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375 Research products, page 1 of 38

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  • English
    Authors: 
    Office for National Statistics;
    Publisher: UK Data Service

    Abstract 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, then 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 available). Further information on the background to the QLFS may be found in the documentation.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. 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.New reweighting policyFollowing the new reweighting policy ONS has reviewed the latest population estimates made available during 2019 and have decided not to carry out a 2019 LFS and APS reweighting exercise. Therefore, the next reweighting exercise will take place in 2020. These will incorporate the 2019 Sub-National Population Projection data (published in May 2020) and 2019 Mid-Year Estimates (published in June 2020). It is expected that reweighted Labour Market aggregates and microdata will be published towards the end of 2020/early 2021.Additional data derived from the QLFSThe Archive also holds further QLFS series: Secure Access datasets (see below); household datasets; two-quarter and five-quarter longitudinal datasets; quarterly, annual and ad hoc module datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.End User Licence and Secure Access QLFS dataUsers should note that there are two discrete versions of the QLFS. 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 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 finer 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 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 5-digit industry subclass and 4-digit 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 other 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.Changes to Country of Birth and Nationality variables, 2017:Following a disclosure review in 2016 by the ONS Data Access Team, changes have been made to the LFS Country of Birth and Nationality variables from the July-September 2017 quarter. Four new variables have been created and four variables removed. The new groupings are consistent with those published by the Migration Statistics Unit and so should facilitate users to carry out required analysis of Country of Birth and Nationality. The variables added are: CRYOX7_EUL_Main, CRYOX7_EUL_Sub, NATOX7_EUL_Main and NATOX7_EUL_Sub. The variables removed are: CRYO7, CRYOX7, NATO7 and NATOX7.Variables DISEA and LNGLSTDataset A08 (Labour market status of disabled people) which ONS suspended due to an apparent discontinuity between April to June 2017 and July to September 2017 is now available. As a result of this apparent discontinuity and the inconclusive investigations at this stage, comparisons should be made with caution between April to June 2017 and subsequent time periods. However users should note that the estimates are not seasonally adjusted, so some of the change between quarters could be due to seasonality. Further recommendations on historical comparisons of the estimates will be given in November 2018 when ONS are due to publish estimates for July to September 2018. An ONS Methodology section article on Analysis of the discontinuity in the Labour Force Survey disability data: April to June 2017 to July to September 2017 has also been published. For any queries about Dataset A08 please email Labour.Market@ons.gov.uk ONS methodology reports on the Labour Force Survey, published 2019: A report on progress to assess potential bias in the LFS through a comparison against alternative data sources including proxy labour measures from administrative data: Exploring the use of external data to assess for observed bias in Labour Force Survey estimates: interim findings An update on Progress against the Labour Force Survey National Statistics Quality Review recommendationsLFS response to COVID-19Since April 2020, additional non-calendar quarter LFS microdata have been delivered to Government Departments and the wider research community through the ONS Secure Research Service and UK Data Service. The first additional microdata to be released covered the period February to April 2020, to coincide with Labour Market Statistical Bulletin publication on 16 June. Further guidance was also provided with the release of the February to April 2020 microdata. Please consult the documentation for full details. Users should note that within the additional COVID-19 quarters, the pseudonymised variables Casenop and Hserialp may contain a significant number of missing cases (set as -9). These variables are only produced once a quarter by ONS, and so are not available in full for the additional COVID-19 datasets until the next standard calendar quarter is produced. It is intended that the Casenop and Hserialp variables in the COVID-19 datasets will be updated at the release of the next standard calendar quarter, when the values for the missing cases will become available. Users should also note that the Income Weight variable, PIWT, is not available in the non-standard quarters, although the Person Weight (PWT) is included.Weighting methodology information, May 2021 Following advice from ONS Labour Market Division regarding concerns over the estimates for Ethnicity, COB, Nationality and Disability from the LFS and APS, users are advised that levels and changes in levels should be used with caution. Rates published from the LFS and APS remain robust. This will particularly affect estimates for country of birth, nationality, ethnicity and disability, so any analysis using levels for these topics should be suppressed.LFS and APS responses are weighted to official 2018-based population projections on demographic trends that pre-date the coronavirus pandemic. In the Labour Market Division's Coronavirus and the impact on payroll employment article, analysis of the population totals currently used in the LFS weighting process is explained, and the intention to continue to make adjustments when appropriate.The document Labour Force Survey weighting methodology details the reweighting methodology and includes release dates for reweighted estimates. Latest edition informationFor the second edition (June 2022), 2022 weighting variable PWT22 was added to the study, and the 2020 weight removed. 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. Face-to-face interview Telephone interview

  • Authors: 
    BDRC Continental;
    Publisher: UK Data Service

    <p>This survey is commissioned by the Business Finance Taskforce to provide an independent and authoritative report into the key issues of small and medium-sized enterprises (SME) Finance. 4,500 telephone interviews are conducted per quarter, across the UK (was 5,000 prior to 2016), to a carefully structured sample of SMEs by size, sector and region.</p> <p>The survey explores demand for external funding amongst SMEs and the response to requests for funding made to banks in the last 12 months. It also asks for future finance needs and assesses business confidence, growth, and barriers to growth for the future, as well as the impact of a lending experience on the overall banking relationship. As well as identifying the proportion of SMEs that have approached a lender for external finance, the survey identified those who would have liked to apply, but haven't, the barriers to such an application, and the impact of the decision not to seek funding on business performance. A wide range of business demographics are collected to allow for sub-group analysis by criteria such as age of business, external risk rating, type of facility requested, and the 'formality' of the business (planning, HR policies, importing, exporting etc).The intention is for this to become the definitive data set on this topic for banks, government, business organisations and other interested parties, including academics. It is hoped it will be used to provide answers, to obviate the need for similar quantitative research, and to provide the starting point for spin off projects into specific aspects of SME Finance. Further information may be found on the <a title="BVA BDRC SME Finance Monitor" href="http://www.sme-finance-monitor.co.uk"> BVA BDRC SME Finance Monitor</a> website.</p> <p>Each data file includes all data collected for the last 10 waves, whilst the reports focus on data gathered from the last 4 quarters. The report is released twice per year, although in Q2 2020 the full report was replaced by a smaller chart pack as questions about how businesses were affected by Covid-19 had been added, and these data were needed more urgently.</p> <p><strong>Latest Edition Information</strong></p> <p class="x_x_MsoBodyText"></p> <p>For the 21st edition (January 2021) additional data and documentation were deposited to extend the coverage to Quarter 2, 2020, but also an extra set to Quarter 3, 2020 as third parties had expressed an interest about that latest data, due to it tracking the very topical Covid-19 situation.</p>

