bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increasing the understanding of patterns of behaviours for alcohol in Wales using R
Authors: Hughes Rhian , Patterson Bethan , Withey Clare 
Published: November 2019

Background Increasing the understanding of patterns of behaviours for alcohol are a key priority for Public Health Wales. We developed an interactive scrolling webpage to support this priority.
Main Aim To develop a tool for understanding behaviour which brings together large amounts of information and presents it in a new and innovative way to inform and support decision makers.
Methods Using the R programming language we developed an interactive scrolling webpage following an agile project management approach to involve key users. Users were engaged throughout the process, and outputs were produced in an iterative way to ensure the tool continued to meet the needs of the user.
Results The interactive tool allows data interrogation and extraction and uses innovative techniques to display information without having to leave the tool.
The profile includes an overview of the pattern of alcohol consumption and its impacts, along with the option to explore the data further at the local level.
The information, presented across a series of tabs, allows users to navigate easily to the area of interest. Interactive elements, including dropdown selectors and checkboxes, were used to display additional information such as caveats and data sources.
Conclusion Whilst R and agile project management require sufficient time investment, they were used successfully to disseminate public health knowledge in an informative way to increase the understanding of patterns of behaviours.
Area Deprivation, Urbanicity and Severe Mental Illness – A Population-Based Linkage Study Using Routinely Collected Primary and Secondary Care Data
Authors: Lee Sze Chim , Delpozo-Banos Marcos , Lloyd Keith , Jones Ian , Walters James TR , Owen Michael J , O‘Donovan Michael , John Ann 
Published: November 2019

Background There is a long-standing debate regarding the associations between area deprivation, urbanicity and elevated risk of severe mental illnesses (SMIs).
Main Aim We investigated the associations between area deprivation, urbanicity and risk of SMIs in a population cohorts in Wales.
Methods/Approach We extracted primary and secondary care electronic health records from 2004 to 2015 from Wales’s population. We identified prevalent and incident individuals with SMIs (schizophrenia related disorders and bipolar disorder) and their level of deprivation and urbanicity. We used the Welsh Index of Multiple Deprivation (WIMD) and urban/rural indicator to measure the level of area deprivation and urbanicity respectively for all lower layer super output areas, the geographic units used in the reporting of small area statistics comprised of approximately 1,500 individuals.
Results Prevalence and incidence of SMIs is not evenly distributed in Wales. Increased prevalence and incidence of SMIs occur in more deprived and urban areas. Such associations occur for both schizophrenia related disorders and bipolar disorder and in both the primary and secondary care cohorts.
Conclusion These findings have implications for resource allocation, service configuration and access to services in deprived communities, as well as, for broader public health interventions addressing poverty, and social and environmental contexts.
Automatic coding of occupation and cause-of-death records
Authors: Tobin Richard , Farrow Elaine , Grover Claire , Alex Beatrice 
Published: November 2019

The Digitising Scotland project aims to digitise 24 million Scottish vital event records of births, marriages and deaths from 1856 to 1973. To use these records effectively for large-scale research they must not only be made machine-readable, but also coded in a form suitable for statistical analysis.
The digitised birth, marriage, and death certificates include textual descriptions of occupations and causes of death. Our aim is to map these descriptions to standard HISCO and ICD-10 codes.
It is impractical to have experts code all the records manually, so we treat the problem as a text classification task and apply machine learning techniques. A proportion of the records will be manually coded and used to train the system. More recent records are already coded and these can also be used for training. Following earlier work by [Kirby et al] and [Carson et al] we are experimenting with Bayesian classifiers for this task.
By combining exact matching for texts that have been seen in the training data and Bayes for the rest, we get an accuracy in cross-validation of 92% for causes of death and 94-97% for occupations.We are investigating methods to improve this, including automatic spelling correction and synonym detection, use of age and sex information, and (for causes of death) the presence of co-occurring causes.We are also investigating the value of coarser-grained but more reliable coding, and reporting second- and third-choice codes.
This is work in progress, and the final paper will consider whether the improvements we are making are sufficient to produce useful data for further research. We will also make recommendations about further manual annotation to provide training data covering the whole timespan of the records.
Combining Hungarian Administrative Data with Google Search Trends to Predict Tendencies in Local Public Health and Consumer Behaviour
Authors: Molnár-Kovács Dorottya 
Published: November 2019

