https://dataverse.nl/api/datasets/:persistentId/versions/9.0/customlicense?persistentId=doi:10.34894/FXUGHWhttps://dataverse.nl/api/datasets/:persistentId/versions/9.0/customlicense?persistentId=doi:10.34894/FXUGHW
Children with a chronic disease face more obstacles than their healthy peers, which may impact their physical, social-emotional, and cognitive development. In the long run, children with a chronic disease reach developmental milestones later than their healthy peers and many children will remain dependent on medication and/ or will be limited in their daily life activities. The PROactive Cohort Study aims to assess fatigue, participation, and psychosocial well-being across children with various chronic diseases over the course of their lifespan since their increased vulnerability is a fact. These factors have the potential to influence their identity and how they grow into autonomous adults that take part in our society. Also the PROactive Cohort Study is aimed at supporting people with chronic and/or life-threatening conditions to increase their ability to adapt, and their self-manage capacities. This means that PROactive also systematically monitors the child's capacity and ability to play and the well-being of the patients and their families. This knowledge can be used as an innovative and interactive method for creating prevention and treatment strategies. This will help to assess vulnerabilities and resilience among children with chronic and/or life-threatening conditions and their families. This cohort study follows a continuous longitudinal design. It is based at the Wilhelmina Children's Hospital in the Netherlands and has been running since December 2016. Children with a chronic disease (e.g. cystic fibrosis, juvenile idiopathic arthritis, chronic kidney disease, or congenital heart disease) in a broad age range (2-18 years) are included, as well as their parent(s). Patient-reported outcome measures (PROMs) are collected from parents (children between 2-18 years) and children (8-18 years). The PROactive Cohort Study uses a flexible design in which the research assessment is an integrated part of clinical care. Children are included when they visit the outpatient clinic and are followed up annually, preferably linked to another outpatient visit.
The College Scorecard is designed to increase transparency, putting the power in the hands of the public — from those choosing colleges to those improving college quality — to see how well different schools are serving their students.
This dataset contains town level and statewide totals information on the number of infants and toddlers referred, evaluated, determined eligible, and had an Individual Family Service Plan (IFSP) developed through the Connecticut Birth to Three (B23) System. Data can be viewed by birth cohort year. See data element definitions listed in detail below. Included data are collected by the Office of Early Childhood (OEC) as the lead agency for the B23 System, in accordance with Part C of the federal Individuals with Disabilities Education Act (IDEA) and CGS 17a-248. For more information regarding B23 data, please visit https://www.birth23.org/how-are-we-doing/data/ Note: Data fields with a value of 5 or lower (<6) during the reporting period have been suppressed to protect confidentiality, as denoted with a “-99.99”.
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Excel data for the cohort
This is a Jupyter notebook demonstrating the concept of creating a group or ���cohort��� that will be used for future analysis. It goes through the process of constructing measures to understand who is included and excluded (coverage) from the cohort and walks through the decisions that need to be made when devising the cohort. Cohorts define the primary population of interest in much research; once created, cohorts may then be used to link to other data sources. This notebook was developed for the Spring 2021 Applied Data Analytics training facilitated by John J. Heldrich Center for Workforce Development and Coleridge Initiative.
Background:
The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:
Further information about the MCS can be found on the Centre for Longitudinal Studies web pages.
The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.
The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old.The Millennium Cohort Study: Linked Health Administrative Data (Scottish Medical Records), Inpatient and Day Care Attendance, 2000-2015: Secure Access includes data files from the NHS Digital Hospital Episode Statistics database for those cohort members who provided consent to health data linkage in the Age 50 sweep, and had ever lived in Scotland. The Scottish Medical Records database contains information about all hospital admissions in Scotland. This study concerns the Scottish Birth Records.
