Centre for Longitudinal Studies - Millennium Cohort Study (MCS)- (Age 17 consent)

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Objective for processing

[28 paragraphs unchanged] 3) The CLS will promote and make possible wider use of this linked data set, through providing wider access to the linked NHS England HES / (HES/ECDS) to CLS MCS data to the research community via the UK Data Service (UKDS) Secure Lab under sublicensing agreements subject to the following access arrangements. [20 paragraphs unchanged] The anticipated volume / number of licences is 1-2 sub-licences per month. Sub-licences shall not exceed a term of 12 months at a time and may be extended/renewed if appropriate. The sub-licences any sub-licence will remain valid only while UCL retains the right to hold and share the data from NHS England. Sub-licences may be extended/renewed but only under the same terms as just stated. [12 paragraphs unchanged]

Processing activities

[1 paragraph unchanged] NHS England data will provide the relevant records from the HES and ECDS HES/ECDS datasets to UCL. The data will contain no direct identifying data items [13 words unchanged] the data with other record level data already held by the recipient. The CLS will carry out validation of the administrative pseudonymised data received (linked ( HES/ECDS data) and combined will combine the supplied administrative data with the information collected from the participant as part of the MCS study using the study ID. [11 paragraphs unchanged] CLS does not link HES/ECDS this data to any other dataset. However, when a researcher accesses the pseudonymised [64 words unchanged] and will only be permitted if CLS DAC approves the project proposal. [7 paragraphs unchanged] Only staff who are permitted to work at the UKDS (and are [74 words unchanged] subject to statistical disclosure control procedure. Access to the Secure Lab is only available to ESRC accredited researchers who are based at a UK academic institution or an ESRC-funded research centre and are an ESRC Accredited Researchers. institution. PhD and research students can request access but must apply jointly with their supervisors from established organisations. Access will also be available to non-academic, non-commercial research organisations. [3 paragraphs unchanged]

Expected output

Following the data quality and validation work, the first output will be the creation of the linked MCS- HES/ ECDS dataset. The HES/ ECDS This is the first step in establishing a robust health research database. This data will add an important layer to this already rich data as well as provide the means for data quality checking. Researchers will be able to use the data for research that can benefit patients the health system and social care. The creation of this MCS- HES/ ECDS database and the research and methodological papers are the first steps in establishing a robust research database which will be of benefit to health and social care. This data linkage opens new research opportunities by combining reliable administrative data [90 words unchanged] collected in the survey, offering huge potential for scientific and policy-related research. [7 paragraphs unchanged] The methodological project above mentioned is currently being was carried out for CLS’s other study, the 1958 National Child Development Study (NCDS) and it is near completion. now complete. The findings suggest that the linkage quality of the NCDS-HES data is [39 words unchanged] linked data resources to undertake and publish similarly thorough evaluations. This paper is expected to can be published during 2023 found here At the time of this renewal, no data has yet been used or sublicensed, there was a delay in receiving the data from NHS England and also a delay in preparing the data for deposit at CLS. The linked data was deposited in November 2022 and is now available for researchers to apply. UCL CLS held a webinar in November 2022 to an attendance of 60+ interested parties, to showcase the availability and content of the linked data and as of yet no applications have been received (December 2022). https://cls.ucl.ac.uk/wp-content/uploads/2017/02/Examining-the-quality-and-sample-representativeness-of-linked-survey-and-administrative-data-CLS-Working-Paper-2022-5.pdf At the time of this renewal, three projects are currently accessing the data. Title 1: Examining structural racism in the processes of identifying mental health needs for children and young people in the UK. Title 2: Mental health service use in young people and its relationship with social media and digital technologies Title 3: Life course air pollution, mental health, and mental health service use in childhood The linked data was deposited in November 2022 and is now available for researchers to apply. UCL CLS held a webinar in November 2022 to an attendance of 60+ interested parties, to showcase the availability and content of the linked data and as of yet no applications have been received (December 2022).

Expected measurable benefits

The main purpose is to provide access to the linked Millennium Cohort Study (MCS) survey data with NHS England Health Episode Statistics (HES) to enhance the research resource for secondary users. Linking HES data with the survey data greatly widens the value of research offering an opportunity to use the HES data alongside rich survey information covering a range of different domains of people's lives. This information is not possible to directly access via NHS England. It provides an invaluable opportunity to better understand some of the social determinants of health. MCS will offer invaluable information on social experiences through the years of adolescence and early adulthood, and its longitudinal nature allows for a life course approach in exploring the relationships between social experiences and health. Releasing the data through the UKDS secure lab as outlined in this application is expected to allow the linked data to be used more widely to maximise societal benefit while maintaining high levels of data security. Benefits from the linked data- The linked MCS/HES dataset received under previous versions of this agreement is now available for researchers to use for research that could potentially influence policy and benefit health and social care as well as improve people's lives. The projects listed under the 'Outputs section' are evidence of how this rich dataset can be used to benefit society. The age 22 survey (currently in development) is expected to enrich the already deposited data for the cohort (waves 1-7) and is expected to be particularly valuable for the research community, including researchers in health and social care, providing rich survey data on a range of different domains of young people's lives. Particularly beneficial is the opportunity for a life course approach and to follow young people's experiences over time to analyse later life outcomes. The specific benefits to society, using the data accessed through the sub-license, would be stated by each applicant as part of their application (as required in the Accredited research form and Research proposal – e.g. ‘How your findings is expected to benefit society?’, ‘How does the project provide a public benefit?’, ‘Contribution towards public policy or journal publications’). CLS is expected to further require the applicant to describe the benefits of their intended research to health and social care. The main purpose is to provide access to the linked Millennium Cohort Study (MCS) survey data with NHS England Health Episode Statistics (HES) and Mental health Service data to enhance the research resource for secondary users. Linking this data with the survey data greatly widens the value of research offering an opportunity to use the HES data alongside rich survey information covering a range of different domains of people's lives. This information is not possible to directly access via NHS England. It provides an invaluable opportunity to better understand some of the social determinants of health. MCS will offer invaluable information on social experiences through the years of adolescence and early adulthood, and its longitudinal nature allows for a life course approach in exploring the relationships between social experiences and health. Releasing the data through the UKDS secure lab as outlined in this application is expected to allow the linked data to be used more widely to maximise societal benefit while maintaining high levels of data security. The age 22 survey currently in the field is expected to enrich the already deposited data for the cohort (waves 1-7) and is expected to be particularly valuable for the research community, including researchers in health and social care, providing rich survey data on a range of different domains of young people's lives. Particularly beneficial is the opportunity for a life course approach and to follow young people's experiences over time to analyse later life outcomes. [1 paragraph unchanged] MCS surveys include questions relating to health. CLS at UCL will use [28 words unchanged] via methodological information which will assess the data quality and comparability of the two important data sources. [19 paragraphs unchanged]

