13 datasets found
  1. International Social Survey Programme: Health and Health Care I-II...

    • datacatalogue.cessda.eu
    • search.gesis.org
    Updated Dec 17, 2024
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    Evans, Ann; McEachern, Steven; Gray, Matthew; Zammit, Adam; Li, Lulu; National Survey Research Center at Renmin University of China, Beijing; Marinović Jerolimov, Dinka; Ančić, Branko; Brajdić Vuković, Marija; Cik, Tomislav; Jaklin, Katarina; Hamplová, Dana; Klusáček, Jan; Clement, Sanne L.; Andersen, Johannes; Møberg, Rasmus; Lolle, Henrik; Shamshiri-Petersen, Ditte; Andersen, Jørgen G.; Larsen, Christian A.; Sønderskov, Kim M.; Sommer Harrits, Gitte; Jæger, Mads; Gundelach, Peter; Levinsen, Klaus; Fridberg, Torben; Blom, Raimo; Melin, Harri; Borg, Sami; Laaksonen, Helena; Hakkola, Emilia; Jääskeläinen, Taina; Forsé, Michel; Bréchon Pierre; Gonthier, Frédéric; Astor, Sandrine; Zolotoukhine, Erik; Wolf, Christof; Naber, Dörte; Scholz, Evi; Lewin-Epstein, Noah; Meraviglia, Cinzia; Pedrazzani, Andrea; Guglielmi, Simona; Murata, Hiroko; Masaki, Miki; Aramaki, Hiroshi; Ganzeboom, Harry; Nagel, Ineke; Kolsrud, Kirstine; Skjåk, Knut K.; Agasøster, Bodil; Karlsen, Gry; Nikolaisen, Kristina; Guerrero, Linda Luz; Sandoval, Gerardo; Labucay, Iremae; Zieliński, Marcin W.; Jerzyński, Tomasz; Khakhulina, Ludmilla; Agapeeva, Ksenia; Bahna, Miloslav; DžambazoviĊ, Roman; Hafner-Fink, Mitja; Malnar, Brina; Struwig, Jare; Roberts, Benjamin; Sapin, Marlène; Joye, Dominique; Steinmetz, Stephanie; Chang, Ying-hwa; Wu, Chyi-In; mith, Tom W.; Marsden, Peter V.; Hout, Michael; Davern, Michael; Bautista, Rene; Freese, Jeremy; Morgan, Stephen L.; Herd, Pamela (2024). International Social Survey Programme: Health and Health Care I-II Cumulation [Dataset]. http://doi.org/10.4232/1.14438
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    Dataset updated
    Dec 17, 2024
    Dataset provided by
    NORC at the University of Chicago
    Human Sciences Research Councilhttps://hsrc.ac.za/
    University of California, Berkeley, USA
    Norwegian Social Science Data Services, Bergen, Norway
    University of Tampere, Finland
    Finnish Social Science Data Archive, University of Tampere, Finland
    Institute for Social Research, Zagreb, Croatia
    Levada-Center, Moscow, Russia
    China
    University of Milan, Dept. Social and Political Science, Milan, Italy
    Social Weather Stations, Quezon City, Philippines
    Department of Political Science, University of Southern Denmark, Odense, Denmark
    Sciences Po Grenoble - Université Grenoble Alpes - Pacte - CNRS, France
    NHK Broadcasting Culture Research Institute, Tokyo, Japan
    The Danish National Institute of Social Research, Copenhagen, Denmark
    VU University Amsterdam, Netherlands
    Institute of Sociology, Academia Sinica, Taipei City, Taiwan
    Institute for Sociology of Slovak Academy of Sciences, Bratislava, Slovakia
    GESIS Leibniz Institute for the Social Sciences, Mannheim, Germany
    Department of Sociology, University of Copenhagen, Denmark
    The Australian National University, Canberra, Australia
    Public Opinion and Mass Communication Research Centre (CJMMK), University of Ljubljana, Slovenia/ Faculty of Social Science, University of Ljubljana, Slovenia
    FRANCE-ISSP (Centre de Recherche en Economie et Statistique, Laboratoire de Sociologie Quantitative), Malakoff, France
    The National Survey Research Center, Renmin University of China, Beijing, China
    Institute of Social Research, University of Eastern Piedmont, Italy
    FORS, c/o University of Lausanne, Switzerland
    Department of Education, University of Aarhus, Aahrhus, Denmark
    Department of Political Science, University of Aarhus, Aarhus, Denmark
    Harvard University, Cambridge, Massachusetts, USA
    ANU Centre for Social Research and Methods, Australian National University, Canberra, Australia
    B.I. and Lucille Cohen Institute for public opinion, Tel-Aviv University, Israel
    Institute for Sociology of the Slovak Academy of Sciences, Comenius University, Bratislava, Slovakian Republic
    FORS swiss foundation for research in soical sciences, c/o University of Lausanne, Switzerland
    Robert B. Zajonc Institute for Social Studies, University of Warsaw, Poland
    Department of Economics, Politics and Public Administration, Aalborg University, Denmark
    Australian Consortium for Social and Political Research Inc., Black Rock, Victoria, Australia
    Institute of Sociology, Czech Academy of Sciences, Prague, Czech Republic
    Authors
    Evans, Ann; McEachern, Steven; Gray, Matthew; Zammit, Adam; Li, Lulu; National Survey Research Center at Renmin University of China, Beijing; Marinović Jerolimov, Dinka; Ančić, Branko; Brajdić Vuković, Marija; Cik, Tomislav; Jaklin, Katarina; Hamplová, Dana; Klusáček, Jan; Clement, Sanne L.; Andersen, Johannes; Møberg, Rasmus; Lolle, Henrik; Shamshiri-Petersen, Ditte; Andersen, Jørgen G.; Larsen, Christian A.; Sønderskov, Kim M.; Sommer Harrits, Gitte; Jæger, Mads; Gundelach, Peter; Levinsen, Klaus; Fridberg, Torben; Blom, Raimo; Melin, Harri; Borg, Sami; Laaksonen, Helena; Hakkola, Emilia; Jääskeläinen, Taina; Forsé, Michel; Bréchon Pierre; Gonthier, Frédéric; Astor, Sandrine; Zolotoukhine, Erik; Wolf, Christof; Naber, Dörte; Scholz, Evi; Lewin-Epstein, Noah; Meraviglia, Cinzia; Pedrazzani, Andrea; Guglielmi, Simona; Murata, Hiroko; Masaki, Miki; Aramaki, Hiroshi; Ganzeboom, Harry; Nagel, Ineke; Kolsrud, Kirstine; Skjåk, Knut K.; Agasøster, Bodil; Karlsen, Gry; Nikolaisen, Kristina; Guerrero, Linda Luz; Sandoval, Gerardo; Labucay, Iremae; Zieliński, Marcin W.; Jerzyński, Tomasz; Khakhulina, Ludmilla; Agapeeva, Ksenia; Bahna, Miloslav; DžambazoviĊ, Roman; Hafner-Fink, Mitja; Malnar, Brina; Struwig, Jare; Roberts, Benjamin; Sapin, Marlène; Joye, Dominique; Steinmetz, Stephanie; Chang, Ying-hwa; Wu, Chyi-In; mith, Tom W.; Marsden, Peter V.; Hout, Michael; Davern, Michael; Bautista, Rene; Freese, Jeremy; Morgan, Stephen L.; Herd, Pamela
    Time period covered
    Mar 2011 - Jul 17, 2023
    Area covered
    Denmark
    Measurement technique
    Face-to-face interview: Paper-and-pencil (PAPI), Face-to-face interview: Computer-assisted (CAPI/CAMI), Self-administered questionnaire: Paper, Self-administered questionnaire: Web-based (CAWI), Telephone interview: Computer-assisted (CATI)
    Description

