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Living Costs and Food Survey, 2022-2023
No full textAbstract copyright UK Data Service and data collection copyright owner.Background:
A household food consumption and expenditure survey has been conducted each year in Great Britain (excluding Northern Ireland) since 1940. At that time the National Food Survey (NFS) covered a sample drawn solely from urban working-class households, but this was extended to a fully demographically representative sample in 1950. From 1957 onwards the Family Expenditure Survey (FES) provided information on all household expenditure patterns including food expenditure, with the NFS providing more detailed information on food consumption and expenditure. The NFS was extended to cover Northern Ireland from 1996 onwards. In April 2001 these surveys were combined to form the Expenditure and Food Survey (EFS), which completely replaced both series. From January 2008, the EFS became known as the Living Costs and Food (LCF) module of the Integrated Household Survey (IHS). As a consequence of this change, the questionnaire was altered to accommodate the insertion of a core set of questions, common to all of the separate modules which together comprised the IHS. Some of these core questions are simply questions which were previously asked in the same or a similar format on all of the IHS component surveys. For further information on the LCF questionnaire, see Volume A of the LCF 2008 User Guide, held with SN 6385. Further information about the LCF, including links to published reports based on the survey, may be found by searching for 'Living Costs and Food Survey' on the ONS website. Further information on the NFS and Living Costs and Food Module of the IHS can be found by searching for 'Family Food' on the GOV.UK website.
History:
The LCF (then EFS) was the result of more than two years' development work to bring together the FES and NFS; both survey series were well-established and important sources of information for government and the wider community, and had charted changes and patterns in spending and food consumption since the 1950s. Whilst the NFS and FES series are now finished, users should note that previous data from both series are still available from the UK Data Archive, under GNs 33071 (NFS) and 33057 (FES).
Purpose of the LCF
The Office for National Statistics (ONS) has overall project management and financial responsibility for the LCF, while the Department for Environment, Food and Rural Affairs (DEFRA) sponsors the food data element. As with the FES and NFS, the LCF continues to be primarily used to provide information for the Retail Prices Index, National Accounts estimates of household expenditure, analysis of the effect of taxes and benefits, and trends in nutrition. The results are multi-purpose, however, providing an invaluable supply of economic and social data. The merger of the two surveys also brings benefits for users, as a single survey on food expenditure removes the difficulties of reconciling data from two sources.
Design and methodology
The design of the LCF is based on the old FES, although the use of new processing software by the data creators has resulted in a dataset which differs from the previous structure. The most significant change in terms of reporting expenditure, however, is the introduction of the European Standard Classification of Individual Consumption by Purpose (COICOP), in place of the codes previously used. An additional level of hierarchy has been developed to improve the mapping to the previous codes. The LCF was conducted on a financial year basis from 2001, then moved to a calendar year basis from January 2006 (to complement the IHS) until 2015-16, when the financial year survey was reinstated at the request of users. Therefore, whilst SN 5688 covers April 2005 - March 2006, SN 5986 covers January-December 2006. Subsequent years cover January-December until 2014. SN 8210 returns to the financial year survey and currently covers April 2015 - March 2016.
Northern Ireland sample
Users should note that, due to funding constraints, from January 2010 the Northern Ireland (NI) sample used for the LCF was reduced to a sample proportionate to the NI population relative to the UK.
Family Food database:
'Family Food' is an annual publication which provides detailed statistical information on purchased quantities, expenditure and nutrient intakes derived from both household and eating out food and drink. Data is collected for a sample of households in the United Kingdom using self-reported diaries of all purchases, including food eaten out, over a two week period. Where possible quantities are recorded in the diaries but otherwise estimated. Energy and nutrient intakes are calculated using standard nutrient composition data for each of some 500 types of food. Current estimates are based on data collected in the Family Food Module of the LCFS. Further information about the LCF food databases can be found on the GOV.UK Family Food Statistics web pages.