Google Trends is a publicly available free tool that provides minute-by-minute, regional statistics on the popularity of keywords users type in the search engine. Although this massive and exponentially growing data set has its limitations, it provides a unique look into the minds of Internet users. As opposed to direct questionnaires, people using Google have no incentives to lie or to hide their true interests, yet they are motivated to be as honest and precise about their questions as they possibly can. This source of information, when combined with official data provided by government institutions can help researchers understand behavioural patterns and overtime can assist in predicting epidemics or anticipating cultural trends.
This presentation will focus on a research aiming to use Hungarian administrative health data concerning the influenza epidemics from 2004 to 2018 to see how frequent certain flu-related searches were in the periods preceding the cold and flu season, and during the period itself. After determining which Google keywords work best as indicators of a flu outbreak, we tested Google Trends solely to measure the accuracy with which we could have predicted a forthcoming flu epidemic in the past few years.
The goal of our research was to experiment with ways in which researchers studying local phenomena could take advantage of the massive amounts of free, public data from digital footprints of the local population. During our research we have experimented with using Google Trends to mirror and possibly predict consumer behaviour and as an alternative to conducting social surveys.
The Hazards and Rewards of Screening Using a Population Register: The Case of HAGIS
Authors: Bell David , Douglas Elaine 
Published: November 2019

This paper focuses on the sampling mechanism used to generate the pilot for the HAGIS (Healthy AGeing In Scotland) study. HAGIS is the Scottish equivalent of ELSA in England and HRS in the US. The sample for the HAGIS pilot was screened using a Scottish population register - the National Health Service Central Register (NHSCR). It is used to identify individuals who use NHS services in Scotland. Each individual using NHS resources is allocated a unique identifier, known as a Community Health Index (CHI) number. CHI numbers form a database which is effectively a population register for Scotland.
CHI numbers have not previously been used to screen a sample for a social survey. Our paper describes the steps involved from obtaining permission to screen using CHI to handing set of addresses to a survey company tasked with approaching individuals and conducting a face-to-face interview. The paper goes on to illustrate the practical difficulties involved in achieving a high response rate from those approached and the compromises that were made to achieve the target sample size. It also discusses the consent rates that HAGIS achieved for linkage to administrative health data.
The final section of the paper outlines the advantages of combining administrative data linkage with screening using a population register. It illustrates this by comparing various health characteristics of consented survey respondents with those of the original randomly drawn sample from the NHSCR. These comparisons facilitate testing of hypotheses that consented sample respondents comprise an unbiased sample from the Scottish population across a variety of health dimensions. The paper concludes with a discussion of the implications of these hypothesis tests and the more general benefits of sample screening using a population register and administrative data linkage.
Do carers care for themselves? A population-based study
Authors: Tseliou Foteini , Atkinson Mark , Paranjothy Shantini , Ashfield-Watt Pauline 
Published: November 2019

Background Informal caregiving has become an integral part of many societies, however there is increasing concern about the well-being of carers and how they manage their care-related responsibilities in conjunction with their health and mental health. Previous studies have reported mixed results with some proposing that carers are intrinsically healthier.
Aims To explore the association between different levels of caregiving and health behaviours and mental health status.
Methods Data were collected through HealthWise Wales (HWW) and linked to healthcare records (N=27,455). These included self-reported data on level of caring responsibilities (0;1-19;20-49;50+ hours per week), whether or not they left employment due to their caring role, mental health using the short Mental Health Inventory (MHI-5) and health behaviour data on smoking status, physical activity and dietary habits. Data on current diagnosis of Anxiety and Depression were drawn from linked healthcare records. Separate logistic regression models adjusted for age, gender and socio-economic status were fitted to assess the association between intensity of caring responsibility and each mental health and health behaviour outcome.
Results Of the 14,451 HWW participants who had complete records, 3,856 (26.7%) reported being an informal carer. Intense carers (20-49 hours per week) were more likely to be physically inactive (OR:1.27, 95%CI:1.04-1.56), smoke cigarettes (OR:1.49, 95%CI:1.11-2.00) and eat unhealthily (OR:1.48, 95%CI:1.13-1.93). They were more also likely to self-report (OR:1.87, 95%CI:1.51-2.32) or have a diagnosis of depression or anxiety (OR:1.57, 95%CI:1.26-1.97). Other levels of caregiving intensity also demonstrated the above associations. Carers who had given up work to care were more likely to be smokers and have common mental disorders.
Conclusion Being an informal carer is associated with unhealthy behaviours and common mental disorders, with a gradient effect dependent on the level of caregiving activity. New interventions that can support carers to improve their health and wellbeing are urgently needed.
Measuring the burden of mental illness and substance use and the level and impact of health care response in patients with spinal trauma: a record linkage study.
Authors: Sharwood Lisa , Vaikuntam Bharat , Craig Ashley , Middleton James , Young Jesse 
Published: November 2019