Benefits reported

The first yielded benefit is the creation of the refreshed linked MCS/HES dataset which will include most recent data. The dataset, which covers up to the year 2019 is now available for researchers to use via the UKDS. A link to the dataset is provided here https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=9030 CLS has produced an MCS/HES user guide. This document provides researchers with a complete guide to the linked data and information on the application process. See: https://doc.ukdataservice.ac.uk/doc/9030/mrdoc/pdf/mcs_hes_user_guide_version_1.pdf CLS delivered a webinar "An Introduction to linked health administrative data in four cohort studies" on the 11th of February 2021 to introduce the HES linked datasets and provide information to researchers on how to access them. No Yielded Benefits can yet be evidenced from the data received for research, under previous version of this agreement. However, UCL are looking to recognise similar to previous yielded benefits as per the previous Millennium Cohort detail provided in expected benefits and expect that some of the projects currently accessing the data will also result in successful yielded benefits. MARCH 2024 COMPLIANCE REPORT UPDATE: First Output: The first output is the MCS/HES dataset which is now available to the research community. https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=9030 Second Output: The second output will be health-related research, alongside methodological papers on the linked dataset, published in peer-reviewed journals. The methodological papers: ‘Examining the linkage quality and sample representativeness of the linked data’ are planned to be published by the end of 2026. In these papers, researchers will examine the quality of the linkage in terms of the associations between key cohort member sociodemographic characteristics and successful linkage and compare the levels of successful linkage within strata of each study variables which may be expected to be associated with hospital attendance, and hence with successful HES linkage (self-reported hospital attendance, self-rated general health, self-reported long-term illness). The researchers would like to additionally evaluate the population representativeness of the linked sample using external data (hospital admission rates in the general population). Third Output: Sublicence applications- The specific benefits to society of using the data accessed through the sub-license, would be stated by each applicant as part of their application to CLS. E.g. researchers applying to use the data will need to complete a project proposal and among other questions, will need to provide a response to the following question “How are your project findings expected to benefit society?”. Project 1- “Examining structural racism in the processes of identifying mental health needs for children and young people in the UK”. This project aims to examine inequalities in the identification of mental health difficulties for children and young people in the UK. The project aims to address the gap in research on mental health difficulties experienced by racially minoritized children and young people, specifically, exploring whether there are systematic differences across racial-ethnic groups in which children and young people are identified with mental health difficulties within administrative data systems. Project 2- “Mental health service use in young people and its relationship with social media and digital technologies”-Demand for mental health services has been increasing in recent years, particularly among young people. In response to this, many have blamed the rise of social media. But is there any truth to this accusation? Previous research has returned very mixed results and mostly uses self-reported measures of mental health. We can get a more objective view of mental health service use by turning to other sources, such as healthcare records. Therefore, the healthcare records provided by participants in the Millennium Cohort Study offer us a new opportunity to answer this question. Throughout their teens, participants answered questions about their use of social media, and at one point also filled in a time use diary. By combining these with the HES records, researchers hope to find out whether it could be possible that social media has caused more people to seek help for mental health conditions. Project 3- “Life course air pollution, mental health, and mental health service use in childhood” Residing in areas with bad air quality has been associated with mental health problems and related service use. However, available research is limited by cross-sectional or short-term longitudinal design without considering the timing of exposure to air pollution during the life course. This project aims to overcome previous limitations by estimating air pollution exposure from early life to young adulthood among cohort participants and by modelling different life course models (i.e., sensitive period, accumulation). Associations between selected life course models, self-reported mental health and HES records related to mental health problems in childhood will be investigated, with a special focus on how self-reported problems predict future service use.