Other datasets are available from the Scottish Medical Records database, these include:
The Early Childhood Longitudinal Study, Birth Cohort (ECLS-B), is a study that is part of the Early Childhood Longitudinal Study program; program data is available since 1998-99 at . ECLS-B (https://nces.ed.gov/ecls/birth.asp) is a longitudinal study that is designed to provide policy makers, researchers, child care providers, teachers, and parents with detailed information about children's early life experiences. The study was conducted using multiple data collection methods (computer-assisted in-person interviews, computer-assisted telephone interviews, self-administered questionnaires, and direct observation) to collect information about children's characteristics, behaviors, development, and experiences from the adults who were important in the children's lives, including mothers, fathers, early care and education providers, and teachers. Direct child assessments were used to measure children's development, knowledge, and skills from the time the children were about 9 months old. A nationally representative sample of approximately 14,000 children born in the U.S. in 2001 was fielded. Key statistics produced from ECLS-B focus on children's health, development, care, and education during the formative years from birth through kindergarten entry.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Connecticut's Birth to Three System (B23) supports families with infants and toddlers that have developmental delays to learn new ways to make everyday activities enhance the child's development. Birth to Three is administered pursuant to Part C of the Individuals with Disabilities Education Act (IDEA). Once families with children below age 3 are referred, the child's development is evaluated for eligibility, and if eligible the family can receive supports until the child no longer has delays or until the child turns age 3. Because an infant can be referred within days of being born, a family may be enrolled for almost three full years. Connecticut's Birth to Three System publishes data annually by the fiscal and calendar year and longitudinally by birth cohort. CTData.org carries both sets of data, here and in 'Birth To Three Annual Data'. Birth cohort data looks at all children born in a particular year and tracks whether the family received B23 support. For example, the latest full year available in this dataset is for those children born in 2013 since they turned age 3 sometime in 2016. The 2013 data will tell you how many children there were whose families received support at some point during the first three years of the child's life. CTData calculates several indicators using total number of births in a town. This provides users with a general idea of the relative number of children in the community eligible for services. Using births is not perfect since families move in and out of town so it should not be used as an exact figure but as a general reference point. Below are how the indicators are calculated: % Referrals = Number referred divided by total number of births % Evaluations = Number evaluated divided by total number of births % Eligible = Number eligible divided by total number of births % Individual Family Service Plans (IFSP) = Number with IFSP divided by total number of births % Served = Number served divided by total number of births % Exited to Early Childhood Special Education = Number exited to early childhood special education divided by total number of births 'Referred that are Evaluated' represents the percent of children that were evaluated out of the total number of children referred to the Birth to Three System. 'Evaluated that are Eligible' represents the percent of children who were deemed eligible out of the total number of children that were evaluated. 'Eligible that Recieve IFSP' represents the percent of children whose family recieved an Individual Family Service Plan out of the total number of eligible children.
Background:
The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:
Further information about the MCS can be found on the Centre for Longitudinal Studies web pages.
The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.
The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old.
End User Licence versions of MCS studies:
The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.
Sub-sample studies:
Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).
Release of Sweeps 1 to 4 to Long Format (Summer 2020)
To support longitudinal research and make it easier to compare data from different time points, all data from across all sweeps is now in a consistent format. The update affects the data from sweeps 1 to 4 (from 9 months to 7 years), which are updated from the old/wide to a new/long format to match the format of data of sweeps 5 and 6 (age 11 and 14 sweeps). The old/wide formatted datasets contained one row per family with multiple variables for different respondents. The new/long formatted datasets contain one row per respondent (per parent or per cohort member) for each MCS family. Additional updates have been made to all sweeps to harmonise variable labels and enhance anonymisation.
How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.
Secure Access datasets:
Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).
Secure Access versions of the MCS include:
The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application.
Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page).
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aDeath.bMetastasis.cTumor grade.dTumor stage. NA, not available. m, month. Yr, year. Ref, reference.