Secure Access version
A Secure Access version of the LCF from 2006 onwards is available from the UK Data Archive under SN 7047, subject to stringent access conditions. The Secure Access version includes variables that are not included in the standard End User Licence (EUL) version, including geographical variables with detail below Government Office Region, to postcode level; urban/rural area indicators; other sensitive variables; raw diary information files (derived variables are available in the EUL) and the family expenditure codes files. Users are strongly advised to check whether the EUL version is sufficient for their needs before considering an application for the Secure Access version.Occupation data for 2021 and 2022 data filesThe ONS have 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. None of
ONS' headline
statistics, other than those directly sourced from occupational data,
are affected and you
can continue to rely on their accuracy. For further information on this
issue, please see:
https://www.ons.gov.uk/news/statementsandletters/occupationaldatainonssurveys.
Latest edition informationFor the fourth edition (July 2025), an updated version of the DEFRA Family Food database has been added to the study. Tables covering a065p (Age of HRP by range - anonymised), a069p (Type of household - Anonymised) and a094 (NS-SEC 12 Class of HRP) have been added, and the variable EqIncDOp (Equivalised income (OECD Scale) - anonymised) has been added to the EFShousehold table. A guide to the additional variables has been added to the documentation.Main Topics:Household questionnaire:
The first part of the LCF questionnaire collects information about households; the majority of the questions are asked at a household-level, with the household reference person typically responding on behalf of the household as a whole. The household questionnaire includes questions on a range of subjects including family relationships, ethnicity, employment details and the ownership of household durables. It is also the source of all expenditure information not recorded in the LCF diary; principally that which concerns regular payments typically made by all households and large, infrequently purchased items such as vehicles, package holidays and home improvements.
Individual questionnaire:
The income questionnaire follows on immediately from the household questionnaire and collects the key person-level variables used on the survey. The principal components of the LCF income questionnaire are the sections covering income from employment, benefits and assets. These together form an overview of the total income received by each household, as well as each household member individually.
LCF Diary:
In addition to the two questionnaires, each individual aged 16 years and over in the household is asked to keep diary records of daily expenditure for two weeks. The EUL version includes only derived variables from the expenditure diary
Quarterly Labour Force Survey, April - June, 2025
No full textAbstract copyright UK Data Service and data collection copyright owner.BackgroundThe 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 Annual Population Survey, also held at the UK Data Archive, is derived from the LFS.The LFS was first conducted biennially from 1973-1983, then annually between 1984 and 1991, comprising a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter. From 1992 it moved to a quarterly cycle with a sample size approximately equivalent to that of the previous annual data. Northern Ireland was also included in the survey from December 1994. Further information on the background to the QLFS may be found in the documentation.The UK Data Service also holds a Secure Access version of the QLFS (see below); household datasets; two-quarter and five-quarter longitudinal datasets; LFS datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.LFS DocumentationThe 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 (the latest questionnaire available covers July-September 2022). Volumes are updated periodically, 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.LFS response to COVID-19From April 2020 to May 2022, additional non-calendar quarter LFS microdata were made available to cover the pandemic period. The first additional microdata to be released covered February to April 2020 and the final non-calendar dataset covered March-May 2022. Publication then returned to calendar quarters only. Within the additional non-calendar COVID-19 quarters, pseudonymised variables Casenop and Hserialp may contain a significant number of missing cases (set as -9). These variables may not be available in full for the additional COVID-19 datasets until the next standard calendar quarter is produced. The income weight variable, PIWT, is not available in the non-calendar quarters, although the person weight (PWT) is included. Please consult the documentation for full details.