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Labour Force Survey Five-Quarter Longitudinal Dataset, July 2024 - September, 2025
No full textAbstract copyright UK Data Service and data collection copyright owner.Background
The Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The LFS was first conducted biennially from 1973-1983. Between 1984 and 1991 the survey was carried out annually and consisted of a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter (data were then collected seasonally). From 1992 quarterly data were made available, with a quarterly sample size approximately equivalent to that of the previous annual data. The survey then became known as the Quarterly Labour Force Survey (QLFS). From December 1994, data gathering for Northern Ireland moved to a full quarterly cycle to match the rest of the country, so the QLFS then covered the whole of the UK (though some additional annual Northern Ireland LFS datasets are also held at the UK Data Archive). Further information on the background to the QLFS may be found in the documentation.
Longitudinal data
The LFS retains each sample household for five consecutive quarters, with a fifth of the sample replaced each quarter. The main survey was designed to produce cross-sectional data, but the data on each individual have now been linked together to provide longitudinal information. The longitudinal data comprise two types of linked datasets, created using the weighting method to adjust for non-response bias. The two-quarter datasets link data from two consecutive waves, while the five-quarter datasets link across a whole year (for example January 2010 to March 2011 inclusive) and contain data from all five waves. A full series of longitudinal data has been produced, going back to winter 1992. Linking together records to create a longitudinal dimension can, for example, provide information on gross flows over time between different labour force categories (employed, unemployed and economically inactive). This will provide detail about people who have moved between the categories. Also, longitudinal information is useful in monitoring the effects of government policies and can be used to follow the subsequent activities and circumstances of people affected by specific policy initiatives, and to compare them with other groups in the population. There are however methodological problems which could distort the data resulting from this longitudinal linking. The ONS continues to research these issues and advises that the presentation of results should be carefully considered, and warnings should be included with outputs where necessary.
LFS Documentation
The documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned. However, volumes are updated periodically by ONS, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.Occupation data for 2021 and 2022 data filesThe ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.2022 WeightingThe population totals used for the latest LFS estimates use projected growth rates from Real Time Information (RTI) data for UK, EU and non-EU populations based on 2021 patterns. The total population used for the LFS therefore does not take into account any changes in migration, birth rates, death rates, and so on since June 2021, and hence levels estimates may be under- or over-estimating the true values and should be used with caution. Estimates of rates will, however, be robust.Main Topics:The five-quarter longitudinal datasets include a subset of the most commonly used variables from the Quarterly Labour Force Survey (QLFS), covering the main areas of the survey
Shame and Medicine Project, 2021-2024
No full textThe Shame and Medicine Project investigated the experiences of shame and self-conscious emotions within the context of contemporary healthcare.
The project explored National Health Service settings and took place in England between June 2020 and February 2026. It involved patients, medical students, and doctors (including general practitioners, those working in hospital settings, and those with experience of the General Medical Council disciplinary procedures). Participants were asked to complete a number of structured Emotional Experience Diary entries detailing a time when they had experienced shame or self-consciousness in healthcare settings. Following this, participants were invited to attend a semi-structured interview to discuss the experiences described in their diary entries in greater detail.
The collection consists of the Emotional Experience Diary entries and interviews of those participants who consented to the archiving of their data. The total dataset involved 265 participants, which included 120 patients, 72 qualified doctors, and 73 medical students. These created 1047 diary entries and undertook 116 interviews. They were all from England. Of these, 95 patients (134 diary entries and 20 semi-structured interviews), 51 doctors (312 diary entries and 41 semi-structured interviews), and 58 medical students (331 diary entries and 20 semi-structured interviews) agreed to their data being made available on the Data Service.The Shame and Medicine Project investigated the experiences of shame and self-conscious emotions within the context of contemporary healthcare. The project explored National Health Service settings and took place in England between June 2020 and February 2026. It involved patients, medical students, and doctors (including general practitioners, those working in hospital settings, and those with experience of the General Medical Council disciplinary procedures). Participants were asked to complete a number of structured Emotional Experience Diary entries detailing a time when they had experienced shame or self-consciousness in healthcare settings. Following this, participants were invited to attend a semi-structured interview to discuss the experiences described in their diary entries in greater detail. The dataset consists of the Emotional Experience Diary entries and interviews of those participants who consented to the archiving of their data. This includes 95 patients (134 diary entries and 20 semi-structured interviews), 51 doctors (312 diary entries and 41 semi-structured interviews), and 58 medical students (331 diary entries and 20 semi-structured interviews).</p
Antenatal Care of Women Who Use Opioids: A Qualitative Study of Practitioners’ Experiences and Perceptions of Current Service Provision in Scotland, 2021-2022
No full textThis project aimed to described different models of antenatal care in Health Boards covering three of the largest urban areas in Scotland and to explore multi-disciplinary practitioners’ perceptions of the strengths and challenges of working with women who use opioids through these specialist services.