    The International Social Survey Programme (ISSP) is a continuous programme of cross-national collaboration running annual surveys on topics important for the social sciences. The programme started in 1984 with four founding members - Australia, Germany, Great Britain, and the United States – and has now grown to almost 50 member countries from all over the world. As the surveys are designed for replication, they can be used for both, cross-national and cross-time comparisons. Each ISSP module focuses on a specific topic, which is repeated in regular time intervals. Please, consult the documentation for details on how the national ISSP surveys are fielded. The present study focuses on questions about individual health and the health care system.

    ISSP Health and Health Care I-II cumulates the data of the integrated data files of • ISSP 2011 (ZA5800 Data file Version 3.0.0, https://doi.org/10.4232/1.12252) and • ISSP 2021 (ZA8000 Data file Version 2.0.0, https://doi.org/10.4232/5.ZA8000.2.0.0). It comprises data from all ISSP member countries participating in at least two Health and Health Care modules. The data set contains: • Cumulated topic-related (substantial) variables, which appear in at least two Health and Health Care and • background variables, mostly covering demographics, which appear in at least two Health and Health Care modules.
    Satisfaction with life (happiness); confidence in the national health care system; justification for better healthcare for people with higher incomes; agreement with various statements on the healthcare system (People use health care services more than necessary, the government should provide only limited health care services, in general, the health care system in the country is inefficient); willingness to pay higher taxes to improve the level of health care for all people in the country; attitude towards the access to publicly funded health care for people without citizenship of the country and even if they behave in ways that damage their health; opinion on causes why people suffer from severe health problems (because they behaved in ways that damaged their health, because of the environment they are exposed to at work or where they live, because of their genes, because they are poor); alternative/ traditional or folk medicine provides better solutions for health problems than mainstream/ Western traditional medicine; assessment of doctors in general in the country (doctors can be trusted, the medical skills of doctors are not as good as they should be, doctors care more about their earnings than about their patients); frequency of difficulties with work or household activities because of health problems, bodily aches or pains, unhappiness and depression, loss of self-confidence and insuperable problems in the past four weeks; frequency of visits to/ by a doctor and an alternative/ traditional/ folk health care practitioner during the past 12 months; reasons why the respondent did not receive needed medical treatment (could not pay for it, could not take the time off work or because of other commitments, the waiting list was too long); likelihood of getting the best treatment available in the country in the case of seriously illness; satisfaction with the health care system in the country; satisfaction with treatment at the last visit to a doctor and to an alternative health care practitioner; smoker status and number of smoked cigarettes per day; frequency of drinking four or more alcoholic drinks on the same day, of strenuous physical activity for at least 20 minutes, and of eating fresh fruit or vegetables; assessment of personal health status; respondent has a long-standing illness, a chronic condition, or a disability; respondent’s height (in cm) and weight (in kg); kind of personal health insurance.

    Demography: sex; age; years of birth; legal partnership status; steady life partner; education: years of schooling; highest education level; currently, formerly, or never in paid work (respondent and partner); employment relationship (respondent and partner); current employment status (respondent and partner); hours worked weekly (respondent and partner); occupation (ISCO 2008) (respondent and partner); supervising function at work (respondent and partner); number of other employees supervised; type of organization: for-profit vs. non-profit and public vs. private; trade union membership; household size; number of children above school entry age in household; number of children below school age in household; party affiliation (left-right); participation in last election; attendance of religious services; religious main groups (derived); Top Bottom self-placement; subjective social class; place of living urban – rural; household income groups (derived); country specific region.

    Additionally coded: ID number of respondent; unique cumulation respondent ID number; Case substitution flag; date of interview (year, month, day); ISSP Module year; country; country...

  2. r

    2000 Male Out Survey Data

    • researchdata.edu.au
    Updated 2011
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    Holt Martin; Kippax Susan; University of New South Wales; University of New South Wales; The University of New South Wales; Susan Kippax; Martin Holt (2011). 2000 Male Out Survey Data [Dataset]. http://doi.org/10.26190/UNSWORKS/1312
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    Dataset updated
    2011
    Dataset provided by
    University of New South Wales
    UNSW, Sydney
    Authors
    Holt Martin; Kippax Susan; University of New South Wales; University of New South Wales; The University of New South Wales; Susan Kippax; Martin Holt
    License

    Attribution-NonCommercial-NoDerivs 3.0 (CC BY-NC-ND 3.0)https://creativecommons.org/licenses/by-nc-nd/3.0/
    License information was derived automatically

    Time period covered
    2000
    Description

    A large sample of homosexually active men was recruited through the mail-out, self complete questionnaire procedure. The participants represent a broad cross-section of the homosexually active population of Australia, both gay community attached and non gay community attached men. The resultant data based on this diverse sample of homosexually active men drawn from every corner of Australia complement those findings from periodic surveys conducted in principal gay communities. Data was collected on demographic variables, sexual relationships, sexual practices, condom use, drug use, HIV optimism, sexual identity and engagement with the gay community. Sample Population: 1832 men who had had sex with another man in the past five years. Method of Data Collection: Self-completion. Kind of Data: SurveySampling Procedures: Questionnaires were distributed through two pornographic video catalogues.