  • Open Access
    Authors: 
    Egger, C.M. (University of Groningen); de Saint Phalle, E. (University of Groningen); Magni-Berton, R. (University Grenoble Alpes, Sciences Po Grenoble, PACTE); Aarts, C.W.A.M. (University of Groningen); Roché Sébastian (CNRS (National Center for Scientific Research), PACTE);
    Publisher: DataverseNL

    Version 1.0 of the EXCEPTIUS project dataset (v.1.0) tracked all exceptional measures in the field of democratic governance/ human rights and international cooperation issued by national authorities in European Union (EU) countries (including UK and Switzerland, excluding Iceland) in order to tackle the COVID-19 pandemic from January to June 2020. The dataset also provides data on the implementation modalities of such measures. Version 2.0 now includes data on measures issued for subnational authorities (Austria, Belgium, Finland, France, Germany, Italy, Spain, Switzerland, UK) and covers the second (July- December 2020) and third (January-April 2021) waves. It also includes a new type event (10, emergency decision-making) allowing to distinguish between countries who implemented a state of emergency (type event 1) and countries which implemented emergency measures without activating state of emergency provisions.

  • Authors: 
    Matheson, Jesse; De Fraja, Gianni; Rockey, James;
    Publisher: UK Data Service

    The increase in the extent of working-from-home determined by the COVID-19 health crisis has led to a substantial shift of economic activity across geographical areas; which we refer to as a Zoomshock. When a person works from home rather than at the office, their work-related consumption of goods and services provided by the locally consumed service industries will take place where they live, not where they work. Much of the clientèle of restaurants, coffee bars, pubs, hair stylists, health clubs, taxi providers and the like located near workplaces is transferred to establishment located near where people live. These data are our calculations of the Zoomshock at the MSOA level. They reflect estimats of the change in the number of people working in UK neighbourhoods due to home-working.

  • Open Access
    Authors: 
    Vicens P; Heredia L; Bustamante E; Pérez Y; Domingo JL; Torrente M;

    The petrochemical industry has made the economic development of many local communities possible, increasing employment opportunities and generating a complex network of closely-related secondary industries. However, it is known that petrochemical industries emit air pollutants, which have been related to different negative effects on mental health. In addition, many people around the world are being exposed to highly stressful situations deriving from the COVID-19 pandemic and the lockdowns adopted by national and regional governments. The present study aims to analyse the possible differential effects on various psychological outcomes (stress, anxiety, depression and emotional regulation strategies) stemming from the COVID-19 pandemic and consequent lockdown experienced by individuals living near an important petrochemical complex and subjects living in other areas, nonexposed to the characteristic environmental pollutants emitted by these kinds of complex. The sample consisted of 1607 subjects who answered an ad hoc questionnaire on lockdown conditions, the Perceived Stress Scale (PSS), the Hospital Anxiety and Depression Scale (HADS), the Barratt Impulsivity Scale (BIS) and the Emotional Regulation Questionnaire (ERQ). The results indicate that people living closer to petrochemical complexes reported greater risk perception [K = 73.42, p < 0.001, with a medium size effect (η = 0.061)]. However, no significant relationship between psychological variables and proximity to the focus was detected when comparing people living near to or far away from a chemical/petrochemical complex. Regarding the adverse psychological effects of the first lockdown due to COVID-19 on the general population in Catalonia, we can conclude that the conditions included in this survey were mai

  • Open Access

    The dataset comprises comments collected from the official Facebook page of the National Institute of Public Health of Kosovo (NIPHK) for a period of 6 months, from March 12 till August 31, 2020. On March 12, the first case of COVID-19 was confirmed in Kosovo. Comments were retrieved using a tool called Comment Exporter. These comments were in Albanian language and reflect the opinions of Kosovo citizens expressed on Facebook about the Covid-19 pandemics. This dataset contains a total of 10,132 comments along with 12 attributes. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

  • Authors: 
    Lamsal, Rabindra;
    Publisher: IEEE DataPort

    Each database (*.db) contain three columns.First column: date and time of the tweetSecond column: tweetThird column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live.To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. New databases will be added to this dataset every week. Bookmark this page for further updates. [1] https://sentiment.live/ [2] https://textblob.readthedocs.io/en/dev/

  • Research data . 2022
    German
    Authors: 
    Diewald, Martin; Kandler, Christian; Riemann, Rainer; Spinath, Frank M.; Baier, Tina; Bartling, Annika; Baum, Myriam A.; Deppe, Marco; Eichhorn, Harald; Eifler, Eike F.; +21 more
    Publisher: GESIS