The Cohort Hip & Cohort Knee (CHECK) is a population-based observational multicenter cohort study of 1002 individuals with early symptomatic osteoarthritis (OA) of knee and/or hip in the Netherlands. The participants were followed for 10 years. The study evaluated clinical, radiographic and biochemical variables in order to establish the course, prognosis and underlying mechanisms of early symptomatic osteoarthritis. The Dutch Artritis Foundation initiated and funded this inception cohort.This dataset covers the data collection of baseline and 6 to 8 years follow-up: T0, T6, T7 and T8. All data files include the variable 'Subject identification number'. Included is a Kellgren-Lawrence radiographic classification covering T0, T2, T5, T8 and T10. Also X-rays of hips, knees, hands and spine of T8 are available. More information on the variables can be found in the documentation.In the description file you can find an overview of the data belonging to this dataset and more information about the format and kind of view of the X rays.See relations for other CHECK datasets and for the overview 'Thematic collection: CHECK (Cohort Hip & Cohort Knee). Date Submitted: 2015-12-24 2019-12-20: a new data file on X-Ray data 'Rontgen_opT10_20191118' was added to the dataset.2017-10-04: A data file on X-Ray ratings has been added and the variable guide is replaced by a new version (6) with information on this data file. Please note the variable names start with 'RontgT10_' in the data file.2017-07-12: Due to an error a data file has been replaced. CHECK_T0_DANS_ENG_20151211.sav is now replaced by CHECK_T0_DANS_ENG_20161128.sav.---The informed consent statements of the participants are stored at the participating hospitals.The .dta (STATA) and .por (SPSS) files are conversions of the original .sav (SPSS) files. In order to link subject identification numbers to the baseline images, please refer to the X-ray data files T0.zip to T0-24.zip from the dataset "CHECK (Cohort Hip & Cohort Knee) data of baseline to 5 years follow-up" at https://doi.org/10.17026/dans-xex-hzww
The 1970 British Cohort Study (BCS70) is a longitudinal birth cohort study, following a nationally representative sample of over 17,000 people born in England, Scotland and Wales in a single week of 1970. Cohort members have been surveyed throughout their childhood and adult lives, mapping their individual trajectories and creating a unique resource for researchers. It is one of very few longitudinal studies following people of this generation anywhere in the world.
Since 1970, cohort members have been surveyed at ages 5, 10, 16, 26, 30, 34, 38, 42, 46, and 51. Featuring a range of objective measures and rich self-reported data, BCS70 covers an incredible amount of ground and can be used in research on many topics. Evidence from BCS70 has illuminated important issues for our society across five decades. Key findings include how reading for pleasure matters for children's cognitive development, why grammar schools have not reduced social inequalities, and how childhood experiences can impact on mental health in mid-life. Every day researchers from across the scientific community are using this important study to make new connections and discoveries.
BCS70 is run by the Centre for Longitudinal Studies (CLS), a research centre in the UCL Institute of Education, which is part of University College London. The content of BCS70 studies, including questions, topics and variables can be explored via the CLOSER Discovery website.
How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from BCS70 that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.
Secure Access datasets
Secure Access versions of BCS70 have more restrictive access conditions than versions available under the standard End User Licence (EUL).
SN 9392 - 1970 British Cohort Study: Age 51, Sweep 11 Geographical Identifiers, 2021 Census Boundaries, 2021-2024: Secure Access includes detailed geographical variables from the BCS70 Age 51 Sweep 11 that can be linked to the main End User Licence data, available under SN 9347 - 1970 British Cohort Study: Age 51, Sweep 11, 2021-2024. The Age 51, Sweep 11 2011 Census Boundaries are available under SN 9391.
International Data Access Network (IDAN)
These data are now available to researchers based outside the UK. Selected UKDS SecureLab/controlled datasets from the Institute for Social and Economic Research (ISER) and the Centre for Longitudinal Studies (CLS) have been made available under the International Data Access Network (IDAN) scheme, via a Safe Room access point at one of the UKDS IDAN partners. Prospective users should read the UKDS SecureLab application guide for non-ONS data for researchers outside of the UK via Safe Room Remote Desktop Access. Further details about the IDAN scheme can be found on the UKDS International Data Access Network webpage and on the IDAN website.
