Centre for Longitudinal Studies Next Steps Data Linkage: Next Steps Age 25 Study

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Datasets: + HES-ID to MPS-ID HES Accident and Emergency; + HES-ID to MPS-ID HES Admitted Patient Care; + HES-ID to MPS-ID HES Outpatients

Objective for processing

[13 paragraphs unchanged] Linking health data from Hospital Episodes Statistics (HES)/Emergency (HES) and Emergency Care Data Set (ECDS) to the Next Steps survey data has greatly [54 words unchanged] diet and exercise, which are all documented as part of the study. [14 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 Next Steps data to the research community via the UK Data Service (UKDS) Secure Lab under sublicensing agreements subject to the following access arrangements. [1 paragraph unchanged] Access to the data via the UKDS will only be granted to third party third-party researchers who meet the following requirements: [18 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 Next Steps study using the study ID. [4 paragraphs unchanged] 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. [6 paragraphs unchanged] CLS does not link HES/ECDS the data received to any other dataset. However, when a researcher accesses the pseudonymised data [63 words unchanged] and will only be permitted if CLS DAC approves the project proposal. [1 paragraph unchanged] UCL only request data for those individuals who have given consent to [16 words unchanged] 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- [5 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 Next Steps- HES/ ECDS dataset. The HES/ ECDS 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 second output will be a methodological paper titled : Examining the linkage quality and sample representativeness of the linked Next Steps Study'. In this paper, researchers will examine the quality of the linkage in terms of the associations between key cohort members sociodemographic characteristics and successful linkage, and compare the levels of successful linkage within strata of Next Steps 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). 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. This is planned to be published by the end of 2024. The target journals for publication are : CLS at UCL actively promotes the use of their data among the research community through publications and events (e.g. training and workshops on each data set to help researchers better use the data), as well as providing extensive documentation, guidance on the use of the data and so ultimately benefit health and social care. 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 second output will be a methodological paper titled: 'Examining the linkage quality and sample representativeness of the linked Next Steps Study'. In this paper, researchers will examine the quality of the linkage in terms of the associations between key cohort members sociodemographic characteristics and successful linkage, and compare the levels of successful linkage within strata of Next Steps 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). This is planned to be published by the end of 2024. The target journals for publication are: [3 paragraphs unchanged] The methodological project above mentioned is currently being was carried out for CLSs 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 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 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 can be published during 2023 found here: https://cls.ucl.ac.uk/wp-content/uploads/2017/02/Examining-the-quality-and-sample-representativeness-of-linkedsurvey-and-administrative-data-CLS-Working-Paper-2022-5.pdf CLS has not yet published any methodological papers reviewing the linkage as promised in previous versions of this DSA. CLS expected to carry out these methodological and research assessments two/three years after the approval of this extension. This is because CLS have a policy of not using data internally for research when not available to external users and the original approval did not allow CLS to share the data with external users. Thus, CLS have focused on getting the necessary permission for sub-licencing the data. [17 paragraphs unchanged] A further application was received for a project titled: 'Understanding social transitions in emerging adulthood and pathways to later health outcomes'. [1 paragraph unchanged] CLS actively promotes the use of their data among the research community through publications and events, as well as providing extensive documentation, guidance, training and workshops on each data set to help researchers better use the data and so ultimately benefit health and social care. CLS has recently delivered a webinar to introduce this dataset to researchers and hope to start receiving more applications soon.

Expected measurable benefits

Benefits from the linked data- The linked Next Steps/HES dataset received under previous versions of this agreement is now available for researchers to use for research that could potentially [23 words unchanged] evidence of how this rich dataset can be used to benefit society. [39 paragraphs unchanged]

Benefits reported

No Yielded Benefits can yet be evidenced however UCL are looking to recognise similar yielded benefits as per the Millennium Cohort detail provided in expected benefits. The first yielded benefit is the creation of the refreshed linked Next Steps/HES dataset which will include most recent data. The dataset, which covers up to the year 2017 is now available for researchers to use via the UKDS. A link to the dataset is provided https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=8681 CLS has produced an Next Steps/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/8681/mrdoc/pdf/nextsteps_hes_user_guide_v1.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 and accessed for research under previous version of this agreement, however, so far 3 projects are accessing this linked data for research on health and we hope that some of these will result in successful yielded benefits. MARCH 2024 COMPLIANCE REPORT UPDATE First Output: The first output is the Next Steps /HES dataset which is now available to the research community. https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=8681 And the creation of the Next Steps/HES user guide. This document provides researchers with a complete guide to the linked data and information on the application process. 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- “Socioeconomic inequalities in perinatal and maternal health care access”. In this paper the researcher will investigate the socioeconomic health inequalities in children’s health and access to maternal healthcare. The overall aim of this article is to study the determinants of perinatal and maternal adverse outcomes, with a specific focus on the interaction between socioeconomic status (SES) and health inequity in early life. Project 2- “Analysis of Mental Health in Young People with Linked Data”- In this research project, researchers will investigate whether mental health services are reaching those most in need. This project has the potential to transform how services are targeted. Project 3- “Young people’s barriers to mental health services” On any given day in the United Kingdom 28.5% of children/young people aged 5 to 19 experience mental health problems. Only one in four of these children/young people receive formal support for these problems. There is a lack of knowledge of what happens to those young people not receiving mental health services. Mental health problems have been shown to limit economic, vocational, and social functioning and international studies have found that 50 to 70% of young people who receive services for their mental health problems continue to experience these problems in adulthood. In this current study researchers would like to explore the barriers experienced by young people in obtaining mental health services. Their aim is to use a developmental epidemiological perspective to: a) Explore characteristics (demographic, onset/development/progression mental health problems, environment) of those young people not receiving professional services for their mental health problems and determine if they have access to informal support. b) Examine resilience of young people not receiving mental health services for their problems during unpredictable challenging times (COVID pandemic) c) Employ a statistical technique that is novel to the field of mental health research to adjust for missing data (Missing-Not-At-Random – NMAR modelling).

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Objective for processing

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. CLS manages a portfolio of birth cohort studies which includes: The National Child Development Study 1958, The British Cohort Study 1970, The Millennium Cohort Study 2000 and Next Steps. The Centre for Longitudinal Studies (CLS) at University College London (UCL) requires access to NHS England data for the purpose of the Next Steps study. Next Steps, previously known as the Longitudinal Study of Young People in England (LSYPE), follows the lives of around 16,000 people in England born in 1989-90. This Data Sharing Agreement covers data access granted to UCL for the purpose of the Next Steps study. The study began in 2004 when the cohort members were aged 14, with an original sample of 15,770 people. Cohort members were surveyed annually until 2010, and the next sweep* after this was when they were aged 25, in 2015-16. Next Steps, previously known as the Longitudinal Study of Young People in England (LSYPE), follows the lives of around 16,000 people in England born in 1989-90. *The term ‘sweep’ is used to refer to a round of data collection in the longitudinal study. The study began in 2004 when the cohort members were aged 14, with an original sample of 15,770 people. Cohort members were surveyed annually until 2010, and the next sweep after this was when they were aged 25, in 2015-16. [1 paragraph unchanged] The Next Steps data has also been linked to National Pupil Database (NPD) records, which include the cohort members’ individual scores at Key Stage 2, 3 and 4 and more administrative linkages are planned (for example: Higher Education Statistics Agency, The Universities and Colleges Admissions Service, Department for Work and Pensions). This Data Sharing Agreement (DSA) sets out three distinct elements for which relevant information is subsequently given for each: The information collected maps participants’ journeys through education and transitions into adulthood and the labour market. 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. Next Steps is the largest and most detailed research study of its kind trying to understand the changing experiences of this generation. As such, Next Steps has already been highly valuable in informing policy decisions and in enhancing understanding of how specific Government policies can influence and shape the lives of young people. The following NHS England data will be accessed, During the 2015/16 survey, CLS obtained informed consent from cohort members for their health data to be linked to the data collected in the study. In total consent was obtained from approximately 4,941 cohort members who are the subject of the data linkage and onward sharing (sub-licensing model) detailed in this Agreement. • Hospital Episode Statistics Linking health data from Hospital Episodes Statistics (HES)/Emergency Care Data Set (ECDS) to the Next Steps survey data has greatly increased the possibilities for using the cohort to study how health outcomes impact on 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. 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. o Admitted Patient Care o Accident & Emergency o Critical Care o Outpatients • Emergency Care Data Set (ECDS) Linking health data from Hospital Episodes Statistics (HES)/Emergency Care Data Set (ECDS) to the Next Steps survey data has greatly increased the possibilities for using the cohort to study how health outcomes impact on 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. 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. [1 paragraph unchanged] The CLS’s aims are to: The level of data required is identifiable - necessary to enable linkage of the data with data collected from other sources, including the participants themselves. 1. Validate and improve the quality of the cohort data The data will be minimised as follows: 2. Produce methodological papers describing the quality of the data and its benefit to health and social care - Limited to a study cohort of 4,941 individuals who consented to participate 3. Develop and create a useful and rich HES/ECDS linked Next Steps dataset 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. 4. Advance learning in the research community by providing access to the linked NHS Digital HES and ECDS / Next Steps data to the research community via the UK Data Service (UKDS) Secure Lab, through a sub-licensing agreement agreed between CLS and NHS Digital. Access will be restricted to CLS researchers who meet the following requirements: The CLS does not use the data for its own research purposes outside of the above aims. Researchers, including employees of UCL, who want to use the matched data must be registered with the UK Data Service. To access the data, researchers must also apply to an independent committee that ensures that the information is used responsibly and safely. Researchers will only be given permission to use the data if they present a strong scientific case and explain the potential impact of the research and its wider value to society. i. The researcher must be substantively employed in the CLS by UCL; The UKDS is funded by the Economic and Social Research Council (ESRC) with contributions from the University of Essex, the University of Manchester and the Joint Information Systems Committee (Jisc*). ii. The researcher must be registered with the UKDS; *Jisc is a United Kingdom not-for-profit company whose role is to support post-16 and higher education, and research, by providing relevant and useful advice, digital resources and network and technology services, while researching and developing new technologies and ways of working. iii. The researcher must have completed NHS England’s Data Security Awareness course; The UKDS provides access to high-quality data to meet the data needs of researchers, students and teachers from all sectors including academia and central and local government. iv. 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; The UKDS is based at, and hosted by, the University of Essex. The University of Essex are therefore a data processor of the data under this Agreement. Only substantive employees of the University of Essex who are permitted to work at the UKDS will process the data. Should any substantively employed researchers from University of Essex wish to use the UKDS data for research purposes, they will be required to apply via the same process as other researchers from other organisations. v. 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). In order to apply for access to the data, applicants will need to submit a Research proposal application form to the UKDS and this is shared with the CLS. In this, applicants need to explain how their proposed use of the data will provide a public benefit and specifically benefits to healthcare provision, adult social care or the promotion of health. CLS will not provide data access to commercial organisations for research for commercial purposes. Applicants will need to be accredited researchers or agree to undertake training and become accredited, prior to accessing the data. Additionally, applicant’s organisation will need to provide evidence that they have IG and security assurances in place. Members of the CLS DAC will review and decide if the evidence provided satisfy the criteria requirements. The level of data required is pseudonymised. If a request is approved, the applicant (the licensee) and their organisations will have to sign two agreements: one with the UKDS and another (a sublicense agreement) with CLS. In both cases the licensee will have to agree to the terms stated in the Confidentiality Section of the CLS 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 users whose data they will receive. The data will be minimised to variables and potentially cases relevant to the purpose. 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. 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 Next Steps data to the research community via the UK Data Service (UKDS) Secure Lab under sublicensing agreements subject to the following access arrangements. To ensure security of the linked information, shared with UCL by NHS Digital, and subsequently shared by UCL with the UKDS, where data could be accessed by approved researchers in a Secure Lab, the following controls are employed at the different steps of the process of depositing, approving and sharing of the linked information: With the exception of individuals substantively employed by UCL in the CLS, all other access will be via the UKDS only. • This Data Sharing Agreement between NHS Digital and UCL permits UCL to onwardly share linked HES/ECDS and CLS information under a “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. Access to the data via the UKDS will only be granted to third party researchers who meet the following requirements: • An agreement between UCL (as a data controller) and UKDS (as a data processor), which outlines the terms and conditions under which the linked data can be accessed via the UKDS Secure Lab. i. The researcher must be registered with the UKDS; • 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. ii. The researcher must successfully apply for approval by the CLS DAC via the process outlined below. • An Agreement between 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 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 that 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. 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. [1 paragraph unchanged] The data held at UCL will be deleted 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. Disclosure control checks are carried before any research publication. Under the “Sub-licensing model”, NHS Digital shares data with UCL, which is 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 The data sharing controls in place between NHS Digital England and UCL are replicated between UCL and the other organisations. UCL, which [13 words unchanged] 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 Digital England and UCL. It also contains 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 UCL will deposit the linked data with UK Data Service, which 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 CLS, as outlined in this document. NHS Digital will retain the ability to directly audit UKDS’s compliance with the outlined and agreed data access arrangements. There will be no charge applied to licenses supplied by UCL. The anticipated volume / number of licences is 1-2 sub-licences per month. 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. UCL does not charge researchers for data access under sub-license agreements. 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. In this sharing model of the linked data, UCL will be the sole data controller, determining the purposes for which and the manner in which the linked data are processed. The UKDS will be the data processor, as they will be processing the data on behalf of CLS. 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. [1 paragraph unchanged] UCL’s 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 processes 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, CLS 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 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. The CLS 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. UCL will not provide data access to commercial organisations for research or for commercial purposes. In the event that a researcher who is employed by UCL applies for data access via the process outlined above, it would not be appropriate for the individual to enter into a sub-license agreement with UCL. In place of the sublicense agreement, the individual would enter into a Data Access Agreement. Like the sublicense agreement, this would define the purposes for which the data will be used. UCL is the controller as the organisation responsible for ensuring that the data will only be processed for the purpose described above. The data disseminated to UCL will be accessed by substantive employees of UCL who will work on the data to make it research ready, will pseudonymise the data and deposit it at the UKDS for researchers applying to use for specific projects. 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 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 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. Amazon Web Services (AWS) is a processor acting under the instructions of UCL. AWS’ role is limited to secure back-up 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. The UKDS is funded by the Economic and Social Research Council (ESRC) with contributions from the University of Essex, the University of Manchester and Jisc (Jisc is a United Kingdom not-for-profit company whose role is to support post-16 and higher education, and research, by providing relevant and useful advice, digital resources and network and technology services, while researching and developing new technologies and ways of working). The UKDS provides access to high quality data to meet the data needs of researchers, students and teachers from all sectors including academia and central and local government