    TwinLife ist eine auf zwölf Jahre angelegte repräsentative verhaltensgenetische Studie zur Entwicklung von sozialen Ungleichheiten. Für eine detaillierte Studien-Dokumention besuchen Sie bitte https://www.twin-life.de/documentation/. Das Langfristvorhaben begann im Jahr 2014 und befragt in einem jährlichen Turnus über 4000 in Deutschland lebende Zwillingspaare und deren Familien zu unterschiedlichen Lebensbereichen. Durch den Vergleich von ein- und zweieiigen, gleichgeschlechtlichen Zwillingspaaren können neben sozialen Mechanismen auch genetische Differenzen zwischen Individuen, sowie die Kovariation und Interaktion sozialer und genetischer Einflussgrößen analysiert werden. Um die individuelle Entwicklung unterschiedlicher Einflussfaktoren zu dokumentieren werden die Familien über mehrere Jahre hinweg umfassend untersucht. Inhaltlich wird dabei auf sechs für soziale Ungleichheiten bedeutsame Lebensbereiche fokussiert: 1. Bildung und Kompetenzerwerb, 2. Karriere und Erfolg auf dem Arbeitsmarkt, 3. Integration und Teilhabe am sozialen, kulturellen und politischen Leben, 4. Lebensqualität und wahrgenommene Handlungsmöglichkeiten, 5. physische und psychologische Gesundheit sowie 6. Verhaltensprobleme und abweichendes Verhalten. In 2020 und 2021 fanden zwei zusätzliche Befragungen zu den Einflüssen und Folgen der COVID-19-Pandemie statt. Die erste Zusatzerhebung hatte zum Ziel, retrospektiv das Verhalten, die Einstellungen, Belastungen, Gesundheit und sozioökonomische Veränderungen im Leben der Befragten während der ersten Welle der COVID-19-Pandemie von März 2020 bis hin zu den ersten Lockerungen der Lockdown-Maßnahmen zu erfassen. Die zweite Zusatzbefragung zielte darauf ab, aktuelle Verhaltensweisen, Einstellungen, Belastungen, gesundheitliche und sozioökonomische Veränderungen während der COVID-19-Pandemie zu erfassen. TwinLife is a 12-year representative behavior genetic study investigating the emergence and development of social inequalities over the life course. For a detailed documentation of the study please visit https://www.twin-life.de/documentation/. The long-term project began in 2014 and surveys more than 4,000 pairs of twins and their families in different stages of life on a yearly basis. All of the subjects reside in Germany. Not only social, but also genetic mechanisms as well as covariations and interactions between these two factors can be examined with the help of identical and fraternal same-sex twins. In order to document the individual development of different aspects it is important to examine the families extensively over the course of several years. Six important contextual domains are focused on: 1. Education and academic performance / skill development, 2. career and labor market attainment, 3. integration and participation in social, cultural and political life, 4. quality of life and perceived capabilities, 5. physical and psychological health and 6. behavioral problems and deviant behavior. In 2020 and 2021, two a supplementary surveys on the influences and consequences of the COVID-19 pandemic took place. The first supplemental survey aimed to retrospectively capture the behavior, attitudes, stresses, health, and socioeconomic changes during the first wave of the COVID-19 pandemic from March 2020 through the first relaxations of the lockdown measures. The second supplemental survey aimed to assess current behaviors, attitudes, stresses, health, and socioeconomic changes during the COVID-19 pandemic. Ein- und zweieiige gleichgeschlechtliche Zwillingspaare der Geburtsjahrgänge 1.) 1990 bis 1993, 2.) 1997/1998, 3.) 2003/2004 und 4.) 2009/2010 (4 Geburtsjahrgangskohorten in 2 Teilstichproben) + mindestens ein biologischer Elternteil (+ ggf. der andere biologische Elternteil, Stiefeltern(-teile), ein Geschwister und die Partner der Zwillinge) Twins and their families (Extended Twin Family Design, ETFD): Monozygotic and dizygotic same-sex twin pairs born in the following years: 1.) 1990 - 1993, 2.) 1997/1998, 3.) 2003/2004 and 4.) 2009/2010 (4 birth cohorts in two subsamples) + at least one biological parent (+ if possible the other biological parent, step-parent(-s), one sibling and the twins´ partners) Wahrscheinlichkeitsauswahl: Mehrstufige Zufallsauswahl; Auswahlverfahren Kommentar: Wahrscheinlichkeitsauswahl: Mehrstufige Zufallsauswahl Probability: Multistage; Sampling Procedure Comment: Probability Sample: Multistage Sample Erhebungseinheit: Erwachsene; Jugendliche; Vorschulkinder; Eltern; sonstiges Die Datenlieferung v6-0-0 besteht aus 19 Datendateien im SPSS- und Stata-Format: • Master (ZA6701_master_v$): Der Masterdatensatz enthält Informationen über die Bruttostichprobe, wie z.B. konsistenzgeprüfte, zeitinvariante Variablen (Geschlecht, Geburtsjahr, Beziehung zu den Zwillingen, Zygotie, Migrationshintergrund) und wellenspezifische Variablen (Personentyp, Befragungsstatus) zu allen in TwinLife erfassten Personen in jeder Datenerhebung. • Befragungsdaten im Personenformat mit Filterfehlerbereinigung (ZA6701_person_wid$_v$ bzw. ZA6701_person_cov$_v$): Für jede Datenerhebung gibt es einen Datensatz. Die Kennung der Datenerhebung ist die Variable wid. Jede Befragungsperson (pid) erhält eine Datenzeile. • Befragungsdaten der COVID-Zusatzerhebungen (ZA6701_person_con$_v$): Für jede COVID-Zusatzerhebung gibt es einen Datensatz. Die Kennung der Datenerhebung ist die variable cov. • Befragungsdaten im Personenformat ohne Filterfehlerbereinigung (ZA6701_person_unadj_wid$_v$): Variablen, die zumindest teilweise im PAPI-Modus (selbstadministriert) erhoben wurden, werden hier noch einmal ohne Filterfehlerbereinigung abgelegt. Die Entscheidung, wie mit den Angaben der Befragten umzugehen ist, obliegt den Nutzer*innen. • Befragungsdaten im Familienformat (ZA6701_family_wide_wid$_v$): Es gibt einen Datensatz für jede Datenerhebung, außer der Corona-Zusatzbefragungen. Jede Familie hat eine Datenzeile mit Informationen zu jeder teilnehmenden Person in der Familie, die in separaten Variablen/Spalten gespeichert sind. Die Datensätze im Personen- und Familienformat enthalten dieselben Daten mit unterschiedlichen Strukturen. • Umfragegewichte (ZA6701_weights_v$): Datendatei mit den Gewichten der Erhebung (Designgewicht, Nonresponsegewicht und Panelgewichte). • Zudem sind jeweils ein Datensatz mit den Informationen aus der Befragung zur Feststellung der Zygotie der Zwillingspaare (ZA6701_zygosity_v$) und ein Datensatz, der für jede Variable auf Personenebene den Befragungsmodus der 1. F2F-Befragung dokumentiert (ZA6701_mode_wid1_v$), Teil des Datenrelease. Alle Daten sind mit englischen und deutschen Variablenbeschreibungen versehen. In Stata sind diese Sprachen in einem Datensatz enthalten, während es sich in SPSS um separate Datendateien handelt. Die Daten sind auf Inkonsistenzen geprüft und filterbereinigt. Variablen und Instrumente werden unter http://www.paneldata.org dokumentiert. Detaillierte Informationen zur Studie und ihren Besonderheiten finden Sie unter https://www.twin-life.de/documentation/. Bei Fragen zu den Dateninhalten wenden Sie sich bitte an data(at)twin-life.de. Die Bestellgebühren für diese Studie werden von TwinLife selbst übernommen, so dass für die Nutzung keine weiteren Gebühren anfallen. Survey unit: adults; teenagers; preschool children; parents; others The data delivery v6-0-0 consists of 19 data files in SPSS and Stata format: • Master data (ZA6701_master_v$): Includes information on the gross sample, such as consistency checked variables that are stable over time (sex, year of birth, relation to the twins, zygosity, migration background) and wave-specific variables (person type, response status, family composition) about all individuals included in TwinLife in each wave. • Survey data in person format with filter error adjustment (ZA6701_person_wid$_v$): There is one data set for each data collection. The data collection identifier is the variable wid. Each surveyed person has one data row (pid). • Data of covid supplemental surveys (ZA6701_person_cov$_v$): There is one data set for each covid supplemental survey. Each surveyed person has one data row. The data collection identifier is the variable cov. • Survey data in family format (ZA6701_family_wide_wid$_v$): There is one data set for each data collection except the COVID-19. Each family has one data row with information of each participating person in the family being stored in separate variables/columns). Person format and family format data sets contain the same data using different structures. • Survey weights (ZA6701_weights_v$): A data file containing the survey weights (design, nonresponse, and panel weights). • Twin zygosity assessment (ZA6701_zygosity_v$): A data file with information of the twin zygosity assessment in F2F 1. • Survey mode (ZA6701_mode_wid1_v$): A datafile with Contains information on the survey mode for each variable in F2F 1. • Unadjusted data of all variables collected in the PAPI survey mode (ZA6701_person_unadj_wid$_v$): One data file for each data collection with data unadjusted for filter errors for all constructs/variables that were at least partly surveyed in the PAPI mode (as of data release v4-1-0 in autumn 2020). All data is provided with English and German variable descriptions. In Stata, these languages are included in one data set while in SPSS, these are separate data files. The data are checked for inconsistencies and adjusted for filter errors. Variables and instruments are documented at http://www.paneldata.org. Detailed information on the study and special features can be found at https://www.twin-life.de/documentation/. For questions regarding the content of the data, please contact data(at)twin-life.de. Charges for downloading this data will be paid by the TwinLife project, so the use of the data is free of charge! Face-to-face interview: CAPI/CAMI Self-administered questionnaire: Computer-assisted (CASI) Self-administered questionnaire: Paper Educational measurements and tests Recording Self-administered questionnaire: Web-based Telephone interview: CATI F2F 1: Persönliche Haushaltsinterviews auf Basis dreier verschiedener Interview-Modi (Persönliches Interview: CAPI (Computerunterstützte persönliche Befragung), Selbstausfüller: CASI (Computerunterstützte Selbstbefragung), Selbstausfüller: Papier) plus Messungen und Tests der kognitiven Fähigkeiten sowie Scans/Fotos von Zeugnissen; Fragebögen für außerhäusig lebende Teilnehmer in zwei Modi: Selbstausfüller: CAWI (Computerunterstütztes Web-Interview) und Selbstausfüller: Papier. CATI 1: Telefonische Haushalts- und Personenbefragung. F2F 2: Persönliche Haushaltsinterviews auf Basis dreier verschiedener Interview-Modi (Persönliches Interview: CAPI (Computerunterstützte persönliche Befragung), Selbstausfüller: CASI (Computerunterstützte Selbstbefragung), Selbstausfüller: Papier) plus Gummibärchentest sowie Scans/Fotos von Zeugnissen CATI 2: Telefonische Haushalts- und Personenbefragung. Corona-Zusatzbefragung CoV 1: CAWI (Computerunterstütztes Web-Interview) F2F 3: Persönliche Haushaltsinterviews auf Basis verschiedener Interview-Modi (Persönliches Interview: CAPI (Computerunterstützte persönliche Befragung), Selbstausfüller: CASI (Computerunterstützte Selbstbefragung) und CAWI (Computerunterstütztes Web-Interview), Selbstausfüller: Papier plus Aufzeichnungen der APGAR-scores, Scans/Fotos von Zeugnissen und Speichelproben). CoV 2: CAPIbyPhone (Computerunterstützte persönliche Befragung), CATI (Computerunterstütztes Telefon-Interview) oder CAWI (Computerunterstütztes Web-Interview) F2F 1: Household interviews with the family via three different interview modes (Face-to-face interview: CAPI (Computer Assisted Personal Interview), Self-administered questionnaire: CASI (Computer Assisted Self-Interview), and Self-administered questionnaire: Paper plus cognitive tests, scans/photos of certificates; interviews with family members living outside the interviewed households by two modes (Self-administered questionnaire: CAWI (Computer Assisted Web Interview), Self-administered questionnaire: Paper. CATI 1: individual and household interviews by phone. F2F 2: Household interviews with the family via three different interview modes (Face-to-face interview: CAPI (Computer Assisted Personal Interview), Self-administered questionnaire: CASI (Computer Assisted Self-Interview), and Self-administered questionnaire: Paper plus gummy bear tests, scans/photos of certificates. CATI 2: individual and household interviews by phone. CoV 1: CAWI (Computer Assisted Web Interview) F2F 3: Household interviews with the family via different interview modes (Face-to-face interview: CAPI (Computer Assisted Personal Interview), Self-administered questionnaire: CASI (Computer Assisted Self-Interview), CAWI (Computer Assisted Web Interview), Self-administered questionnaire: Paper plus recording of the APGAR score, scans/photos of school reports, saliva sample). CoV 2: CAPIbyPhone (Computer Assisted Personal Interview), CATI (Computer Assisted Telephone Interview) or CAWI (Computer Assisted Web Interview)