The collection comprises 12 transcripts of a range of professionals working with women who use opioids in pregnancy across three health boards in Scotland.Why do we need this study?
Internationally, the rising use of opioid drugs has been described as a crisis. In Scotland, around 500 children a year are born to women who use opioid drugs, for example, heroin and methadone. The little we do know about these children is that they are likely to have poorer health in the first few years of life. We also know that they are more likely to be disadvantaged in other ways, e.g. living in poverty and in unstable housing. The research which has been conducted tends to have collected data on small numbers of children for a limited period of time. This is because these families often have pretty chaotic lives, and may move around a lot, making it difficult for researchers to keep in contact and return to interview them over time.
This has led to a lack of information about what happens to these children in the longer term, and where they might need additional support. We also don't know much about the impact of differences in how these children are treated when they are born, and what makes some of these children have better health and development than others.
What will the study involve?
This study has three stages to it. Firstly we will speak to a range of people who work with women who use drugs about the way that they record data on these families, e.g. midwives, health visitors, nurses, doctors and social workers. We want to find out from them why they record data in certain ways, whether any data is missing or incomplete, and how reliable data are. This information will be used to inform the main study, which will use data recorded in hospital records, birth records, and school records, for example.
In Scotland, everyone has a unique health ID number, which allows their data to be linked together. The second stage of the study will bring together data from health, education and social work, to allow us to compare what happens to different groups of children. These groups will contain children who had a mother who used opioids such as methadone in pregnancy because they are addicted to illegal drugs, such as heroin, as well as a group of children whose mother used opioids in pregnancy as chronic pain relief, and children who are similarly disadvantaged, for example living in poverty, but did not have a mother who used opioids in pregnancy. At this stage, we will look at different measures of health, e.g. whether children are obese/overweight, have been admitted to hospital for accidents and injuries, or have conditions such as asthma. We will try to work out the differences in these outcomes between the different groups of children, and what other risks (such as being born very early, or having a mother who smoked during pregnancy) are associated with these outcomes.
The third stage of this study will look at the social work data on children born to mothers who used opioids in pregnancy. Many of these children will spend time living away from home, either with other family members or with foster carers. We will look at patterns of movement between different carers and what factors make a child more at risk of having different patterns of care away from home. We will then look at whether being cared for away from home leads to different health and developmental outcomes, compared with children who did not live away from home.
Who will benefit?
Our study findings will help a range of people and agencies in different ways. It will benefit women who use drugs and their children because it will help to show how practices and policies might better meet their needs. It will benefit society more widely as it will provide a better understanding of the everyday lives of parents and their families. It will also benefit professionals, services and policymakers by offering new understandings about what these families need to support them to give their children the best start in life. It will also advise on how we could collect better data on these families to improve services.</p
Trust in Social Media Images of Health, 2023
No full textThe data collection consists of transcripts contain conversation about sensitive experiences and health issues, including reflections on body size and weight, restrictive eating, eating disorders, body dysmorphia, self-harm, suicide, mental illness, pregnancy loss, infertility, sexuality and homophobia.