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Objective for processing

This Data Sharing Agreement permits the retention and reuse of data that was previously supplied to University College London under earlier versions of this Agreement, for the purposes described. The Centre for Longitudinal Studies (CLS) at University College London (UCL) requires access to NHS England data for the purpose of the Millennium Cohort Study (MCS). The Centre for Longitudinal Studies (CLS) at University College London (UCL) is an academic resource centre responsible for producing and disseminating data resources for the scientific community. It is responsible for four of Britain's internationally renowned longitudinal cohort studies, the 1958 National Child Development Study, the 1970 British Cohort Study, the Next Steps and the Millennium Cohort Study (MCS). All these studies are following the groups of participants from cradle to grave. As such, this group of studies is unique and has, and still is, providing a wealth of information used in the policy decisions affecting society's health and well-being. The purpose of this application covers two aspects: MCS is renowned worldwide for the evidence it provides on children’s experience of growing up in the United Kingdom in the 21st Century. Since the study’s launch there have been seven attempts to re-contact and gather information from the whole cohort (at ages 9 months, 3 years, 5 years, 7 years, 11 years,14 years and 17 years). a) Request linkage of Hospital Episodes Statistics (HES) and Emergency Care Data Set (ECDS) data to a subset of the MCS (only cohort members who consented to have their health records linked to their survey data) The MCS covers such diverse topics as parenting; childcare; schooling and education (e.g. academic qualifications, vocational qualifications); daily activities and behaviour; cognitive development; child and parent mental and physical health; employment and education; income and poverty; housing, neighbourhood and residential mobility; and social capital, ethnicity and identity. The information collected in previous sweeps* of the study has formed the high-quality data resource, that is MCS, for scientific investigation across the life course and domains. b) CLS seeks permission to sub-licence this linked data with the research community via the UKDS. *The term sweep is used to refer to a round of data collection in the longitudinal study. MCS is renowned worldwide for the evidence it provides on children’s experience of growing up in the United Kingdom in the 21st Century. Since the study’s launch there have been seven attempts to re-contact and gather information from the whole cohort (at ages 9 months, 3 years, 5 years, 7 years, 11 years, 14 years and 17 years). The MCS covers such diverse topics as parenting; childcare; schooling and education (e.g academic qualifications, vocational qualifications); daily activities and behaviour; cognitive development; child and parent mental and physical health; employment and education; income and poverty; housing, neighbourhood and residential mobility; and social capital, ethnicity and identity. The information collected in previous sweeps of the study has formed the high quality data resource, that is MCS, for scientific investigation across the life course and domains. The seventh sweep, Age 17 survey (2018-19) added to the data already collected in previous sweeps by updating information on current circumstances of the cohort and the experiences they have had since the last sweep. In previous sweeps, schooling will have been the main activity common to the vast majority of cohort members. The Age 17 survey marked an important transitional time in the cohort members’ lives, where educational and occupational paths can diverge significantly. It is also an important age in data collection terms since it may be the last sweep at which parents are interviewed and it is an age when direct engagement with the cohort members themselves rather than their families is crucial to the long-term viability of the study. To reflect this, CLS conducted face-to-face interviews with the cohort members for the first time. Cohort members were also asked to do a range of other activities including filling in a self-completion questionnaire on the interviewer’s tablet, completing a cognitive assessment (number activity) and having their height weight and body fat measurements taken. The seventh, Age 17 survey (2018-19) added to the data already collected in previous sweeps by updating information on current circumstances of the cohort and experiences they have had since the last sweep. In previous sweeps, schooling will have been the main activity common to the vast majority of cohort members. The Age 17 survey marked an important transitional time in the cohort members’ lives, where educational and occupational paths can diverge significantly. It is also an important age in data collection terms since it may be the last sweep at which parents are interviewed and it is an age when direct engagement with the cohort members themselves rather than their families is crucial to the long term viability of the study. To reflect this, CLS conducted face to face interviews with the cohort members for the first time. Cohort members were also asked to do a range of other activities including filling in a self-completion questionnaire on the interviewer’s tablet, completing a cognitive assessment (number activity) and having their height weight and body fat measurements taken. This Agreement sets out three distinct elements for which relevant information is subsequently given for each: This was a unique opportunity to measure factors that underlie different types of transition into adult life, which may affect future wellbeing in unprecedented ways. Capturing these transitions well, alongside the contemporary factors underlying them was critical. It was important to build up a picture of daily life, including factors such as: relationship with parents, family and peers, risky behaviours, social media engagement and efforts on activities such as education /school. Additional factors affecting decisions at this age include attitudes and preferences, such as preferences for education, attitudes to risk, willingness to trade off resources at different points in time, and expectations about future life events. Measuring social and emotional development, mental health and cognitive development and using well-validated instruments, was also a critical component of the survey. 1) The CLS will receive linked data for the cohort and will use that data to validate, enhance and improve the quality of the cohort data, in this way creating a uniquely rich administrative/survey-linked data set. During this survey, CLS also obtained informed consent from cohort members for their health data to be linked to the data collected in the study. In total, consent to health linkage was obtained from approximately 6118 cohort members in England. These are the cases which CLS is seeking permission to link to HES and ECDS data. More information about this survey can be found here- https://cls.ucl.ac.uk/wp-content/uploads/2020/09/MCS7-user-guide-Age-17-ed1.pdf The following NHS England data will be accessed: Linking health data from HES and ECDS to the MCS survey data will greatly increase the possibilities for using the cohort to study how health outcomes impact on the individual aspects of their life such as education, work, relationships and family life and, likewise, how health outcomes relate to the individual behaviours and lifestyles aspects such as drug and alcohol use, sexual health, diet and exercise, which are all documented as part of the study. The successful inclusion of HES and ECDS data will enrich these data by revealing which cohort members have been admitted to or attended hospital and the reasons for this, e.g. drug and alcohol treatment, accident and emergency, maternity and mental health services which could help CLS better understand how health conditions could be better treated or supported. This kind of analysis necessitates pseudonymised record level data. • Hospital Episode Statistics Data about health behaviours may be more accurate if obtained from administrative records as a result of misreporting of complex health conditions, under-reporting of particular health problems or due to perceived sensitivities around certain behaviours and lifestyle aspects. There are no alternative, less intrusive ways of obtaining such information. This also offers an interesting methodological opportunity to validate the data collected in the survey and vice versa. o Admitted Patient Care CLS at UCL is requesting data from 2001 (where available) to most recent data available. The first data collection of the MCS study happened in 2001 when cohort members were 9 months old. CLS therefore wants to access the historical information for its cohort members. Health events can be experienced over an extended period. The objective HES/ ECDS data will complement and enhance the existing survey data, also improving the accuracy of the data collected in the survey. The large data range will facilitate research that CLS anticipate will be carried out on the effects of familial socioeconomic circumstances, lifestyle and environmental factors on the evolution of the wellbeing, health and development of cohort members, offering huge potential for scientific and policy-related research. This will build on the extensive body of work focused on the millennium cohort as given in ‘Yielded Benefits’. o Accident & Emergency The MCS study follows the lives of young people across England, Scotland, Wales and Northern Ireland. As this project requests data linkage to the MCS study, the geographical spread of the data requested will be across England. o Critical Care CLS at UCL have considered data minimisation in terms of what CLS needs but further minimisation is not possible. The data requested in this application will be part of a database, created to serve various research projects. Data minimisation will be applied when CLS sub-licences the data to third parties. Third party organisations wishing to access the data will need to specify the variables needed and will only be given access to a sub-set of the data which is needed to conduct their research. o Outpatients The overall aim of the linkage is to: • Emergency Care Data Set (ECDS) 1. Validate, enhance and improve the quality of the cohort data, in this way creating a uniquely rich administrative/survey linked data set (HES/ECDS - MCS). Linking health data from Hospital Episodes Statistics (HES)/Emergency Care Data Set (ECDS) to the MCS survey data has greatly increased the possibilities for using the cohort to study how health outcomes impact the individual and aspects of their life such as work, relationships and family life and, likewise, how health outcomes relate to the individual behaviours and social or economic determinations of health behaviours such as drug and alcohol use, sexual health, diet and exercise, which are all documented as part of the study. 