  • Open Access
    Authors: 
    Oncini, Filippo;
    Publisher: UK Data Service
    Project: EC | HUNG (838965)

    The survey aimed to gather data on the impact of the COVID19 outbreak on the food support providers active in Greater Manchester. The lockdown created organizational hurdles to many services providing food to the most vulnerable. The survey explored more in depth the obstacles, the needs and the prospects of 55 organizations that were on the frontline in the first months of the crisis.

  • Research data . 2022
    Authors: 
    Sport England; Ipsos;
    Publisher: UK Data Service

    <p>The <span style="font-style: italic;">Active Lives Survey</span> (ALS) commenced in November 2015. It replaces the Active People Survey, which ran from 2005 to 2015. The survey provides the largest sample size ever established for a sport and recreation survey and allows levels of detailed analysis previously unavailable. It identifies how participation varies from place to place, across different sports, and between different groups in the population. The survey also measures levels of activity (active, fairly active and inactive), the proportion of the adult population that volunteer in sports on a weekly basis, club membership, sports spectating and wellbeing measures such as happiness and anxiety, etc. The questionnaire was designed to enable analysis of the findings by a broad range of demographic information, such as gender, social class, ethnicity, household structure, age, and disability.<br><br>More general information about the study can be found on the Sport England <a href="https://www.sportengland.org/research/active-lives-survey/">Active Lives Survey</a> webpage and the <a href="https://activelives.sportengland.org/">Active Lives Online</a> website, including reports and data tables.<br> </p> <p><span style="font-style: italic;">Active Lives Adults Survey, 2020-2021</span><br></p> <p>The Coronavirus (COVID-19) pandemic developed rapidly during 2020 and 2021. Fieldwork for the Active Lives survey continued throughout the pandemic. This data, therefore, reflects the impact of coronavirus (COVID-19) on activity levels and the government’s policies to contain its spread. The survey instrument was largely unchanged. More general information about the study can be found on the Sport England&nbsp;<a href="https://www.sportengland.org/research/about-our-research/active-people-survey/" style="background-color: rgb(255, 255, 255);">Active People Survey</a>&nbsp;and&nbsp;<a href="https://www.sportengland.org/research/active-lives-survey/" style="background-color: rgb(255, 255, 255);">Active Lives Survey</a>&nbsp;webpages and&nbsp;<a href="https://activelives.sportengland.org/" style="background-color: rgb(255, 255, 255);">Active Lives Online</a>&nbsp;website.</p>

