7 datasets found
  1. e

    Disabled People and Leisure, 1979 - Dataset - B2FIND

    • b2find.eudat.eu
    Updated Apr 26, 2023
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    (2023). Disabled People and Leisure, 1979 - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/88086592-1e06-50a1-9129-1194e4674346
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    Dataset updated
    Apr 26, 2023
    Description

    Abstract copyright UK Data Service and data collection copyright owner. The object of this study was to gain more knowledge about the role of PHAB (Physically Handicapped and Able-Bodied clubs) in the lives of the people involved, and to provide a basis for decisions about the best use of resources. Separate samples of physically-handicapped and able-bodied respondents allow comparisons between the two groups. Main Topics: Variables (1) Members of PHAB clubs: Length of membership, attendance, reasons for joining, attitudes towards club, activities with club, social networks, other memberships, frequency of outings, household composition, educational background, employment, travel. Physically handicapped members: disability, attitude to help, attitude to able-bodied members, use of wheelchair or walking aids, mobility allowance. Able-bodied members: attitude to physically handicapped people outside club, voluntary work. (2) Leaders' questionnaire When club started, committee membership, frequency of meetings, transport problems, leaders' attitude to mentally handicapped memers, current number of mentally handicapped members, activities at last four meetings, average attendance, leaders' sex and age, whether physically handicapped, proportion of members needing wheelchair. (3) Disabled People Main interests and ability to pursue them, holiday away from home in last four weeks, leisure time activities, membership of clubs, transport, whether heard of PHAB clubs, participation in courses away from home in last five years, holidays in last five years, participation in holidays arranged by Croydon Social Services Department, perception of leisure facilities in Croydon, nature of disability, use of wheelchair or walking aids, ability to get out alone, receipt of mobility allowance, attitude to help, details of spare time activities in last week, regular visitors during normal week, visitors in last week, social networks, marital status, sex, age, educational background, employment. Leaders of 50 clubs randomly selected were interviewed and provided separate lists of their physically-handicapped and able-bodied members ages over 15. Ten names were selected from each club. Names of recently `lapsed' able-bodied and physically-handicapped members were also provided by club leaders Face-to-face interview

  2. d

    Disability Employment Services Outcome Rates by Disability Type

    • data.gov.au
    .pdf, excel (.xlsx) +1
    Updated Mar 28, 2025
    + more versions
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    Department of Social Services (2025). Disability Employment Services Outcome Rates by Disability Type [Dataset]. https://www.data.gov.au/data/dataset/disability-employment-services-outcome-rates-by-disability-type
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    xlsx, xlsx(3909968), excel (.xlsx)(3605550), excel (.xlsx)(9613499), excel (.xlsx)(3918487), excel (.xlsx), excel (.xlsx)(3707789), .pdf, excel (.xlsx)(9691513)Available download formats
    Dataset updated
    Mar 28, 2025
    Dataset authored and provided by
    Department of Social Services
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    This report of DES Outcome Rates by Disability Type provides information about the performance of DES providers in each Employment Services Area by primary disability groupings. The report aims to help people with disability, family, carers or others choose a DES provider.

    There are a number of factors that should be taken into account when choosing a DES Provider, such as the location of their office in relation to public transport and your home or other available information. This Outcome Rates by Disability Type report is just one piece of information to help you decide which provider might be best for you. You can find out more about your local DES providers on the Job Access or Workforce Australia websites.

    Find a Service Provider | Job Access - https://www.jobaccess.gov.au/find-a-provider

    Find Your Employment Services Provider - Workforce Australia - https://www.workforceaustralia.gov.au/individuals/coaching/providers/

    To access the report you will require Excel 2010 or a more recent version. If you have Excel 2007 or earlier, no access to Excel or have a Macintosh/Apple computer, then you will need to access the report from other available spreadsheet software. Some examples of alternative and free spreadsheet software (not a complete list) are; Google Sheets, Zoho Sheet or Microsoft Office Excel Online.

  3. e

    Health Survey for England, 2000-2001: Small Area Estimation Teaching Dataset...

    • b2find.eudat.eu
    Updated Oct 4, 2023
    + more versions
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    (2023). Health Survey for England, 2000-2001: Small Area Estimation Teaching Dataset - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/500ca1f6-b649-5324-aab9-2d28dd4dc308
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    Dataset updated
    Oct 4, 2023
    Description