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 2022.2024 ReweightingIn February 2024, reweighted person-level data from July-September 2022 onwards were released. Up to July-September 2023, only the person weight was updated (PWT23); the income weight remains at 2022 (PIWT22). The 2023 income weight (PIWT23) was included from the October-December 2023 quarter. Users are encouraged to read the ONS methodological note of 5 February, Impact of reweighting on Labour Force Survey key indicators: 2024, which includes important information on the 2024 reweighting exercise.End User Licence and Secure Access QLFS dataTwo versions of the QLFS are available from UKDS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes country and Government Office Region geography, 3-digit Standard Occupational Classification (SOC) and 3-digit industry group for main, second and last job (from July-September 2015, 4-digit industry class is available for main job only).The Secure Access version contains more detailed variables relating to:age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent childfamily unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of familynationality and country of originfiner detail geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district, and other categories;health: including main health problem, and current and past health problemseducation and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeshipsindustry: including industry, industry class and industry group for main, second and last job, and industry made redundant fromoccupation: including 5-digit industry subclass and 4-digit SOC for main, second and last job and job made redundant fromsystem variables: including week number when interview took place and number of households at addressother additional detailed variables may also be included.The Secure Access datasets (SNs 6727 and 7674) have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.Latest edition informationFor the second edition (September 2025), the variables YLESS20 and subsequent derived variable DIFFHR20 have been replaced. The new versions include previously missing imputed values for 'IOUTCOME=6' cases.Main Topics:The QLFS questionnaire comprises a 'core' of questions which are included in every survey, together with some 'non-core' questions which vary from quarter to quarter.The questionnaire can be split into two main parts. The first part contains questions on the respondent's household, family structure, basic housing information and demographic details of household members. The second part contains questions covering economic activity, education and health, and also may include a few questions asked on behalf of other government departments (for example the Department for Work and Pensions and the Home Office). Until 1997, the questions on health covered mainly problems which affected the respondent's work. From that quarter onwards, the questions cover all health problems. Detailed questions on income have also been included in each quarter since 1993. The basic questionnaire is revised each year, and a new version published, along with a transitional version that details changes from the previous year's questionnaire.</div
Next Generation: United Kingdom, 2024
No full textAbstract copyright UK Data Service and data collection copyright owner.The British Council Next Generation research series uncovers the aspirations and needs of young people around the world, focusing on countries that are experiencing significant change. It aims to ensure that young people’s interests are properly represented in policies that are impacting their lives and shaping their futures.Next Generation: United Kingdom, 2024 was a nationally representative survey conducted to explore the attitudes, values, and aspirations of young people in the UK aged 18-30. Conducted by Savanta via an online survey between 16 July and 7 August 2024, this study captured the views and experiences of 3,084 young people across the UK. It focused on three key thematic areas: Youth Lifestyles and Attitudes; Youth Voice, including political and civic engagement; and Education, Skills, and Employment. Using a stratified random sampling approach, the survey aimed to reflect the demographic diversity of the UK youth population. Responses were collected using the standardised Next Generation Questionnaire and have undergone data cleaning and coding for accuracy and consistency. The study provides a valuable resource for understanding the priorities, challenges, and aspirations of young people in the UK in 2024.Main Topics:Youth Lifestyles and Attitudes; Youth Voice, including political and civic engagement; and Education, Skills, and Employment.</p
Understanding Society: Calendar Year Dataset, 2023
No full textAbstract copyright UK Data Service and data collection copyright owner.Understanding Society, (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.The Understanding Society: Calendar Year Dataset, 2023, is designed for analysts to conduct cross-sectional analysis for the 2023 calendar year. The Calendar Year datasets combine data collected in a specific year from across multiple waves and these are released as separate calendar year studies, with appropriate analysis weights, starting with the 2020 Calendar Year dataset. Each subsequent year, an additional yearly study is released.
The Calendar Year data is designed to enable timely cross-sectional analysis of individuals and households in a calendar year. Such analysis can however, only involve variables that are collected in every wave (excluding rotating content which is only collected in some of the waves). Due to overlapping fieldwork the data files combine data collected in the three waves that make up a calendar year. Analysis cannot be restricted to data collected in one wave during a calendar year, as this subset will not be representative of the population. Further details and guidance on this study can be found in the xxxx_main_survey_calendar_year_user_guide_2023.
These calendar year datasets should be used for cross-sectional analysis only. For those interested in longitudinal analyses using Understanding Society please access the main survey datasets: Safeguarded (End User Licence) version or Safeguarded/Special Licence version.