2. Use this data set to produce methodological papers on the quality of the data (eg around measurement, representativeness) and research papers helping to showcase its benefits for health and social care. The successful inclusion of HES/ECDS data has enriched these data by revealing which cohort members have been admitted to or attended hospital and the reasons for this - e.g. drug and alcohol treatment, accident and emergency, maternity and mental health services which have helped CLS better understand how health conditions could be better treated or supported. 3. Promote and make possible wider use of this linked data set, through providing wider access to the linked NHS Digital HES / CLS MCS data to the research community via the UK Data Service (UKDS) Secure Lab, through a sub-licensing agreement agreed between CLS and NHS Digital Data about health behaviours are more accurate when obtained from administrative records because of misreporting of complex health conditions, under-reporting of health problems or due to perceived sensitivities around certain behaviours and social or economic determinations of health. This offers an interesting methodological opportunity to validate the data collected in the survey and vice versa. THE SUB-LICENCE: The level of data required is identifiable - necessary to enable linkage of the data with data collected from other sources, including the participants themselves. Sub-licensing of the data will be in line with the DARS sub-licensing data standard: https://digital.nhs.uk/services/data-access-request-service-dars/dars-guidance/sub-licencing-and-onward-sharing-of-data The data will be minimised as follows: UCL seeks permission to include onward sharing of the linked HES/ ECDS and CLS MCS data with the UK Data Service (UKDS), where data can be accessed by accredited researchers in a Secure Research Environment, known as Secure Lab, following a "Sub-licensing model". - Limited to a study cohort of approximately 6,118. Of these, UCL only linked those members of the cohort gave their permission to add information from health records held by the NHSE in the 7th Survey Sweep. 2) The CLS will use this data set to produce methodological papers on the quality of the data (e.g. around measurement, and representativeness) and research papers helping to showcase its benefits for healthcare, adult social care, or the promotion of health. Access will be restricted to CLS researchers who meet the following requirements: i. The researcher must be substantively employed in the CLS by UCL; ii. The researcher must have completed NHS England’s Data Security Awareness course; iii. The researcher must have submitted a project proposal for review by the CLS Data Access Committee (DAC) and the CLS DAC must have approved the access request; iv. Once, approved, the researcher will sign a licence agreement with CLS and will then be granted access to the relevant subset of data via the UCL Data Safe Haven (DSH). The level of data required is pseudonymised. The data will be minimised to variables and potential cases relevant to the purpose. 3) The CLS will promote and make possible wider use of this linked data set, through providing wider access to the linked NHS England HES / CLS MCS data to the research community via the UK Data Service (UKDS) Secure Lab under sublicensing agreements subject to the following access arrangements. With the exception of individuals substantively employed by UCL in the CLS, all other access will be via the UKDS only. Access to the data via the UKDS will only be granted to third party researchers who meet the following requirements: i. The researcher must be registered with the UKDS; ii. The researcher must successfully apply for approval by the CLS DAC via the process outlined below. The process for applying for approval is as follows: i. The researcher submits an application, including an 'Accredited Researcher application form' and 'Research proposal', to the UKDS. ii. The UKDS screens the application and either rejects or forwards the application to the CLS at UCL. iii. The CLS checks the organisational Information Governance and security assurance evidence provided and either requests further evidence, if the evidence of provided does not meet the requirements (as outlined in the sub-licence), or submits the application for CLS DAC approval. iv. The CLS DAC assesses both project documents (UKDS project proposal and the “UCL Licence agreement”) and makes a decision to approve it, not approve it, or require further information. CLS DAC considerations include an assessment of the expected benefits to health care, adult social care or the promotion of health. Should an application be rejected, a researcher can apply again with a revised application. v. If the CLS DAC approves the project: a. CLS informs UKDS that the project has been approved. b. The CLS authorised representative signs the “UCL License agreement” and sends it back to the UKDS to be forwarded to the researcher. vi. UKDS informs the researcher that their project was approved; sends them a countersigned copy of the “UCL Licence agreement’ and makes the data available to them via Secure access to linked data at the Safe Centre at the UKDS (hosted at the University of Essex) or via the researcher's own institutional desktop PC, depending on the sensitivity/impact level of the data being requested. The agreement with the UKDS is signed at the point of deposit of the data. The data manager will prepare the data for deposit and as part of the depositing of the data, the Deposit Licence agreement is signed. vii. CLS DAC will publish the information about any data dissemination on the CLS website, including the name of the organisation to which data was provided, purpose (summary of the project) and what data was released. (NB: If CLS DAC does not approve the project, no data will be disseminated). The data will be provided to the researcher via their own project folder, which will contain only the data that the researcher needs to see for their project. The research-linked data provided to researchers are pseudonymised and de-identified, and will never contain identifiable information such as name, address, date of birth, NHS or NI number. The researcher accessing the data via the UKDS Secure Lab will not be able to download any data. Once the researcher has finished their research, the UKDS will delete the data folder with the tailored dataset for the specific project. Disclosure control checks are carried before any research publication. The data sharing controls in place between NHS England and UCL are replicated between UCL and the other organisations. UCL, which houses CLS at the UCL Institute of Education, is fully accountable for the actions of the parties involved in subsequent data share and use. The UCL Licence agreement mirrors the Data Sharing Framework Contract in place between NHS England and UCL. There will be no charge applied to licenses supplied by UCL. NHS England will retain the ability to directly audit UKDS's compliance with the outlined and agreed data access arrangements. Access to the deposited data can be remote access via the secure lab or physically present at UKDS, depending on which environment is more suitable for the researcher. The anticipated volume / number of licences is 1-2 sub-licences per month. Sub-licences shall not exceed a term of 12 months at a time and may be extended/renewed if appropriate. The sub-licences remain valid only while UCL retains the right to hold and share the data from NHS England. The territory of use in the sub-licence will be the same or narrower than the territory of use stated in this data sharing agreement, namely the UK. The UKDS (hosted by University of Essex) is a processor acting under the instructions of UCL. UKDS’ role is limited to holding the linked data in a secure environment; screening for completeness of applications for data access; providing training for use of linked data securely; entering into contractual agreements with approved researchers; extraction of approved data and setting up access systems, and approving statistical outputs, following a statistical disclosure control procedure. UCL will maintain an agreement with UKDS which outlines the terms and conditions under which the linked data can be accessed via the UKDS Secure Lab. UCL will not provide data access to commercial organisations for research or for commercial purposes. UCL is the controller as the organisation responsible for ensuring that the data will only be processed for the purpose described above. The lawful basis for processing personal data under the UK GDPR is Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller; The lawful basis for processing special category data under UK GDPR is Article 9(2)(j) processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes. In addition, for ethical reasons and under the Common Law Duty of Confidentiality, UCL sought permission from cohort members to access and link their routine health records to their survey data, and to the onward sharing of this linked data in pseudonymised form (via a secure setting with appropriate