This collection contains 30 transcripts of social media elicitation interviews conducted with young adult social media users. The interviews were semi-structured, covering topics related to participants' everyday use of social media as well as their encounters with wellbeing and health related content on social media specifically. We were open to participants’ own interpretations of what counted as a social media platform and as everyday health and well-being content, meaning that participants defined this in a way that was most relevant to their own lived experience. Interviews therefore referred to a wide variety of health topics that were of personal or general interest to the participant, including (but not limited to) nutrition and diet, skincare, fitness, mental health, sexual health, specific illnesses, public health messaging (Covid-19), vaccination and medical science. The main social media platforms that participants talked about and engaged with in the interview setting were Instagram, YouTube, TikTok, and Facebook, although others were mentioned. Participants often showed the interviewer examples of content on their personal phones, and the interviewer would take photographs of phone screens during the interview. The photographs taken have not been included in the archive for reasons of participant confidentiality.
The collection contains the project's Interview Guide, Consent Form and Information Letter, as approved by The Departmental Research Ethics Committee for the School of Geography and the Environment, University of Oxford (ID: C1A-23-09).The ongoing crisis of trust in specific institutions (government, media, healthcare system) is often blamed for many of the social, cultural and political problems European societies are currently facing. While many researchers are exploring the relations between trust, technology and misinformation, we need to understand how trust is practiced in our everyday, ordinary lives and media practices.
Trust And Visuality - Everyday digital practices (TRAVIS) is a research project that explored how people experience, build and express trust in social media images related to wellbeing and health.
We chose this focus for three reasons: First, humans experience visual information as more trustworthy than other communicative modes. Second, while trust continues to be crucial for social life, it is significantly complicated by our increasing reliance on online communication, where we have to infer our communication partners and their intentions from their on-screen representations and algorithmic manipulation. And finally, the pandemic showed us that visual digital representations related to our individual (step counts, recovery selfies) and collective (visualisations of infection rates) experiences of health are increasingly central to our lives. This makes every day, visual social media communication of health news and personal health content the perfect case study to understand trust.
Thus, TRAVIS investigated how and why people trust some visuals over others, and how content-creators and professionals create trustworthiness with and through digital visual content. Our research was undertaken in four different cultural contexts – Austria, Estonia, Finland and the UK – allowing us to combine perspectives from Nordic, Eastern-European/Post-Soviet, Anglo-Saxon and Germanic cultures, each with their own traditions and norms of trust as well as significant differences in how much institutions are trusted.</p
Children of the 2020s: Wave 1, 2021-2022: Secure Access
No full textAbstract copyright UK Data Service and data collection copyright owner.Children of the 2020s (COT20s), also known as Education and Outcomes Panel Studies (EOPS) Early Years, is a Department for Education (DfE)-funded study focusing on early childhood. It follows a random probability sample of 8,500 children, starting from the age of 9 months in 2022, with plans to conduct annual data collection until the age of 5 years. Data are currently only available for Wave 1.The study gathers evidence via questionnaires about parents/carers and their children's background, behaviours and experiences. The study will build up rich statistical evidence of the highest standard to enable varied analyses and intends to improve our understanding of factors associated with variations in intermediate and longer-term learning and wellbeing outcomes for different groups of children.The sample for the COT20s study was selected from HMRC Child Benefit records for all registered births between September and November 2021. The sample was designed to boost the sample in the most deprived quintile of areas, in order to ensure a large enough sub-sample for analysis of families experiencing economic deprivation. The over-sampling was based on the aggregated Income Deprivation Affecting Children Index scores for lower super output areas.Main Topics:Key topics for data collection include:child developmental outcomesthe home environmentparental mental health, wellbeing, relationship quality, social support, demographics and contextual/community variablesprovision/use of servicesexperiences and life events.</ul
Scotland's Census 2022: Safeguarded Individual Microdata Sample at Grouped Local Authority Level
No full textAbstract copyright UK Data Service and data collection copyright owner.The 2021 UK Census was the 23rd official census of the United Kingdom. The UK Census is generally conducted once every 10 years, and the 2021 censuses of England, Wales, and Northern Ireland took place on 21 March 2021. In Scotland, the decision was made to move the census to March 2022 because of the impact of the coronavirus pandemic (see SNs 9461 and 9462). The censuses were administered by the Office for National Statistics (ONS), the Northern Ireland Statistics and Research Agency (NISRA) and National Records of Scotland (NRS), respectively. Census 2021 was the first census with a digital-first design, encouraging participants to respond online rather than on a paper questionnaire. Support was given to people who could not respond online, including paper questionnaires, telephone contact centres, field force support, and an extended collection period.Topics covered in the 2021 UK Census included:demography and migrationethnic group, national identity, language and religionlabour market and travel to workhousingeducationhealth, disability, and unpaid careWelsh and other languagesUK armed forces veteranssexual orientation and gender identity.The Scotland's Census 2022: Safeguarded Individual Microdata Sample at Grouped Local Authority Level dataset consists of a random sample of 5% of person records from the 2022 Census. It includes records for 274,068 persons. These data cover Scotland only. The lowest level of geography is grouped local authority. This means groups of local authorities or single local authorities where the population reaches at least 120,000 persons. The dataset contains 72 variables and a medium level of detail. Further information can be found on the Scotland's Census website.