  3. Data from: Australian National Social Science Survey, 1984

    • icpsr.umich.edu
    • search.datacite.org
    ascii, spss
    Updated Feb 16, 1992
    + more versions
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    Kelley, Jonathan; Cushing, Robert G.; Headey, Bruce (1992). Australian National Social Science Survey, 1984 [Dataset]. http://doi.org/10.3886/ICPSR09084.v1
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    spss, asciiAvailable download formats
    Dataset updated
    Feb 16, 1992
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Kelley, Jonathan; Cushing, Robert G.; Headey, Bruce
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/9084/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/9084/terms

    Time period covered
    1984
    Area covered
    Australia, Global
    Description

    This multipurpose survey measures a wide range of variables of interest in sociology, political science, and labor economics. It is similar to national social surveys conducted regularly in the United States, Britain, and West Germany, and much of the data are directly comparable. The questionnaire covers attitudes toward a broad range of topics, including government expenditures, taxation, inflation, crime, poverty, women and careers, migrants, political figures, and confidence in institutions such as banks and police. Other questions relate to the respondent's personal feelings about life, health, religion, moral issues, and family relationships. Political and economic data provided include party preference and voting history, income, and occupation. Additional background variables are available on education, birthplace, ethnic origin, religion, age, sex, location and size of town of residence, marital status, and union membership.

  4. A

    Australian Survey of Social Attitudes, 2021

    • dataverse.ada.edu.au
    pdf, type/x-r-syntax +2
    Updated Mar 13, 2025
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    Nicola McNeil; Steven McEachern; Steven McEachern; Bruce Tranter; Bruce Tranter; Shaun Wilson; Shaun Wilson; Nicola McNeil (2025). Australian Survey of Social Attitudes, 2021 [Dataset]. http://doi.org/10.26193/AH8VKX
    Explore at:
    xlsx(117015), zip(156714), zip(158260), pdf(5559622), pdf(48146), type/x-r-syntax(27370), pdf(56499), zip(686658), zip(325486), zip(296414), zip(149591), zip(226642), zip(174396), pdf(104549)Available download formats
    Dataset updated
    Mar 13, 2025
    Dataset provided by
    ADA Dataverse
    Authors
    Nicola McNeil; Steven McEachern; Steven McEachern; Bruce Tranter; Bruce Tranter; Shaun Wilson; Shaun Wilson; Nicola McNeil
    License

    https://dataverse.ada.edu.au/api/datasets/:persistentId/versions/4.0/customlicense?persistentId=doi:10.26193/AH8VKXhttps://dataverse.ada.edu.au/api/datasets/:persistentId/versions/4.0/customlicense?persistentId=doi:10.26193/AH8VKX

    Time period covered
    Dec 1, 2020 - Apr 29, 2022
    Area covered
    Australia
    Dataset funded by
    Australian Consortium for Social and Political Research Incorporated
    Description

    The Australian Survey of Social Attitudes (AuSSA) is Australia’s main source of data for the scientific study of the social attitudes, beliefs and opinions of Australians, how they change over time, and how they compare with other societies. The survey is used to help researchers better understand how Australians think and feel about their lives. It produces important information about the changing views and attitudes of Australians as we move through the 21st century. Similar surveys are run in other countries, so data from the AuSSA also allows us to compare Australia with countries all over the world. The aims of the survey are to discover: the range of Australians’ views on topics that are important to all of us; how these views differ for people in different circumstances; how they have changed over the past quarter century; and how they compare with people in other countries. AuSSA is also the Australian component of the International Social Survey Project (ISSP). The ISSP is a cross-national collaboration on surveys covering important topics. Each year, survey researchers in some 40 countries each do a national survey using the same questions. The ISSP focuses on a special topic each year, repeating that topic from time to time. The topic for the 2021 survey is "Health and Healthcare". This is the second time this has been the topic of the survey, having previously been the theme for the survey in 2011. The data from questions in sections B, C, D, E, F and G are embargoed until 1 January 2025.

  5. r

    PHIDU - Community Strengths (PHN) 2014-2016

    • researchdata.edu.au
    null
    Updated Jun 28, 2023
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    Torrens University Australia - Public Health Information Development Unit (2023). PHIDU - Community Strengths (PHN) 2014-2016 [Dataset]. https://researchdata.edu.au/phidu-community-strengths-2014-2016/2743872
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    nullAvailable download formats
    Dataset updated
    Jun 28, 2023
    Dataset provided by
    Australian Urban Research Infrastructure Network (AURIN)
    Authors
    Torrens University Australia - Public Health Information Development Unit
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Area covered
    Description

    This dataset, released July 2018, contains the community strength of areas based on Voluntary work for an organisation or group - people aged 15 years and over, 2016; Estimated number of people aged 18 years and over who did unpaid voluntary work in the last 12 months through an organisation (modelled estimates), 2014; Estimated number of people aged 18 years and over who are able to get support in times of crisis from people outside the household (modelled estimates), 2014; Estimated number of people aged 18 years and over (or their partner) who provide support to other relatives living outside the household (modelled estimates), 2014; Estimated number of people aged 18 years and over who disagree/strongly disagree with acceptance of other cultures (modelled estimates), 2014; Estimated number of people aged 18 years and over who, in the past 12 months, felt that they had experienced discrimination or have been treated unfairly by others (modelled estimates), 2014.

    The data is by Primary Health Network (PHN) 2017 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).

    There are 31 PHNs set up by the Australian Government. Each network is controlled by a board of medical professionals and advised by a clinical council and community advisory committee. The boundaries of the PHNs closely align with the Local Hospital Networks where possible.

    For more information please see the data source notes on the data.

    Source: Compiled by PHIDU based on the ABS Census of Population and Housing, August 2016; Estimates for Population Health Areas (PHAs) are modelled estimates and were produced by the ABS from the 2014 General Social Survey; estimates at the LGA and PHN level were derived from the PHA estimates; Estimates for Quintiles and Remoteness Areas were compiled by PHIDU based on direct estimates from the 2014 General Social Survey, ABS Survey TableBuilder.

    AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

  6. w

    Global Financial Inclusion (Global Findex) Database 2021 - Australia

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Dec 16, 2022
    + more versions
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    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - Australia [Dataset]. https://microdata.worldbank.org/index.php/catalog/4613
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    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    Australia
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Australia is 1000.