    Abstract copyright UK Data Service and data collection copyright owner. The Health Survey for England, 2000-2001: Small Area Estimation Teaching Dataset was prepared as a resource for those interested in learning introductory small area estimation techniques. It was first presented as part of a workshop entitled 'Introducing small area estimation techniques and applying them to the Health Survey for England using Stata'. The data are accompanied by a guide that includes a practical case study enabling users to derive estimates of disability for districts in the absence of survey estimates. This is achieved using various models that combine information from ESDS government surveys with other aggregate data that are reliably available for sub-national areas. Analysis is undertaken using Stata statistical software; all relevant syntax is provided in the accompanying '.do' files. The data files included in this teaching resource contain HSE variables and data from the Census and Mid-year population estimates and projections that were developed originally by the National Statistical agencies, as follows:The main data file, 'hse_data.dta', is a reduced version of the HSE for 2000 and 2001. In order to combine data from two years of the HSE in a consistent way some changes have been made to the weights in each year. Additionally, some recoding of the limiting long term illness (LLTI), disability and the age variable has also been undertaken.File 'practical_1_task_5_data.dta' contains population counts and model mobility disability rates (estimated during practical 1) distinguishing single year of age and sex for the six case study districts.File 'practical_2_data.dta' contains the aggregate data required for Practical 2, including age- and sex-specific rates of LLTI (Census) for six UK case study districts, age- and sex-specific rates of mobility disability for England (HSE), and population counts for the six districts.File 'pop_data_practical_3.dta' contains population counts for the six districts (by age, sex and LLTI status) required for practical 3The original HSEs for 2000 and 2001 are held at the UK Data Archive under SNs 4628 and 4912 respectively. Full details of the recoding of HSE variables and how the aggregate data was produced can be found in the data documentation. This unrestricted access data collection is freely available to download under an Open Government Licence from the UK Data Service. Note that the files should be unzipped/saved to the C: drive of the computer to be used; all syntax assumes files are saved at this location. Main Topics: The main HSE file, 'hse_data.dta', contains 12 variables and 28,451 cases. The file includes the boosted sample of older people in care/residential homes from the HSE 2000. All the variables in the file are at individual level and are almost all are categorical, often indicating whether or not a respondent has a limiting illness or a particular type of disability. The disability types covered include mobility, personal care, sight and hearing disability as well as a measure of overall disability. See documentation for details. Compilation or synthesis of existing material The original HSE was conducted using Face-to-face interview; Self-completion; Clinical measurements and Physical measurements.

  4. A

    Climate Ready Boston Social Vulnerability

    • data.boston.gov
    • cloudcity.ogopendata.com
    • +2more
    Updated Sep 21, 2017
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    Boston Maps (2017). Climate Ready Boston Social Vulnerability [Dataset]. https://data.boston.gov/dataset/climate-ready-boston-social-vulnerability
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    arcgis geoservices rest api, html, csv, kml, geojson, zipAvailable download formats
    Dataset updated
    Sep 21, 2017
    Dataset provided by
    BostonMaps
    Authors
    Boston Maps
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Area covered
    Boston
    Description
    Social vulnerability is defined as the disproportionate susceptibility of some social groups to the impacts of hazards, including death, injury, loss, or disruption of livelihood. In this dataset from Climate Ready Boston, groups identified as being more vulnerable are older adults, children, people of color, people with limited English proficiency, people with low or no incomes, people with disabilities, and people with medical illnesses.

    Source:

    The analysis and definitions used in Climate Ready Boston (2016) are based on "A framework to understand the relationship between social factors that reduce resilience in cities: Application to the City of Boston." Published 2015 in the International Journal of Disaster Risk Reduction by Atyia Martin, Northeastern University.

    Population Definitions:

    Older Adults:
    Older adults (those over age 65) have physical vulnerabilities in a climate event; they suffer from higher rates of medical illness than the rest of the population and can have some functional limitations in an evacuation scenario, as well as when preparing for and recovering from a disaster. Furthermore, older adults are physically more vulnerable to the impacts of extreme heat. Beyond the physical risk, older adults are more likely to be socially isolated. Without an appropriate support network, an initially small risk could be exacerbated if an older adult is not able to get help.
    Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for population over 65 years of age.
    Attribute label: OlderAdult

    Children:
    Families with children require additional resources in a climate event. When school is cancelled, parents need alternative childcare options, which can mean missing work. Children are especially vulnerable to extreme heat and stress following a natural disaster.
    Data source: 2010 American Community Survey 5-year Estimates (ACS) data by census tract for population under 5 years of age.
    Attribute label: TotChild

    People of Color:
    People of color make up a majority (53 percent) of Boston’s population. People of color are more likely to fall into multiple vulnerable groups as
    well. People of color statistically have lower levels of income and higher levels of poverty than the population at large. People of color, many of whom also have limited English proficiency, may not have ready access in their primary language to information about the dangers of extreme heat or about cooling center resources. This risk to extreme heat can be compounded by the fact that people of color often live in more densely populated urban areas that are at higher risk for heat exposure due to the urban heat island effect.
    Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract: Black, Native American, Asian, Island, Other, Multi, Non-white Hispanics.
    Attribute label: POC2