Background with rationale Traumatic spinal injuries (TSI) include column fractures, spinal cord injury, or both. They are among the most severe injuries with potential long-term physical, psychological, and social consequences. Primary causes of TSIs are falls and motor vehicle crashes, however, mental illness and substance use are known to significantly increase all injury risk. Injury is also known to increase risks of mental deterioration and physical complications including self-harm and self-neglect.
Main Aim We aimed to identify comorbid mental illness and/or substance use at incident TSI, quantifying associated costs and health service management of these inequities.
Methods NSW record-linkage administrative data analyses (2013-2016) will determine accurate prevalence of mental illness and/or substance use disorder among all patients who sustained acute TSI during the study period. Using recurrent event analyses, we will estimate the contributions of mental illness and/or substance use disorder on the impact on hospital acquired complications (HAC), length of stay and costs; assessing records for social work and/or psychologist consultation.
Results 13,489 individuals were hospitalised with acute TSI; 21% had either mental health and/or substance use diagnoses; 8.7% had both. These patients were more likely to have experienced falls or intentional self-harm, be male and have multiple comorbidity. Acute care stay and costs were on average twice that of patients with TSI without mental health and/or substance use diagnoses; additionally they were more than twice as likely to experience HACs. Only 56% of TSI patients with these comorbid conditions in the context of TSI, had documented social work or psychologist consultation.
Conclusion Patients with mental illness and/or substance use disorder, experience significant health disparities that require concerted health system attention that should begin early in acute care.
Co-design of data collection with participants of the Aberdeen Children of the 1950s cohort study
Authors: Johnston Marjorie , Butler Jessica , Clark Heather , Locock Louise , Murray Alison , Robertson Lynn , Chapko Dorota , Hannaford Phil , Iversen Lisa , Skea Zoe , Black Corri 
Published: November 2019

Background The Aberdeen Children of the 1950s (ACONF) cohort contains 12,150 individuals born in Aberdeen, Scotland in the 1950s. The study includes rich early life data, information from questionnaire in middle age, and linkage to electronic healthcare records.
Involving the participants in designing future data collection and research is key to ensure research is acceptable and reflects public priorities.
Aim To gather ACONF participants’ views to inform how to: define healthy ageing, optimise recruitment and maximise participation.
Method We undertook three co-design workshops with 8 to 10 ACONF members. The workshops operated as a discussion, led by a facilitator using guidance questions developed by the study team. Workshops were recorded and transcribed.
Results Healthy ageing: Participants viewed healthy ageing as keeping socially and physically active, taking responsibility for oneself and having a positive attitude to ageing. Key research priorities were: dementia, healthy living advice, improvements in the social care system and engaging hard-to-reach groups.
Optimising recruitment and participation: Participants were keen for further involvement in research. Recruitment may be maximised by: more information online, involving participants in recruitment of other study members and clarity about potential benefits to themselves or others. It is acceptable to ask their offspring to participate.
There were high levels of trust in researchers, but ongoing data protection is vital. Participation may be improved by regular contact (informing participants of results, engagement events, newsletters, mobile phone “apps”).
Participants were happy with data collection methods: questionnaires, applications, wearable devices, and in-person tests. They raised no concerns regarding DNA collection and electronic record linkage.
Conclusion Participant involvement in research is a fundamental part of securing a social license for research. Participants were in favour of ongoing research, including recruitment of their children and linkage of electronic records. The workshops highlighted key considerations for future research and data collection.
Does physical ill-health increase the risk of suicide? A Census-based follow-up study of over 1 million people
Authors: Onyeka Ifeoma , Ross Emma , Maguire Aideen , O’Reilly Dermot 
Published: November 2019

Background/Main Aim Prior poor mental ill-health is a recognised risk factor for suicide but the relationship between multiple physical health conditions and suicide risk is less clear.
Methods Data of 1,196,364 adults (18-90years+) enumerated in Northern Ireland’s 2011 Census records were linked to death registrations until the end of 2015. Logistic regression models were generated to determine association between physical health status and both all-cause mortality and death from suicide, with adjustment for census-based attributes including the presence of mental health status. Physical health conditions severity was assessed using limiting long-term illness (LLTI: none, a little, a lot) and number of physical health conditions.
Results About 14% of the cohort (n=164,473) had physical multimorbidity (two or more conditions) and 51,672 individuals died during follow-up; 877 due to suicide. A dose-response relationship was evident between number of physical conditions and all-cause death reaching an adjusted odds ratio (AOR) of 3.79 (95%CI: 3.65–3.94) in those with 4-or-more conditions (compared to those with no physical condition), but the association between number of physical conditions and suicide risk disappeared with adjustment for mental health. LLTI however, was an independent risk factor for suicide even after adjustment for mental health (AOR 1.52, 95%CI: 1.25–1.87 for those with daily activities limited a lot). The relationship between LLTI and suicide risk was only evident at younger ages (people aged less than 60).
Conclusion This study demonstrates that the number of physical conditions is not an independent risk for suicide but that activity limitation is, though only at younger ages.
Unlocking the potential of health systems using privacy preserving record linkage: A pilot project exploring the research potential of developing a linkable general practice dataset
Authors: Boyd James , Lee Yuen Ai , Brown Adrian , Randall Sean , Ferrante Anna 
Published: November 2019