safeguards). The funding is provided by the Economic and Social Research Council. The funding is specifically for the study described. Funding is in place until 2025. The University of Essex is a processor acting under the instructions of UCL. The University of Essex hosts the UKDS and their role is limited to storing the linked pseudonymised data and facilitating access to third-party researchers who have the necessary approvals from the CLS DAC and an active sublicense agreement with UCL. Only staff who are permitted to work at the UKDS (and are substantively employed by the University of Essex) will process the data. Should any substantively employed researchers from the University of Essex wish to use the UKDS data, they will be required to apply via the sub-licence route, the same as other researchers from other organisations. Amazon Web Services (AWS) is a processor acting under the instructions of UCL. AWS’ role is limited to secure backup of data stored in UCL’s Data Safe Haven. UCL uses offsite data centre services provided by VIRTUS data centre. VIRTUS does not have access to the data. [1 paragraph unchanged] The UKDS is based at, and hosted by, the University of Essex. The University of Essex are therefore listed as a data processor and also listed in the data processing and storage location sections. Only staff who are permitted to work at the UKDS (and are substantively employed by University of Essex) will process the data. Should any substantively employed researchers from University of Essex wish to use the UKDS data, they will be required to apply via the sub-licence route, the same as other researchers from other organisations. Under the "Sub-licensing model", NHS Digital shares data with UCL who are in turn licensed to share these data with other organisations, subject to agreed controls, scoped in this agreement between NHS Digital and UCL. In line with this onward sharing model, the data sharing controls in place between NHS Digital and UCL are replicated between UCL and the other organisations. UCL, which houses CLS at the UCL Institute of Education, is fully accountable for the actions of the parties involved in subsequent data share and use. The agreement mirrors the Data Sharing Framework Contract in place between NHS Digital and UCL. It also requests information about the research proposal, benefits to health and/or social care, organisational security assurance and terms and conditions regarding onward sharing of data, responsibilities and processing activities etc. Under the sub-licensing model, CLS will deposit the linked data with UKDS who will serve as a data repository. Access to the deposited data will be granted to approved researchers within a Secure Research Environment on behalf of UCL as outlined below. NHS Digital will retain the ability to directly audit UKDS's compliance with the outlined and agreed data access arrangements. The anticipated volume / number of licences is 1-2 sub-licences per month, and the potential length of the sub-licences is 2-3 years in length. There will be no charge applied to licenses supplied by UCL. The territory of use in the sub-licence will be the same or narrower than the territory of use stated in this data sharing agreement, namely the UK. In this sharing model of the linked data, UCL will be a data controller, determining the purposes for which and the manner in which the linked data are processed. UKDS will be a data processor, as they will be processing the data on behalf of UCL. This includes holding the linked data in a secure environment, screening for completeness of applications for data access, providing training for use of linked data securely, entering into contractual agreements with approved researchers, extraction of approved data and setting up access systems, and approving statistical outputs, following a statistical disclosure control procedure. The approved organisations and researchers who are granted an access to the linked data via the UKDS Secure Lab, agree to terms and conditions of use, their rights and responsibilities as users of the linked data, as defined by the UKDS. In addition to the agreements signed with the UKDS, the organisation of the researcher applying to use the linked data will enter into a Licence agreement with UCL. ORGANISATIONAL AGREEMENTS UCL will provide a sub-licence to UK organisations undertaking research that will be of benefit to the public (this will be assessed in the project proposal form submitted to the UKDS and to UCL). Applicants (potential licensees) will need to show that the provision of the sub licencing will be in the public interest and that the data will be used either (i) for the provision of health care or adult social care; or (ii) for the promotion of health. UCL will not provide data access to commercial organisations for research for commercial purposes. Additionally, the UCL Licence agreement will assess the project proposal against its assessment criteria to determine the details of the project, the people who will be accessing the data, and what data will be requested. Applicants will need to be accredited researchers or agree to undertake training and become accredited, prior to accessing the data. Additionally, an applicant's organisation will need to provide evidence that they have information governance and security assurances in place. Members of the CLS Data Access Committee (DAC) will review and decide if the evidence provided satisfy the criteria requirements. Applicants (licensees) and their organisations will have to sign two agreements to obtain a sub-licence, one with the UKDS and another with UCL. In both cases the licensee will agree with the terms stated in the Confidentiality Section of the UCL Licence Agreement and with the Confidentiality Terms stated in the Secure Access Agreement which will be signed with the UKDS. By signing these agreements, the licensee agrees to adhere to these terms, including respecting the privacy of health services user data they will receive. Licensees are also reminded of the penalties they are likely to incur if they do not comply with the terms they have agreed. In addition to the above, the UKDS agreement stipulates that data users must complete mandatory training before they are allowed to access the data. To ensure the security of the linked information, shared with UCL by NHS Digital, and subsequently shared by CLS at UCL with the UKDS; where data could be accessed by approved researchers in a Secure Lab, UCL envisage the following controls employed at the different steps of the process of depositing, approving and sharing of the linked information: -An agreement between NHS Digital and UCL to onwardly share linked HES/ ECDS and CLS MCS information under the "Sub-licencing model" which outlines the terms and conditions of use of the linked data via the UKDS Service Secure Lab as the data repository, and the full accountability of UCL (housing CLS at the UCL Institute of Education) to the actions of the parties involved in subsequent access to the linked data. -An agreement between UCL (as a data controller) and UKDS at The University of Essex (as a data processor), which outlines the terms and conditions under which the linked data can be accessed via the UKDS Secure Lab. -An agreement between UKDS and the approved researcher, which outlines the terms and conditions of use of the linked data in the UKDS's Secure Lab. -An Agreement between CLS at UCL and the organisation requesting to use the linked data via the UKDS, which outlines the terms and conditions of use of the linked data. The researcher accessing the data via the UKDS Secure Lab will not be able to download any data. Once the researcher has finished their research, the UKDS will destroy the data folder with the tailored dataset for the specific project. The data held at UCL will be destroyed if the data sharing agreement between NHS Digital and UCL were to cease. If it were to cease, the license agreement between UCL and the licensee organisation will be terminated. UCL legal basis for processing (acquiring, linking and sharing) personal data is for a public task under GDPR (article 6(1)(e)) i.e. processing is necessary for the performance of a task carried out in the public interest (as is made explicit to participants in the information leaflets provided). UCL also process special categories of personal data for research under GDPR (article 9(2)(j)) i.e. processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes. In addition, for ethical reasons and under the Common Law Duty of Confidentiality, UCL sought permission from cohort members to access and link their routine health records to their survey data, and to the onward sharing of this linked data in pseudonymised form (via a secure setting with appropriate safeguards). This data dissemination includes the following safeguards: i. Linkages are based on informed consent ii. Identifying variables are held separately to the survey responses, including during the matching process iii. Data transfers are made securely e.g. encrypted iv. The data will only be used for statistical research purposes and will not involve any decision making affecting a person v. Data are stored in secure environments certified to ISO 27001 vi. Data are only accessed in pseudonymised form and treated for disclosure if necessary vii. Data are accessed in a secure environment. viii. Disclosure control checks are carried before any research publication. All data processed under the sub-license will be completed using the same legal basis as mentioned above, namely GDPR (article 6(1)(e))and GDPR (article 9(2)(j)). The UCL Licence agreement will require licensees to provide the Legal Basis of their request to link health data via CLS and therefore CLS Data Access Committee (DAC) will only grant approval to applications from researchers within public bodies who have a legal basis to process data under GDPR. The data disseminated to UCL will be accessed by substantive employees of UCL who will work on the data to make it research ready and deposit it at the UKDS for researchers applying to use it for specific projects.