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  • English
    Authors: 
    Office for National Statistics;
    Publisher: UK Data Service

    Abstract 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, then 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 available). Further information on the background to the QLFS may be found in the documentation.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. 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.New reweighting policyFollowing the new reweighting policy ONS has reviewed the latest population estimates made available during 2019 and have decided not to carry out a 2019 LFS and APS reweighting exercise. Therefore, the next reweighting exercise will take place in 2020. These will incorporate the 2019 Sub-National Population Projection data (published in May 2020) and 2019 Mid-Year Estimates (published in June 2020). It is expected that reweighted Labour Market aggregates and microdata will be published towards the end of 2020/early 2021.Additional data derived from the QLFSThe Archive also holds further QLFS series: Secure Access datasets (see below); household datasets; two-quarter and five-quarter longitudinal datasets; quarterly, annual and ad hoc module datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.End User Licence and Secure Access QLFS dataUsers should note that there are two discrete versions of the QLFS. 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 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 finer 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 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 5-digit industry subclass and 4-digit 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 other 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.Changes to Country of Birth and Nationality variables, 2017:Following a disclosure review in 2016 by the ONS Data Access Team, changes have been made to the LFS Country of Birth and Nationality variables from the July-September 2017 quarter. Four new variables have been created and four variables removed. The new groupings are consistent with those published by the Migration Statistics Unit and so should facilitate users to carry out required analysis of Country of Birth and Nationality. The variables added are: CRYOX7_EUL_Main, CRYOX7_EUL_Sub, NATOX7_EUL_Main and NATOX7_EUL_Sub. The variables removed are: CRYO7, CRYOX7, NATO7 and NATOX7.Variables DISEA and LNGLSTDataset A08 (Labour market status of disabled people) which ONS suspended due to an apparent discontinuity between April to June 2017 and July to September 2017 is now available. As a result of this apparent discontinuity and the inconclusive investigations at this stage, comparisons should be made with caution between April to June 2017 and subsequent time periods. However users should note that the estimates are not seasonally adjusted, so some of the change between quarters could be due to seasonality. Further recommendations on historical comparisons of the estimates will be given in November 2018 when ONS are due to publish estimates for July to September 2018. An ONS Methodology section article on Analysis of the discontinuity in the Labour Force Survey disability data: April to June 2017 to July to September 2017 has also been published. For any queries about Dataset A08 please email Labour.Market@ons.gov.uk ONS methodology reports on the Labour Force Survey, published 2019: A report on progress to assess potential bias in the LFS through a comparison against alternative data sources including proxy labour measures from administrative data: Exploring the use of external data to assess for observed bias in Labour Force Survey estimates: interim findings An update on Progress against the Labour Force Survey National Statistics Quality Review recommendationsLFS response to COVID-19Since April 2020, additional non-calendar quarter LFS microdata have been delivered to Government Departments and the wider research community through the ONS Secure Research Service and UK Data Service. The first additional microdata to be released covered the period February to April 2020, to coincide with Labour Market Statistical Bulletin publication on 16 June. Further guidance was also provided with the release of the February to April 2020 microdata. Please consult the documentation for full details. Users should note that within the additional COVID-19 quarters, the pseudonymised variables Casenop and Hserialp may contain a significant number of missing cases (set as -9). These variables are only produced once a quarter by ONS, and so are not available in full for the additional COVID-19 datasets until the next standard calendar quarter is produced. It is intended that the Casenop and Hserialp variables in the COVID-19 datasets will be updated at the release of the next standard calendar quarter, when the values for the missing cases will become available. Users should also note that the Income Weight variable, PIWT, is not available in the non-standard quarters, although the Person Weight (PWT) is included.Weighting methodology information, May 2021 Following advice from ONS Labour Market Division regarding concerns over the estimates for Ethnicity, COB, Nationality and Disability from the LFS and APS, users are advised that levels and changes in levels should be used with caution. Rates published from the LFS and APS remain robust. This will particularly affect estimates for country of birth, nationality, ethnicity and disability, so any analysis using levels for these topics should be suppressed.LFS and APS responses are weighted to official 2018-based population projections on demographic trends that pre-date the coronavirus pandemic. In the Labour Market Division's Coronavirus and the impact on payroll employment article, analysis of the population totals currently used in the LFS weighting process is explained, and the intention to continue to make adjustments when appropriate.The document Labour Force Survey weighting methodology details the reweighting methodology and includes release dates for reweighted estimates. Latest edition informationFor the second edition (June 2022), 2022 weighting variable PWT22 was added to the study, and the 2020 weight removed. 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. Face-to-face interview Telephone interview

  • Authors: 
    BDRC Continental;
    Publisher: UK Data Service

    <p>This survey is commissioned by the Business Finance Taskforce to provide an independent and authoritative report into the key issues of small and medium-sized enterprises (SME) Finance. 4,500 telephone interviews are conducted per quarter, across the UK (was 5,000 prior to 2016), to a carefully structured sample of SMEs by size, sector and region.</p> <p>The survey explores demand for external funding amongst SMEs and the response to requests for funding made to banks in the last 12 months. It also asks for future finance needs and assesses business confidence, growth, and barriers to growth for the future, as well as the impact of a lending experience on the overall banking relationship. As well as identifying the proportion of SMEs that have approached a lender for external finance, the survey identified those who would have liked to apply, but haven't, the barriers to such an application, and the impact of the decision not to seek funding on business performance. A wide range of business demographics are collected to allow for sub-group analysis by criteria such as age of business, external risk rating, type of facility requested, and the 'formality' of the business (planning, HR policies, importing, exporting etc).The intention is for this to become the definitive data set on this topic for banks, government, business organisations and other interested parties, including academics. It is hoped it will be used to provide answers, to obviate the need for similar quantitative research, and to provide the starting point for spin off projects into specific aspects of SME Finance. Further information may be found on the <a title="BVA BDRC SME Finance Monitor" href="http://www.sme-finance-monitor.co.uk"> BVA BDRC SME Finance Monitor</a> website.</p> <p>Each data file includes all data collected for the last 10 waves, whilst the reports focus on data gathered from the last 4 quarters. The report is released twice per year, although in Q2 2020 the full report was replaced by a smaller chart pack as questions about how businesses were affected by Covid-19 had been added, and these data were needed more urgently.</p> <p><strong>Latest Edition Information</strong></p> <p class="x_x_MsoBodyText"></p> <p>For the 21st edition (January 2021) additional data and documentation were deposited to extend the coverage to Quarter 2, 2020, but also an extra set to Quarter 3, 2020 as third parties had expressed an interest about that latest data, due to it tracking the very topical Covid-19 situation.</p>