Census Microdata
Microdata are small samples of individual records from a single census from which identifying information have been removed. They contain a range of individual and household characteristics and can be used to carry out analysis not possible from standard census outputs, such as:
creating tables using bespoke variable combinationsinvestigating specific combinations of variables or categories in a high level of detailconducting non-tabular statistical analyses on record-level data.
The microdata samples are designed to protect the confidentiality of individuals and households. This is done by applying access controls and removing information that might directly identify a person, such as names, addresses and date of birth. Record swapping is applied to the census data used to create the microdata samples. This is a statistical disclosure control (SDC) method, which makes very small changes to the data to prevent the identification of individuals. The microdata samples use further SDC methods, such as collapsing variables and restricting detail. The samples also include records that have been edited to prevent inconsistent data and contain imputed persons, households, and data values. To protect confidentiality, imputation flags are not included in any 2022 Census microdata sample.Main Topics:The Scotland's Census 2022: Safeguarded Individual Microdata Sample at Grouped Local Authority Level dataset covers: communal establishments, demography, education, ethnicity, identity, language, religion, health, disability, unpaid care, housing, internal migration, international migration, labour market, students, and travel to work.</p
Interviews with Managers, Employees and Other Stakeholders on Automation Processes in Knowledge-Intensive Business Services, UK and Germany, 2022-2023
No full textThe data consist of information from 27 semi-structured interview sessions (two interviewees were interviewed twice) between March 2022 and March 2023. Data collection began around two focal cases - two major banks, one in the UK and one in Germany, which remain anonymous for reasons of confidentiality. In addition, we conducted interviews with participants from a variety of service organisations in the field, including competitor banks, other service companies engaged in automation, automation vendors, other financial services companies, consulting companies, and representatives from professional and trade union associations.This project gathered data on Robotic Process Automation as a technology and how it affects workers’ employment and skills. It investigated whether and how the institutional context influences the adjustment to automation via re-skilling, redeployment, or redundancies. It focused on knowledge-intensive services, such as financial services, which are undergoing a massive digital transformation of their back-office operations. Drawing on the inter-disciplinary expertise of the investigators, it will contribute to theory and evidence on (1) the characteristics of automation, its effects on the work restructuring and workers’ skill-mix; and (2) the national/sectoral institutional responses and the reconfiguration of sectoral ecosystems and business models. The comparative research design and institutional analysis in the UK and Germany will contribute to DIGIT’s objectives, while the investigators aspire to co-create knowledge with external users and stakeholders so that they produce impactful and relevant findings.</p
The Mental Health of Children and Young People Growing Up in State Care in England, 2020-2021
No full textThis collection contains the self-reported survey data from young people in State care aged 11-18 years. The survey was conducted in 2020 and repeated in 2021. The Wave 1 survey data contains information on 905 children and young people in care from 18 local authorities (LAs) in England. The Wave 2 survey data contains information on 681 children and young people in care from 14 LAs in England. Of these, 262 children and young people responded to both the Wave 1 and 2 survey.Around two-thirds of children are taken into State care due to experiences of severe maltreatment such as abuse or neglect. Consequently, being taken into care is an ‘intervention’ for this vulnerable group of children, with the expectation that State care will then ameliorate or stabilise their mental health. Despite this, numerous research studies indicate that mental health concerns in this vulnerable child population remains very high. Mental ill health experienced in childhood and adolescence impacts the short and long-term health, well-being, socioeconomic trajectories and family life of children and young people. This also exerts pressure and a financial toll on the health and social care systems, and the State through its impact on mental health services, the cost of interventions and pressure on State benefits systems. To facilitate recovery and better mental health, it is important to understand if and how the mental health of children in care varies over time and the contextual factors that influence their mental health.