    Mode of data collection

    Landline and mobile telephone

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  7. A

    Australian Family Project, 1986

    • dataverse.ada.edu.au
    Updated Apr 1, 2018
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    Michael Bracher; Gordon Carmichael; Michael Bracher; Gordon Carmichael (2018). Australian Family Project, 1986 [Dataset]. http://doi.org/10.4225/87/DQCZ6C
    Explore at:
    tsv(785535), txt(406926), pdf(6090575), pdf(8218748), application/x-sas-syntax(971), tsv(1396995), application/x-sas-system(6744064), pdf(128307), pdf(72502), application/x-sas-syntax(6027), pdf(1498915), tsv(5279669), application/x-sas-system(2816512), txt(201091), pdf(2624606), application/x-sas-system(34146304)Available download formats
    Dataset updated
    Apr 1, 2018
    Dataset provided by
    ADA Dataverse
    Authors
    Michael Bracher; Gordon Carmichael; Michael Bracher; Gordon Carmichael
    License

    https://dataverse.ada.edu.au/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.4225/87/DQCZ6Chttps://dataverse.ada.edu.au/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.4225/87/DQCZ6C

    Time period covered
    Apr 1, 1986 - Apr 30, 1987
    Area covered
    Australia
    Description

    The Australian Family Project was established in 1985 to investigate the social, demographic and economic forces that have been changing the shape and nature of the Australian family over the last generation. To this end, a national survey program was initiated in 1986 to collect data which would facilitate this investigation. There are two waves of this survey: the survey of women aged 20 to 59 years, which was the first component of the national survey program; and the companion survey of men aged 20 to 59 years. The core of the women's questionnaire is a collection of detailed life histories, on marital unions, childbearing and children, contraception, work history and residential mobility. The use of a life history chart throughout the interview enabled the accurate recording of key events and changes in status, regardless of the number of events or changes for each respondent. Background information included date and country of birth; arrival in Australia; parents' country of birth, schooling; father's occupation; mother's age at marriage and subsequent work history; and details on respondent's childhood at age 14, such as place of residence and religious upbringing. Questions were also asked on respondent's schooling, both secondary and post-secondary, and qualifications gained. Further sections of the questionnaire dealt with marital unions: dates of commencement, background details of spouse, and attitudes to remarriage; childbearing and children: information such as age, sex, education and leaving home for each child, as well as responses to questions on numbers and timing of children; and contraception and health. Respondent's work history covered questions on all periods of work, whether full-time or part-time, changes to working hours, reasons for stopping and starting work, earnings and satisfaction with current job. The section on residential history included timing of moves, housing and rental issues, mortgages and financing and house acquisition. Questions were also asked on supplementary sources of income, division of household tasks and financial decision making. The interview concluded with a set of questions on the relative ease or difficulty of setting up a home and bringing up a family today, compared with twenty years ago, and more specific questions on decision making about the timing of first marriage and first birth. The men's questionnaire began with questions seeking attitudes towards sex roles within the family and towards home ownership. Other questions sought details of all marriages and cohabiting relationships and of the current divisions of labour and decision making within the home. Fertility histories and plans were then canvassed, followed by the 'leaving home' experience. The next section asked about activity in the housing market, after which details of labour force activity (past and current), income and position with respect to superannuation were sought. The final questions assessed current financial situation, personal wellbeing, perceptions of the relative ease or difficulty of raising a family and buying a home nowadays compared to a generation ago, and perceptions of the circumstances and decision making processes surrounding the transitions to marriage and parenthood. Background variables covering personal and parental characteristics include: age, education level, qualifications obtained, country of birth and religious observance. Also covered are respondent's childhood family circumstances and religious denomination, father's employment circumstances when respondent was aged 14, and parents' marital status. At ADA the data for the Australian Family Project are held in three files: Women's survey (File f), Men's survey (File m) and Household data (File hh).

  8. f

    Proposed examination sites for the AEEHS.

    • plos.figshare.com
    xls
    Updated May 31, 2024
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    Richard Kha; Oonagh Macken; Paul Mitchell; Gerald Liew; Lisa Keay; Colina Waddell; Eleanor Yang; Vu Do; Tim Fricke; John Newall; Bamini Gopinath (2024). Proposed examination sites for the AEEHS. [Dataset]. http://doi.org/10.1371/journal.pone.0301846.t001
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    xlsAvailable download formats
    Dataset updated
    May 31, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Richard Kha; Oonagh Macken; Paul Mitchell; Gerald Liew; Lisa Keay; Colina Waddell; Eleanor Yang; Vu Do; Tim Fricke; John Newall; Bamini Gopinath
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    IntroductionVision and hearing impairments are highly prevalent and have a significant impact on physical, psychological and social wellbeing. There is a need for accurate, contemporary national data on the prevalence, risk factors and impacts of vision and hearing loss in Australian adults.ObjectivesThe Australian Eye and Ear Health Survey (AEEHS) aims to determine the prevalence, risk factors and impacts of vision and hearing loss in both Aboriginal and Torres Strait Islander and non-Indigenous older adults.Methods and analysisThe AEEHS is a population-based cross-sectional survey which will include 5,000 participants (3250 non-Indigenous aged 50 years or older and 1750 Aboriginal and Torres Strait Islander people aged 40 years or older) from 30 sites covering urban and rural/regional geographic areas, selected using a multi-stage, random cluster sampling strategy. Questionnaires will be administered to collect data on socio-demographic, medical, ocular and ontological history. The testing battery includes assessment of blood pressure, blood sugar, anthropometry, visual acuity (presenting, unaided, pinhole and best-corrected), refraction, tonometry, slit lamp and dilated eye examination, ocular imaging including optical coherence tomography (OCT), OCT-angiography and retinal photography, and automated visual fields. Audiometry, tympanometry and video otoscopy will also be performed. The primary outcomes are age-standardised prevalence of cause-specific vision and hearing impairment. Secondary outcomes are prevalence of non-blinding eye diseases (including dry eye disease), patterns in health service utilisation, universal health coverage metrics, risk factors for vision and hearing impairment, and impact on quality of life.

  9. i

    World Values Survey - Wave 7, 2018 - Australia

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    Updated Oct 12, 2023
    + more versions
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    The World Values Survey (WVS) (2023). World Values Survey - Wave 7, 2018 - Australia [Dataset]. https://catalog.ihsn.org/catalog/11554
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    Dataset updated
    Oct 12, 2023
    Dataset authored and provided by
    The World Values Survey (WVS)
    Time period covered
    2021
    Area covered
    Australia
    Description

    Abstract

    The World Values Survey (WVS) is an international research program devoted to the scientific and academic study of social, political, economic, religious and cultural values of people in the world. The project’s goal is to assess which impact values stability or change over time has on the social, political and economic development of countries and societies. The project grew out of the European Values Study and was started in 1981 by its Founder and first President (1981-2013) Professor Ronald Inglehart from the University of Michigan (USA) and his team, and since then has been operating in more than 120 world societies. The main research instrument of the project is a representative comparative social survey which is conducted globally every 5 years. Extensive geographical and thematic scope, free availability of survey data and project findings for broad public turned the WVS into one of the most authoritative and widely-used cross-national surveys in the social sciences. At the moment, WVS is the largest non-commercial cross-national empirical time-series investigation of human beliefs and values ever executed.

    The project’s overall aim is to analyze people’s values, beliefs and norms in a comparative cross-national and over-time perspective. To reach this aim, project covers a broad scope of topics from the field of Sociology, Political Science, International Relations, Economics, Public Health, Demography, Anthropology, Social Psychology and etc. In addition, WVS is the only academic study which covers the whole scope of global variations, from very poor to very rich societies in all world’s main cultural zones.