Processing activities

No new data will be supplied under this version of the Data Sharing Agreement. The following describes data flows which took place under previous versions of this Agreement. Continuing use of the data within the UKDS (as described below) is permitted under this Agreement. The CLS UCL will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Date of Birth, full name, Postcode, Sex and a unique person ID) for the cohort to be linked with NHS England data. 1. CLS at UCL will supply NHS Digital with identifiers of cohort members who have consented to this data linkage, including full name, sex, postcode, date of birth, NHS number (if known) and study ID (study-specific pseudonymised identifier). NHS England data will provide the relevant records from the HES and ECDS datasets to UCL. The data will contain no direct identifying data items but will contain a unique person ID which can be used to link the data with other record level data already held by the recipient. 2. NHS Digital will link the identifiable study data to HES and ECDS data. NHS Digital will then remove identifiers from the linked datasets and return the pseudonymised datasets to the CLS team at UCL with the study ID. The data disseminated to UCL will be accessed by substantive employees of UCL who have been appropriately trained in data protection and confidentiality. The data will be held at the secure server in the UCL Data Safe Haven (DSH) and accessed remotely by CLS staff. The CLS will carry out validation of the administrative pseudonymised data received (linked HES/ECDS data) and combined the supplied administrative data with the information collected from the participant as part of the MCS study using the study ID. 3. CLS will carry out validation of the administrative pseudonymised data received (linked HES/ ECDS data) and will combine the supplied administrative data with the information collected from the participant as part of the MCS study using the study ID. Once the linked survey-administrative data files have been created, the CLS may perform other activities to prepare the data for use, such as coding and cleaning, derivation of summary variables and compilation of data documentation. Once the linked survey-administrative data files have been created, CLS may perform other activities to prepare the data for use such as coding and cleaning, derivation of summary variables and compilation of data documentation. The CLS will use these data to create an analysis file which does not contain any identifiable data. 4. CLS researchers will use these data to create an analysis file which will not contain any identifiable data. The CLS creates derived variables that summarise study members’ hospitalisation and health histories (e.g. hospital admissions and re-admissions, incidence of common diseases, children’s ailments etc.) and compare MCS survey data with data from hospital statistics in order to compare and validate the data collected in CLS surveys. 5. CLS will create derived variables that summarise study members' hospitalisation and health histories (e.g. hospital admissions and re-admissions, incidence of common diseases, children's ailments etc.), and will compare MCS survey data with data from hospital statistics, in order to compare and validate the data collected in CLS surveys. The CLS will securely transfer the analysis file to the UKDS (hosted by University of Essex). CLS researchers who need to access the data to produce methodological papers on the quality of the data (eg around measurement, representativeness) and research papers helping to showcase its benefits for health and social care will need to submit an application to CLS DAC detailing their project proposal. Upon DAC approval, a pseudonymised dataset will be provided to the researcher. The data will be held at the secure server in the UCL Data Safe Haven. The data will be stored on servers at both UCL and the UK Data Archive based at the University of Essex. The UK Data Archive will store the pseudonymised analysis file only. Identifiers will be held separately from attribute characteristics. HES/ ECDS data will not be relinked to the identifiable data which is held separately from the survey responses. Re-identification will only happen at the occasion of a request, made from a cohort member, for withdrawal from the study, and this includes removal of data. Where a participant wishes to withdraw from the study, the identifiable data is used to locate the study id, and then in turn destroy their data. Amazon Web Services provides cloud hosting services to UCL and will store the data as contracted by UCL. UCL DATA SAFE HAVEN The data will be accessed by authorised personnel via remote access. The data will remain on the servers at UCL, AWS and the University of Essex at all times. The UCL DSH is certified to ISO 27001:2013 and is compliant with NHS Digital’s Data Security and Protection Toolkit. Research teams using the DSH complete annual training and regularly review data access arrangements ensuring data is only limited to those authorised to access it. UCL Computing Regulations are based on the premise that access to resources is generally forbidden unless expressly permitted. All data transfers from the DSH require approval and are carried out through secure portals which are fully audited. Access to the UCL DSH is via remote desktop and requires multi-factor authentication. In addition to a strong password each user has to use a six digit number generated by a smartphone app or physical token at each login. Passwords must be changed at regular intervals, and unused accounts are automatically disabled after a fixed period. Once inside the environment, robust access control ensures that researchers can only examine information that they are approved to use. Personnel are prohibited from downloading or copying data to local devices. UKDS DATA ACCESS MECHANISMS: The data will not leave the UK at any time. As an ESRC resource centre, CLS at UCL shares its survey data with the research community via the UKDS under safeguarded or controlled access mechanisms, dependent on the likelihood and potential impact of disclosure. Data with higher risk of disclosure is treated with an appropriate degree of security and management. CLS data fall into the following categories which are defined by the likelihood and potential impact of disclosure: Access is restricted to authorised individuals within the CLS at UCL, individuals employed by the UK Data Archive at the University of Essex and access to appropriately minimised subsets of the pseudonymised analysis file will be granted to authorised third parties under sublicense. -Tier 1: data with low level of disclosure: e.g. participant self-reported survey data. These data are made available through the UKDS End User Licence and have a low impact of disclosure; All personnel accessing the data have been appropriately trained in data protection and confidentiality. -Tier 2a: data that is potentially disclosive: e.g. medium level and coarse geographies or sensitive information about cohort members. These data are made available through the UKDS Special Licence and have a medium impact of disclosure; CLS does not link HES/ECDS data to any other dataset. However, when a researcher accesses the pseudonymised data via the UKDS, they may wish to access this data in combination with other pseudonymised datasets which are also available at the UKDS. If a researcher wishes to use the data in combination with other datasets they may do so by using the two datasets together in a secure environment. However, they will need to explicitly mention this in their application to CLS and will only be permitted if CLS DAC approves the project proposal. -Tier 2: data that are too detailed, sensitive or confidential to be made available under the standard End User Licence or Special Licence, such as detailed geographical indicators or fine-grained individual level linked data. These data have a high impact of disclosure and are made available through the UKDS Secure Access. At UCL, identifiers will be held separately from attribute characteristics. HES/ECDS data will not be relinked to the identifiable data which is held separately from the survey responses. Re-identification will only happen at the occasion of a request, made from a cohort member, for withdrawal from the study, and this includes removal of data. Where a participant wishes to withdraw from the study, the identifiable data is used to locate the study ID and then in turn destroy their data. ACCESS MECHANISMS TO NHS DIGITAL HES/ ECDS DATA LINKED TO CLS COHORT STUDIES VIA THE UKDS: UCL only request data for those individuals who have given consent to link their health records to their survey data. Before preparing the file to be sent to NHS England, for the matching of consenting participants to the NHS England HES/ECDS datasets, the data manager will check for withdrawals and will remove participants who- The HES/ ECDS data provided to CLS at UCL by NHS Digital, which are linked to the CLS cohort members, have been processed by the CLS data management team to minimise the risk of disclosure when linked to the CLS survey data. This has been achieved by removing highly identifiable variables and altering other variables by top-coding or truncating them. Following this processing, the final health datasets have been classified under Tier 2. · Have asked CLS to withdraw their consent to health data linkage It is UCL's intention to deposit these Tier 2 linked HES/ ECDS data with UKDS under the UKDS Secure Access, and provide access to this information for approved researchers, following the process and contractual arrangements, outlined above and described in more detail below, following the onward sharing model agreed between NHS Digital, CLS at UCL, and UKDS. · Have asked CLS to delete their data The data provided will be pseudonymised, and will be accessed only via the UKDS secure lab. Data accessed in this way cannot be downloaded. This means that researchers will have access to a screen view only and it is not possible to remove data from the environment. Once researchers and their projects are approved, they can analyse the data remotely from their organisational desktop, or by using the UKDS Safe Room. Specialised staff will apply statistical control techniques to ensure the delivery of safe statistical results. The file will only contain details of those who consented to their health data being linked to MCS study data and have not subsequently withdrawn their consent or requested that their data be deleted. ADDITION OF THE SUB-LICENCE: The HES/ECDS data provided by NHS England, which are linked to the CLS cohort members, are processed by the CLS data management team to minimise the risk of disclosure when linked to the CLS survey data. This is achieved by removing highly identifiable variables and altering other variables by top-coding or truncating them. The process of accessing the linked data via the UKDS Service Secure Lab include the following steps: The data provided to the UK Data Archive will be pseudonymised and will be accessed only via the UKDS secure lab. Data accessed in this way cannot be downloaded. This means that researchers will have access to a screen view only and it is not possible to remove data from the environment. Once researchers and their projects are approved, they can analyse the data remotely from their organisational desktop, or by using the UKDS Safe Room. Specialised staff will apply statistical control techniques to ensure the delivery of safe statistical results. -Registration with the UKDS Service. Only staff who are permitted to work at the UKDS (and are substantively employed by University of Essex) will process the data for sub-licensing. Note that any data accessed through the UKDS Secure Lab can only be accessed under secure conditions and cannot be downloaded. The linked data provided to approved researchers may be subject to sub-setting of variables (and, if necessary, cases) to minimize disclosure risks and ensure that no individual or organisation can be identified from the results. In addition, all statistical outputs are subject to statistical disclosure control procedure. Access to the Secure Lab is only available to researchers who are based at a UK academic institution or an ESRC-funded research centre and are an ESRC Accredited Researchers. PhD and research students can request access but must apply jointly with their supervisors from established organisations. -Submission of an application, including an 'Accredited Researcher application form' and 'Research proposal'. -Screening of application by UKDS for completeness. Once a researcher has registered and UKDS has screened / approved the application: 1) UKDS sends project proposal (researcher application forms) to CLS at UCL for Data Access Committee (DAC) approval. Applicants are required to demonstrate they have security assurance in place (System Level Security Policy/ISO Certificate/DSPT). 2) CLS sends the “CLS Licence Agreement for linked NHS Digital Data” (henceforth referred to as “UCL License Agreement”) to researchers to be completed and signed by their organisation (this includes the benefits to health and social care and evidence of organisational security assurances) not covered by UKDS application. 3) Researcher/their organisation representative will send the UCL License Agreement for Linked NHS Digital data completed and signed back to CLS. 4) CLS will: a) check the organisational Information Governance and security assurance evidence provided as per Section 15 Organisational Security Assurance of the UCL Licence agreement, b) send the project for CLS DAC approval. 5) Should evidence of organisational Information Governance and security assurance provided not meet the requirements (as outlined in the sub-license), CLS will request the applicant to provide further evidence, and will only submit the project to CLS DAC for approval when evidence provided is satisfactory. Approval for data access will only be granted to applicant organisations that meet the security assurance requirement. 6) CLS DAC will assess both documents (UKDS project proposal + UCL Licence agreement) and make a decision to approve it, not approve it, or require further information. Should an application be rejected, a researcher can apply again with a revised application. 7) In the UCL License agreement, CLS DAC will, among other things, assess the benefits for health and social care statement and decide whether it is satisfied with the answer. 8) Once CLS DAC approves the project : a) CLS will inform UKDS that the project has been approved. b) CLS representative should sign the UCL License agreement noting the DAC reference number on the License document and send it back to the organisation of the applicant (the Principal Investigator for the study requiring access will sign the agreement - they will be an authorised signatory for their organisation). 9) If CLS DAC is not satisfied with the evidence provided by the applicant about the benefits to health and social care, then CLS DAC can ask the applicant to provide additional information and the project can be re-submitted for CLS DAC approval on the next CLS DAC meeting or via Chair approval. 10) UKDS will inform the researcher that their project was approved and make the data available to them via Secure access to linked data at the Safe Centre at the UKDS (hosted at the University of Essex) or via the researcher's own institutional desktop PC, depending on the sensitivity/impact level of the data being requested. 11) UCL will inform NHS Digital as to who they have issued sub-licences to, in a format agreed with NHS Digital. Only staff who are permitted to work at the UKDS (and are substantively employed by University of Essex) will process the data for sub-licensing. Note that any data accessed through the UKDS Secure Lab can only be accessed under secure conditions and cannot be downloaded. The linked data provided to approved researchers may be subject to sub-setting of variables (and if necessary cases) to minimize disclosure risks and ensure that no individual or organisation can be identified from the results. In addition, all statistical outputs are subject to statistical disclosure control procedure. Access to the Secure Lab is only available to researchers who are based at a UK academic institution or an ESRC-funded research centre, and are an ESRC Accredited Researcher. PhD and research students can request access but must apply jointly with their supervisors from established organisations. [1 paragraph unchanged] UKDS SECURE DATA HANDLING PROCEDURES: The UKDS home working policy does not involve Bring your own device (BYOD). Researchers applying to use the data (stored at the UKDS Secure lab) remotely from home, will only be given permission to access the data if they agree that they will use their work organisation office computer remotely and from there access to the Secure lab. UKDS has received government technical accreditation and has been certified for its secure data handling procedures under the international standard for information security (ISO 27001). To maintain this certification, regular internal and external audits are undertaken. UKDS also hires a government-approved company to conduct internal and external penetration testing of its Secure Lab systems. The data can be accessed by authorised CLS personnel via remote access on UCL-issued devices from their work organisation office or from home. The data will always remain on the servers at UCL CLS. Personnel are prohibited from downloading or copying data to local devices More widely, the UKDS employs an Information Security Management System (ISMS) to ensure compliance with the ISO accreditation. The Secure Lab falls into this system, and a number of documented processes are regularly maintained and reviewed to ensure these processes are robust, relevant, and fit-for-purpose. The ISMS is overseen by an Information Security Management Group (ISMG), which regularly meets and approves changes to procedures. All organisations party to this Agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by 'Personnel' (as defined within the Data Sharing Framework Contract - i.e. employees, agents and contractors of the Data Recipient who may have access to that data).