  • Open Access
    Authors: 
    Egger, C.M. (University of Groningen); de Saint Phalle, E. (University of Groningen); Magni-Berton, R. (University Grenoble Alpes, Sciences Po Grenoble, PACTE); Aarts, C.W.A.M. (University of Groningen); Roché Sébastian (CNRS (National Center for Scientific Research), PACTE);
    Publisher: DataverseNL

    Version 1.0 of the EXCEPTIUS project dataset (v.1.0) tracked all exceptional measures in the field of democratic governance/ human rights and international cooperation issued by national authorities in European Union (EU) countries (including UK and Switzerland, excluding Iceland) in order to tackle the COVID-19 pandemic from January to June 2020. The dataset also provides data on the implementation modalities of such measures. Version 2.0 now includes data on measures issued for subnational authorities (Austria, Belgium, Finland, France, Germany, Italy, Spain, Switzerland, UK) and covers the second (July- December 2020) and third (January-April 2021) waves. It also includes a new type event (10, emergency decision-making) allowing to distinguish between countries who implemented a state of emergency (type event 1) and countries which implemented emergency measures without activating state of emergency provisions.

  • Authors: 
    Matheson, Jesse; De Fraja, Gianni; Rockey, James;
    Publisher: UK Data Service

    The increase in the extent of working-from-home determined by the COVID-19 health crisis has led to a substantial shift of economic activity across geographical areas; which we refer to as a Zoomshock. When a person works from home rather than at the office, their work-related consumption of goods and services provided by the locally consumed service industries will take place where they live, not where they work. Much of the clientèle of restaurants, coffee bars, pubs, hair stylists, health clubs, taxi providers and the like located near workplaces is transferred to establishment located near where people live. These data are our calculations of the Zoomshock at the MSOA level. They reflect estimats of the change in the number of people working in UK neighbourhoods due to home-working.

  • Open Access
    Authors: 
    Vicens P; Heredia L; Bustamante E; Pérez Y; Domingo JL; Torrente M;

    The petrochemical industry has made the economic development of many local communities possible, increasing employment opportunities and generating a complex network of closely-related secondary industries. However, it is known that petrochemical industries emit air pollutants, which have been related to different negative effects on mental health. In addition, many people around the world are being exposed to highly stressful situations deriving from the COVID-19 pandemic and the lockdowns adopted by national and regional governments. The present study aims to analyse the possible differential effects on various psychological outcomes (stress, anxiety, depression and emotional regulation strategies) stemming from the COVID-19 pandemic and consequent lockdown experienced by individuals living near an important petrochemical complex and subjects living in other areas, nonexposed to the characteristic environmental pollutants emitted by these kinds of complex. The sample consisted of 1607 subjects who answered an ad hoc questionnaire on lockdown conditions, the Perceived Stress Scale (PSS), the Hospital Anxiety and Depression Scale (HADS), the Barratt Impulsivity Scale (BIS) and the Emotional Regulation Questionnaire (ERQ). The results indicate that people living closer to petrochemical complexes reported greater risk perception [K = 73.42, p < 0.001, with a medium size effect (η = 0.061)]. However, no significant relationship between psychological variables and proximity to the focus was detected when comparing people living near to or far away from a chemical/petrochemical complex. Regarding the adverse psychological effects of the first lockdown due to COVID-19 on the general population in Catalonia, we can conclude that the conditions included in this survey were mai

  • Open Access

    The dataset comprises comments collected from the official Facebook page of the National Institute of Public Health of Kosovo (NIPHK) for a period of 6 months, from March 12 till August 31, 2020. On March 12, the first case of COVID-19 was confirmed in Kosovo. Comments were retrieved using a tool called Comment Exporter. These comments were in Albanian language and reflect the opinions of Kosovo citizens expressed on Facebook about the Covid-19 pandemics. This dataset contains a total of 10,132 comments along with 12 attributes. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

  • Authors: 
    Lamsal, Rabindra;
    Publisher: IEEE DataPort

    Each database (*.db) contain three columns.First column: date and time of the tweetSecond column: tweetThird column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live.To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. New databases will be added to this dataset every week. Bookmark this page for further updates. [1] https://sentiment.live/ [2] https://textblob.readthedocs.io/en/dev/

  • Research data . 2022
    German
    Authors: 
    Diewald, Martin; Kandler, Christian; Riemann, Rainer; Spinath, Frank M.; Baier, Tina; Bartling, Annika; Baum, Myriam A.; Deppe, Marco; Eichhorn, Harald; Eifler, Eike F.; +21 more
    Publisher: GESIS