    The WVS combines two institutional components. From one side, WVS is a scientific program and social research infrastructure that explores people’s values and beliefs. At the same time, WVS comprises an international network of social scientists and researchers from 120 world countries and societies. All national teams and individual researchers involved into the implementation of the WVS constitute the community of Principal Investigators (PIs). All PIs are members of the WVS.

    The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. The WVS findings have proved to be valuable for policy makers seeking to build civil society and stable political institutions in developing countries. The WVS data is also frequently used by governments around the world, scholars, students, journalists and international organizations such as the World Bank, World Health Organization (WHO), United Nations Development Program (UNDP) and the United Nations Headquarters in New York (USA). The WVS data has been used in thousands of scholarly publications and the findings have been reported in leading media such as Time, Newsweek, The New York Times, The Economist, the World Development Report, the World Happiness Report and the UN Human Development Report.

    The World Values Survey Association is governed by the Executive Committee, the Scientific Advisory Committee, and the General Assembly, under the terms of the Constitution.

    Strategic goals for the 7th wave included:

    Expansion of territorial coverage from 60 countries in WVS-6 to 80 in WVS-7; Deepening collaboration within the international development community; Deepening collaboration within NGOs, academic institutions and research foundations; Updating the WVS-7 questionnaire with new topics & items covering new social phenomena and emerging processes of value change; Expanding the 7th wave WVS with data useful for monitoring the SDGs; Expanding capacity and resources for survey fieldwork in developing countries. The 7th wave continued monitoring cultural values, attitudes and beliefs towards gender, family, and religion; attitudes and experience of poverty; education, health, and security; social tolerance and trust; attitudes towards multilateral institutions; cultural differences and similarities between regions and societies. In addition, the WVS-7 questionnaire has been elaborated with the inclusion of such new topics as the issues of justice, moral principles, corruption, accountability and risk, migration, national security and global governance.

    For more information on the history of the WVSA, visit https://www.worldvaluessurvey.org/WVSContents.jsp ›Who we are › History of the WVSA.

    Geographic coverage

    Australia.

    The WVS has just completed wave 7 data that comprises 64 surveys conducted in 2017-2022. With 64 countries and societies around the world and more than 80,000 respondents, this is the latest resource made available for the research community.

    The WVS-7 survey was launched in January 2017 with Bolivia becoming the first country to conduct WVS-7. In the course of 2017 and 2018, WVS-7 has been conducted in the USA, Mexico, Brazil, Argentina, Chile, Ecuador, Peru, Andorra, Greece, Serbia, Romania, Turkey, Russia, Germany, Thailand, Australia, Malaysia, Indonesia, China, Pakistan, Egypt, Jordan, Nigeria, Iraq and over dozen of other world countries. Geographic coverage has also been expanded to several new countries included into the WVS for the first time, such as Bolivia, Greece, Macao SAR, Maldives, Myanmar, Nicaragua, and Tajikistan.

    Analysis unit

    Household, Individual

    Sampling procedure

    The sample type preferable for using in the World Values Survey is a full probability sample of the population aged 18 years and older. A detailed description of the sampling methodology is provided in the country specific sample design documentation available for download from WVS.

    A detailed description of the sampling methodology is provided in the Australia 2018 sample design documentation available for download from WVS and also from the Downloads section of the metadata.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    The survey was fielded in the following language(s): Armenian. The questionnaire is available for download from the WVS website.

  10. STEPS 2004, Non Communicable Disease Risk Factor - Nauru

    • microdata.pacificdata.org
    Updated May 27, 2019
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    Centre for Physical Activity and Health at the Universities of New South Wales and Sydney in Australia (2019). STEPS 2004, Non Communicable Disease Risk Factor - Nauru [Dataset]. https://microdata.pacificdata.org/index.php/catalog/239
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    Dataset updated
    May 27, 2019
    Dataset provided by
    World Health Organizationhttps://who.int/
    Centre for Physical Activity and Health at the Universities of New South Wales and Sydney in Australia
    Nauru Ministry of Health
    Time period covered
    2004
    Area covered
    Nauru
    Description

    Abstract

    The Nauru-STEPS was a nation-wide representative survey of 15 to 64 year olds with the following objectives: 1. To document the national prevalence and patterns of tobacco use, alcohol consumption, dietary behaviours, physical activity, body mass index, elevated blood pressure, and biochemical markers such as blood glucose and blood lipids in Nauru. 2. To provide reliable and up-to-date information on NCD risk factors for planning and evaluating public health initiatives, and for identifying future demands for health services in managing and treating NCDs.

    The planning and implementation of the survey was a collaborative initiative between the Nauru Ministry of Health (MOH), the World Health Organization (WHO) and the Centre for Physical Activity and Health at the Universities of New South Wales and Sydney in Australia. The study was supported by the Australian Agency for International Development (AusAID).

    Geographic coverage

    National coverage

    Analysis unit

    -individual -households

    Universe

    The survey population included non-institutionalised individuals in the 15-64 year-old age category living in Nauru during the survey period. Indigenous Nauruans, I-Kiribati and Tuvaluan residents comprised approximately 90% of the total population (Bureau of Statistics, 2004). The remaining population consisted of Asians (Chinese, Filipinos and other South East Asians), other Pacific islanders and expatriate residents (i.e. Australians, Europeans, New Zealanders).

    This latter group was excluded from the sampling frame as they were considered to be highly transient and relatively low users of health services in Nauru. Individuals with mental illness, physical or developmental disabilities were also excluded from the survey.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Sample selection - approximately 2,500 randomly selected participants aged 15-64 years Selection process - using a simple random sampling method Stratification - stratified by age and sex Stages of sample selection - initial sample size calculations were performed assuming a prevalence of approximately 10% for major variables of interest (e.g.diabetes), an ability to ascertain an estimated prevalence within approximately 1% of the true prevalence with a 95% confidence level. These calculations suggested that a total sample size of approximately 2,584 in the target population of 15 to 64 year olds would be sufficient for the purposes of this study Strategy for absent respondent/not found/refusals (replacement or not) - a reserve list of an additional 250 participants was generated for each age/sex group to replace any of the original participants in that age/sex group who were ineligible to participate in the study (i.e. those not being in the country during the survey or those individuals with physical or mental disabilities or already deceased). Overall, usable data for STEPS 1-3 were obtained from 2,272 participants, with a total response rate of 89.7%. Of the 2,272 respondents, 1086 were men and 1186 were women.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaires or instrument for the Nauru Steps Survey 2004 were the core questions in the STEPS 1-3 instrument remained unchanged (Bonita et al., 2001). The Step 1 questionnaire was administered in each household, which collected various information on household members including sex, age and time spent in schools. The Step 1 questionnaire includes behaviours measures for tobacco use, alcohol consumption, diet, physical activity, history of high blood pressure, history of diabetes and general well being.