Processing activities

1. The CLS team at UCL 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). 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. 2. NHS Digital link the identifying details to HES/ECDS data. NHS Digital provide the linked HES/ECDS records to the CLS team at UCL including the study ID but no other identifying details. 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. 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 Next Steps study using the study ID. 3. CLS 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 Next Steps 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 used these data to create an analysis file, which do 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 Next Steps survey data with data from hospital statistics in order to compare and validate the data collected in CLS surveys. 5. CLS 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 compare Next Steps 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). 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. 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. The data subjects' identifying details are held separately from attribute characteristics. HES/ECDS data is not be re-linked to the identifying data which is held separately from the survey responses. Re-identification would 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. The process of accessing the linked data via the UKDS Service Secure Lab include the following steps: 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. • Registration with the UKDS Service. Personnel are prohibited from downloading or copying data to local devices. • Submission of an application, including an ‘Accredited Researcher application form’ and ‘Research proposal’. The data will not leave the UK at any time. • Screening of application by UKDS for completeness. 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. Once a researcher has registered and UKDS has screened / approved the application: All personnel accessing the data have been appropriately trained in data protection and confidentiality. 1) UKDS sends project proposal (researcher application forms) to CLS-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). 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. 2) CLS-UCL sends the CLS License Agreement for Linked NHS Digital data 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. 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. 3) Researcher/their organisation representative will send the CLS License Agreement for Linked NHS Digital completed and signed back to CLS-UCL. 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- 4) CLS-UCL will: · Have asked CLS to withdraw their consent to health data linkage a) check the organisational Information Governance and security assurance evidence provided as per Section 15 Organisational Security Assurance of the CLS Licence agreement · Have asked CLS to delete their data b) send the project for CLS DAC approval. The file will only contain details of those who consented to their health data being linked to Next Steps study data and have not subsequently withdrawn their consent or requested that their data be deleted. 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. 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. 6) CLS DAC will assess both documents (UKDS project proposal + CLS Licence agreement) and make a decision to approve, not approve or require further information. Should an application be rejected, a researcher can apply again with a revised application. 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. 7) In the CLS 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. 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. 8) Once CLS DAC approves the project: a) CLS will inform UKDS that project has been approved. b) CLS representative should sign the CLS 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). c) CLS DAC will provide information about any data dissemination to NHS Digital, 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). 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 UK Data Service (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) University College London will inform NHS Digital as to who they have issued sub-licences to, in a format agreed with NHS Digital. 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 be based at a UK institution or an ESRC-funded research centre and be an ESRC Accredited Researcher. PhD and research students can request access but must apply jointly with their supervisors from established organisations. This would allow researchers from other organisations to apply (e.g NHS Digital researchers willing to use the linked data). [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. The UK Data Service 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 several 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. UKDS DATA ACCESS MECHANISMS: As an ESRC resource centre, CLS 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: • 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; • 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; • 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. Access mechanisms to NHS Digital HES/ECDS data linked to CLS cohort studies via the UKDS. The HES/ECDS data provided to CLS 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 disclosivity 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. It is therefore CLS’s intention to deposit these Tier 2 linked HES/ECDS data with the UK Data Service 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 an agreed between NHS Digital, CLS and UKDS onward sharing model. The UKDS’s ‘Controlled access to data’ specification is supplied to NHS Digital as part of this application amendment. The data provided will be pseudonymised and will be predominantly accessed via the UKDS secure lab. Downloading the data is not possible. In exceptional circumstances when determined by UCL, CLS will provide access to the pseudonymised data to CLS researchers via the UCL Data Safe Haven. Researchers accessing the data either via the UKDS or the UCL Data Safe Haven may use the Survey/HES/ECDS linked data in combination with other pseudonymised datasets. For example, the survey has also been linked to education data which can be a richer resource combined with the health data. The researcher will need to describe in detail if they wish to use the data in combination with other datasets, access will only be given if the DAC approves the project proposal. 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

The first output, the creation of the linked Next Steps/HES dataset, is now available for researchers to apply to access. The most recent HES data requested in this application will refresh this already rich linked dataset. Following the data quality and validation work, the first output will be the creation of the linked Next Steps- HES/ ECDS dataset. The HES/ ECDS data will add an important layer to this already rich data as well as provide the means for data quality checking. CLS has not yet sub-licensed the available Next Steps/HES data as CLS only recently got permission for sub-licensing this data. CLS has recently delivered a webinar to introduce this dataset to researchers and hope to start receiving applications soon. A first application to use the data is currently in progress, details provided below: The second output will be a methodological paper titled : Examining the linkage quality and sample representativeness of the linked Next Steps Study'. In this paper, researchers will examine the quality of the linkage in terms of the associations between key cohort members sociodemographic characteristics and successful linkage, and compare the levels of successful linkage within strata of Next Steps 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). Project Title: 'Linkage of National Longitudinal Cohort Studies and Administrative Data: A Mutually Beneficial Arrangement' This is planned to be published by the end of 2024. The target journals for publication are : This research will be addressing the following three methodological research questions, which will be directly reflected in the project work packages. 1) Journal for Survey Statistics and Methodology special issue on Recent Advances in Data Integration 1. How can linked administrative data aid the handling of missing cohort data? 2) Public Opinion Quarterly special issue on Augmenting Surveys with Paradata, Administrative Data, and Contextual Data͟ 2. How can linked cohort data improve our understanding of the quality of administrative data? 3) International Journal of Population Data Science 3. How can linked cohort data help address residual confounding in analyses of administrative data The methodological project above mentioned is currently being carried out for CLSs 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 The second output will be methodological papers published in peer reviewed journals reviewing the linkage and validating the data from the two data sources. These methodological assessments are expected to finish two years after obtaining the data. Outputs will contain only aggregate level data with small numbers suppressed in line with HES analysis guide. providers and users of other linked data resources to undertake and publish similarly thorough evaluations. This paper is expected to be published during 2023 CLS has not yet published any methodological papers reviewing the linkage. linkage as promised in previous versions of this DSA. CLS expects expected to carry out these methodological and research assessments two/three years after the [40 words unchanged] CLS have focused on getting the necessary permission for sub-licencing the data. There are currently two projects (sub-licences) using the data received under previous version of this DSA. The first project is Titled: ' Socioeconomic inequalities in perinatal and maternal health care access' In this paper, the researcher from Lancaster University is investigating the socioeconomic health inequalities in children’s health and access to maternal healthcare. The time from conception to the age of 2 is a critical time for development and can impact physical health, mental health and opportunity throughout life. Health inequalities can be observed in early life as unfavourable birth outcomes. preterm birth, with substantially higher rates among women from more deprived areas both in the UK (de Graaf et al. (2013)). Perinatal mental health problems carry a total economic and social long-term cost to society of about £8.1 billion for each one-year cohort of births in the UK. The researchers intend to disseminate the findings of this project in the following academic papers: 1. Present results in the internal research seminars in the Management Department as well as the Faculty of Medicine and Health Research at the Lancaster University. 2. Present results in Health Economics specialized conferences/workshops such as the Spanish Health Economics Association Meeting (Jornadas AES), the Evaluation Research for Health-Care Policies workshop (EvaluAES, AES), the Health Economics Study Group (HESG) meeting, the European Health Economics Conferences (EuHEA), the EuHEA PhD Student-Supervisor and Early Career Researcher Conference, the biannual meeting of the International Health Economics Association (iHEA). 3. Publish a non-technical summary of our work in “Blog Economía y Salud” and/or general interest portals such as “Nada Es gratis (NeG)”. 4. Submit the working papers for publication in professional journals. The second project is Titled: 'Analysis of Mental Health in Young People with Linked Data' There has been increasing policy focus on mental health in recent years given the rising prevalence of anxiety and psychological distress, and the COVID-19 pandemic has brought it into even sharper focus than ever before. In analysing whether mental health services are reaching those most in need, this project has the potential to transform how services are best targeted. The researchers intend to liaise closely with policymakers to ensure findings reach those designing and delivering services. In providing an in-depth understanding of the changes in mental health in young people over time, and exactly how services are meeting their needs, this work will enable policymakers to better plan and allocate healthcare resources for this generation. The impact of this research on society can be far reaching, with the potential to benefit the lives of several thousands of individuals and their families. The researchers plan the following outputs from the research: 1. Peer-reviewed academic journal articles conveying the research project and its findings. 2. Policy briefs based on journal articles, to help disseminate the findings in user-friendly ways; we expect to make use of infographics as part of these. This will include presentations and engagements with the Department for Health and Social Care (DHSC). 3. Engagement with All-Party Parliamentary Group (APPG); e.g., APPG on Young People’s Health, exploring the health needs of young people; APPG on Mental Health, focussing on all issues related to mental health. 4. Press releases and media engagement in collaboration with Centre for Longitudinal Studies communications team. 5. Engagement (e.g., presentation) with a charity focussing on adolescent mental health (e.g., The Children’s Society). 6. Conference presentations (UK) x2 – NHS Annual Conference ; Academic conference [1 paragraph unchanged] CLS actively promotes the use of their data among the research community [21 words unchanged] better use the data and so ultimately benefit health and social care. CLS has recently delivered a webinar to introduce this dataset to researchers and hope to start receiving more applications soon.