Understanding Society: the UK Household Longitudinal Study, started in 2009 with a general population sample (GPS) of UK residents living in private households of around 26,000 households and an ethnic minority boost sample (EMBS) of 4,000 households. All members of these responding households and their descendants became part of the core sample who were eligible to be interviewed every year. Anyone who joined these households after this initial wave, were also interviewed as long as they lived with these core sample members to provide the household context. At each annual interview, some basic demographic information was collected about every household member, information about the household is collected from one household member, all 16+ year old household members are eligible for adult interviews, 10-15 year old household members are eligible for youth interviews, and some information is collected about 0-9 year olds from their parents or guardians. Since 1991 until 2008/9 a similar survey, the British Household Panel Survey (BHPS), was fielded. The surviving members of this survey sample were incorporated into Understanding Society in 2010. In 2015, an immigrant and ethnic minority boost sample (IEMBS) of around 2,500 households was added. In 2022 a GPS boost sample (GPS2) of around 5,700 households was added. To know more about the sample design, following rules, interview modes, incentives, consent, questionnaire content please see the study overview and user guide.
Co-funders
In addition to the Economic and Social Research Council, co-funders for the study included the Department of Work and Pensions, the Department for Education, the Department for Transport, the Department of Culture, Media and Sport, the Department for Community and Local Government, the Department of Health, the Scottish Government, the Welsh Assembly Government, the Northern Ireland Executive, the Department of Environment and Rural Affairs, and the Food Standards Agency.
End User Licence and Special Licence versions:
There are two versions of the Calendar Year 2023 data. One is available under the standard End User Licence (EUL) agreement, and the other is a Special Licence (SL) version. The SL version contains month and year of birth variables instead of just age, more detailed country and occupation coding for a number of variables and various income variables have not been top-coded (see document '9471_eul_vs_sl_variable_differences' for more details). Users are advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. The SL data have more restrictive access conditions; prospective users of the SL version will need to complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables in order to get permission to use that version. The main longitudinal versions of the Understanding Society study may be found under SNs 6614 (Safeguarded (EUL)) and 6931 (Safeguarded/SL).
Low- and Medium-level geographical identifiers produced for the mainstage longitudinal dataset can be used with this Calendar Year 2023 dataset, subject to SL access conditions. See the User Guide for further details.
Suitable data analysis software
These data are provided by the depositor in Stata format. Users are strongly advised to analyse them in Stata. Transfer to other formats may result in unforeseen issues. Stata SE or MP software is needed to analyse the larger files, which contain about 1,800 variables.Main Topics:The survey instrument is constructed with modules. For a fuller listing of modules and questionnaire content see the User Manual or the online documentation system. The household grid or enumeration grid has a listing of all household members with information about gender, date of birth, marital and employment status, and relationship to the household respondent. The household questionnaire has questions about housing, mortgage or rent payments, material deprivation, and consumer durables and cars. The individual adult interview is asked of every person in the household aged 16 or over. It has questions about demographics, baseline information, family background, ethnicity and language use; migration, partnership and fertility histories; health, disability and caring; current employment and earnings; employment status; parenting and childcare arrangements; family networks; benefit payments; political party identification; household finances; environmental behaviours; consents to administrative data linkage. A proxy module is a much-shortened version of the individual questionnaire that collects demographic, health and employment information, as well as a summary income measure. It is completed by one person on behalf of another. Those who completed an individual adult interview also complete a self-completion questionnaire. It includes subjective questions, particularly those which are potentially sensitive or require more privacy. For example, feelings of depression (GHQ-12) and well-being, sleep behaviour, environmental attitudes and beliefs, neighbourhood participation and belonging, life satisfaction, activities with partner and relationship quality. A youth self-completed questionnaire is completed by 10-15 year olds. It includes questions on computer and technology use, family support, sibling relationships, feelings about areas of life, Strengths and Difficulties Questionnaire, health behaviours, smoking and drinking, and aspirations.</p
Kids' Life and Times Survey, 2025
No full textAbstract copyright UK Data Service and data collection copyright owner.The Kids' Life and Times Survey (KLT) began in 2008 and is conducted by Access Research Knowledge (ARK) which runs the Northern Ireland Life and Times Survey (NILT) and the Young Life and Times Survey (YLT). The KLT is a survey of Primary year 7 (P7) children in Northern Ireland which is carried out online and in school. (Note that NILT did not run in 2011, but resumed in 2012. The KLT and YLT both ran as normal in 2011.)