    TwinLife ist eine auf zwölf Jahre angelegte repräsentative verhaltensgenetische Studie zur Entwicklung von sozialen Ungleichheiten. Für eine detaillierte Studien-Dokumention besuchen Sie bitte https://www.twin-life.de/documentation/. Das Langfristvorhaben begann im Jahr 2014 und befragt in einem jährlichen Turnus über 4000 in Deutschland lebende Zwillingspaare und deren Familien zu unterschiedlichen Lebensbereichen. Durch den Vergleich von ein- und zweieiigen, gleichgeschlechtlichen Zwillingspaaren können neben sozialen Mechanismen auch genetische Differenzen zwischen Individuen, sowie die Kovariation und Interaktion sozialer und genetischer Einflussgrößen analysiert werden. Um die individuelle Entwicklung unterschiedlicher Einflussfaktoren zu dokumentieren werden die Familien über mehrere Jahre hinweg umfassend untersucht. Inhaltlich wird dabei auf sechs für soziale Ungleichheiten bedeutsame Lebensbereiche fokussiert: 1. Bildung und Kompetenzerwerb, 2. Karriere und Erfolg auf dem Arbeitsmarkt, 3. Integration und Teilhabe am sozialen, kulturellen und politischen Leben, 4. Lebensqualität und wahrgenommene Handlungsmöglichkeiten, 5. physische und psychologische Gesundheit sowie 6. Verhaltensprobleme und abweichendes Verhalten. In 2020 und 2021 fanden zwei zusätzliche Befragungen zu den Einflüssen und Folgen der COVID-19-Pandemie statt. Die erste Zusatzerhebung hatte zum Ziel, retrospektiv das Verhalten, die Einstellungen, Belastungen, Gesundheit und sozioökonomische Veränderungen im Leben der Befragten während der ersten Welle der COVID-19-Pandemie von März 2020 bis hin zu den ersten Lockerungen der Lockdown-Maßnahmen zu erfassen. Die zweite Zusatzbefragung zielte darauf ab, aktuelle Verhaltensweisen, Einstellungen, Belastungen, gesundheitliche und sozioökonomische Veränderungen während der COVID-19-Pandemie zu erfassen. TwinLife is a 12-year representative behavior genetic study investigating the emergence and development of social inequalities over the life course. For a detailed documentation of the study please visit https://www.twin-life.de/documentation/. The long-term project began in 2014 and surveys more than 4,000 pairs of twins and their families in different stages of life on a yearly basis. All of the subjects reside in Germany. Not only social, but also genetic mechanisms as well as covariations and interactions between these two factors can be examined with the help of identical and fraternal same-sex twins. In order to document the individual development of different aspects it is important to examine the families extensively over the course of several years. Six important contextual domains are focused on: 1. Education and academic performance / skill development, 2. career and labor market attainment, 3. integration and participation in social, cultural and political life, 4. quality of life and perceived capabilities, 5. physical and psychological health and 6. behavioral problems and deviant behavior. In 2020 and 2021, two a supplementary surveys on the influences and consequences of the COVID-19 pandemic took place. The first supplemental survey aimed to retrospectively capture the behavior, attitudes, stresses, health, and socioeconomic changes during the first wave of the COVID-19 pandemic from March 2020 through the first relaxations of the lockdown measures. The second supplemental survey aimed to assess current behaviors, attitudes, stresses, health, and socioeconomic changes during the COVID-19 pandemic. Ein- und zweieiige gleichgeschlechtliche Zwillingspaare der Geburtsjahrgänge 1.) 1990 bis 1993, 2.) 1997/1998, 3.) 2003/2004 und 4.) 2009/2010 (4 Geburtsjahrgangskohorten in 2 Teilstichproben) + mindestens ein biologischer Elternteil (+ ggf. der andere biologische Elternteil, Stiefeltern(-teile), ein Geschwister und die Partner der Zwillinge) Twins and their families (Extended Twin Family Design, ETFD): Monozygotic and dizygotic same-sex twin pairs born in the following years: 1.) 1990 - 1993, 2.) 1997/1998, 3.) 2003/2004 and 4.) 2009/2010 (4 birth cohorts in two subsamples) + at least one biological parent (+ if possible the other biological parent, step-parent(-s), one sibling and the twins´ partners) Wahrscheinlichkeitsauswahl: Mehrstufige Zufallsauswahl; Auswahlverfahren Kommentar: Wahrscheinlichkeitsauswahl: Mehrstufige Zufallsauswahl Probability: Multistage; Sampling Procedure Comment: Probability Sample: Multistage Sample Erhebungseinheit: Erwachsene; Jugendliche; Vorschulkinder; Eltern; sonstiges Die Datenlieferung v6-0-0 besteht aus 19 Datendateien im SPSS- und Stata-Format: • Master (ZA6701_master_v$): Der Masterdatensatz enthält Informationen über die Bruttostichprobe, wie z.B. konsistenzgeprüfte, zeitinvariante Variablen (Geschlecht, Geburtsjahr, Beziehung zu den Zwillingen, Zygotie, Migrationshintergrund) und wellenspezifische Variablen (Personentyp, Befragungsstatus) zu allen in TwinLife erfassten Personen in jeder Datenerhebung. • Befragungsdaten im Personenformat mit Filterfehlerbereinigung (ZA6701_person_wid$_v$ bzw. ZA6701_person_cov$_v$): Für jede Datenerhebung gibt es einen Datensatz. Die Kennung der Datenerhebung ist die Variable wid. Jede Befragungsperson (pid) erhält eine Datenzeile. • Befragungsdaten der COVID-Zusatzerhebungen (ZA6701_person_con$_v$): Für jede COVID-Zusatzerhebung gibt es einen Datensatz. Die Kennung der Datenerhebung ist die variable cov. • Befragungsdaten im Personenformat ohne Filterfehlerbereinigung (ZA6701_person_unadj_wid$_v$): Variablen, die zumindest teilweise im PAPI-Modus (selbstadministriert) erhoben wurden, werden hier noch einmal ohne Filterfehlerbereinigung abgelegt. Die Entscheidung, wie mit den Angaben der Befragten umzugehen ist, obliegt den Nutzer*innen. • Befragungsdaten im Familienformat (ZA6701_family_wide_wid$_v$): Es gibt einen Datensatz für jede Datenerhebung, außer der Corona-Zusatzbefragungen. Jede Familie hat eine Datenzeile mit Informationen zu jeder teilnehmenden Person in der Familie, die in separaten Variablen/Spalten gespeichert sind. Die Datensätze im Personen- und Familienformat enthalten dieselben Daten mit unterschiedlichen Strukturen. • Umfragegewichte (ZA6701_weights_v$): Datendatei mit den Gewichten der Erhebung (Designgewicht, Nonresponsegewicht und Panelgewichte). • Zudem sind jeweils ein Datensatz mit den Informationen aus der Befragung zur Feststellung der Zygotie der Zwillingspaare (ZA6701_zygosity_v$) und ein Datensatz, der für jede Variable auf Personenebene den Befragungsmodus der 1. F2F-Befragung dokumentiert (ZA6701_mode_wid1_v$), Teil des Datenrelease. Alle Daten sind mit englischen und deutschen Variablenbeschreibungen versehen. In Stata sind diese Sprachen in einem Datensatz enthalten, während es sich in SPSS um separate Datendateien handelt. Die Daten sind auf Inkonsistenzen geprüft und filterbereinigt. Variablen und Instrumente werden unter http://www.paneldata.org dokumentiert. Detaillierte Informationen zur Studie und ihren Besonderheiten finden Sie unter https://www.twin-life.de/documentation/. Bei Fragen zu den Dateninhalten wenden Sie sich bitte an data(at)twin-life.de. Die Bestellgebühren für diese Studie werden von TwinLife selbst übernommen, so dass für die Nutzung keine weiteren Gebühren anfallen. Survey unit: adults; teenagers; preschool children; parents; others The data delivery v6-0-0 consists of 19 data files in SPSS and Stata format: • Master data (ZA6701_master_v$): Includes information on the gross sample, such as consistency checked variables that are stable over time (sex, year of birth, relation to the twins, zygosity, migration background) and wave-specific variables (person type, response status, family composition) about all individuals included in TwinLife in each wave. • Survey data in person format with filter error adjustment (ZA6701_person_wid$_v$): There is one data set for each data collection. The data collection identifier is the variable wid. Each surveyed person has one data row (pid). • Data of covid supplemental surveys (ZA6701_person_cov$_v$): There is one data set for each covid supplemental survey. Each surveyed person has one data row. The data collection identifier is the variable cov. • Survey data in family format (ZA6701_family_wide_wid$_v$): There is one data set for each data collection except the COVID-19. Each family has one data row with information of each participating person in the family being stored in separate variables/columns). Person format and family format data sets contain the same data using different structures. • Survey weights (ZA6701_weights_v$): A data file containing the survey weights (design, nonresponse, and panel weights). • Twin zygosity assessment (ZA6701_zygosity_v$): A data file with information of the twin zygosity assessment in F2F 1. • Survey mode (ZA6701_mode_wid1_v$): A datafile with Contains information on the survey mode for each variable in F2F 1. • Unadjusted data of all variables collected in the PAPI survey mode (ZA6701_person_unadj_wid$_v$): One data file for each data collection with data unadjusted for filter errors for all constructs/variables that were at least partly surveyed in the PAPI mode (as of data release v4-1-0 in autumn 2020). All data is provided with English and German variable descriptions. In Stata, these languages are included in one data set while in SPSS, these are separate data files. The data are checked for inconsistencies and adjusted for filter errors. Variables and instruments are documented at http://www.paneldata.org. Detailed information on the study and special features can be found at https://www.twin-life.de/documentation/. For questions regarding the content of the data, please contact data(at)twin-life.de. Charges for downloading this data will be paid by the TwinLife project, so the use of the data is free of charge! Face-to-face interview: CAPI/CAMI Self-administered questionnaire: Computer-assisted (CASI) Self-administered questionnaire: Paper Educational measurements and tests Recording Self-administered questionnaire: Web-based Telephone interview: CATI F2F 1: Persönliche Haushaltsinterviews auf Basis dreier verschiedener Interview-Modi (Persönliches Interview: CAPI (Computerunterstützte persönliche Befragung), Selbstausfüller: CASI (Computerunterstützte Selbstbefragung), Selbstausfüller: Papier) plus Messungen und Tests der kognitiven Fähigkeiten sowie Scans/Fotos von Zeugnissen; Fragebögen für außerhäusig lebende Teilnehmer in zwei Modi: Selbstausfüller: CAWI (Computerunterstütztes Web-Interview) und Selbstausfüller: Papier. CATI 1: Telefonische Haushalts- und Personenbefragung. F2F 2: Persönliche Haushaltsinterviews auf Basis dreier verschiedener Interview-Modi (Persönliches Interview: CAPI (Computerunterstützte persönliche Befragung), Selbstausfüller: CASI (Computerunterstützte Selbstbefragung), Selbstausfüller: Papier) plus Gummibärchentest sowie Scans/Fotos von Zeugnissen CATI 2: Telefonische Haushalts- und Personenbefragung. Corona-Zusatzbefragung CoV 1: CAWI (Computerunterstütztes Web-Interview) F2F 3: Persönliche Haushaltsinterviews auf Basis verschiedener Interview-Modi (Persönliches Interview: CAPI (Computerunterstützte persönliche Befragung), Selbstausfüller: CASI (Computerunterstützte Selbstbefragung) und CAWI (Computerunterstütztes Web-Interview), Selbstausfüller: Papier plus Aufzeichnungen der APGAR-scores, Scans/Fotos von Zeugnissen und Speichelproben). CoV 2: CAPIbyPhone (Computerunterstützte persönliche Befragung), CATI (Computerunterstütztes Telefon-Interview) oder CAWI (Computerunterstütztes Web-Interview) F2F 1: Household interviews with the family via three different interview modes (Face-to-face interview: CAPI (Computer Assisted Personal Interview), Self-administered questionnaire: CASI (Computer Assisted Self-Interview), and Self-administered questionnaire: Paper plus cognitive tests, scans/photos of certificates; interviews with family members living outside the interviewed households by two modes (Self-administered questionnaire: CAWI (Computer Assisted Web Interview), Self-administered questionnaire: Paper. CATI 1: individual and household interviews by phone. F2F 2: Household interviews with the family via three different interview modes (Face-to-face interview: CAPI (Computer Assisted Personal Interview), Self-administered questionnaire: CASI (Computer Assisted Self-Interview), and Self-administered questionnaire: Paper plus gummy bear tests, scans/photos of certificates. CATI 2: individual and household interviews by phone. CoV 1: CAWI (Computer Assisted Web Interview) F2F 3: Household interviews with the family via different interview modes (Face-to-face interview: CAPI (Computer Assisted Personal Interview), Self-administered questionnaire: CASI (Computer Assisted Self-Interview), CAWI (Computer Assisted Web Interview), Self-administered questionnaire: Paper plus recording of the APGAR score, scans/photos of school reports, saliva sample). CoV 2: CAPIbyPhone (Computer Assisted Personal Interview), CATI (Computer Assisted Telephone Interview) or CAWI (Computer Assisted Web Interview)