Expected measurable benefits

The information provided by cohort members provides valuable evidence for the research and policy community about the cohort’s transitions out of education and into early adult life. To enhance the research resource for secondary users, a fully documented, anonymised dataset has been archived with the UK Data Service in May 2017. Benefits from the linked data- The linked Next Steps/HES dataset 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 two projects listed under the 'Outputs section' are evidence of how this rich dataset can be used to benefit society. Next Steps Age 25 and subsequent age 31 survey data is expected to enrich the already deposited data for the cohort (waves 1 to 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. Benefits from projects currently accessing the data as stated in their project proposal: Project Title : 'Analysis of Mental Health in Young People with Linked Data' With mental health among young people of major public health and societal concern, it is more vital than ever to understand changes in mental health in young people over time, to enable policymakers to better plan and allocate healthcare resources for this generation of young people. The proposed research expects to gain a better understanding how self-reported mental health among young people in adolescence (at age 17) relates to their subsequent interactions with the health service through A&E admissions in hospital. Further, through this research researchers will gain an understanding of how self-reported self-harm in the mid-twenties (at age 25) is correlated with admission to A&E. Gaining these insights into the associations between self-reported mental health and interactions with hospital services will help to better understand the clinical needs of young people, particularly in relation to mental health. If it is the case that young people with poorer self-reported mental health have a greater association with A&E admissions, for example, this would underline the need for targeted interventions earlier in life, to provide timely support to young people when it is needed and reduce the burden on the healthcare system later in life. Project Title: 'Socioeconomic inequalities in perinatal and maternal health care access' This research aims to estimate the socio-economic health inequalities in children health and maternal health care access. Identifying the population groups with more risk of experiencing worse birth outcomes or lower perinatal health care use rates will help to provide a more equitable health care access from the first stages of life. Then, policymakers will be able to implement policies to mitigate health inequalities in early life, which will reduce the health gaps between the most deprived individuals and the less ones later in life. This might also help to reduce the social care used by most deprived individuals since having a better health status from the first stage in life improves education levels, which implies an increase in the probability of having a healthy lifestyle and more economic resources to access a better health care. Moreover, poor access to antenatal care or receipt of suboptimal care during the pregnancy could be a cause of risk of worse perinatal and maternal health. Investigating the associations between socioeconomic position and worse perinatal and maternal health or risk of being diagnosed with a disease during childhood is an important component of efforts to advance knowledge about health prevention and a component of broader strategies to interrupt the transgenerational cycle of ill-health. This research topic is an important area of investigation since it could be a powerful tool for identifying population-based risk factors and health care policies that contribute to perinatal aetiology and thereby prevent worse perinatal and maternal health for the benefit of all women. Comparing outcomes between social groups might illustrate the poorer health associated with socioeconomic disadvantage and the outcomes achieved in the absence of these inequalities. Having reliable indicators for measuring social inequalities in perinatal and children health enables target-setting for health policies, performance benchmarking, and trends over time. In this study, the researcher sought to assess the magnitude of social inequalities in perinatal and children health and maternity health care use in the United Kingdom. Improving maternal health remains an important global health priority. The Sustainable Development Goals (SDGs) that replaced the Millennium Development Goals (MDGs) include maternal health and health care as overarching goals. This requires sufficient and sustainable efforts to remove various barriers to health care access and utilization. Health inequalities arising in the antenatal period need to be tackled from public policy and all public services. Policy-makers and public health service can contribute to reducing health inequalities by ensuring equal access to and quality of healthcare services, improving the assessment of health and social needs of pregnant women, promoting multidimensional care (nutrition, health education), and upholding the implementation of intervention measures with existing evidence, like healthy lifestyle choices (healthy diet, no smoking, control pre-pregnancy weight, etc.), with particular emphasis on the most vulnerable women. These public policies are beneficial to all the population with a deep legitimate interest in accessing them. Proper care during pregnancy requires the monitoring of common clinical variables and the knowledge of socioeconomic circumstances of pregnant women to attempt to change risky habits and promote self-care. In this study, the researcher will assess the inequalities in health and habits of the newborns due to their parents' social status. The main purpose to provide access to the linked Next Steps survey data with NHS England Health Episode Statistics (HES) is to enhance the research resource for secondary users. Linking HES data with the survey data greatly widens the value for 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 the NHS England. It provides an invaluable opportunity to better understand some of the social determinants of health. Next Steps offers invaluable information on social experiences though 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 survey- The information provided by cohort members provides valuable evidence for the research and policy community about the cohort’s transitions out of education and into early adult life. To enhance the research resource for secondary users, a fully documented, anonymised dataset has been archived with the UK Data Service in May 2017. Next Steps Age 25 Survey data has been deposited with the UKDS and the cohort members’ health is an important aspect in the Age 25 Sweep. Cohort members were asked a range of questions about their physical and emotional health and wellbeing and CLS is currently looking at initial findings on probable mental ill health at age 25 and its association with a number of potential risk factors. There is, however, a great deal more information about potential underlying determinants, in this and the earlier sweeps of Next Steps, available for researchers via the UKDS. Age 32 survey data is expected to enrich the already deposited data for the cohort (waves 1 to 8) 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] Next Steps Age 25 Survey data has been deposited with the UKDS and the cohort members’ health is an important aspect in the Age 25 Sweep. Cohort members were asked a range of questions about their physical and emotional health and wellbeing and CLS is currently looking at initial findings on probable mental ill health at age 25 and its association with a number of potential risk factors. There is, however, a great deal more information about potential underlying determinants, in this and the earlier sweeps of Next Steps, available for researchers via the UKDS. [21 paragraphs unchanged] The Next Steps data linkage in this Agreement DSA is expected to facilitate research that CLS anticipate is expected to be [38 words unchanged] community services interfacing with schools through informing policy to improve healthy lifestyles. [1 paragraph unchanged] Next Steps (formally known as the Longitudinal Study of Young People in England - LSYPE) data is a resource with great potential for research and policy community, [8 words unchanged] social determinants widens its potential value for health research and policy interventions. Researchers currently have access to the LSYPE data and can apply and carry out research utilising the established link to benefit health and social care. There are many examples of LSYPE data producing findings in research and being cited by researchers and government articles. Next Steps Age 25 survey broadens the information collected on health and well-being, including family relationships, employment, education and income, which is expected to add to the potential of the data and future research in the area of health. Amendment to include the sub-licence The main purpose to provide access to the linked Next Steps survey data with NHS Digital Health Episode Statistics (HES) is to enhance the research resource for secondary users. Linking HES data with the survey data greatly widens the value for 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 the NHS Digital. It provides an invaluable opportunity to better understand some of the social determinants of health. Next Steps offers invaluable information on social experiences though 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 our 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 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.

Benefits reported

Currently there have been no direct benefits to this study from processing the data under this DSA as the data has only been recently acquired. No Yielded Benefits can yet be evidenced however UCL are looking to recognise similar yielded benefits as per the Millennium Cohort detail provided in expected benefits. The CLS have already achieved demonstrable benefits using research and other data including adding outputs to the existing body of evidence that influences research and decision making. These demonstrable benefits have been listed in the above section and include the following: - adding to the existing body of evidence supporting various scientific publications; - research evidence used for government briefing papers; - attracting media coverage to the wider issues surrounding the research.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Datasets: + Emergency Care Data Set (ECDS)