The aims of the KLT are to:provide broad-based monitoring systems to examine children's views on policy issues on a regular basisensure that the information from the survey is fed back to policymakers and others engaged in the policy debates around children and their livesprovide a high profile endorsement of 'participation' by Northern Ireland's childrenFurther information about KLT, including the comic-style publication with key results especially designed for children, may be found on the ARK main Kids' Life and Times Survey web pages.Main Topics:In 2025 the following topics were included in the survey: Home and family; School and bullying; Respect and disrespect; Mental Health; The Environment.</p
Modelling the Cross-Linguistic Pattern of Verb-Marking Deficits in Children With Developmental Language Disorder, 2019-2025
No full textWP1.3 - Modelling the cross-linguistic pattern of verb-marking deficits in children with developmental language disorder Daniel Freudenthal, Fernand Gobet, Larry Leonard and Julian Pine (Lead)
This work package is a modelling project, which uses existing publicly available corpora of naturalistic speech to test different hypotheses about the way typically developing children and children with DLD acquire language (and in particular) verb inflection. Since no behavioural data were collected, there are no spreadsheets of behavioural data to upload. However, where possible, we provide relevant scripts and output and analysis files for the 4 studies that make up the work package.
These files are organised into three folders as follows:
1. Language Learning Paper contains files relating to a study of the effect of adding a defaulting mechanism to MOSAIC – a computational model of the cross-linguistic pattern of verb-marking error. A paper describing this model has been published in Language Learning:
https://onlinelibrary.wiley.com/doi/10.1111/lang.12580
2. Rescorla Paper contains files relating to a study that uses a modified version of the classic Rescorla-Wagner model to simulate differences in the ease with which both TD children and children with DLD master English and Spanish verb inflection. The simulations show that these differences can be understood in terms of the interaction between a deficit in sequential learning ability and the structure and statistics of English and Spanish child-directed speech. A paper describing this work has been published in Cognitive Science.
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/cogs.12945
3. Deep learning contains files relating to a series of studies in which we investigated the suitability of modern Generative AI models to simulate aspects of language acquistion in both typically developing children and in children with DLD. This work has been published in the proceedings of the Annual Conference of the Cognitive Science society and can be found at the following links:
https://escholarship.org/content/qt9gr4v5rb/qt9gr4v5rb.pdf
https://escholarship.org/content/qt3pg3q39r/qt3pg3q39r.pd
Annual Population Survey, January - December, 2024
No full textAbstract copyright UK Data Service and data collection copyright owner.The Annual Population Survey (APS) is a major survey series, which aims to provide data that can produce reliable estimates at the local authority level. Key topics covered in the survey include education, employment, health and ethnicity. The APS comprises key variables from the Labour Force Survey (LFS), all its associated LFS boosts and the APS boost. The APS aims to provide enhanced annual data for England, covering a target sample of at least 510 economically active persons for each Unitary Authority (UA)/Local Authority District (LAD) and at least 450 in each Greater London Borough. In combination with local LFS boost samples, the survey provides estimates for a range of indicators down to Local Education Authority (LEA) level across the United Kingdom.For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.Occupation data for 2021 and 2022The 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. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. The affected datasets have now been updated. 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 2022APS Well-Being DatasetsFrom 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Further information on the transition can be found in the Personal well-being in the UK: 2015 to 2016 article on the ONS website.APS disability variablesOver time, there have been some updates to disability variables in the APS. An article explaining the quality assurance investigations on these variables that have been conducted so far is available on the ONS Methodology webpage. End User Licence and Secure Access APS dataUsers should note that there are two versions of each APS dataset. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes Government Office Region geography, banded age, 3-digit SOC and industry sector for main, second and last job. The Secure Access version contains more detailed variables relating to:
age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child
family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family
nationality and country of origin
geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district