Expected output

Following the data quality and validation work, the first output will be [14 words unchanged] add an important layer to this already rich data as well as providing provide the means for data quality checking. The second output will be health-related research, alongside methodological papers on the linked dataset, published in peer-reviewed journals. The methodological assessments are expected to finish three years after obtaining the data. Outputs will contain only aggregate level data with small numbers suppressed in line with HES analysis guide. CLS researchers doing research and/or methodological work will access this data via the UCL Data Safe Heaven. The creation of this MCS- HES/ ECDS database and the research and methodological papers are the first steps in establishing a robust research database which will be of benefit to health and social care. This data linkage opens new research opportunities by combining reliable administrative data with detailed survey data. This linkage increases the number of variables available for research in the dataset and complements the health information provided by the participants in the survey. Combined, these data sources enhance each other, making it possible to capture detailed information regarding an individual’s health and well-being. Health events can be experienced over an extended period, tracking all relevant events over such a long period may not be feasible in a single database. Using HES/ ECDS data which records such information can improve the accuracy of the data collected in the survey, offering huge potential for scientific and policy-related research. The creation of this MCS- HES/ ECDS database and the research and methodological papers are the first steps in establishing a robust research database which will be of benefit to health and social care. This data linkage opens new research opportunities by combining reliable administrative data with detailed survey data. This linkage increases the number of variables available for research in the dataset and complements the health information provided by the participants in the survey. Combined, these data sources enhance each other, making it possible to capture detailed information regarding an individual’s health and wellbeing. Health events can be experienced over an extended period, tracking all relevant events over such a long period may not be feasible in a single database. Using HES/ ECDS data which records such information can improve the accuracy of the data collected in the survey, offering huge potential for scientific and policy-related research. [1 paragraph unchanged] The second output will be health-related research, alongside methodological papers on the linked dataset, published in peer-reviewed journals. The methodological assessments are expected to finish three years after obtaining the data. Outputs will contain only aggregate-level data with small numbers suppressed in line with HES analysis guide. CLS researchers doing research and/or methodological work will access this data via the UCL Data Safe Heaven. The methodological paper will be titled: “Examining the linkage quality and sample representativeness of the linked MCS”. This is planned to be published by the end of 2026. The target journals for publication are : 1) Journal for Survey Statistics and Methodology special issue on “Recent Advances in Data Integration” 2) Public Opinion Quarterly special issue on “Augmenting Surveys with Paradata, Administrative Data, and Contextual Data” 3) International Journal of Population Data Science In this paper, researchers will examine the quality of the linkage in terms of the associations between key cohort member sociodemographic characteristics and successful linkage, and compare the levels of successful linkage within strata of MCS variables which may be expected to be associated with hospital attendance, and hence with successful HES linkage (self-reported hospital attendance, self-rated general health, self-reported long-term illness). The researchers will additionally evaluate the population representativeness of the linked sample using external data (hospital admission rates in the general population). The methodological project above mentioned is currently being carried out for CLS’s other study, the 1958 National Child Development Study (NCDS) and it is near completion. The findings suggest that the linkage quality of the NCDS-HES data is high and that the linked sample maintains an excellent level of population representativeness. Researchers hope that these analyses will both improve the quality and transparency of research using this linked data resource and encourage providers and users of other linked data resources to undertake and publish similarly thorough evaluations. This paper is expected to be published during 2023 At the time of this renewal, no data has yet been used or sublicensed, there was a delay in receiving the data from NHS England and also a delay in preparing the data for deposit at CLS. The linked data was deposited in November 2022 and is now available for researchers to apply. UCL CLS held a webinar in November 2022 to an attendance of 60+ interested parties, to showcase the availability and content of the linked data and as of yet no applications have been received (December 2022).

