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Trial Evaluation of Business in the Community's (BITC) "Time to Read" Pupil Mentoring Programme 2006-2008
No full textThis dataset pertains to the findings of a randomized control trial (RCT) evaluating the 'Time to Read' pupil mentoring programme from Business in the Community. The programme is delivered by volunteer metors who spend one hour per week reading with two children on a one-to-one basis (30 minutes each). The RCT aimed to assess the impact of the 'Time to Read' programme on children. A total of seven hundred and thirty four children form fifty schools in Northern Ireland took part in the RCT between September 2006 and June 2008. Three hundred and sixty children were randomly assigned to the intervention group and three hundred and seventy four to the control group. Children in both groups were tested on outcomes relating to self-esteem, aspirations for the future, reading ability and enjoyment of education. Outcomes were measured before the intervention, and again every four months for the next two years
European Union Survey of Income and Living Conditions (EU-SILC), 2020
No full textThe Survey on Income and Living Conditions (SILC) in Ireland is a household survey covering a broad range of issues in relation to income and living conditions. It is the official source of data on household and individual income and also provides a number of key national poverty indicators, such as the ‘at risk of poverty’ rate, the consistent poverty rate and rates of enforced deprivation. The primary focus of the Survey on Income and Living Conditions (SILC) is the collection of information on the income and living conditions of different types of households in Ireland, in order to derive indicators on poverty, deprivation and social exclusion. It is a voluntary survey of private households. The SILC Anonymised Microdata File (AMF) contains both personal and household level data. Household data is at present duplicated for each member of the household. If performing household level analysis, please be aware of this and subset the data to include a single entry per (interview_1). In 2021 the European legislative basis (Regulation No 1177/2003) for the production of statistics on income and living conditions has been repealed by Regulation 2019/1700. This new framework regulation establishes a common framework for European statistics relating to persons and households, based on data at individual level collected by samples. In order to meet the requirements of the new regulation, the Central Statistics Office (CSO) introduced changes to many SILC business processes. These changes have resulted in a break in the SILC time series for 2020. Data from 2020 onwards is not directly comparable with data from 2004-2019. To make the difference clear, national use variables from 2020 onwards have been re-named. Census Revision to SILC 2020-SILC 2022 The annual Survey of Income and Living Condition (SILC) results are weighted using population estimates which are generated on an ongoing basis. Census of Population 2022 results have been used to revise population estimates for 2020 to 2022, and consequently results for SILC survey years 2020, 2021 and 2022 are revised
Survey of Lifestyle, Attitudes and Nutrition (SLÁN), 2007
No full textThe SLÁN 2007 survey was commissioned by the Health Promotion Unit of the Department of Health & Children and carried out by Royal College of Surgeons (RCSI), The Economic and Social Research Institute (ESRI), University College Cork (UCC) and The National University of Ireland Galway (NUIG). SLÁN 2007 is the largest survey to date. The survey deals with general health, behaviours relating to health and the use of certain health services. 1,200 respondents of the survey also participated in a detailed medical examination
Healthy Ireland Survey, 2015
No full textThe Healthy Ireland Survey is an annual interviewer administered face-to-face survey conducted on behalf of the Department of Health by Ipsos MRBI. The first wave with 7,539 participants was carried out in 2014/2015. Its purpose is to provide current and credible data about the wide variety of factors which determine health and wellbeing in the population aged 15 years and older. The topics covered include general health, health service utilisation and key lifestyle factors, such as smoking, alcohol consumption, physical activity, diet, sexual health and wellbeing to monitor the key trends and policy impacts in those areas. It also offers flexibility for the substitution of further modules to meet particular policy needs, including cross-sectoral /health determinant ‘health in all policies’ issues. A questionnaire was developed using validated questions where possible. This was done to ensure comparability with other surveys and to facilitate our international reporting to the EU, the OECD and the World Health Organization. In addition to completing the survey questionnaire individuals interviewed on this wave of the survey were asked to undertake a physical measurement module. Within this module interviewers measured and recorded the respondent’s height, weight and waist circumference. A total of 6,142 respondents (81%) participated in this module. After completing the survey questionnaire, respondents aged 17 and over were asked to complete a self-completion questionnaire on issues relating to sexual health. A total of 6,529 respondents (87% of those aged 17 and over) completed at least part of this questionnaire. Approval to conduct the study was provided by the Research Ethics Committee at the Royal College of Physicians of Ireland