Objective for processing

***TO CORRECT INVOICE 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. CLS manages a portfolio of birth cohort studies which includes: The National Child Development Study 1958, The British Cohort Study 1970, The Millennium Cohort Study 2000 and Next Steps. Previous iterations of this DSA have covered the dissemination of HES data as part of the Next Steps longitudinal study. Version 1 of this agreement was an amendment for the addition of a sub-licence to allow onward sharing of the linked HES data with the UK Data Services (UKDS) where data can be accessed by accredited researchers. Further details are outlined below: This Data Sharing Agreement covers data access granted to UCL for the purpose of the Next Steps study. 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. CLS manages three world-renowned birth cohort studies: The National Child Development Study 1958, The British Cohort Study 1970, and The Millennium Cohort Study 2000. CLS now have the Next Steps cohort in their portfolio. Next Steps, previously known as the Longitudinal Study of Young People in England (LSYPE), follows the lives of around 16,000 people in England born in 1989-90. Next Steps is a longitudinal study following the lives of 16,000 people born in 1989/90, originally sampled from schools in England at age 13/14 years and initially managed by the Department for Education. Next Steps participants were interviewed annually between 2004 and 2010 and again in 2015/16 to map their journeys through education and transitions into adulthood and the labour market. The study began in 2004 when the cohort members were aged 14, with an original sample of 15,770 people. Cohort members were surveyed annually until 2010, and the next sweep after this was when they were aged 25, in 2015-16. Next Steps is the largest and most detailed research study of its kind trying to understand the changing experiences of this generation. As such, Next Steps has already been highly valuable in informing policy decisions and in enhancing understanding of how specific Government policies can influence and shape the lives of young people. Next Steps data has also been widely used by academic researchers in the UK and elsewhere. Next Steps has collected information about cohort members’ education and employment, economic circumstances, family life, physical and emotional health and wellbeing, social participation and attitudes. During the 2015/16 survey, CLS obtained informed consent from cohort members for their health data to be linked to the data collected in the study. In total consent was obtained from approximately 4941 cohort members who are the subject of the data linkage and onward sharing (sub-licensing model) detailed in this application. The Next Steps data has also been linked to National Pupil Database (NPD) records, which include the cohort members’ individual scores at Key Stage 2, 3 and 4 and more administrative linkages are planned (for example: Higher Education Statistics Agency, The Universities and Colleges Admissions Service, Department for Work and Pensions). Linking health data from Hospital Episodes Statistics (HES) to the Next Steps survey data has greatly increased the possibilities for using the cohort to study how health outcomes impact on 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 lifestyles choices 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 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. The information collected maps participants’ journeys through education and transitions into adulthood and the labour market. 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 lifestyle choices. So, this offers an interesting methodological opportunity to validate the data collected in the survey and vice versa. Next Steps is the largest and most detailed research study of its kind trying to understand the changing experiences of this generation. As such, Next Steps has already been highly valuable in informing policy decisions and in enhancing understanding of how specific Government policies can influence and shape the lives of young people. The overall aim of the research is to: During the 2015/16 survey, CLS obtained informed consent from cohort members for their health data to be linked to the data collected in the study. In total consent was obtained from approximately 4,941 cohort members who are the subject of the data linkage and onward sharing (sub-licensing model) detailed in this Agreement. Linking health data from Hospital Episodes Statistics (HES)/Emergency Care Data Set (ECDS) to the Next Steps survey data has greatly increased the possibilities for using the cohort to study how health outcomes impact on 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. 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. 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 CLS’s aims are to: [2 paragraphs unchanged] 3. Develop and create a useful and rich HES HES/ECDS linked Next Steps dataset 4. Advance learning in the research community by providing access to the linked NHS Digital HES and ECDS / CLS Next Steps data to the research community via the UK Data Service (UKDS) Secure Lab, through a sub-licensing agreement agreed between CLS and NHS Digital. THE SUB-LICENCE: The CLS does not use the data for its own research purposes outside of the above aims. Researchers, including employees of UCL, who want to use the matched data must be registered with the UK Data Service. To access the data, researchers must also apply to an independent committee that ensures that the information is used responsibly and safely. Researchers will only be given permission to use the data if they present a strong scientific case and explain the potential impact of the research and its wider value to society. CLS are permitted to include onward sharing of the linked HES and CLS Next Steps 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”. The UKDS is funded by the Economic and Social Research Council (ESRC) with contributions from the University of Essex, the University of Manchester and the Joint Information Systems Committee (Jisc*). The UKDS is funded by the Economic and Social Research Council (ESRC) with contributions from the University of Essex, the University of Manchester and the Joint Information Systems Committee (Jisc) (Jisc *Jisc is a United Kingdom not-for-profit company whose role is to support post-16 [15 words unchanged] and technology services, while researching and developing new technologies and ways of working). The UKDS provides access to high-quality data to meet the data needs of researchers, students and teachers from all sectors including academia and central and local government. working. The UKDS is based at, and hosted by, the University of Essex. The University of Essex are therefore listed as a data processor and listed in the data processing and storage location sections. Only staff who are permitted to work at the UKDS will process the data (and are substantively employed by University of Essex) 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. The UKDS provides access to high-quality data to meet the data needs of researchers, students and teachers from all sectors including academia and central and local government. Under the “Sub-licensing model”, NHS Digital shares data with CLS, who are in turn licensed to share these data with other organisations, subject to agreed controls, scoped in this agreement between NHS Digital and CLS. In line with this onward sharing model, the data sharing controls in place between NHS Digital and CLS are replicated between CLS 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. The UKDS is based at, and hosted by, the University of Essex. The University of Essex are therefore a data processor of the data under this Agreement. Only substantive employees of the University of Essex who are permitted to work at the UKDS will process the data. Should any substantively employed researchers from University of Essex wish to use the UKDS data for research purposes, they will be required to apply via the same process as other researchers from other organisations. Under the sub-licensing model CLS will deposit the linked data with UK Data Service, 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 CLS, as outlined in this document. NHS Digital will retain the ability to directly audit UKDS’s compliance with the outlined and agreed data access arrangements. In order to apply for access to the data, applicants will need to submit a Research proposal application form to the UKDS and this is shared with the CLS. In this, applicants need to explain how their proposed use of the data will provide a public benefit and specifically benefits to healthcare provision, adult social care or the promotion of health. CLS will not provide data access to commercial organisations for research for commercial purposes. Applicants will need to be accredited researchers or agree to undertake training and become accredited, prior to accessing the data. Additionally, applicant’s organisation will need to provide evidence that they have IG and security assurances in place. Members of the CLS DAC will review and decide if the evidence provided satisfy the criteria requirements. 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. If a request is approved, the applicant (the licensee) and their organisations will have to sign two agreements: one with the UKDS and another (a sublicense agreement) with CLS. In both cases the licensee will have to agree to the terms stated in the Confidentiality Section of the CLS 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 users whose data they will receive. There will be no charge applied to sub-licence. 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. The territory of use in the sub-licence will be the same or narrower than the territory of use stated in this DSA, namely England and Wales. To ensure security of the linked information, shared with UCL by NHS Digital, and subsequently shared by UCL with the UKDS, where data could be accessed by approved researchers in a Secure Lab, the following controls are employed at the different steps of the process of depositing, approving and sharing of the linked information: In this sharing model of the linked data, CLS will be a data controller, determining the purposes for which and the manner in which the linked data are processed. The UKDS will be the data processor, as they will be processing the data on behalf of CLS. 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. • This Data Sharing Agreement between NHS Digital and UCL permits UCL to onwardly share linked HES/ECDS and CLS information under a “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. 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. • An agreement between UCL (as a data controller) and UKDS (as a data processor), which outlines the terms and conditions under which the linked data can be accessed via the UKDS Secure Lab. ORGANISATIONAL AGREEMENTS CLS 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 CLS). Applicants (potential licencees) will need to show in Schedule 1 Section 18 (a) and (b) that the provision of the sub licencing will be in the public interest and that 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. CLS will not provide data access to commercial organisations for research for commercial purposes. Additionally, the CLS Licence agreement, Schedule 1 Section 18, 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 the 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, applicant’s organisation will need to provide evidence that they have IG and security assurances in place (covered in Schedule 1, Section 15 of the CLS Licence agreement). Members of the CLS Data Access Committee (DAC) will review and decide if the evidence provided satisfy the criteria requirements. Applicants (licencees) and their organisations will have to sign two agreements to obtain a sub-licence, one with the UKDS and another with CLS, in both cases the licencee will agree with the terms stated in the Confidentiality Section of the CLS 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 licencee agrees to adhere to these terms, including respecting the privacy of health services users data they will receive. Licencees 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 security of the linked information, shared with CLS by NHS Digital, and subsequently shared by CLS with the UKDS, where data could be accessed by approved researchers in a Secure Lab, CLS 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 CLS to onwardly share linked HES and CLS information under “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 CLS (as a data controller) and UKDS (as a data processor), which outlines the terms and conditions under which the linked data can be accessed via the UKDS Secure Lab. [3 paragraphs unchanged] The data held at CLS UCL will be deleted if the data sharing agreement between NHS Digital and CLS UCL were to cease. If it were to cease, the license agreement between CLS 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, CLS 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 pseudo-anonymised form (via a secure setting with appropriate safeguards). Under the “Sub-licensing model”, NHS Digital shares data with UCL, which is 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 contains 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. 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 CLS Licence agreement will require licencees 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. Under the sub-licensing model UCL will deposit the linked data with UK Data Service, which 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 CLS, as outlined in this document. NHS Digital will retain the ability to directly audit UKDS’s compliance with the outlined and agreed data access arrangements. The data disseminated to CLS will be accessed by substantive employees of UCL who will work on the data to make it research ready, will pseudo-anonymise the data and deposit it at the UKDS for researchers applying to use for specific projects. The anticipated volume / number of licences is 1-2 sub-licences per month. UCL does not charge researchers for data access under sub-license agreements. In this sharing model of the linked data, UCL will be the sole data controller, determining the purposes for which and the manner in which the linked data are processed. The UKDS will be the data processor, as they will be processing the data on behalf of CLS. 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. The territory of use in the sub-licence will be the same or narrower than the territory of use stated in this DSA, namely the UK. UCL’s 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 processes 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, CLS 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 CLS 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. In the event that a researcher who is employed by UCL applies for data access via the process outlined above, it would not be appropriate for the individual to enter into a sub-license agreement with UCL. In place of the sublicense agreement, the individual would enter into a Data Access Agreement. Like the sublicense agreement, this would define the purposes for which the data will be used. The data disseminated to UCL will be accessed by substantive employees of UCL who will work on the data to make it research ready, will pseudonymise the data and deposit it at the UKDS for researchers applying to use for specific projects.

Processing activities

No new data is being requested and no further data is being sent to NHS Digital under this version of the Agreement. The CLS team is based at UCL. 1. The CLS team at UCL 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). 1. CLS team have supplied 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). 2. NHS Digital link the identifying details to HES/ECDS data. NHS Digital provide the linked HES/ECDS records to the CLS team at UCL including the study ID but no other identifying details. 2. NHS Digital have linked the identifiable study data to HES data. NHS Digital have removed identifiers from linked dataset and returned the pseudonymised dataset 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. 3. CLS carried carry out validation of the administrative pseudonymised data received (linked HES HES/ECDS data) and combined the supplied administrative data with the information collected from the participant as part of the Next Steps study using the study ID. [2 paragraphs unchanged] 5. CLS created create derived variables that summarise study members’ hospitalisation and health histories (e.g. hospital [21 words unchanged] in order to compare and validate the data collected in CLS surveys. Identifiers are held separately from attribute characteristics. HES data is 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. 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. Addition of the sub-licence: The data subjects' identifying details are held separately from attribute characteristics. HES/ECDS data is not be re-linked to the identifying data which is held separately from the survey responses. Re-identification would 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. [17 paragraphs unchanged] c) CLS DAC will publish the provide information about any data dissemination on the to NHS Digital release register, Digital, including the name of the organisation to which data was provided, purpose [10 words unchanged] If CLS DAC doesn't approve the project, no data will be disseminated). [3 paragraphs unchanged] Note that any data accessed through the UKDS Secure Lab can only [61 words unchanged] is only available to researchers who are be based at a UK academic institution or an ESRC-funded research centre and be an ESRC Accredited Researcher. [5 words unchanged] request access but must apply jointly with their supervisors from established organisations. This would allow researchers from other organisations to apply (e.g NHS Digital researchers willing to use the linked data). [1 paragraph unchanged] UKDS SECURE DATA HANDLING PROCEDURES PROCEDURES: [2 paragraphs unchanged] UKDS DATA ACCESS MECHANISMS MECHANISMS: [4 paragraphs unchanged] Access mechanisms to NHS Digital HES HES/ECDS data linked to CLS cohort studies via the UKDS UKDS. The HES HES/ECDS data provided to CLS by NHS Digital, which are linked to the [44 words unchanged] this processing, the final health datasets have been classified under Tier 2. It is therefore CLS’s intention to deposit these Tier 2 linked HES HES/ECDS data with the UK Data Service under the UKDS Secure Access, and [40 words unchanged] specification is supplied to NHS Digital as part of this application amendment. The data provided will be pseudo-anonymised pseudonymised and will be predominantly accessed only via the UKDS secure lab. Downloading the data is not possible. 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 ie: employees, agents and contractors of the Data Recipient who may have access to that data). In exceptional circumstances when determined by UCL, CLS will provide access to the pseudonymised data to CLS researchers via the UCL Data Safe Haven. Researchers accessing the data either via the UKDS or the UCL Data Safe Haven may use the Survey/HES/ECDS linked data in combination with other pseudonymised datasets. For example, the survey has also been linked to education data which can be a richer resource combined with the health data. The researcher will need to describe in detail if they wish to use the data in combination with other datasets, access will only be given if the DAC approves the project proposal. 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 The first output will be output, the creation of the linked Next Steps/HES dataset. dataset, is now available for researchers to apply to access. The most recent HES data requested in this application will add an important layer to refresh this already rich data as well as providing the means for data quality checking. linked dataset. CLS has not yet sub-licensed the available Next Steps/HES data as CLS only recently got permission for sub-licensing this data. CLS has recently delivered a webinar to introduce this dataset to researchers and hope to start receiving applications soon. A first application to use the data is currently in progress, details provided below: Project Title: 'Linkage of National Longitudinal Cohort Studies and Administrative Data: A Mutually Beneficial Arrangement' This research will be addressing the following three methodological research questions, which will be directly reflected in the project work packages. 1. How can linked administrative data aid the handling of missing cohort data? 2. How can linked cohort data improve our understanding of the quality of administrative data? 3. How can linked cohort data help address residual confounding in analyses of administrative data [1 paragraph unchanged] CLS has not yet published any methodological papers reviewing the linkage. CLS expects to carry out these methodological and research assessments two/three years after the approval of this extension. This is because CLS have a policy of not using data internally for research when not available to external users and the original approval did not allow CLS to share the data with external users. Thus, CLS have focused on getting the necessary permission for sub-licencing the data. [2 paragraphs unchanged]

