Discover peer-reviewed journal articles and reports that use ADR UK-funded flagship datasets. This collection is being expanded over time.
Displaying results 1 to 10 out of 19
Increasing access to children’s social care data presents enormous potential for research and policy evaluation, with opportunities increased where data can be anonymously linked to other sources of information, such as health and education data. The purpose of this scoping review was to provide an overview of all UK data linkage studies that have used routinely collected individual-level children’s social care administrative data. Six research databases were searched and twenty-five studies were identified as meeting the inclusion criteria, with the majority (n = 18) based on English data. Complexities and the time-consuming nature of these studies are highlighted, as are issues with missing data and inconsistencies in recording information across local authorities, impacting on the linkage process. Increased access to such data, and improvements to data capture, could improve the utility of these valuable administrative data assets in the social care sector.
Dataset used: Looked After Children Dataset - Wales
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This study examines health service indicators of stress-related presentations (relating to pain, mental illness, psychosomatic symptoms and self-harm) in adolescents of secondary school age, using Hospital Episode Statistics data for England. We examined weekly time series data for three academic years spanning the time before (2018–2019) and during the COVID-19 pandemic (2019–2020 and 2020–2021), including the first lockdown when schools were closed to the majority of pupils. For all secondary school children, weekly stress presentations dropped following school closures. However, patterns of elevated stress during school terms re-established after reopening, with girls aged 11–15 showing an overall increase compared with pre-pandemic rates.
Dataset used: Education and Child Health Insights from Linked Data - England
We use a large and novel administrative dataset to investigate returns to different university ‘degrees’ (subject-institution combinations) in the United Kingdom. Conditioning on a rich set of background characteristics, we find substantial variation in returns across degrees with similar selectivity levels, suggesting students’ degree choices matter a lot for later-life earnings. Returns increase with university selectivity much more at the top of the selectivity distribution than further down, and much more for some subjects than others. Returns are poorly correlated with observable degree characteristics other than selectivity, which could have important implications for student choices and the incentives of universities.
Dataset used: Longitudinal Education Outcomes - England
This aimed to assess the feasibility of using linked education and offending data (from the National Pupil Database, Department for Education and the Police National Computer, Ministry of Justice) to identify matched control groups to evaluate violence prevention interventions.
Dataset used: Ministry of Justice & Department for Education linked dataset - England
We aimed to quantify differences in number and timing of first primary cleft lip and palate (CLP) repair procedures during the first year of the COVID-19 pandemic (1 April 2020 to 31 March 2021; 2020/2021) compared with the preceding year (1 April 2019 to 31 March 2020; 2019/2021).
This study investigated the impact of change in community alcohol availability on alcohol consumption and alcohol-related harms to health, assessing the effect of population migration and small-area deprivation.
Dataset used: Welsh Environment Dataset
We used all-of-England inpatient data (Hospital Episode Statistics) to identify groups of adolescents with CHCs from age 5 to 15. Cohorts were born in 2000/01 to 2002/03. Data were linked to England’s National Pupil Database for secondary school (age 11 to 16) persistent absence (>1 month missed/year), exclusion, and non-enrolment to examine rates of each outcome by CHC groups.
Monitoring the incidence of chronic health conditions (CHCs) in childhood in England, using administrative data to derive numerators and denominators, is challenged by unmeasured migration. We used open and closed birth cohort designs to estimate the cumulative incidence of CHCs to age 16 years.
Using administrative data from the Annual Survey of Hours and Earnings linked to the 2011 Census of England and Wales, this paper explores the labour market performance of first-generation immigrants and compares it to that of UK-born employees. By focusing on various labour market outcomes and distinguishing immigrants based on their years of residence in the UK, the analysis reveals that more recent immigrants, on average, earn less, work longer hours, and are more likely to be employed in low-skilled occupations or temporary employment compared to observationally equivalent UK-born employees. However, the labour market performance of immigrants with ten or more years of residence in the UK is more comparable to that of their UK-born counterparts. These patterns are similar for males and females, but there is considerable heterogeneity in terms of ethnicity, country of birth, and reason for migration, as well as across the pay distribution.
Dataset used: Annual Survey of Hours and Earnings linked to 2011 Census - England and Wales
In 2020, COVID-19 forced the cancellation of all student end-of-school examinations in England. Schools were asked to provide centre assessment grades (CAGs), offering their best estimates for what students would have achieved had they sat their examinations. Although initially ignored in favour of grades calculated via an algorithm, students were eventually awarded their CAGs following widespread public outcry over the calculated grades. Whether CAGs were unfairly awarded across different student groups and schools in 2020 compared to previous years is a key question. However, existing analyses of bias in CAGs are limited by a lack of attention to potential interactions between student characteristics, and thus to hidden differential grade inflation across intersectional groups. We address this by examining student GCSE performance in 2018, 2019, and 2020 via a Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) analysis of intersectional sociodemographic variation which we cross-classify with schools given their role in generating CAGs. Overall, a picture of stability emerges, where despite substantial overall grade inflation in 2020, the use of CAGs does not appear to have generated new or divergent intersectional relationships in comparison to previous years, suggesting CAGs showed a similar susceptibility to bias as normal examinations.
Dataset used: Grading and Admissions Data for England