European Union Survey of Income and Living Conditions (EU-SILC), 2006
No full textThe Survey on Income and Living Conditions (SILC) in Ireland is a household survey covering a broad range of issues in relation to income and living conditions. It is the official source of data on household and individual income and also provides a number of key national poverty indicators, such as the ‘at risk of poverty’ rate, the consistent poverty rate and rates of enforced deprivation. The primary focus of the Survey on Income and Living Conditions (SILC) is the collection of information on the income and living conditions of different types of households in Ireland, in order to derive indicators on poverty, deprivation and social exclusion. It is a voluntary survey of private households. The SILC Anonymised Microdata File (AMF) contains both personal and household level data. Household data is at present duplicated for each member of the household. If performing household level analysis, please be aware of this and subset the data to include a single entry per household (interview_hh = 1). Please note: In 2020 AMF was revised to be more in line with the SILC RMF. Variables were renamed in accordance with Eurostats Doc65, which provides methodological guidelines and description of EU-SILC target variables. The target variables within the AMF are data on household and individual income as well as a number of key national poverty indicators, therefore variables identified as being not relevant to SILC were removed from the AMF. Furthermore, additional statistical disclosure controls were also implemented in the revisions so as to adhere to updates of the Legislation, Governance & Data Policies of the CSO. Please note: SILC AMF data is cross-sectional microdata in which household and/or individuals cannot be tracked over time. The household id variables in each cross sectional file are randomly generated and cannot be linked between yearly datasets
Irish Health Survey (IHS), 2015
No full textThe Irish Health Survey (IHS) was collected under Regulation (EC) No 1338/2008 of the European Parliament and of the Council of 16 December 2008 on Community statistics on public health and health and safety at work. This survey fulfils the need for public health policies to obtain reliable data on health status, health care usage and health determinants. Questionnaire The Irish Health Survey was designed in line with the third wave of the European Health Interview Survey (EHIS)2. The collection of the data under the aforementioned European Regulation implies that harmonised data can be obtained across the European continent. The Irish Health Survey can be divided into three fundamental components. These are the European Health Status Module (EHSM), the European Health Care Module (EHCM), and the European Health Determinants Module (EHDM). The European Health Status Module: The module on health status is a central element of the survey. It allows measurement of the health status of the population in general, and not only in relation to specific health problems. It covers different aspects and dimensions of health: physical and mental health, chronic and temporary problems and specific conditions. It covers the general impact on the functional status and the limitations in activities of daily living of the respondents. The first three general questions on self-perceived health, long standing illnesses or health problems, and activity limitations constitute the Minimum European Health Module (MEHM). The European Health Care Module: The ECHM module collects data on the use of health care services and the unmet needs for health care. Information on health care consumption is an essential part of the health information system in order to assign necessary resources to the population. This allows analysis of the relationships between health consumption and several determinants such as health status, lifestyles or socio-demographic characteristics as well as the relationships between different types of health care use. The European Health Determinants Module: The general focus of this module is to measure aspects in lifestyles or health-related behaviours. These may have a positive or negative impact on an individual’s health status. Along with the above data, additional variables collected included were; NUTS3 region, sex, age, nationality, and level of deprivatio
Digitale Ungleichheiten in Deutschland
No full textDeutsch: Die Daten für dieses Projekt stammen aus einer Webbefragung von in Deutschland lebenden Personen mit Internetzugang im Alter zwischen 18 und 64 Jahren. Die Rekrutierung der Befragten erfolgte über das Online Access Panel Bilendi. Vom 07. bis 16. August 2024 wurden 17.226 im Bilendi-Panel registrierte Personen per E-Mail eingeladen, an der Webumfrage teilzunehmen. Zur Annäherung an die Zielpopulation wurden einfache Quoten für Alter, Bildung und Geschlecht verwendet. 1.718 Panelmitglieder starteten die Befragung, 402 Personen wurden aufgrund ihres Alters oder Wohnorts ausquotiert, 230 Personen wegen bereits erfüllter Quoten. V on den verbleibenden 1.086 Personen haben 32 den Fragebogen nicht beendet (2,9%). Insgesamt haben 1.054 Personen den Fragebogen komplett ausgefüllt. Zwei Beobachtungen wurden aus dem Datensatz entfernt, da sie von derselben Panel-ID stammten. Damit ergibt sich ein Datensatz mit insgesamt 1.052 Beobachtungen. Die Befragung umfasst Fragen zu Einstellungen zu Künstlicher Intelligenz und dem Large Language Model ChatGPT, digitalen Kompetenzen, Arbeitsplatzzufriedenheit, Arbeitsplatzunsicherheit und Digitalisierung am Arbeitsplatz, der Nutzung sozialer Medien, politischen Einstellungen und Radikalismus, Geschlechterrollenbildern und Soziodemografie. Der Fragebogen wurde in UniPark programmiert. Die mittlere Zeit zum Ausfüllen des Fragebogens betrug 12 Minuten und 22 Sekunden. 