Expected measurable benefits

Next Steps surveys include questions relating to health outcomes and hospitalisations. CLS will use these responses to compare with their data available on HES 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 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 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. It is difficult to predict in advance the type of research question that might be put forward. Below are examples of existing publications using Longitudinal Study of Young People in England (LSYPE) data benefiting public health. Calderwood, L., and Sanchez, C. (2016). Next Steps (formerly known as the Longitudinal Study of Young People in England). Open Health Data, 4(1), e2 Hale, D., and Viner, R. (2016). The correlates and course of multiple health risk behaviour in adolescence. BMC Public Health. 2016 May 31; 16: 458. doi: 10.1186/s12889-016-3120-z. Semlyen, J., King, M., Varney, J., and Hagger-Johnson, G. (2016). Sexual orientation and symptoms of common mental disorder or low wellbeing: combined meta-analysis of 12 UK population health surveys. BMC Psychiatry. 2016 Mar 24;16: 67. doi: 10.1186/s12888-016-0767-z. Symonds, J., Dietrich, J., Chow, A., and Salmela-Aro, K. (2016). Mental health improves after transition from comprehensive school to vocational education or employment in England: A national cohort study. Developmental Psychology, 52(4), 652-665 Chatzitheochari, S., Parsons, S., and Platt, l. (2015). Doubly Disadvantaged? Bullying Experiences among Disabled Children and Young People in England. Sociology, advance online access, 28 April 2015 Debell, D. (2015). Public Health for Children, Second Edition. London: CRC Press. Hale, D., and Viner, R. (2015). Health in adolescence influences educational attainments and life chances: longitudinal associations in the Longitudinal Study of Young People in England (LSYPE). Archives of Disease in Childhood, 100 (Suppl.3), A210-A211. Hatton, C., and Emerson, E. (2015). International Review of Research into Developmental Disabilities: Health Disparities and Intellectual Disabilities. London: Academic Press. Department for Education, TNS BMRB. (2015). Second Longitudinal Study of Young People in England: Wave 1, 2013: Secure Access. [Data collection]. UK Data Service. SN: 7838, http://dx.doi.org/10.5255/UKDA-SN-7838-1. Department for Education, NatCen Social Research (2013). First Longitudinal Study of Young People in England: Waves One to Seven, 2004-2010: Secure Access. [Data collection]. 2nd Edition. UK Data Service. SN: 7104, http://dx.doi.org/10.5255/UKDA-SN-7104-2. Next Steps (formally known as the Longitudinal Study of Young People in England - LSYPE) data is a resource with great potential for research and policy community, and the information collected on health and its social determinants widens its potential value for health research and policy interventions. Researchers currently have access to the LSYPE data and are able to apply and carry out research utilising the established link to benefit health and social care. Below are some examples of existing publications using LSYPE data (waves 1 to 7) benefiting public health. Hale and Viner (2015), for example, examine longitudinally the causal pathways from poor adolescent health to low academic attainment and unemployment in young adulthood, and make recommendations for policy interventions to focus on improving outcomes for unhealthy adolescents. Having a chronic condition, poor mental health and poor self-reported general health were assessed between ages 13 and 15. Outcome variables included poor academic performance (non-attainment of expected academic proficiency based on mandated school examinations) at age 16 and NEET status (not in education, employment or training) at age 19. The authors examined associations between health and subsequent outcomes, and conducted mediator analyses to assess the proportion of the association attributable to hypothesised mediators including school absences, classroom behaviour, truancy, social exclusion, health behaviours and psychological distress. The study revealed that poor mental and general health and long-term conditions predicted low educational attainment at age 16. Poor mental health and poor general health (but not long-term conditions) predicted unemployment. Social exclusion was a consistent mediating variable. Long-term absences mediated associations between general health and mental health and later outcomes whereas school behaviour, truancy and substance use were significant mediators for general health and mental health. Poor adolescent health disrupts educational and employment pathways. Due to the economic and social costs of educational underachievement and unemployment, policy interventions should focus on improving outcomes for unhealthy adolescents (Hale, D., and Viner, R. (2015). Health in adolescence influences educational attainments and life chances: longitudinal associations in the Longitudinal Study of Young People in England (LSYPE). Archives of Disease in Childhood, 100 (Suppl.3), A210-A211.). The same authors - Hale and Viner (2016) - examined the association between health risk behaviours (such as smoking, alcohol use, illicit drug use, delinquency and unsafe sexual behaviour) throughout adolescence (and at ages 14, 16, and 19) and identified common risk factors for multiple risk behaviour (involvement in two or more risk behaviours) in late adolescence (at age 19), drawing attention to policy focus on prevention of adolescence health risk behaviours. All early risk behaviours were found to be associated with other risk behaviours at age 19. A number of sociodemographic, interpersonal, school and family factors at age 14 predicted risk behaviour and multiple risk behaviour at age 19. Past risk behaviour being a strong predictor of age 19 risk behaviour with those involved in multiple risk behaviour in early adolescence being far more likely to be multiple risk-takers at age 19, while many involved in only one form of risk behaviour in mid-adolescence do no progress to multiple risk behaviour (Hale, D., and Viner, R. (2016). The correlates and course of multiple health risk behaviour in adolescence. BMC Public Health. 2016 May 31; 16: 458. doi: 10.1186/s12889-016-3120-z.). LSYPE data has also contributed to evidence on childhood disability. Chatzitheochari, Parsons and Platt (2015) enhanced the evidence on school bullying experience among disabled children, likely to have a strong negative impact on social and psychological later life outcomes. The authors studied the relationship between bullying victimisation and childhood disability, and revealed an independent association of disability with bullying victimisation, suggesting potential pathway to cumulative disability-related disadvantage, drawing attention to the school as a site of reproduction of social inequalities (Chatzitheochari, S., Parsons, S., and Platt, l. (2015). Doubly Disadvantaged? Bullying Experiences among Disabled Children and Young People in England. Sociology, advance online access, 28 April 2015). Semlyen, King, Varney, and Hagger-Johnson (2016) studied the association between sexual orientation identity and poor mental health and drew attention on LGB adults in UK and their higher prevalence of poor mental health and low well-being when compared to heterosexuals. They addressed the need of routine measurement of sexual orientation in health studies and administrative data in order to influence national and local policy development and service delivery. Their findings reiterate for local government, NHS providers and public health policy makers to consider how to address inequalities in mental health among these minority groups (Semlyen, J., King, M., Varney, J., and Hagger-Johnson, G. (2016). Sexual orientation and symptoms of common mental disorder or low wellbeing: combined meta-analysis of 12 UK population health surveys. BMC Psychiatry. 2016 Mar 24;16: 67. doi: 10.1186/s12888-016-0767-z.). Symonds et al. (2016) analysed mental health at the school to work transition. The authors examined how adolescents’ anxiety, depressive symptoms, and positive functioning developed as they transferred from comprehensive school to further education, employment or training, or became NEET (not in education, employment or training), at age 16 years. Controlling for childhood achievement, socioeconomic status, ethnicity, and gender, the authors found that NEET adolescents had the largest losses in mental health. This pattern was similar to adolescents staying on at school who had increased anxiety and depression, and decreased positive functioning, after transition. In comparison, adolescents transferring to full time work, apprenticeships or vocational college experienced gains in mental health (Symonds, J., Dietrich, J., Chow, A., and Salmela-Aro, K. (2016). Mental health improves after transition from comprehensive school to vocational education or employment in England: A national cohort study. Developmental Psychology, 52(4), 652-665). Next Steps Age 25 survey broadens the information collected on health and well-being, including family relationships, employment, education and income, which will add to the potential of the data and future research in the area of health. Amendment to include the sub-license The main purpose to provide access to the linked Next Steps survey data with NHS Digital Health Episode Statistics (HES) is to enhance the research resource for secondary users. Linking HES data with the survey data greatly widens the value for 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 the NHS Digital. It provides an invaluable opportunity to better understand some of the social determinants of health. Next Steps offers invaluable information on social experiences though 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 our application will allow the linked data to be used more widely in order to maximise societal benefit, while maintaining high levels of data security. 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 will benefit society?’, ‘How does the project provide a public benefit?’, ‘Contribution towards public policy or journal publications’). CLS will further require the applicant to describe the benefits of their intended research to health and social care. The expected measurable benefits from the original agreement: The study produces rich, longitudinal, policy-relevant data, currently unavailable elsewhere, for a large, representative sample of young adults. LSYPE data is widely used by policy makers to evaluate and develop policy and improve services for young people and also by academic researchers to chart and understand social change. [1 paragraph unchanged] Next Steps Age 25 and subsequent age 31 survey data will is expected to enrich the already deposited data for the cohort (waves 1 to 7) [43 words unchanged] to follow young people’s experiences over time to analyse later life outcomes. [2 paragraphs unchanged] Retaining contact details of non-respondents (to an annual mail-out) will enable the researcher to try and re-establish contact before the next wave of the longitudinal study (date to be confirmed) to be able to continue with the research. A further list clean will be carried out in the future in preparation to our next wave age 31, this will be subject to a further renewal of this Agreement. The CLS have already demonstrated yielded measurable benefits within the Health and Social care system with various studies to date. Whilst a single output is not expected to change healthcare policy or practice the variety of outputs that are expected are planned to add to the existing body of evidence supporting improvements to healthcare policy and practice in the long term. Using the Millennium Cohort Study (MCS), another existing study being researched at the CLS, as an example below are examples highlighting each point, which are expected to be replicated with 1. CLS researchers have already added to the existing body of evidence supporting various scientific publications. 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 educational attainment and mental health outcomes for children and young people. This policy announcement uniquely recognises young people’s 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 £12 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 wellbeing. 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 about 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 third sector, participated in the Public Health England Special Interest Group on young people’s 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 wellbeing, 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 wellbeing. It also adapted 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. Next Steps surveys include questions relating to health outcomes and hospitalisations. CLS is expected to use these responses to compare with their data available on HES to obtain a better understanding of relationship between self-reporting and administrative data. This is expected to be shared via methodological information which is expected to assess the data quality and comparability of two important data sources. This is expected to benefit research looking at Health and Social Care adding to the existing body of evidence used by policy makers and researchers to analyse and contribute toward implementation of healthcare policy and decision making. Next Steps (formally known as the Longitudinal Study of Young People in England - LSYPE) data is a resource with great potential for research and policy community, and the information collected on health and its social determinants widens its potential value for health research and policy interventions. Researchers currently have access to the LSYPE data and can apply and carry out research utilising the established link to benefit health and social care. There are many examples of LSYPE data producing findings in research and being cited by researchers and government articles. Next Steps Age 25 survey broadens the information collected on health and well-being, including family relationships, employment, education and income, which is expected to add to the potential of the data and future research in the area of health. Amendment to include the sub-licence The main purpose to provide access to the linked Next Steps survey data with NHS Digital Health Episode Statistics (HES) is to enhance the research resource for secondary users. Linking HES data with the survey data greatly widens the value for 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 the NHS Digital. It provides an invaluable opportunity to better understand some of the social determinants of health. Next Steps offers invaluable information on social experiences though 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 our 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 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.