Expected measurable benefits

MCS surveys include questions relating to health. CLS at UCL will use these responses to compare with their data available on HES/ ECDS to obtain a better understanding of relationship between self-reporting and administrative data. This will be shared via methodological information which will assess the data quality and comparability of two important data sources. This will benefit research looking at Health and Social Care. The main purpose is to provide access to the linked Millennium Cohort Study (MCS) survey data with NHS England Health Episode Statistics (HES) to enhance the research resource for secondary users. Linking HES data with the survey data greatly widens the value of research offering an opportunity to use the HES data alongside rich survey information covering a range of different domains of people's lives. This information is not possible to directly access via NHS England. It provides an invaluable opportunity to better understand some of the social determinants of health. MCS will offer invaluable information on social experiences through the years of adolescence and early adulthood, and its longitudinal nature allows for a life course approach in exploring the relationships between social experiences and health. Releasing the data through the UKDS secure lab as outlined in this application is expected to allow the linked data to be used more widely to maximise societal benefit while maintaining high levels of data security. This data linkage will facilitate research that CLS anticipate will be carried out on the effects of familial socioeconomic circumstances, lifestyle and environmental factors on the evolution of the wellbeing, health and development of cohort members. This could be of direct benefit to the NHS and to community services interfacing with schools through informing policy to improve healthy lifestyles. The age 22 survey (currently in development) is expected to enrich the already deposited data for the cohort (waves 1-7) and is expected to be particularly valuable for the research community, including researchers in health and social care, providing rich survey data on a range of different domains of young people's lives. Particularly beneficial is the opportunity for a life course approach and to follow young people's experiences over time to analyse later life outcomes. The creation of this linked MCS- HES/ ECDS database will be a rich data resource with great potential for research on health and for informing policy interventions on health and social care. Millennium Cohort Study (MCS) data is a resource with great potential for the research and policy community, and the information collected on health and its social determinants widens its potential value for health research and policy interventions. Through the set-up at the UK Data Service, researchers are able to apply and carry out research utilising the established link to benefit health and social care. Sublicensees are expected to publish/ and or make a conscious effort to inform policymakers and researchers of their findings. MCS surveys include questions relating to health. CLS at UCL will use these responses to compare with the data available on HES/ ECDS to obtain a better understanding of the relationship between self-reporting and administrative data. This will be shared via methodological information which will assess the data quality and comparability of two important data sources. CLS also expects that this data linkage will facilitate research that CLS anticipate will be carried out on the effects of familial socioeconomic circumstances, lifestyle and environmental factors on the evolution of the well-being, health and development of cohort members. This could be of direct benefit to the NHS and to community services interfacing with schools through informing policy to improve healthy lifestyles. Below are examples of high-impact research using MCS data: 1. Based on ESRC-supported research and using both Millennium Cohort and Understanding Society data, the Department for Work and Pensions (DWP) has launched a policy initiative aimed at supporting parents/carers and families who experience worklessness and economic disadvantage, with the objective of improving education attainment and mental health outcomes for children and young people. This policy announcement uniquely recognises young peoples educational attainment and mental health as primary pillars of future employability, and the importance of the longitudinal studies employed to support these conclusions and policy investment recommendations. As an example of longitudinal study data use, the DWP describe: This innovative, research-led policy investment is directing support to front-line professionals aimed at improving educational and mental health outcomes for children whose parents/carers experience -worklessness. Proposals based on the findings include: - Redefining the Troubled Families Programme “to encourage a greater emphasis on tackling worklessness and issues associated with it”. - Strengthening support to help reduce relationship distress between parents/carers, whether together or separated, announcing an innovative new programme, backed initially by £30 million (April 2017), with an additional 30 million added in the November 2017 Budget Statement. Using data from the Millennium Cohort Study (MCS), CLS researchers and collaborators have investigated the prevalence of mental ill-health during childhood and adolescence, up to age 14. Their research has aimed to identify the factors associated with mental ill-health and the groups most at risk and in need of support. In addition, their studies have examined the distinction between poor mental health and poor well-being. This research has received widespread public attention and achieved a variety of impacts on policy and practice. Following on from this work, CLS researchers are exploring the prevalence of mental ill-health among the cohort in their mid-teens, using MCS data, collected at age 17. 2. Research evidence used for government briefing papers. CLS academics wrote accessible briefing papers available on the link below, which were shared with government departments. The extensive media coverage of the research drew huge interest from policymakers, practitioners, parents, and educators. The research rapidly became part of the bloodstream of public discussion of young people’s mental health. https://cls.ucl.ac.uk/briefings_impact/ The researchers hosted an ESRC Festival of Social Science event, attended by policymakers and the third sector, participated in the Public Health England Special Interest Group on young peoples mental health, and presented at a Conservative Party roundtable on youth mental health, and at the Public Health England (PHE) annual conference. To help communicate the distinction between mental health and well-being, the researchers translated complex statistical analysis into an infographic showing risk and protective factors at age 11. This was used in several contexts and by practitioners in public health, including PHE, the Department for Education and many local government and child mental health training programmes. Concrete policy impacts include decisions to increase children and young people's (CYP) mental health services capacity and changes to PHE strategies for tackling CYP mental health. For example, due to this work, PHE has expanded its focus from one that had previously been on mental health, to also include mental well-being. It also adopted the framework it uses to identify how to best support young people, by extending the range of multi-level and multi-setting risk and protective factors associated with mental health and wellbeing. This work has also framed discussion among policymakers at the Department for Education. The research based on MCS age 14 data highlighted for the first time the extent of mental ill-health among young people across the UK. Through widespread dissemination in the media, it was instrumental in bringing the scale of the issue to public consciousness. Coverage included front-page headlines and follow-up features in a variety of national newspapers, and high-profile interviews in the broadcast media. As NHS England’s National Mental Health Director stated to The Guardian in response to the research: “After decades in the shadows, children’s mental health is finally in the spotlight” 3. Attracting public attention to the wider issues surrounding the research. There was also extensive coverage for the findings on changes in mental health over time, and on the links between parental break-up and children’s mental health. For example: The Times -Quarter of girls are depressed at 14 in mental health crisis BBC News - Quarter of 14-year-old girls ‘have signs of depression’ The data linkage in this Agreement is expected to facilitate research that CLS anticipate is expected to be carried out on the effects of social or economic determinations of health, and environmental factors on the evolution of the wellbeing, health, and development of family members. This could be of direct benefit to the NHS and to community services interfacing with schools through informing policy to improve healthy lifestyles.

Benefits reported

Below are examples of existing publications using the MCS data benefiting public health. The first yielded benefit is the creation of the refreshed linked MCS/HES dataset which will include most recent data. Drinking in pregnancy In the age 3 survey, MCS cohort children completed activities to show which words they understood and spoke, and which colours, letters, numbers, shapes and objects they were familiar with. Parents were also asked about different aspects of children's behaviour, such as how well they got on with other children and how active they were. Research using MCS survey data have found that children whose mothers drank heavily while they were pregnant were more likely to have behaviour problems at age 3 than those whose mothers didn’t drink or drank lightly. On average they also did less well in the different activities, although lots of other factors are also important too. Smoking in pregnancy Several studies based on MCS have looked at how smoking during pregnancy relates to children’s development. One group of researchers found that babies with mothers who smoked at any point while they were pregnant weighed on average 146 grams less when they were born (around the weight of a smartphone) than babies with mums who did not smoke. Overall, the more cigarettes a mother smoked a day, the less her baby weighed at birth. Babies with mothers whose partners smoked around them while they were pregnant also weighed on average 36 grams less (about the weight of a chocolate bar) than those with mothers who were not exposed to smoke. Breastfeeding and child health An influential study found that babies who were breastfed in the first months of their lives were less likely to go to hospital for diarrhoea or respiratory problems, such as infections and pneumonia. The researchers estimated that half of hospital stays for diarrhoea, and a quarter of stays for respiratory problems, could be prevented every month if all babies in the UK were fed entirely on breast milk for at least six months. Breastfeeding and child development Between ages 3 and 7 MCS children took part in a range of activities to show which words they knew and the patterns they could identify in shapes and images. Studies have found that children who were breastfed tended to do better in these exercises and to have less behaviour problems. Research has also suggested that there is a relationship between breastfeeding and young children’s ability to coordinate the movements of their arms and legs and to reach milestones such as standing up for the first time and taking their first steps.

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Objective for processing

This Data Sharing Agreement permits the retention and reuse of data that was previously supplied to University College London under earlier versions of this Agreement, for the purposes described. [49 paragraphs unchanged]

Processing activities

No new data will be supplied under this version of the Data Sharing Agreement. The following describes data flows which took place under previous versions of this Agreement. Continuing use of the data within the UKDS (as described below) is permitted under this Agreement. [35 paragraphs unchanged] c) CLS DAC will publish the information about any data dissemination on the NHS Digital release register, including the name of the organisation to which data was provided, purpose (summary of the project) and what data was released. (NB. If CLS DAC doesn't approve the project, no data will be disseminated). [8 paragraphs unchanged] All organisations party to this agreement Agreement must comply with the Data Sharing Framework Contract requirements, including those regarding [5 words unchanged] that use) by 'Personnel' (as defined within the Data Sharing Framework Contract ie: - i.e. employees, agents and contractors of the Data Recipient who may have access to that data).

Unchanged: Expected output, Expected measurable benefits, Benefits reported.