The two linked ESRC-funded research studies set out to answer these questions, through (1) a 5-year longitudinal follow-up of the mental health of children in care in England through secondary analyses of longitudinal, national-level administrative data (2016-2021) and (2) a survey of children and young people aged 11-18 years in care in 2020 (Wave 1) and 2021 (Wave 2).
This collection contains the self-reported survey data from young people in State care aged 11-18 years. The survey was conducted in 2020 and repeated in 2021. The Wave 1 survey contains information on 905 children and young people in care from 18 local authorities (LAs) in England. The Wave 2 survey data contains information on 681 children and young people in care from 14 LAs in England. Of these, 262 children and young people responded to both the Wave 1 and 2 survey.</p
Cancer Research UK Local Cancer Awareness Measure: Leicester, Leicestershire and Rutland (LLR), April-August 2024
No full textAbstract copyright UK Data Service and data collection copyright owner.The Cancer Awareness Measure (CAM) was developed in 2007-8 to address the absence of a validated measure of general public awareness of cancer (Stubbings, S., Robb, K., Waller, J., Ramirez, A., Austoker, J., Macleod, U., Hion, S., and Wardle, J. (2009) 'Development of a measurement tool to assess public awareness of cancer', British Journal of Cancer, 101(2), S13-S17.).The survey includes measures of awareness of signs and symptoms of cancer, cancer risk factors, age-related risk, screening programmes and potential barriers to seeing the GP. Since then, Cancer Research UK (CRUK) has significantly revised and updated the survey, including a wider range of questions and collecting data online instead of face-to-face. The CAM was also previously known as the National Awareness and Early Diagnosis Initiative Cancer Awareness Measure (NAEDI-CAM).In 2023-2024 Cancer Research UK ran two Local Cancer Awareness Measure Plus (CAM+) pilots, collecting data in two local regions (Greater Manchester and Leicester, Leicestershire and Rutland (LLR)) using both an online panel and community sampling to recruit participants. The Greater Manchester pilot Local CAM+ datasets are available under SNs 9342 and 9358.The LLR pilot Local CAM+ dataset does not include National CAM+ questions on alcohol consumption, physical activity, perception of health services capacity and closeness to cancer. However, it includes additional questions on possible facilitators for cancer screening attendance and willingness to travel for hospital tests.A Special Licence version of this data, including more geography and demographic variables, is available under SN 9359.Further information about the CAM+ may be found on the Cancer Research UK Cancer Awareness Measure Plus (CAM+) webpage.Main Topics:The CAM questionnaire addressed the following topics:public awareness of cancer symptomspublic knowledge of cancer risk factorsbarriers and enablers to help seekinguptake of screening programmesbarriers to cancer screening (cervical, breast and bowel)experience of breast and cervical cancer screeningsymptom experienceco-morbiditiesperception of symptom seriousnesshelp seeking behaviours including remote consultation and re-presentationperceptions of remote consultationdemographic variables including health behaviours such as smoking.</div
Dietary Intake in Scotland's CHildren (DISH), 2024
No full textAbstract copyright UK Data Service and data collection copyright owner.Dietary Intake in Scotland's CHildren (DISH) was a cross-sectional representative survey conducted in Scotland in 2024. Commissioned by Food Standards Scotland and led by the University of Edinburgh, the survey provides information on aspects of dietary intake in children and young people aged 2 to 15 years living in Scotland. Diet data were collected using an online platform called Intake24. Up to four 24-hour dietary recalls were collected from each child. Diets were reported by parents/guardians for children in pre-school or primary school. Children in secondary school had the opportunity to report their own diets, and answer additional questions on purchasing food and drink off school grounds during their lunch break, using food delivery apps and consumption of energy drinks. Parents/guardians also answered questions on food insecurity. The final sample was 1,700 children and young people.Data labelsSPSS and Stata users: variable labels have been added to the data files, but value labels can be found in the codebook in the documentation. The data were deposited in CSV format, which is also available for download.Main Topics:</p