Benefits reported

The age 25 survey data is already providing important research evidence on transitions out of education and into early adult life, informing a range of key interlinked policy questions relating to higher education, employment, housing and family formation, and health. Data from the age 25 survey was deposited at the UK Data Service in June 2017 and have already been downloaded for over 100 research projects in many disciplines including economics, education and sociology. Its’ influence and impact will grow over the next few years, as it is used for research and policy on a wide-range of different issues, and as the existing data is enhanced and augmented, particularly with linked administrative data. Currently there have been no direct benefits to this study from processing the data under this DSA as the data has only been recently acquired. Initial findings from the age 25 data, produced and published by CLS, have already contributed to political debate in relation to the labour market conditions for this generation, with reference to findings on the negative impact of zero hours contracts on health in Prime Ministers’ questions in July 2017. The CLS have already achieved demonstrable benefits using research and other data including adding outputs to the existing body of evidence that influences research and decision making. These demonstrable benefits have been listed in the above section and include the following: Below are some examples of existing publications using LSYPE data (waves 1 to 7) - adding to the existing body of evidence supporting various scientific publications; BAINES, S, EMERSON, E, ROBERTSON, J and HATTON, C. (2018) Sexual activity and sexual health among young adults with and without mild/moderate intellectual disability. BMC Public Health, 18(1), 667. - research evidence used for government briefing papers; ROBERTSON, J, EMERSON, E, BAINES, S and HATTON, C. (2018) Self-reported smoking, alcohol and drug use among adolescents and young adults with and without mild to moderate intellectual disability. Journal of Intellectual & Developmental Disability, published online, 23 April 2018. - attracting media coverage to the wider issues surrounding the research. HATTON, C, EMERSON, E, ROBERTSON, J and BAINES, S. (2018) The mental health of adolescents with and without mild/moderate intellectual disabilities in England: Secondary analysis of a longitudinal cohort study. Journal of Applied Research in Intellectual Disabilities, 31(5), 768-777. ROBERTSON, J, EMERSON, E, BAINES, S and HATTON, C. (2018) Self-Reported Participation in Sport/Exercise Among Adolescents and Young Adults With and Without Mild to Moderate Intellectual Disability. Journal of Physical Activity and Health, 15(4), 247-254. BOWE, A. (2017) The cultural fairness of the 12-item General Health Questionnaire among diverse adolescents. Psychological Assessment, 29(1), 87-97. BOURNE, M, BUKODI, E, BETTHAEUSER, B and GOLDTHORPE, J.H. (2018) ‘Persistence of the social’: The role of cognitive ability in mediating the effects of social origins on educational attainment in Britain. Research in Social Stratification and Mobility, 58(Dec 2018), 11-21. I, S, THEOCHARAKI, F, SULLIVAN, A and PLOUBIDIS, G.B. (2018) Social determinants of health in population-based cohort studies, UK: a systematic review. European Journal of Public Health, 28(Suppl.4), cky214.063. • ALCOTT, B. (2017) Does Teacher Encouragement Influence Students’ Educational Progress? A Propensity-Score Matching Analysis. Research in Higher Education, 58(7), 773–804. • ANDERS, J. (2017) The influence of socioeconomic status on changes in young people’s expectations of applying to university. Oxford Review of Education, 43(4), 381-401. • ANDERS, J and DORSETT, R. (2017) What young English people do once they reach school-leaving age: A cross-cohort comparison for the last 30 years. Longitudinal and Life Course Studies, 8(1), 75-103. • ANDERS, J, HENDERSON, M, MOULTON, V and SULLIVAN, A. (2017) Incentivising specific combinations of subjects: does it make any difference to university access? CLS Working Paper 2017/11. London: Centre for Longitudinal Studies. • ANDERS, J, HENDERSON, M, MOULTON, V and SULLIVAN, A. (2017) A note on subject choice at age 14 and socio-economic inequality in access to university. CLS Working Paper 2017/10. • ANDERS, J.D, MOULTON, V, HENDERSON, M and SULLIVAN, A. (2018) The role of schools in explaining individuals’ subject choices at age 14. Oxford Review of Education, 44(1), 75-93. • BAINES, S, EMERSON, E, ROBERTSON, J and HATTON, C. (2018) Sexual activity and sexual health among young adults with and without mild/moderate intellectual disability. BMC Public Health, 18(1), 667. • BELLFIELD, C and VAN DER ERVE, L. (2018) The impact of higher education on the living standards of female graduates. IFS Working Paper W18/25. London: Institute for Fiscal Studies. • BOURNE, M, BUKODI, E, BETTHAEUSER, B and GOLDTHORPE, J.H. (2018) ‘Persistence of the social’: The role of cognitive ability in mediating the effects of social origins on educational attainment in Britain. Research in Social Stratification and Mobility, 58(Dec 2018), 11-21. • BOWE, A. (2017) The cultural fairness of the 12-item General Health Questionnaire among diverse adolescents. Psychological Assessment, 29(1), 87-97. • BOWE, A.G. (2017) The immigrant paradox on internalizing symptoms among immigrant adolescents. Journal of Adolescence, 55(February 2017), 72-76. • CAMERON, C, HOLLINGWORTH, K, SCHOON, I, VAN SANTEN, E, SCHROER, W, RISTIKARI, T, HEINO, T and PEKKARINEN, E. (2018) Care leavers in early adulthood: How do they fare in Britain, Finland and Germany? Children and Youth Services Review, 87(April 2018), 163-172. • CODIROLI McMASTER, N. (2017) What role do enjoyment and students’ perception of ability play in social disparities in subject choices at university? CLS Working Paper 2017/12. London: Centre for Longitudinal Studies. • CODIROLI McMASTER, N. (2018) Stratification into field of study in Higher Education. Doctoral Thesis.University College London. • CODIROLI MCMASTER, N. (2017) Who studies STEM subjects at A level and degree in England? An investigation into the intersections between students’ family background, gender and ethnicity in determining choice. British Educational Research Journal, 43(3), 528-553. • COLLIER W, VALBUENA J and ZHU, Y. (2018) What determines post-compulsory academic studies? Evidence from the longitudinal survey of young people in England. Applied Economics Letters, 25(9), 607-610. • FAN, W. (2017) School tenure and student achievement. School Effectiveness and School Improvement, 28(4), 578-607. • GILLBORN,D, DEMACK,S, ROLLOCK,N and WARMINGTON,P. (2017) Moving the goalposts: Education policy and 25 years of the Black/White achievement gap. British Educational Research Journal, 43(5), 848-874. • GOLDMAN, R and BURGESS, A. (2018) Contemporary Fathers in the UK: Review of Research on British Dads. Fatherhood Institute Report, June 2018. Marlborough: Fatherhood Institute. • GUTMAN, L.M and SCHOON, I. (2018) Emotional engagement, educational aspirations, and their association during secondary school. Journal of Adolescence, 67(Aug 2018), 109-119. Hale, D., and Viner, R. (2016). The correlates and course of multiple health risk behaviour in adolescence. BMC Public Health. 2016 May 31; 16: 458. doi: 10.1186/s12889-016-3120-z. Semlyen, J., King, M., Varney, J., and Hagger-Johnson, G. (2016). Sexual orientation and symptoms of common mental disorder or low wellbeing: combined meta-analysis of 12 UK population health surveys. BMC Psychiatry. 2016 Mar 24;16: 67. doi: 10.1186/s12888-016-0767-z. Symonds, J., Dietrich, J., Chow, A., and Salmela-Aro, K. (2016). Mental health improves after transition from comprehensive school to vocational education or employment in England: A national cohort study. Developmental Psychology, 52(4), 652-665 Further examples of what has been learnt from the study includes: Education: Next Steps has provided information on the factors that influence young people's performance at school, including; attainment gaps between young people from rich and poor backgrounds emerged early in life and were very large by the time GCSEs were taken. Findings were used in setting up the Education Maintenance Allowance which is a scheme which helps young people from low income families with the costs of travel, books and equipment for school or college. Employment: Next Steps has contributed to the understanding of young people's experiences of the labour market. It has shown that young people's educational attainment at age 16 is the most important factor affecting if they are in education, training or employment at age 18. In 2011 the government used the findings in their policy on tackling the root causes of youth unemployment. Social exclusion linked to academic struggles for young people in poor health- According to new research from Next Steps. Teenagers with poor physical and mental health are often excluded from social circles and activities, which can have a knock-on effect on their performance at school and in the labour market. More information can be found here - https://nextstepsstudy.org.uk/social-exclusion-linked-to-academic-struggles-for-young-people-in-poor-health/

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Objective for processing

***TO CORRECT INVOICE [36 paragraphs unchanged]

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

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Objective for processing

Previous iterations of this DSA have covered the dissemination of HES data as part of the Next Steps longitudinal study. This Version 1 of this agreement was an amendment request (version 1) is for the addition of a sub-licence to allow onward sharing of the [6 words unchanged] Data Services (UKDS) where data can be accessed by accredited researchers. Further detail of this is details are outlined below: The Centre for Longitudinal Studies (CLS) at University College London (UCL) is [9 words unchanged] data resources for the scientific community. CLS manages three world-renowned birth cohort studies; the studies: The National Child Development Study 1958, the The British Cohort Study 1970, and the The Millennium Cohort Study 2000 and 2000. CLS now have the Next Steps cohort in their portfolio. [3 paragraphs unchanged] Linking health data from Hospital Episodes Statistics (HES) to the Next Steps survey data will has greatly increase increased the possibilities for using the cohort to study how health outcomes impact [42 words unchanged] documented as part of the study. The successful inclusion of HES data will enrich has enriched these data by revealing which cohort members have been admitted to or [9 words unchanged] and alcohol treatment, accident and emergency, maternity and mental health services which could help have helped CLS better understand how health conditions could be better treated or supported. Data about health behaviours may be are more accurate if when obtained from administrative records as a result because of misreporting of complex health conditions, under-reporting of particular health problems or due to perceived sensitivities around certain behaviours and lifestyle choices. So So, this also offers an interesting methodological opportunity to validate the data collected in the survey and vice versa. [7 paragraphs unchanged] The UKDS is funded by the Economic and Social Research Council (ESRC) with contributions from the University of Essex, the University of Manchester and Jisc the Joint Information Systems Committee (Jisc) (Jisc is a United Kingdom not-for-profit company whose role is to support [44 words unchanged] and teachers from all sectors including academia and central and local government. 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 [40 words unchanged] via the sub-licence route, the same as other researchers from other organisations. Under the “Sub-licensing model”, NHS Digital shares data with CLS, who are [104 words unchanged] organisational security assurance and terms and conditions regarding onward sharing of data, responsibilities responsibilities, and processing activities etc. [8 paragraphs unchanged] Applicants (licencees) and their organisations will have to sign two agreements to [40 words unchanged] Access Agreement which will be signed with the UKDS. By signing these agreements agreements, the licencee agrees to adhere to these terms, including respecting the privacy of health services users data they will receive. Licencees are also be reminded of the penalties they are likely to incur if they do [20 words unchanged] must complete mandatory training before they are allowed to access the data. To ensure the security of the linked information, shared with CLS by NHS Digital, and [29 words unchanged] of the process of depositing, approving and sharing of the linked information: [9 paragraphs unchanged]