    In addition to a Step 1 questionnaire, questionnaires were administered in each selected household for peoples age 15-64.

    The Step 2 questionnaire is mainly for Physical measurements and it includes measurements of heights and weights, blood pressure and heart rate.

    The Step 3 questionnaire is for women respondents for Biochemical measurements and it includes blood glucose, blood lipids and albuminuria.

    The questionnaires were developed in English from the Steps 1-3 instruments model Questionnaires. After an initial review the questionnaires were translated back into English by an independent translator with no prior knowledge of the survey.

    The survey team agreed for additional social and or environmental items relating to NCD control and prevention to be included in the STEPS 1 questionnaire. Examples of some optional items include self-reported health status, perceived susceptability to diabetes, perceived barriers or factors that would enhance adoption of a healthy lifestyle.

    To investigate the prevalence of kidney disease in Nauru, items measuring the albuminuria level were added to STEP 3 measures, but the results for this are not presented in the report. Survey participants were requested to bring their urine sample in a collection jar provided by the staff when they presented for STEP 3. For those who forgot to bring in their sample, their urine was collected on the day of the visit.

    All questionnaires and modules are provided as external resources.

    Cleaning operations

    Two staff manually double-entered all survey data into EpiInfo 6.04d database. The double data entry process was preceded by a series of data cleaning activities by STEP 1 staff. These activities included identifying and investigating various issues related to ineligible handwriting, duplicate records, data values outside of preset ranges, and inconsistencies between answers to different but related questions. Any inconsistencies noted by the data entry staff were resolved with the STEPS personnel or Team Supervisors before data entry was completed. Data entry was conducted concurrently with data collection.

    Response rate

    Usable data for STEPS 1-3 were obtained from 2,272 participants, with a total response rate of 89.7%. Of the 2,272 respondents, 1086 were men and 1186 were women.

  11. r

    Data from: Accounting for the Diversity of Women’s Experiences in Surveys

    • researchdata.edu.au
    Updated Sep 6, 2023
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    Shih Joo; Emily Dang; Chloe Keel (2023). Accounting for the Diversity of Women’s Experiences in Surveys [Dataset]. http://doi.org/10.26180/24021552.V1
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    Dataset updated
    Sep 6, 2023
    Dataset provided by
    Monash University
    Authors
    Shih Joo; Emily Dang; Chloe Keel
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Sexual harassment of women in the workplace has received growing attention in the past decade and is recognised as a substantial human rights and public health issue, with significant ramifications for workplaces and communities (Willness, Steel & Lee 2007). Nationally, this is reflected in recent legislative amendments:

    • In 2022, the Anti-Discrimination and Human Rights Legislation Amendment (Respect at Work) Act 2022 (Cth), introduced a positive duty on employers and persons conducting business or undertaking (PCBUs).
    • In 2023, the Fair Work Act was amended to prohibit sexual harassment in the workplace, and is now considered as a form of ‘serious misconduct’.

    These efforts reflect a commitment to eliminating gender-based violence and harassment, and ensuring safe working environments for women.

    Underpinning and driving these efforts for change is the growing body of research that have sought to bridge the significant gaps in current knowledge pertaining to sexual harassment in the workplace. This includes studies examining the impacts of workplace sexual harassment (Birinxhikai & Guggisberg 2017), its risk factors, preventative measures and responses (Champions of Change Coalition 2021, Healey 2018, Saunders & Easteal 2013, Wynen 2016), and issues around underreporting (MacDermott 2020, Charlesworth, McDonald & Cerise 2011).

    Since 2003, the Australian Human Rights Commission (AHRC) has also regularly conducted national surveys into workplace sexual harassment, with the fifth iteration released in 2022. The survey has offered important insights and data on the prevalence and nature of workplace sexual harassment in Australia. However, there remain significant gaps in accounting for the breadth of diversity and intersectionality of women’s experiences of violence and harassment. Specifically, migrant and refugee women were captured only through a single variable of ‘language spoken at home.’

    This gap has prompted the development of an ANROWS-funded study (ANROWS 2022) focusing on migrant and refugee women’s experiences of sexual harassment in the workplace. Utilising a mixed-methods approach of large-scale surveys, focus groups and interviews, the study builds on existing knowledge of workplace sexual harassment to further contribute to the national picture of the diverse experiences of migrant and refugee women.

    This research brief maps out the role, contribution and limitations of utilising large-scale surveys in gender-based violence research in Australia, specifically in relation to workplace sexual harassment.

  12. Nauru STEPS 2004, Non Communicable Disease Risk Factor

    • pacificdata.org
    pdf
    Updated May 27, 2019
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    ['Centre for Physical Activity and Health at the Universities of New South Wales and Sydney in Australia', 'Nauru Ministry of Health', 'World Health Organisation'] (2019). Nauru STEPS 2004, Non Communicable Disease Risk Factor [Dataset]. https://pacificdata.org/data/dataset/groups/spc_nru_2004_steps_v01_m
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    pdfAvailable download formats
    Dataset updated
    May 27, 2019
    Dataset provided by
    World Health Organizationhttps://who.int/
    Time period covered
    Jan 1, 2004 - Dec 31, 2004
    Area covered
    Nauru
    Description

    The Nauru-STEPS was a nation-wide representative survey of 15 to 64 year olds with the following objectives: 1. To document the national prevalence and patterns of tobacco use, alcohol consumption, dietary behaviours, physical activity, body mass index, elevated blood pressure, and biochemical markers such as blood glucose and blood lipids in Nauru. 2. To provide reliable and up-to-date information on NCD risk factors for planning and evaluating public health initiatives, and for identifying future demands for health services in managing and treating NCDs.

    The planning and implementation of the survey was a collaborative initiative between the Nauru Ministry of Health (MOH), the World Health Organization (WHO) and the Centre for Physical Activity and Health at the Universities of New South Wales and Sydney in Australia. The study was supported by the Australian Agency for International Development (AusAID).

    • v0.1: Basic raw data, obtained from data entry (before editing).

    The Nauru-STEPS survey was a representative, population-wide cross-sectional survey and involved collectingdata on levels of NCD risk factors among 15-64 year olds. Data collection moved along a sequential three-step process as follows:

    STEP 1: Interview-based questionnaire on selected major health risk behaviours including smoking, alcohol consumption, fruit and vegetable consumption, and physical activity. Additional issues deemed to be of importance in Nauru included history of high blood pressure, diabetes, self-rated general well-being, perceived susceptibility to diabetes and psychosocial and environmental factors related to health behaviours.

    STEP 2: Physiological measures of health risks such as blood pressure, body mass and waist girth circumference.

    STEP 3: Biochemical measures of health risks including fasting blood glucose and blood lipids. Assessment of albuminuria level was also undertaken in Nauru.