Age-period-cohort analysis of incidence and/or mortality data has received much attention in the literature. To circumvent the non-identifiability problem inherent in the age-period-cohort model, additional constraints are necessary on the parameters estimates. We propose setting the constraint to reflect the different nature of the three temporal variables: age, period, and birth cohort. There are two assumptions in our method. Recognizing age effects to be deterministic (first assumption), we do not explicitly incorporate the age parameters into constraint. For the stochastic period and cohort effects, we set a constant-relative-variation constraint on their trends (second assumption). The constant-relative-variation constraint dictates that between two stochastic effects, one with a larger curvature gets a larger (absolute) slope, and one with zero curvature gets no slope. We conducted Monte-Carlo simulations to examine the statistical properties of the proposed method and analyzed the data of prostate cancer incidence for whites from 1973–2012 to illustrate the methodology. A driver for the period and/or cohort effect may be lacking in some populations. In that case, the CRV method automatically produces an unbiased age effect and no period and/or cohort effect, thereby addressing the situation properly. However, the method proposed in this paper is not a general purpose model and will produce biased results in many other real-life data scenarios. It is only useful in situations when the age effects are deterministic and dominant, and the period and cohort effects are stochastic and minor.
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License information was derived automatically
This repository stores synthetic datasets derived from the database of the UK Biobank (UKB) cohort.
The datasets were generated for illustrative purposes, in particular for reproducing specific analyses on the health risks associated with long-term exposure to air pollution using the UKB cohort. The code used to create the synthetic datasets is available and documented in a related GitHub repo, with details provided in the section below. These datasets can be freely used for code testing and for illustrating other examples of analyses on the UKB cohort.
Note: while the synthetic versions of the datasets resemble the real ones in several aspects, the users should be aware that these data are fake and must not be used for testing and making inferences on specific research hypotheses. Even more importantly, these data cannot be considered a reliable description of the original UKB data, and they must not be presented as such.
The original datasets are described in the article by Vanoli et al in Epidemiology (2024) (DOI: 10.1097/EDE.0000000000001796) [freely available here], which also provides information about the data sources.
The work was supported by the Medical Research Council-UK (Grant ID: MR/Y003330/1).
The series of synthetic datasets (stored in two versions with csv and RDS formats) are the following:
In addition, this repository provides these additional files:
The datasets resemble the real data used in the analysis, and they were generated using the R package synthpop (www.synthpop.org.uk). The generation process involves two steps, namely the synthesis of the main data (cohort info, baseline variables, annual PM2.5 exposure) and then the sampling of death events. The R scripts for performing the data synthesis are provided in the GitHub repo (subfolder Rcode/synthcode).
The first part merges all the data including the annual PM2.5 levels in a single wide-format dataset (with a row for each subject), generates a synthetic version, adds fake IDs, and then extracts (and reshapes) the single datasets. In the second part, a Cox proportional hazard model is fitted on the original data to estimate risks associated with various predictors (including the main exposure represented by PM2.5), and then these relationships are used to simulate death events in each year. Details on the modelling aspects are provided in the article.
This process guarantees that the synthetic data do not hold specific information about the original records, thus preserving confidentiality. At the same time, the multivariate distribution and correlation across variables as well as the mortality risks resemble those of the original data, so the results of descriptive and inferential analyses are similar to those in the original assessments. However, as noted above, the data are used only for illustrative purposes, and they must not be used to test other research hypotheses.
The National Center for Advancing Translational Sciences (NCATS) has systematically compiled clinical, laboratory and diagnostic data from electronic health records to support COVID-19 research efforts via the National COVID Cohort Collaborative (N3C) Data Enclave. As of August 2, 2022, the repository contains information from over 15 million patients (including 5.8 million COVID-19 positive patients) across the United States.
The N3C Data Enclave is organized into 3 levels of data with varying access restrictions:
The 1970 British Cohort Study (BCS70) is a longitudinal birth cohort study, following a nationally representative sample of over 17,000 people born in England, Scotland and Wales in a single week of 1970. Cohort members have been surveyed throughout their childhood and adult lives, mapping their individual trajectories and creating a unique resource for researchers. It is one of very few longitudinal studies following people of this generation anywhere in the world.