57,5% der Befragten füllten den Fragebogen auf einem Smartphone aus. English: The data for this project come from a web survey of people living in Germany with Internet access aged between 18 and 64. Respondents were recruited via the Bilendi online access panel. From August 7 to 16, 2024, 17,226 people registered in the Bilendi panel were invited by email to take part in the web survey. Simple quotas for age, education and gender were used to approximate the target population. 1,718 panel members started the survey, 402 people were excluded due to their age or place of residence, 230 people due to already fulfilled quotas. Of the remaining 1,086 people, 32 did not complete the questionnaire (2.9%). A total of 1,054 people completed the questionnaire in full. Two observations were removed from the data set as they came from the same panel ID. This results in a data set with a total of 1,052 observations. The survey includes questions on attitudes towards artificial intelligence and the Large Language Model ChatGPT, digital competences, job satisfaction, job insecurity and digitalization in the workplace, the use of social media, political attitudes and radicalism, gender role attitudes, and socio-demographics. The questionnaire was programmed in UniPark. The median time to complete the questionnaire was 12 minutes and 22 seconds. 57.5% of respondents completed the questionnaire on a smartphone.Deutsch: Die Daten für dieses Projekt stammen aus einer Webbefragung von in Deutschland lebenden Personen mit Internetzugang im Alter zwischen 18 und 64 Jahren. Die Rekrutierung der Befragten erfolgte über das Online Access Panel Bilendi. Vom 07. bis 16. August 2024 wurden 17.226 im Bilendi-Panel registrierte Personen per E-Mail eingeladen, an der Webumfrage teilzunehmen. Zur Annäherung an die Zielpopulation wurden einfache Quoten für Alter, Bildung und Geschlecht verwendet. 1.718 Panelmitglieder starteten die Befragung, 402 Personen wurden aufgrund ihres Alters oder Wohnorts ausquotiert, 230 Personen wegen bereits erfüllter Quoten. V on den verbleibenden 1.086 Personen haben 32 den Fragebogen nicht beendet (2,9%). Insgesamt haben 1.054 Personen den Fragebogen komplett ausgefüllt. Zwei Beobachtungen wurden aus dem Datensatz entfernt, da sie von derselben Panel-ID stammten. Damit ergibt sich ein Datensatz mit insgesamt 1.052 Beobachtungen. Die Befragung umfasst Fragen zu Einstellungen zu Künstlicher Intelligenz und dem Large Language Model ChatGPT, digitalen Kompetenzen, Arbeitsplatzzufriedenheit, Arbeitsplatzunsicherheit und Digitalisierung am Arbeitsplatz, der Nutzung sozialer Medien, politischen Einstellungen und Radikalismus, Geschlechterrollenbildern und Soziodemografie. Der Fragebogen wurde in UniPark programmiert. Die mittlere Zeit zum Ausfüllen des Fragebogens betrug 12 Minuten und 22 Sekunden. 57,5% der Befragten füllten den Fragebogen auf einem Smartphone aus. English: The data for this project come from a web survey of people living in Germany with Internet access aged between 18 and 64. Respondents were recruited via the Bilendi online access panel. From August 7 to 16, 2024, 17,226 people registered in the Bilendi panel were invited by email to take part in the web survey. Simple quotas for age, education and gender were used to approximate the target population. 1,718 panel members started the survey, 402 people were excluded due to their age or place of residence, 230 people due to already fulfilled quotas. Of the remaining 1,086 people, 32 did not complete the questionnaire (2.9%). A total of 1,054 people completed the questionnaire in full. Two observations were removed from the data set as they came from the same panel ID. This results in a data set with a total of 1,052 observations. The survey includes questions on attitudes towards artificial intelligence and the Large Language Model ChatGPT, digital competences, job satisfaction, job insecurity and digitalization in the workplace, the use of social media, political attitudes and radicalism, gender role attitudes, and socio-demographics. The questionnaire was programmed in UniPark. The median time to complete the questionnaire was 12 minutes and 22 seconds. 57.5% of respondents completed the questionnaire on a smartphone
Code/Syntax: Ungleiche Chancen beim Zugang zu kognitiv anspruchsvolleren Ausbildungsberufen