    All aspects of the survey were managed by the Nauru MOH staff.

    • Collection start: 2004
    • Collection end: 2004
  13. r

    Data from: Contemporary epidemiology of rising atrial septal defect trends...

    • researchdata.edu.au
    • data.mendeley.com
    Updated Aug 12, 2021
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    Psychiatry; Albert Stuart Reece (2021). Contemporary epidemiology of rising atrial septal defect trends across USA 1991-2016: A combined ecological geotemporospatial and causal inferential study [Dataset] [Dataset]. http://doi.org/10.17632/VRNFBYTRRR.1
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    Dataset updated
    Aug 12, 2021
    Dataset provided by
    Edith Cowan University
    Authors
    Psychiatry; Albert Stuart Reece
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    Background: Cardiovascular anomalies are the largest group of congenital anomalies and the major cause of death in young children, with a range of data linking rising atrial septal defect incidence (ASDI) with prenatal cannabis exposure. Objectives / Hypotheses. Is cannabis associated with ASDI in USA? Is this relationship causal?

    Methods: Geospatiotemporal cohort study, 1991-2016. Census populations of adults, babies, congenital anomalies, income and ethnicity. Drug exposure data on cigarettes, alcohol abuse, past month cannabis use, analgesia abuse and cocaine taken from National Survey of Drug Use and Health (78.9% response rate). Cannabinoid concentrations from Drug Enforcement Agency. Inverse probability weighted (ipw) regressions. Analysis conducted in R.

    Results. ASDI rose nationally three-fold from 27.4 to 82.8 / 10,000 births 1991-2014 during a period when tobacco and alcohol abuse were falling but cannabis was rising. States including Nevada, Kentucky, Mississippi and Tennessee had steeply rising epidemics (Time: Status β-estimate=10.72 (95%C.I. 8.39-13.05), P1.5.

    Conclusions. ASDI is associated with cannabis use, frequency, intensity and legalization in a spatiotemporally significant manner, robust to socioeconomicodemographic adjustment and fulfilled causal criteria, consistent with multiple biological mechanisms and similar reports from Hawaii, Colorado, Canada and Australia. Not only are these results of concern in themselves, but they further imply that our list of the congenital teratology of cannabis is as yet incomplete, and highlight the particular cardiovascular toxicology of prenatal cannabinoid and drug exposure.

  14. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Evans, Ann; McEachern, Steven; Gray, Matthew; Zammit, Adam; Li, Lulu; National Survey Research Center at Renmin University of China, Beijing; Marinović Jerolimov, Dinka; Ančić, Branko; Brajdić Vuković, Marija; Cik, Tomislav; Jaklin, Katarina; Hamplová, Dana; Klusáček, Jan; Clement, Sanne L.; Andersen, Johannes; Møberg, Rasmus; Lolle, Henrik; Shamshiri-Petersen, Ditte; Andersen, Jørgen G.; Larsen, Christian A.; Sønderskov, Kim M.; Sommer Harrits, Gitte; Jæger, Mads; Gundelach, Peter; Levinsen, Klaus; Fridberg, Torben; Blom, Raimo; Melin, Harri; Borg, Sami; Laaksonen, Helena; Hakkola, Emilia; Jääskeläinen, Taina; Forsé, Michel; Bréchon Pierre; Gonthier, Frédéric; Astor, Sandrine; Zolotoukhine, Erik; Wolf, Christof; Naber, Dörte; Scholz, Evi; Lewin-Epstein, Noah; Meraviglia, Cinzia; Pedrazzani, Andrea; Guglielmi, Simona; Murata, Hiroko; Masaki, Miki; Aramaki, Hiroshi; Ganzeboom, Harry; Nagel, Ineke; Kolsrud, Kirstine; Skjåk, Knut K.; Agasøster, Bodil; Karlsen, Gry; Nikolaisen, Kristina; Guerrero, Linda Luz; Sandoval, Gerardo; Labucay, Iremae; Zieliński, Marcin W.; Jerzyński, Tomasz; Khakhulina, Ludmilla; Agapeeva, Ksenia; Bahna, Miloslav; DžambazoviĊ, Roman; Hafner-Fink, Mitja; Malnar, Brina; Struwig, Jare; Roberts, Benjamin; Sapin, Marlène; Joye, Dominique; Steinmetz, Stephanie; Chang, Ying-hwa; Wu, Chyi-In; mith, Tom W.; Marsden, Peter V.; Hout, Michael; Davern, Michael; Bautista, Rene; Freese, Jeremy; Morgan, Stephen L.; Herd, Pamela (2024). International Social Survey Programme: Health and Health Care I-II Cumulation [Dataset]. http://doi.org/10.4232/1.14438
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International Social Survey Programme: Health and Health Care I-II Cumulation