Processing activities

1. CLS team 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). No new data is being requested and no further data is being sent to NHS Digital under this version of the Agreement. The CLS team is based at UCL. 2. NHS Digital will link the identifiable study data to HES data. NHS Digital will then remove identifiers from linked dataset and return the pseudonymised dataset to the CLS team at UCL with the study ID. 1. CLS team have supplied 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). 3. CLS will carry out validation of the administrative pseudonymised data received (linked HES data) and will combine the supplied administrative data with the information collected from the participant as part of the Next Steps study using the study ID. 2. NHS Digital have linked the identifiable study data to HES data. NHS Digital have removed identifiers from linked dataset and returned the pseudonymised dataset to the CLS team at UCL with the study ID. 3. CLS carried out validation of the administrative pseudonymised data received (linked HES data) and combined the supplied administrative data with the information collected from the participant as part of the Next Steps study using the study ID. [1 paragraph unchanged] 4. CLS researchers will use used these data to create an analysis file, which to confirm will do not contain any identifiable data. 5. CLS will create created 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.), etc.) and will compare Next Steps survey data with data from hospital statistics, in order to compare and validate the data collected in CLS surveys. Identifiers will be are held separately from attribute characteristics. HES data will is not be relinked to the identifiable data which is held separately from [43 words unchanged] to locate the study id, and then in turn destroy their data. [9 paragraphs unchanged] 4) CLS-UCL will: a) check the organisational Information Governance and security assurance evidence provided as per Section 15 Organisational Security Assurance of the CLS Licence agreement, b) send the project for CLS DAC approval. 4) CLS-UCL will: a) check the organisational Information Governance and security assurance evidence provided as per Section 15 Organisational Security Assurance of the CLS Licence agreement b) send the project for CLS DAC approval. [1 paragraph unchanged] 6) CLS DAC will assess both documents (UKDS project proposal + CLS Licence agreement) and make a decision to approve it or approve, not approve it or require further information. Should an application be rejected, a researcher can apply again with a revised application. [1 paragraph unchanged] 8) Once CLS DAC approves the project : project: [2 paragraphs unchanged] c) CLS DAC will publish the information about any data dissemination on [14 words unchanged] 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). (NB. If CLS DAC doesn't approve the project, no data will be disseminated). [3 paragraphs unchanged] Note that any data accessed through the UKDS Secure Lab can only [67 words unchanged] are be based at a UK academic institution or an ESRC-funded research centre, centre and be an ESRC Accredited Researcher. PhD and research students can request access but must apply jointly with their supervisors from established organisations. [3 paragraphs unchanged] 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 several documented processes are regularly maintained and reviewed to ensure these processes are [11 words unchanged] Security Management Group (ISMG), which regularly meets and approves changes to procedures. [8 paragraphs unchanged] The data provided will be pseudo-anonymised, pseudo-anonymised and will be accessed only via the UKDS secure lab. Downloading the data is not possible. [1 paragraph unchanged]

Expected output

[3 paragraphs unchanged] The outputs in the long term from this dataset are difficult to quantify, but the CLS currently has a searchable bibliography on its website with over 3,600 publications based on data from the 1958, 1970, Millennium cohort and Next Steps studies. CLS actively promotes the use of their data among the research community [21 words unchanged] better use the data and so ultimately benefit health and social care.

Expected measurable benefits

[32 paragraphs unchanged] Retaining contact details of non-respondents (to an annual mail-out) will enable the [14 words unchanged] (date to be confirmed) to be able to continue with the research. We also would like to carry a A further list clean will be carried out in the future in preparation to our next wave age 31. 31, this will be subject to a further renewal of this Agreement.

Unchanged: Benefits reported.

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Objective for processing

The Centre for Longitudinal Studies (CLS) is an academic resource centre responsible for producing and disseminating data resources for the scientific community. CLS manages three world-renowned birth cohort studies; the National Child Development Study 1958, the British Cohort Study 1970, and the Millennium Cohort Study 2000 and now have the Next Steps cohort in their portfolio. Previous iterations of this DSA have covered the dissemination of HES data as part of the Next Steps longitudinal study. This amendment request (version 1) is for the addition of a sub-licence to allow onward sharing of the linked HES data with the UK Data Services (UKDS) where data can be accessed by accredited researchers. Further detail of this is outlined below: 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. CLS manages three world-renowned birth cohort studies; the National Child Development Study 1958, the British Cohort Study 1970, and the Millennium Cohort Study 2000 and now have the Next Steps cohort in their portfolio. [2 paragraphs unchanged] During the 2015/16 survey, CLS obtained informed consent from cohort members for [10 words unchanged] in the study. In total consent was obtained from approximately 4941 cohort members. members who are the subject of the data linkage and onward sharing (sub-licensing model) detailed in this application. Linking health data from Hospital Episodes Statistics (HES) to the Next Steps [96 words unchanged] treatment, accident and emergency, maternity and mental health services which could help us CLS better understand how health conditions could be better treated or supported. [1 paragraph unchanged] At this stage the The overall aim of the researchers research is to: [3 paragraphs unchanged] 4. Advance learning in the research community by providing access to the linked NHS Digital HES / CLS Next Steps data to the research community via the UK Data Service (UKDS) Secure Lab, through a sub-licensing agreement agreed between CLS and NHS Digital. THE SUB-LICENCE: CLS are permitted to include onward sharing of the linked HES and CLS Next Steps 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”. The UKDS is funded by the Economic and Social Research Council (ESRC) with contributions from the University of Essex, the University of Manchester and Jisc (Jisc is a United Kingdom not-for-profit company whose role is to support post-16 and higher education, and research, by providing relevant and useful advice, digital resources and network and technology services, while researching and developing new technologies and ways of working). The UKDS provides access to high-quality data to meet the data needs of researchers, students and teachers from all sectors including academia and central and local government. 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 will process the data (and are substantively employed by University of Essex) 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 CLS, who are in turn licensed to share these data with other organisations, subject to agreed controls, scoped in this agreement between NHS Digital and CLS. In line with this onward sharing model, the data sharing controls in place between NHS Digital and CLS are replicated between CLS 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 UK Data Service, 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 CLS, as outlined in this document. 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 sub-licence. The territory of use in the sub-licence will be the same or narrower than the territory of use stated in this DSA, namely England and Wales. In this sharing model of the linked data, CLS will be a data controller, determining the purposes for which and the manner in which the linked data are processed. The UKDS will be the data processor, as they will be processing the data on behalf of CLS. 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 CLS 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 CLS). Applicants (potential licencees) will need to show in Schedule 1 Section 18 (a) and (b) that the provision of the sub licencing will be in the public interest and that 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. CLS will not provide data access to commercial organisations for research for commercial purposes. Additionally, the CLS Licence agreement, Schedule 1 Section 18, 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 the 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, applicant’s organisation will need to provide evidence that they have IG and security assurances in place (covered in Schedule 1, Section 15 of the CLS Licence agreement). Members of the CLS Data Access Committee (DAC) will review and decide if the evidence provided satisfy the criteria requirements. Applicants (licencees) and their organisations will have to sign two agreements to obtain a sub-licence, one with the UKDS and another with CLS, in both cases the licencee will agree with the terms stated in the Confidentiality Section of the CLS 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 licencee agrees to adhere to these terms, including respecting the privacy of health services users data they will receive. Licencees are also be 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 CLS by NHS Digital, and subsequently shared by CLS with the UKDS, where data could be accessed by approved researchers in a Secure Lab, CLS 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 CLS to onwardly share linked HES and CLS information under “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 CLS (as a data controller) and UKDS (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 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 delete the data folder with the tailored dataset for the specific project. The data held at CLS will be deleted if the data sharing agreement between NHS Digital and CLS were to cease. If it were to cease, the license agreement between CLS 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, CLS 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 pseudo-anonymised form (via a secure setting with appropriate safeguards). 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 CLS Licence agreement will require licencees 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 CLS will be accessed by substantive employees of UCL who will work on the data to make it research ready, will pseudo-anonymise the data and deposit it at the UKDS for researchers applying to use for specific projects.

Processing activities

Data disseminated from NHSD to UCL will only be accessed by substantive employees of UCL and only for the purposes described in this document. 1. CLS team 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). Identifiers will be held separately from attribute characteristics. HES 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. 2. NHS Digital will link the identifiable study data to HES data. NHS Digital will then remove identifiers from linked dataset and return the pseudonymised dataset to the CLS team at UCL with the study ID. 1. CLS team will supply NHS Digital with identifiers of cohort members who have consented to this data linkage, including full name, sex, postcode, date of birth and study ID (study-specific pseudonymised identifier). 3. CLS will carry out validation of the administrative pseudonymised data received (linked HES data) and will combine the supplied administrative data with the information collected from the participant as part of the Next Steps study using the study ID. 2. NHS Digital will link the identifiable study data to HES data. NHS Digital will then remove identifiers from linked dataset and return the dataset to the CLS team at UCL with the study ID. 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. 3. CLS will carry out validation of the administrative data received (linked HES data) and will combine the supplied administrative data with the information collected from the participant as part of the Next Steps study using the study ID. 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. [2 paragraphs unchanged] Identifiers will be held separately from attribute characteristics. HES 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. Addition of the sub-licence: The process of accessing the linked data via the UKDS Service Secure Lab include the following steps: • Registration with the UKDS Service. • 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-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-UCL sends the CLS License Agreement for Linked NHS Digital data 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 CLS License Agreement for Linked NHS Digital completed and signed back to CLS-UCL. 4) CLS-UCL will: a) check the organisational Information Governance and security assurance evidence provided as per Section 15 Organisational Security Assurance of the CLS 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 + CLS Licence agreement) and make a decision to approve it or not approve it or require further information. Should an application be rejected, a researcher can apply again with a revised application. 7) In the CLS 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 project has been approved. b) CLS representative should sign the CLS 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). 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). 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 UK Data Service (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) University College London will inform NHS Digital as to who they have issued sub-licences to, in a format agreed with NHS Digital. 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 be based at a UK academic institution or an ESRC-funded research centre, and be an ESRC Accredited Researcher. PhD and research students can request access but must apply jointly with their supervisors from established organisations. No further onward sharing can occur beyond the sub-licence. UKDS secure data handling procedures The UK Data Service 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. 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. UKDS data access mechanisms As an ESRC resource centre, CLS 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: • 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; • 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; • 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. Access mechanisms to NHS Digital HES data linked to CLS cohort studies via the UKDS The HES data provided to CLS 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 disclosivity 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. It is therefore CLS’s intention to deposit these Tier 2 linked HES data with the UK Data Service 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 an agreed between NHS Digital, CLS and UKDS onward sharing model. The UKDS’s ‘Controlled access to data’ specification is supplied to NHS Digital as part of this application amendment. The data provided will be pseudo-anonymised, and will be accessed only via the UKDS secure lab. Downloading the data is not possible. 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 ie: employees, agents and contractors of the Data Recipient who may have access to that data).