health: including main health problem, and current and past health problems
education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships
industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from
occupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant from
system variables: including week number when interview took place and number of households at address
The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.Latest edition informationFor the third edition (December 2025), smoking variables were added to the dataset.Main Topics:Topics covered include: household composition and relationships, housing tenure, nationality, ethnicity and residential history, employment and training (including government schemes), workplace and location, job hunting, educational background and qualifications. Many of the variables included in the survey are the same as those in the LFS.<br
Development of the Social Response Biases in Loneliness for Young Adults Scale: Rooting Scale Development in Young Peoples’ Lived Experiences, 2022
No full textYouth loneliness is common and associated with poorer health and wellbeing. Chronic loneliness could arise from a cognitive bias towards forming threatening over benign interpretations of social situations, leading to a behavioural bias favouring social withdrawal over social approach, thereby facilitating and maintaining persistent loneliness. We have developed an age-appropriate assessment tool, the Social Response Biases in Loneliness for Young Adults (SRBL-YA), for measuring these cognitive and behavioural biases. The SRBL-YA consists of 12 open-ended ambiguous loneliness-relevant scenarios that are followed by both a negative and a positive resolution to the scenario. When completing the SRBL-YA, one rates the likelihood of each of the resolutions occurring, on a 5-point Likert scale, from “extremely unlikely” to “extremely likely”.
The data presented here consists of an online survey, collected for the purpose of examining the psychometric properties of the SRBL-YA. Specifically, the factor structure of the SRBL-YA and its association with loneliness, depression, anxiety and social anxiety were examined in a sample of University students (n=416).
Confirmatory factor analysis indicated that a 7-item scale may improve upon the 12-item version, however, the reliability of both versions was somewhat low (α = 0.68-0.81). Both versions of the SRBL-YA showed convergent validity with loneliness, even when accounting for depressive, anxiety and social anxiety symptoms, but require further validation in independent samples.Loneliness is a negative emotion that occurs when one perceives his/her social relationships and networks to fall short of his/her social needs. Because loneliness is thought to have evolved as a powerful motivator to connect with others and solicit their support, it may arise during periods of life that are characterised by social turbulence. One such period is youth, where there are major changes in the external social environment such as the amount of time spent with peers and in the emergence of new peer hierarchies and cliques - but also in internal factors, such as the need for peer approval and the aversiveness of peer rejection. Accordingly, as these social changes may bring about instability in social relationships, loneliness can arise to facilitate re-connection with others, and therefore be considered a normal part of growing up for many young people. However for some young people loneliness can be intense, upsetting and persistent, predicting poorer mental and physical health. Delivering interventions to manage loneliness in youth is therefore crucial, made more so as this may reflect a period of plasticity for learning more effective ways of regulating emotions. As some negative thinking styles such as a tendency to endorse threatening over benign expectations and explanations of ambiguous social situations is associated with youth loneliness, measuring and targeting these earlier in life may be a powerful 'vaccine' for reducing the risk of loneliness.
However before any early interventions programs are planned around the targeting of threat interpretations, there are some key questions that need to addressed. First there is only one study showing that threat interpretations precede and predict risk for loneliness rather than reflect consequences. Disentangling these roles may inform whether it is useful to modify threat interpretations in order to alter loneliness. In addition it is not clear whether threat interpretations affect loneliness by influencing social withdrawal behaviour, as theories would suggest. Second all studies investigating threat interpretations in relation to loneliness have used questionnaires about hypothetical social scenarios rather than directly assess thoughts to real-life events. Establishing the relationship between threat interpretations and loneliness in everyday life is important, again for informing whether it is helpful to modify these thinking styles to alter lonely feelings. Finally, although methods have been developed for challenging threat interpretations related to other social behavioural problems like social anxiety, it is not clear if these methods are as relevant to and well tolerated by young people who are lonely.