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8 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Dec 17, 2024
Dataset provided by
NORC at the University of Chicago
Human Sciences Research Councilhttps://hsrc.ac.za/
University of California, Berkeley, USA
Norwegian Social Science Data Services, Bergen, Norway
University of Tampere, Finland
Finnish Social Science Data Archive, University of Tampere, Finland
Institute for Social Research, Zagreb, Croatia
Levada-Center, Moscow, Russia
China
University of Milan, Dept. Social and Political Science, Milan, Italy
Social Weather Stations, Quezon City, Philippines
Department of Political Science, University of Southern Denmark, Odense, Denmark
Sciences Po Grenoble - Université Grenoble Alpes - Pacte - CNRS, France
NHK Broadcasting Culture Research Institute, Tokyo, Japan
The Danish National Institute of Social Research, Copenhagen, Denmark
VU University Amsterdam, Netherlands
Institute of Sociology, Academia Sinica, Taipei City, Taiwan
Institute for Sociology of Slovak Academy of Sciences, Bratislava, Slovakia
GESIS Leibniz Institute for the Social Sciences, Mannheim, Germany
Department of Sociology, University of Copenhagen, Denmark
The Australian National University, Canberra, Australia
Public Opinion and Mass Communication Research Centre (CJMMK), University of Ljubljana, Slovenia/ Faculty of Social Science, University of Ljubljana, Slovenia
FRANCE-ISSP (Centre de Recherche en Economie et Statistique, Laboratoire de Sociologie Quantitative), Malakoff, France
The National Survey Research Center, Renmin University of China, Beijing, China
Institute of Social Research, University of Eastern Piedmont, Italy
FORS, c/o University of Lausanne, Switzerland
Department of Education, University of Aarhus, Aahrhus, Denmark
Department of Political Science, University of Aarhus, Aarhus, Denmark
Harvard University, Cambridge, Massachusetts, USA
ANU Centre for Social Research and Methods, Australian National University, Canberra, Australia
B.I. and Lucille Cohen Institute for public opinion, Tel-Aviv University, Israel
Institute for Sociology of the Slovak Academy of Sciences, Comenius University, Bratislava, Slovakian Republic
FORS swiss foundation for research in soical sciences, c/o University of Lausanne, Switzerland
Robert B. Zajonc Institute for Social Studies, University of Warsaw, Poland
Department of Economics, Politics and Public Administration, Aalborg University, Denmark
Australian Consortium for Social and Political Research Inc., Black Rock, Victoria, Australia
Institute of Sociology, Czech Academy of Sciences, Prague, Czech Republic
Authors
Evans, Ann; McEachern, Steven; Gray, Matthew; Zammit, Adam; Li, Lulu; National Survey Research Center at Renmin University of China, Beijing; Marinović Jerolimov, Dinka; Ančić, Branko; Brajdić Vuković, Marija; Cik, Tomislav; Jaklin, Katarina; Hamplová, Dana; Klusáček, Jan; Clement, Sanne L.; Andersen, Johannes; Møberg, Rasmus; Lolle, Henrik; Shamshiri-Petersen, Ditte; Andersen, Jørgen G.; Larsen, Christian A.; Sønderskov, Kim M.; Sommer Harrits, Gitte; Jæger, Mads; Gundelach, Peter; Levinsen, Klaus; Fridberg, Torben; Blom, Raimo; Melin, Harri; Borg, Sami; Laaksonen, Helena; Hakkola, Emilia; Jääskeläinen, Taina; Forsé, Michel; Bréchon Pierre; Gonthier, Frédéric; Astor, Sandrine; Zolotoukhine, Erik; Wolf, Christof; Naber, Dörte; Scholz, Evi; Lewin-Epstein, Noah; Meraviglia, Cinzia; Pedrazzani, Andrea; Guglielmi, Simona; Murata, Hiroko; Masaki, Miki; Aramaki, Hiroshi; Ganzeboom, Harry; Nagel, Ineke; Kolsrud, Kirstine; Skjåk, Knut K.; Agasøster, Bodil; Karlsen, Gry; Nikolaisen, Kristina; Guerrero, Linda Luz; Sandoval, Gerardo; Labucay, Iremae; Zieliński, Marcin W.; Jerzyński, Tomasz; Khakhulina, Ludmilla; Agapeeva, Ksenia; Bahna, Miloslav; DžambazoviĊ, Roman; Hafner-Fink, Mitja; Malnar, Brina; Struwig, Jare; Roberts, Benjamin; Sapin, Marlène; Joye, Dominique; Steinmetz, Stephanie; Chang, Ying-hwa; Wu, Chyi-In; mith, Tom W.; Marsden, Peter V.; Hout, Michael; Davern, Michael; Bautista, Rene; Freese, Jeremy; Morgan, Stephen L.; Herd, Pamela
Time period covered
Mar 2011 - Jul 17, 2023
Area covered
Denmark
Measurement technique
Face-to-face interview: Paper-and-pencil (PAPI), Face-to-face interview: Computer-assisted (CAPI/CAMI), Self-administered questionnaire: Paper, Self-administered questionnaire: Web-based (CAWI), Telephone interview: Computer-assisted (CATI)
Description

The International Social Survey Programme (ISSP) is a continuous programme of cross-national collaboration running annual surveys on topics important for the social sciences. The programme started in 1984 with four founding members - Australia, Germany, Great Britain, and the United States – and has now grown to almost 50 member countries from all over the world. As the surveys are designed for replication, they can be used for both, cross-national and cross-time comparisons. Each ISSP module focuses on a specific topic, which is repeated in regular time intervals. Please, consult the documentation for details on how the national ISSP surveys are fielded. The present study focuses on questions about individual health and the health care system.

ISSP Health and Health Care I-II cumulates the data of the integrated data files of • ISSP 2011 (ZA5800 Data file Version 3.0.0, https://doi.org/10.4232/1.12252) and • ISSP 2021 (ZA8000 Data file Version 2.0.0, https://doi.org/10.4232/5.ZA8000.2.0.0). It comprises data from all ISSP member countries participating in at least two Health and Health Care modules. The data set contains: • Cumulated topic-related (substantial) variables, which appear in at least two Health and Health Care and • background variables, mostly covering demographics, which appear in at least two Health and Health Care modules.
Satisfaction with life (happiness); confidence in the national health care system; justification for better healthcare for people with higher incomes; agreement with various statements on the healthcare system (People use health care services more than necessary, the government should provide only limited health care services, in general, the health care system in the country is inefficient); willingness to pay higher taxes to improve the level of health care for all people in the country; attitude towards the access to publicly funded health care for people without citizenship of the country and even if they behave in ways that damage their health; opinion on causes why people suffer from severe health problems (because they behaved in ways that damaged their health, because of the environment they are exposed to at work or where they live, because of their genes, because they are poor); alternative/ traditional or folk medicine provides better solutions for health problems than mainstream/ Western traditional medicine; assessment of doctors in general in the country (doctors can be trusted, the medical skills of doctors are not as good as they should be, doctors care more about their earnings than about their patients); frequency of difficulties with work or household activities because of health problems, bodily aches or pains, unhappiness and depression, loss of self-confidence and insuperable problems in the past four weeks; frequency of visits to/ by a doctor and an alternative/ traditional/ folk health care practitioner during the past 12 months; reasons why the respondent did not receive needed medical treatment (could not pay for it, could not take the time off work or because of other commitments, the waiting list was too long); likelihood of getting the best treatment available in the country in the case of seriously illness; satisfaction with the health care system in the country; satisfaction with treatment at the last visit to a doctor and to an alternative health care practitioner; smoker status and number of smoked cigarettes per day; frequency of drinking four or more alcoholic drinks on the same day, of strenuous physical activity for at least 20 minutes, and of eating fresh fruit or vegetables; assessment of personal health status; respondent has a long-standing illness, a chronic condition, or a disability; respondent’s height (in cm) and weight (in kg); kind of personal health insurance.

Demography: sex; age; years of birth; legal partnership status; steady life partner; education: years of schooling; highest education level; currently, formerly, or never in paid work (respondent and partner); employment relationship (respondent and partner); current employment status (respondent and partner); hours worked weekly (respondent and partner); occupation (ISCO 2008) (respondent and partner); supervising function at work (respondent and partner); number of other employees supervised; type of organization: for-profit vs. non-profit and public vs. private; trade union membership; household size; number of children above school entry age in household; number of children below school age in household; party affiliation (left-right); participation in last election; attendance of religious services; religious main groups (derived); Top Bottom self-placement; subjective social class; place of living urban – rural; household income groups (derived); country specific region.

Additionally coded: ID number of respondent; unique cumulation respondent ID number; Case substitution flag; date of interview (year, month, day); ISSP Module year; country; country...

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