Since 1970, cohort members have been surveyed at ages 5, 10, 16, 26, 30, 34, 38, 42, 46, and 51. Featuring a range of objective measures and rich self-reported data, BCS70 covers an incredible amount of ground and can be used in research on many topics. Evidence from BCS70 has illuminated important issues for our society across five decades. Key findings include how reading for pleasure matters for children's cognitive development, why grammar schools have not reduced social inequalities, and how childhood experiences can impact on mental health in mid-life. Every day researchers from across the scientific community are using this important study to make new connections and discoveries.
BCS70 is run by the Centre for Longitudinal Studies (CLS), a research centre in the UCL Institute of Education, which is part of University College London. The content of BCS70 studies, including questions, topics and variables can be explored via the CLOSER Discovery website.
How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from BCS70 that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.
Secure Access datasets
Secure Access versions of BCS70 have more restrictive access conditions than versions available under the standard End User Licence (EUL).
SN 8547 - 1970 British Cohort Study: Age 46, Sweep 10, 2016-2018:
The aim of the 46-year follow-up was to collect key details of the cohort members’ lives including their socio-economic circumstances (e.g. household composition, cohabiting relationships, housing, economic activity, and income) and their health (physical health, mental health, medication, and health behaviours). This survey had a significant biomedical focus, with objective health measurements and assessments being conducted for the first time in the cohort members’ adulthood.
The 'bcs_age46_child_died' and 'bcs_age46_unsuccessful_pregnancies' datasets
This note is to inform researchers that the 'bcs_age46_child_died' and 'bcs_age46_unsuccessful_pregnancies' datasets, which were previously available as safeguarded data under EUL, have been classified as controlled data by CLS and can only be accessed via the UKDS SecureLab, subject to the UKDS Secure Access licence. The aim of this note is to provide practical information and guidance to researchers who have downloaded the BCS70 Age 46 datasets 'bcs_age46_child_died' and 'bcs_age46_unsuccessful_pregnancies' from the UK Data Archive. CLS requires that all EUL holders delete their versions of these datasets. Should they require them, users can apply for access through the new Secure Access study SN 9115. However, where a user has downloaded these dataset and is using them in a current project, they may continue to use the data and any outputs derived from their use until the project is completed. On completion of the project, users are then required to delete the original datasets. Future projects should use the new versions of the data. Any users having concerns about this should contact CLS. Further guidelines on destroying data are provided in the UKDS guidelines.
Latest edition information
For the second edition (July 2023), a new data file including newly derived nutritional intake variables based on the food composition table from the UK Nutrient Databank (UKNDB) has been added to the study. In addition, four data files have been updated (main, employment, relationships and dietary questionnaire) and a new version of the user guide is available. Sensitive survey data for Sweep 10 is now available under restrictive access conditions under SN 9115.
This excel workbook provides a minimal dataset including all variables analyzed in this analysis. A data dictionary is provided on worksheet two of the excel workbook. (XLS)
https://lida.dataverse.lt/api/datasets/:persistentId/versions/1.2/customlicense?persistentId=hdl:21.12137/RA4TUGhttps://lida.dataverse.lt/api/datasets/:persistentId/versions/1.2/customlicense?persistentId=hdl:21.12137/RA4TUG
This dataset covers anonymised student-level population data on students enrolled in grade 8 during the school year 2020-2021, including historical data for this student cohort. The NO-GAP research team was provided with student-level primary population data by the National Agency for Education (NAE) from the Education Information Management System (EMIS) database. This database contains the data that is needed by education stakeholders to analyse and assess the state of education in various aspects, forecast educational change, make data-driven decisions, and manage education for quality. The primary data provided by the NAE was cleaned, additionally coded to prevent reidentification, and merged into a single data file by the NO-GAP research team. In addition, the team prepared the codebook "NO-GAP Codebook. School and Student Level Variables: 2020-2021 Cohort of 8th-Grade Students". Dataset "NO-GAP: Student-Level Data: Cohort of 8th Graders of the School Year 2020-2021" metadata and data were prepared implementing project "Disparities in School Achievement from a Person and Variable-Oriented Perspective: A Prototype of a Learning Analytics Tool NO-GAP" from 2020 to 2023. Project leader is chief research fellow Rasa Erentaitė. Project is funded by the European Regional Development Fund according to the 2014–2020 Operational Programme for the European Union Funds’ Investments, under measure’s No. 01.2.2-LMT-K-718 activity “Research Projects Implemented by World-class Researcher Groups to develop R&D activities relevant to economic sectors, which could later be commercialized” under a grant agreement with the Lithuanian Research Council (LMTLT). These data are not open for external use based on the agreement with NAE.