Expected output

[2 paragraphs unchanged] The creation of this HES/Next Steps database and the methodological papers are [7 words unchanged] research database which will be of benefit to health and social care. The onward sharing to researchers via an agreed mechanism will be subject to a further application to NHS Digital. [1 paragraph unchanged]

Expected measurable benefits

[23 paragraphs unchanged] Amendment to include the sub-license The main purpose to provide access to the linked Next Steps survey data with NHS Digital Health Episode Statistics (HES) is to enhance the research resource for secondary users. Linking HES data with the survey data greatly widens the value for 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 the NHS Digital. It provides an invaluable opportunity to better understand some of the social determinants of health. Next Steps offers invaluable information on social experiences though 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 our application will allow the linked data to be used more widely in order to maximise societal benefit, while maintaining high levels of data security. 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 will benefit society?’, ‘How does the project provide a public benefit?’, ‘Contribution towards public policy or journal publications’). CLS will further require the applicant to describe the benefits of their intended research to health and social care. The expected measurable benefits from the original agreement: The study produces rich, longitudinal, policy-relevant data, currently unavailable elsewhere, for a large, representative sample of young adults. LSYPE data is widely used by policy makers to evaluate and develop policy and improve services for young people and also by academic researchers to chart and understand social change. The information provided by cohort members provides valuable evidence for the research and policy community about the cohort’s transitions out of education and into early adult life. To enhance the research resource for secondary users, a fully documented, anonymised dataset has been archived with the UK Data Service in May 2017. Next Steps Age 25 and subsequent age 31 survey data will enrich the already deposited data for the cohort (waves 1 to 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. Next Steps 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. Next Steps Age 25 Survey data has been deposited with the UKDS and the cohort members’ health is an important aspect in the Age 25 Sweep. Cohort members were asked a range of questions about their physical and emotional health and wellbeing and CLS is currently looking at initial findings on probable mental ill health at age 25 and its association with a number of potential risk factors. There is, however, a great deal more information about potential underlying determinants, in this and the earlier sweeps of Next Steps, available for researchers via the UKDS. Retaining contact details of non-respondents (to an annual mail-out) will enable the researcher to try and re-establish contact before the next wave of the longitudinal study (date to be confirmed) to be able to continue with the research. We also would like to carry a further list clean in preparation to our next wave age 31.

Benefits reported

Yielded Benefits is not a requirement for new applications. The age 25 survey data is already providing important research evidence on transitions out of education and into early adult life, informing a range of key interlinked policy questions relating to higher education, employment, housing and family formation, and health. Data from the age 25 survey was deposited at the UK Data Service in June 2017 and have already been downloaded for over 100 research projects in many disciplines including economics, education and sociology. Its’ influence and impact will grow over the next few years, as it is used for research and policy on a wide-range of different issues, and as the existing data is enhanced and augmented, particularly with linked administrative data. Initial findings from the age 25 data, produced and published by CLS, have already contributed to political debate in relation to the labour market conditions for this generation, with reference to findings on the negative impact of zero hours contracts on health in Prime Ministers’ questions in July 2017. Below are some examples of existing publications using LSYPE data (waves 1 to 7) BAINES, S, EMERSON, E, ROBERTSON, J and HATTON, C. (2018) Sexual activity and sexual health among young adults with and without mild/moderate intellectual disability. BMC Public Health, 18(1), 667. ROBERTSON, J, EMERSON, E, BAINES, S and HATTON, C. (2018) Self-reported smoking, alcohol and drug use among adolescents and young adults with and without mild to moderate intellectual disability. Journal of Intellectual & Developmental Disability, published online, 23 April 2018. HATTON, C, EMERSON, E, ROBERTSON, J and BAINES, S. (2018) The mental health of adolescents with and without mild/moderate intellectual disabilities in England: Secondary analysis of a longitudinal cohort study. Journal of Applied Research in Intellectual Disabilities, 31(5), 768-777. ROBERTSON, J, EMERSON, E, BAINES, S and HATTON, C. (2018) Self-Reported Participation in Sport/Exercise Among Adolescents and Young Adults With and Without Mild to Moderate Intellectual Disability. Journal of Physical Activity and Health, 15(4), 247-254. BOWE, A. (2017) The cultural fairness of the 12-item General Health Questionnaire among diverse adolescents. Psychological Assessment, 29(1), 87-97. BOURNE, M, BUKODI, E, BETTHAEUSER, B and GOLDTHORPE, J.H. (2018) ‘Persistence of the social’: The role of cognitive ability in mediating the effects of social origins on educational attainment in Britain. Research in Social Stratification and Mobility, 58(Dec 2018), 11-21. I, S, THEOCHARAKI, F, SULLIVAN, A and PLOUBIDIS, G.B. (2018) Social determinants of health in population-based cohort studies, UK: a systematic review. European Journal of Public Health, 28(Suppl.4), cky214.063. • ALCOTT, B. (2017) Does Teacher Encouragement Influence Students’ Educational Progress? A Propensity-Score Matching Analysis. Research in Higher Education, 58(7), 773–804. • ANDERS, J. (2017) The influence of socioeconomic status on changes in young people’s expectations of applying to university. Oxford Review of Education, 43(4), 381-401. • ANDERS, J and DORSETT, R. (2017) What young English people do once they reach school-leaving age: A cross-cohort comparison for the last 30 years. Longitudinal and Life Course Studies, 8(1), 75-103. • ANDERS, J, HENDERSON, M, MOULTON, V and SULLIVAN, A. (2017) Incentivising specific combinations of subjects: does it make any difference to university access? CLS Working Paper 2017/11. London: Centre for Longitudinal Studies. • ANDERS, J, HENDERSON, M, MOULTON, V and SULLIVAN, A. (2017) A note on subject choice at age 14 and socio-economic inequality in access to university. CLS Working Paper 2017/10. • ANDERS, J.D, MOULTON, V, HENDERSON, M and SULLIVAN, A. (2018) The role of schools in explaining individuals’ subject choices at age 14. Oxford Review of Education, 44(1), 75-93. • BAINES, S, EMERSON, E, ROBERTSON, J and HATTON, C. (2018) Sexual activity and sexual health among young adults with and without mild/moderate intellectual disability. BMC Public Health, 18(1), 667. • BELLFIELD, C and VAN DER ERVE, L. (2018) The impact of higher education on the living standards of female graduates. IFS Working Paper W18/25. London: Institute for Fiscal Studies. • BOURNE, M, BUKODI, E, BETTHAEUSER, B and GOLDTHORPE, J.H. (2018) ‘Persistence of the social’: The role of cognitive ability in mediating the effects of social origins on educational attainment in Britain. Research in Social Stratification and Mobility, 58(Dec 2018), 11-21. • BOWE, A. (2017) The cultural fairness of the 12-item General Health Questionnaire among diverse adolescents. Psychological Assessment, 29(1), 87-97. • BOWE, A.G. (2017) The immigrant paradox on internalizing symptoms among immigrant adolescents. Journal of Adolescence, 55(February 2017), 72-76. • CAMERON, C, HOLLINGWORTH, K, SCHOON, I, VAN SANTEN, E, SCHROER, W, RISTIKARI, T, HEINO, T and PEKKARINEN, E. (2018) Care leavers in early adulthood: How do they fare in Britain, Finland and Germany? Children and Youth Services Review, 87(April 2018), 163-172. • CODIROLI McMASTER, N. (2017) What role do enjoyment and students’ perception of ability play in social disparities in subject choices at university? CLS Working Paper 2017/12. London: Centre for Longitudinal Studies. • CODIROLI McMASTER, N. (2018) Stratification into field of study in Higher Education. Doctoral Thesis.University College London. • CODIROLI MCMASTER, N. (2017) Who studies STEM subjects at A level and degree in England? An investigation into the intersections between students’ family background, gender and ethnicity in determining choice. British Educational Research Journal, 43(3), 528-553. • COLLIER W, VALBUENA J and ZHU, Y. (2018) What determines post-compulsory academic studies? Evidence from the longitudinal survey of young people in England. Applied Economics Letters, 25(9), 607-610. • FAN, W. (2017) School tenure and student achievement. School Effectiveness and School Improvement, 28(4), 578-607. • GILLBORN,D, DEMACK,S, ROLLOCK,N and WARMINGTON,P. (2017) Moving the goalposts: Education policy and 25 years of the Black/White achievement gap. British Educational Research Journal, 43(5), 848-874. • GOLDMAN, R and BURGESS, A. (2018) Contemporary Fathers in the UK: Review of Research on British Dads. Fatherhood Institute Report, June 2018. Marlborough: Fatherhood Institute. • GUTMAN, L.M and SCHOON, I. (2018) Emotional engagement, educational aspirations, and their association during secondary school. Journal of Adolescence, 67(Aug 2018), 109-119. Hale, D., and Viner, R. (2016). The correlates and course of multiple health risk behaviour in adolescence. BMC Public Health. 2016 May 31; 16: 458. doi: 10.1186/s12889-016-3120-z. Semlyen, J., King, M., Varney, J., and Hagger-Johnson, G. (2016). Sexual orientation and symptoms of common mental disorder or low wellbeing: combined meta-analysis of 12 UK population health surveys. BMC Psychiatry. 2016 Mar 24;16: 67. doi: 10.1186/s12888-016-0767-z. Symonds, J., Dietrich, J., Chow, A., and Salmela-Aro, K. (2016). Mental health improves after transition from comprehensive school to vocational education or employment in England: A national cohort study. Developmental Psychology, 52(4), 652-665 Further examples of what has been learnt from the study includes: Education: Next Steps has provided information on the factors that influence young people's performance at school, including; attainment gaps between young people from rich and poor backgrounds emerged early in life and were very large by the time GCSEs were taken. Findings were used in setting up the Education Maintenance Allowance which is a scheme which helps young people from low income families with the costs of travel, books and equipment for school or college. Employment: Next Steps has contributed to the understanding of young people's experiences of the labour market. It has shown that young people's educational attainment at age 16 is the most important factor affecting if they are in education, training or employment at age 18. In 2011 the government used the findings in their policy on tackling the root causes of youth unemployment. Social exclusion linked to academic struggles for young people in poor health- According to new research from Next Steps. Teenagers with poor physical and mental health are often excluded from social circles and activities, which can have a knock-on effect on their performance at school and in the labour market. More information can be found here - https://nextstepsstudy.org.uk/social-exclusion-linked-to-academic-struggles-for-young-people-in-poor-health/