  • Open Access
    Authors: 
    Oncini, Filippo;
    Publisher: UK Data Service
    Project: EC | HUNG (838965)

    The survey aimed to gather data on the impact of the COVID19 outbreak on the food support providers active in Greater Manchester. The lockdown created organizational hurdles to many services providing food to the most vulnerable. The survey explored more in depth the obstacles, the needs and the prospects of 55 organizations that were on the frontline in the first months of the crisis.

  • Research data . 2022
    Authors: 
    Sport England; Ipsos;
    Publisher: UK Data Service

    <p>The <span style="font-style: italic;">Active Lives Survey</span> (ALS) commenced in November 2015. It replaces the Active People Survey, which ran from 2005 to 2015. The survey provides the largest sample size ever established for a sport and recreation survey and allows levels of detailed analysis previously unavailable. It identifies how participation varies from place to place, across different sports, and between different groups in the population. The survey also measures levels of activity (active, fairly active and inactive), the proportion of the adult population that volunteer in sports on a weekly basis, club membership, sports spectating and wellbeing measures such as happiness and anxiety, etc. The questionnaire was designed to enable analysis of the findings by a broad range of demographic information, such as gender, social class, ethnicity, household structure, age, and disability.<br><br>More general information about the study can be found on the Sport England <a href="https://www.sportengland.org/research/active-lives-survey/">Active Lives Survey</a> webpage and the <a href="https://activelives.sportengland.org/">Active Lives Online</a> website, including reports and data tables.<br> </p> <p><span style="font-style: italic;">Active Lives Adults Survey, 2020-2021</span><br></p> <p>The Coronavirus (COVID-19) pandemic developed rapidly during 2020 and 2021. Fieldwork for the Active Lives survey continued throughout the pandemic. This data, therefore, reflects the impact of coronavirus (COVID-19) on activity levels and the government’s policies to contain its spread. The survey instrument was largely unchanged. More general information about the study can be found on the Sport England&nbsp;<a href="https://www.sportengland.org/research/about-our-research/active-people-survey/" style="background-color: rgb(255, 255, 255);">Active People Survey</a>&nbsp;and&nbsp;<a href="https://www.sportengland.org/research/active-lives-survey/" style="background-color: rgb(255, 255, 255);">Active Lives Survey</a>&nbsp;webpages and&nbsp;<a href="https://activelives.sportengland.org/" style="background-color: rgb(255, 255, 255);">Active Lives Online</a>&nbsp;website.</p>