Human data obtained from the Kyotango cohort study
The 1970 British Cohort Study (BCS70) is a longitudinal birth cohort study, following a nationally representative sample of over 17,000 people born in England, Scotland and Wales in a single week of 1970. Cohort members have been surveyed throughout their childhood and adult lives, mapping their individual trajectories and creating a unique resource for researchers. It is one of very few longitudinal studies following people of this generation anywhere in the world.
Since 1970, cohort members have been surveyed at ages 5, 10, 16, 26, 30, 34, 38, 42, 46, and 51. Featuring a range of objective measures and rich self-reported data, BCS70 covers an incredible amount of ground and can be used in research on many topics. Evidence from BCS70 has illuminated important issues for our society across five decades. Key findings include how reading for pleasure matters for children's cognitive development, why grammar schools have not reduced social inequalities, and how childhood experiences can impact on mental health in mid-life. Every day researchers from across the scientific community are using this important study to make new connections and discoveries.
BCS70 is run by the Centre for Longitudinal Studies (CLS), a research centre in the UCL Institute of Education, which is part of University College London. The content of BCS70 studies, including questions, topics and variables can be explored via the CLOSER Discovery website.
How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from BCS70 that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.
Secure Access datasets
Secure Access versions of BCS70 have more restrictive access conditions than versions available under the standard End User Licence (EUL).
https://dataverse.nl/api/datasets/:persistentId/versions/9.0/customlicense?persistentId=doi:10.34894/FXUGHWhttps://dataverse.nl/api/datasets/:persistentId/versions/9.0/customlicense?persistentId=doi:10.34894/FXUGHW
Children with a chronic disease face more obstacles than their healthy peers, which may impact their physical, social-emotional, and cognitive development. In the long run, children with a chronic disease reach developmental milestones later than their healthy peers and many children will remain dependent on medication and/ or will be limited in their daily life activities. The PROactive Cohort Study aims to assess fatigue, participation, and psychosocial well-being across children with various chronic diseases over the course of their lifespan since their increased vulnerability is a fact. These factors have the potential to influence their identity and how they grow into autonomous adults that take part in our society. Also the PROactive Cohort Study is aimed at supporting people with chronic and/or life-threatening conditions to increase their ability to adapt, and their self-manage capacities. This means that PROactive also systematically monitors the child's capacity and ability to play and the well-being of the patients and their families. This knowledge can be used as an innovative and interactive method for creating prevention and treatment strategies. This will help to assess vulnerabilities and resilience among children with chronic and/or life-threatening conditions and their families. This cohort study follows a continuous longitudinal design. It is based at the Wilhelmina Children's Hospital in the Netherlands and has been running since December 2016. Children with a chronic disease (e.g. cystic fibrosis, juvenile idiopathic arthritis, chronic kidney disease, or congenital heart disease) in a broad age range (2-18 years) are included, as well as their parent(s). Patient-reported outcome measures (PROMs) are collected from parents (children between 2-18 years) and children (8-18 years). The PROactive Cohort Study uses a flexible design in which the research assessment is an integrated part of clinical care. Children are included when they visit the outpatient clinic and are followed up annually, preferably linked to another outpatient visit.