more seriously.
Childhood Adversity and Traumatic Disorders: A self-report and Danish linkage study
Authors: Murphy Siobhan , Shevlin Mark , Elklit Ask , Christoffersen Mogens 
Published: June 2018

BackgroundAccurate assessment of childhood adversity is fundamental in understanding risk and resilient factors that can inform appropriate intervention and prevention strategies. Different statistical and methodological approaches (e.g., prospective, selfreported data) have been used to assess pathways and outcomes associated with childhood adversity, however, each is limited in a number of ways.
ObjectivesLinking administrative data to population-based studies provides a powerful tool to overcome some of the challenges in trauma research and permits the estimation of temporally ordered models of risk. The current study seeks to assess the effect of childhood adversity on a diagnosis of traumatic disorder (TD).
MethodsData were collected from a Danish national study in 2008/2009. A sample of 4,718 young adults were randomly selected from the birth cohort of children born in 1984. Structured interviews were conducted on 2,980 participants. This data was then linked with parental data (including 4 years prior to birth of child) and a ICD 10 diagnosis of a TD using information from the Danish registries.
FindingsHierarchical regression analysis was used to examine parental risk factors, self-reported child maltreatment, experiencing violence in young adulthood and risk of a TD diagnosis at age 28. Findings indicated the dominant factor associated with TD was self-reported PTSD symptoms at age 24 (OR =3.82); followed by a parental mental health diagnosis (OR = 2.80). Being of female gender (OR = 2.42) and experiencing violence in young adulthood (OR = 1.94) also increased risk of a TD diagnosis.
ConclusionThis study highlights the benefits of incorporating administrative data with self-report data to provide a more nuanced understanding of childhood adversity across different developmental stages. These findings have important conceptual and methodological implications and may be useful in informing future trauma studies.