No full textMit den veröfffentlichten Stata-Syntaxdateien (.do) ist es möglich, die im zitierten Artikel berichteten Ergebnisse zu replizieren. Dazu benötigen Sie zudem folgende Datensätze: - NEPS-Netzwerk (2021): Nationales Bildungspanel, Scientific Use File der Startkohorte Klasse 9. Leibniz-Institut für Bildungsverläufe (LIfBi), Bamberg. https://doi.org/10.5157/NEPS:SC4:13.0.0. LIfBi Leibniz Institute for Educational Trajectories via RemoteNEPS - Darüber hinaus wird das kognitiven Anforderungsniveau der Ausbildungsberufe benötigt. Ein entsprechender Datensatz kann , nach Absprache mit dem Datengeber Nicolas Sander vom berufspsychologischen Service der Bundesagentur für Arbeit, von den Autorinnen zur Verfügung gestellt werden.Mit den veröfffentlichten Stata-Syntaxdateien (.do) ist es möglich, die im zitierten Artikel berichteten Ergebnisse zu replizieren. Dazu benötigen Sie zudem folgende Datensätze: - NEPS-Netzwerk (2021): Nationales Bildungspanel, Scientific Use File der Startkohorte Klasse 9. Leibniz-Institut für Bildungsverläufe (LIfBi), Bamberg. https://doi.org/10.5157/NEPS:SC4:13.0.0. LIfBi Leibniz Institute for Educational Trajectories via RemoteNEPS - Darüber hinaus wird das kognitiven Anforderungsniveau der Ausbildungsberufe benötigt. Ein entsprechender Datensatz kann , nach Absprache mit dem Datengeber Nicolas Sander vom berufspsychologischen Service der Bundesagentur für Arbeit, von den Autorinnen zur Verfügung gestellt werden
Gemeinderatswahlen im deutschen Mehrebenensystem
No full textStandardisierte telefonische Bevölkerungsbefragungen nach den Gemeinderatswahlen in Nordrhein-Westfalen (2020), Niedersachsen (2021), Hessen (2021) und Schleswig-Holstein (2023). Erfasst wurden Wahlbeteiligung, Wahlentscheidung sowie politische Einstellungen auf lokaler und nationaler Ebene, lokale Kontexte und soziodemografische Merkmale zur Analyse kommunalen Wahlverhaltens in vier Bundesländern.Standardisierte telefonische Bevölkerungsbefragungen nach den Gemeinderatswahlen in Nordrhein-Westfalen (2020), Niedersachsen (2021), Hessen (2021) und Schleswig-Holstein (2023). Erfasst wurden Wahlbeteiligung, Wahlentscheidung sowie politische Einstellungen auf lokaler und nationaler Ebene, lokale Kontexte und soziodemografische Merkmale zur Analyse kommunalen Wahlverhaltens in vier Bundesländern
Replication material: Adaptations in Youths’ Willingness to Be Spatially Mobile: Influence of Status Aspirations and Regional Disparities
No full textThis study includes Stata script files for the replication of quantitative results from an article published in the journal 'Social Inclusion' (see below for citation of the article). Abstract of the referenced article: Spatial mobility is key to facilitating successful transitions into vocational education and training (VET), especially for youths from disadvantaged regions. In line with the agency-structure framework, the decision to become mobile is conceptualized as an adaptive strategy that young people employ to achieve their goals when faced with persistent challenges or regional barriers. This study investigates how youths applying for VET adapt their willingness to be spatially mobile over time. It examines the influence of occupational status aspirations and the regional opportunity structure on this decision-making process. Using data from the National Educational Panel Study (NEPS), multilevel growth curve models are estimated to analyze adaptations in the mobility radius of VET applicants over up to three years (N = 1,017). To assess the regional opportunity structure, small-scale administrative geospatial data on the availability of youths’ aspired occupations are used as an individualized indicator of regional mismatch. The results show that VET applicants’ willingness to be mobile increases over time. High-status aspirations are consistently associated with a greater willingness to be mobile, largely independent of search duration or regional mismatch. Conversely, VET applicants with lower status aspirations exhibit notable adaptations, adjusting their mobility radius, particularly in response to increasing search duration or regional mismatch. These findings highlight the complex interplay between individual aspirations and the regional opportunity structure in shaping adaptations in the willingness to become mobile of unsuccessful VET applicants.This study includes Stata script files for the replication of quantitative results from an article published in the journal 'Social Inclusion' (see below for citation of the article). Abstract of the referenced article: Spatial mobility is key to facilitating successful transitions into vocational education and training (VET), especially for youths from disadvantaged regions. In line with the agency-structure framework, the decision to become mobile is conceptualized as an adaptive strategy that young people employ to achieve their goals when faced with persistent challenges or regional barriers. This study investigates how youths applying for VET adapt their willingness to be spatially mobile over time. It examines the influence of occupational status aspirations and the regional opportunity structure on this decision-making process. Using data from the National Educational Panel Study (NEPS), multilevel growth curve models are estimated to analyze adaptations in the mobility radius of VET applicants over up to three years (N = 1,017). To assess the regional opportunity structure, small-scale administrative geospatial data on the availability of youths’ aspired occupations are used as an individualized indicator of regional mismatch. The results show that VET applicants’ willingness to be mobile increases over time. High-status aspirations are consistently associated with a greater willingness to be mobile, largely independent of search duration or regional mismatch. Conversely, VET applicants with lower status aspirations exhibit notable adaptations, adjusting their mobility radius, particularly in response to increasing search duration or regional mismatch. These findings highlight the complex interplay between individual aspirations and the regional opportunity structure in shaping adaptations in the willingness to become mobile of unsuccessful VET applicants