The goals of this research are to address these questions. Three studies will be performed. First a longitudinal study of around 1000 young people will be conducted to examine the cross-time relationships between threat interpretations, social withdrawal and loneliness with a nested interview study supplementing quantitative data. Second an ecological momentary assessment study that assesses threat interpretations to real social situations and loneliness at several times in the day for a week will be conducted to investigate these relationships in daily life. Finally, together with some young people we will develop some materials for a training program that aims to modify threat interpretations. These will then be presented to another group of young people to assess for relevance, acceptability and how helpful and feasible such an intervention is. Potential effectiveness at reducing loneliness and threat interpretations, and changing social behaviour will be considered.
The data deposited here were generated during the project in addition to the studies described above. When developing the materials for the training program targeting threat interpretations in loneliness, we generated additional materials that we decided to use to develop a new age-appropriate questionnaire for measuring biases in cognitive and behavioural responses to social situations that are relevant to loneliness in young people: the Social Response Biases in Loneliness for Young Adults scale (SRBL-YA). The analyses which were conducted using this dataset aimed to examine the psychometric properties of the SRBL-YA.
These studies will generate data to support further investigation into cognitive interventions for youth
loneliness and contribute to the national dialogue on loneliness between professionals/practitioners working with youth, policymakers, the public and young people themselves.</p
2021 Census: Flow Data
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.Census flow data involve flows of individuals in the UK between origins and destinations. These flows are either the residential migrations of individuals from one place of usual residence to another, or of commuters making journeys from home to workplace or place of study.
These data are derived from the questions on the census form relating to usual place of residence one year ago, and the place of work for the respondent's main job. Flow data are currently available at a range of different spatial scales ranging from Output Areas to Local Authority Districts.
Main Topics:The Census Support: Flow Data website facilitates access to the interaction data for members of UK higher and further education institutions. Access is provided through the Web-based Interface to Census Interaction Data (WICID).Explicit registration is not required for the 2021 Census products that have been released under the Open Government Licence. However, outputs from the 2021 Census classified as 'Safeguarded' require users to agree on additional terms and conditions. Access to these datasets is only permitted via Federated Access.
The Flow Data website provides two basic routes to the data.WICID is the main route to the flow data. It provides a flexible service to download extracts of data in a variety of forms;the Downloads page allows users to download the original tables as released by ONS and NISRA.Access data through the WICID Flow Data website.
View the Census flow data guide
Harmonised Asthma in the MRC National Survey of Health and Development, 1952-2021: Special Licence Access
No full textAbstract copyright UK Data Service and data collection copyright owner.The Harmonised Data in Five National Longitudinal Cohort Studies project, supported by the Economic and Social Research Council (ESRC), brings together data from five British cohort studies: the 1946 National Survey of Health and Development (NSHD), the 1958 National Child Development Survey (NCDS), the 1970 British Cohort Study (BCS70), Next Steps (formerly the Longitudinal Study of Young People in England), and the Millennium Cohort Study (MCS). NCDS, BCS70, Next Steps, and MCS receive core funding from the ESRC and are hosted by the Centre for Longitudinal Studies at UCL. NSHD is funded by the Medical Research Council (MRC) and is hosted by the Unit for Lifelong Health and Ageing at UCL.The Asthma Harmonisation project aimed to document all self-reported measures related to asthma in these five British cohort studies and produce harmonised indicators of self-reported asthma through retrospective harmonisation. This harmonisation serves two primary purposes: improving the measurement of asthma (as an outcome, predictor, or control variable) within cohort analyses, and facilitating cross-cohort research on asthma using these rich datasets.Separate longitudinal datasets were created for each cohort, focusing on self-reported data and some measures derived from doctors' reports and medical records. Biomarkers and linked health data were not included. Focus was given to measures that were administered to entire cohorts only and on the asthma status of cohort members themselves (not their parents).SN 9420 includes harmonised asthma data for the MRC National Survey of Health and Development only. Harmonised asthma data for NCDS, BCS70, Next Steps and MCS are available under Safeguarded data access from SN 9417.Main Topics:Harmonised indicators of self-reported asthma in the 1946 NSHD and includes sweep-specific indicators and derived cumulative indicators.The research IDs differ from the original research IDs and data can therefore not be merged with other NSHD data files. Access to the harmonised variables in connection with other NSHD variables can be requested via the usual NSHD data sharing request.</p