BackgroundGeneral practice is a rich source of health data for research. It is an important resource which can be used to improve patient management, reduce costs and improve patient outcomes. Traditionally, the challenge has been around access to general practice data which remains hard to ‘join up’.
This abstract describes technology developed to support aspirations of the MedicineInsight program to provide linked de-identified general practice data that can be used to derive insights to enable better patient outcomes.
Main AimThe aim of this project was to use real-world data to identify technical, logistical and analytical requirements throughout the linkage process. Logistical aims covered the negotiation, approval and data acquisition processes, as well as data linkage and data delivery aspects performed by technical and data service stakeholders.
Methods/Approach Given the sensitivity of the information involved, the project employed a privacy preserving record linkage methodology. This method uses encrypted personal identifying information (Bloom filters) in a probability-based linkage framework to help mitigate risk while maximising linkage quality.
Existing MedicineInsight systems were extended to automatically generate encoded linkage data at each general practice. Pilot linkages were then used to validate the capability/capacity of CDL infrastructure to create secure extensible linked general practice datasets.
ResultsThe project has successfully developed interoperable technology to create a transparent data catalogue which is linkable to other datasets. This technology has been embedded with MedicineInsight systems and results of the pilot linkages are being evaluated. The project will make recommendations to enable consistent delivery of linkage services across care settings.
ConclusionOutcomes from the project will improve delivery of record linkage services to the health and broader research community. Using linked data from across the care continuum, researchers will be able to evaluate the effectiveness of service delivery and provide evidence for policy and programme development.
Protecting children during child protection research using administrative data
Authors: Hooper Jade , Cusworth Linda , Whincup Helen 
Published: November 2019

Background with rationaleChild protection systems aim to protect children from harm. Child protection research shares the same goal. However, the process of undertaking this research can present a risk. For child protection research using administrative data, children and families are at risk through breaches of privacy and identification, and further ethical issues of fair and necessary processing. This can be particularly challenging for countries such as Scotland, where smaller communities may mean children and families are more easily identifiable. For researchers and data gatekeepers alike, it is our duty to protect children in every way that we can throughout the process.
Main AimThis paper aims to discuss with delegates the importance of protecting children during child protection research using administrative data, and some of the ways this can be done.
Methods/ApproachThe paper will use an example of a recent research study which used administrative data from child protection systems in Scotland – Permanently Progressing? Building secure futures for children in Scotland. The methods used to protect children within this research and the lessons learned will be discussed. Input from delegates and the sharing of experiences will be most welcome throughout.
Results and ConclusionChild protection research using administrative data often aim to inform and improve child protection systems. Such research can thereby enable more effective protection. However, such a research process raises its own child protection challenges, both to researchers and to the gatekeepers of this data. Despite this, although tricky at times to navigate, risks can be reduced through thoughtful care and consideration of these issues throughout the research process, from application to publication.
The case for integrated transport and health surveillance in Wales
Authors: Jones Sarah 
Published: November 2019

Background with rationaleTransport is an under-recognised wider determinant of health. But, there is growing recognition, among policy makers and the general public, that significant modal shift, from cars and to greater use of public transport and active travel is needed to improve and protect health directly and indirectly, and in the short and long term, including with regards to climate change.
In Wales, this comes when a new Welsh Transport Strategy is being written. This is likely to encourage greater recognition of the links between transport and health and demand data to support understanding of the ways in which transport affects health, as well as to evaluate the effects of the strategy, and to support wider research into the links between transport and health.
Main AimThis suggests the need for a formal, routine transport and health surveillance system. This study will therefore aim to determine whether this is needed.
Methods/ApproachThe approach is a review of existing systems and the evidence for the links between transport and health.
ResultsThis paper will present the results of the review noted above and outline the rationale for and structure of a Welsh Transport and Health Surveillance System that will support policy evaluation at local and national levels.