    Limited English Proficiency:
    Without adequate English skills, residents can miss crucial information on how to prepare
    for hazards. Cultural practices for information sharing, for example, may focus on word-of-mouth communication. In a flood event, residents can also face challenges communicating with emergency response personnel. If residents are more socially
    isolated, they may be less likely to hear about upcoming events. Finally, immigrants, especially ones who are undocumented, may be reluctant to use government services out of fear of deportation or general distrust of the government or emergency personnel.
    Data Source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract, defined as speaks English only or speaks English “very well”.
    Attribute label: LEP

    Low to no Income:
    A lack of financial resources impacts a household’s ability to prepare for a disaster event and to support friends and neighborhoods. For example, residents without televisions, computers, or data-driven mobile phones may face challenges getting news about hazards or recovery resources. Renters may have trouble finding and paying deposits for replacement housing if their residence is impacted by flooding. Homeowners may be less able to afford insurance that will cover flood damage. Having low or no income can create difficulty evacuating in a disaster event because of a higher reliance on public transportation. If unable to evacuate, residents may be more at risk without supplies to stay in their homes for an extended period of time. Low- and no-income residents can also be more vulnerable to hot weather if running air conditioning or fans puts utility costs out of reach.
    Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for low-to- no income populations. The data represents a calculated field that combines people who were 100% below the poverty level and those who were 100–149% of the poverty level.
    Attribute label: Low_to_No

    People with Disabilities:
    People with disabilities are among the most vulnerable in an emergency; they sustain disproportionate rates of illness, injury, and death in disaster events.46 People with disabilities can find it difficult to adequately prepare for a disaster event, including moving to a safer place. They are more likely to be left behind or abandoned during evacuations. Rescue and relief resources—like emergency transportation or shelters, for example— may not be universally accessible. Research has revealed a historic pattern of discrimination against people with disabilities in times of resource scarcity, like after a major storm and flood.
    Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for total civilian non-institutionalized population, including: hearing difficulty, vision difficulty, cognitive difficulty, ambulatory difficulty, self-care difficulty, and independent living difficulty.
    Attribute label: TotDis

    Medical Illness:
    Symptoms of existing medical illnesses are often exacerbated by hot temperatures. For example, heat can trigger asthma attacks or increase already high blood pressure due to the stress of high temperatures put on the body. Climate events can interrupt access to normal sources of healthcare and even life-sustaining medication. Special planning is required for people experiencing medical illness. For example, people dependent on dialysis will have different evacuation and care needs than other Boston residents in a climate event.
    Data source: Medical illness is a proxy measure which is based on EASI data accessed through Simply Map. Health data at the local level in Massachusetts is not available beyond zip codes. EASI modeled the health statistics for the U.S. population based upon age, sex, and race probabilities using U.S. Census Bureau data. The probabilities are modeled against the census and current year and five year forecasts. Medical illness is the sum of asthma in children, asthma in adults, heart disease, emphysema, bronchitis, cancer, diabetes, kidney disease, and liver disease. A limitation is that these numbers may be over-counted as the result of people potentially having more than one medical illness. Therefore, the analysis may have greater numbers of people with medical illness within census tracts than actually present. Overall, the analysis was based on the relationship between social factors.
    Attribute label: MedIllnes

    Other attribute definitions:
    GEOID10: Geographic identifier: State Code (25), Country Code (025), 2010 Census Tract
    AREA_SQFT: Tract area (in square feet)
    AREA_ACRES: Tract area (in acres)
    POP100_RE: Tract population count
    HU100_RE: Tract housing unit count
    Name: Boston Neighborhood
  5. f

    Rates per 100,000 inhabitants and relative change of years lived with...

    • plos.figshare.com
    xls
    Updated Nov 20, 2024
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    Erica Santos dos Reis; Wandklebson Silva Paz; Rosália Elen Santos Ramos; Caíque Jordan Nunes Ribeiro; Laiza Santos Biano; Márcio Bezerra-Santos; Camila Indiani de Oliveira; Michael Wheeler Lipscomb; Tatiana Rodrigues de Moura (2024). Rates per 100,000 inhabitants and relative change of years lived with disability (YLD), in years of life lost (YLL) and disability-adjusted life years (DALY) by sex and regions of Brazil in the periods 2001–2007 (P1), 2008–2014 (P2), 2015–2021 (P3). [Dataset]. http://doi.org/10.1371/journal.pntd.0012668.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Nov 20, 2024
    Dataset provided by
    PLOS Neglected Tropical Diseases
    Authors
    Erica Santos dos Reis; Wandklebson Silva Paz; Rosália Elen Santos Ramos; Caíque Jordan Nunes Ribeiro; Laiza Santos Biano; Márcio Bezerra-Santos; Camila Indiani de Oliveira; Michael Wheeler Lipscomb; Tatiana Rodrigues de Moura
    License

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

    Area covered
    Brazil
    Description

    Rates per 100,000 inhabitants and relative change of years lived with disability (YLD), in years of life lost (YLL) and disability-adjusted life years (DALY) by sex and regions of Brazil in the periods 2001–2007 (P1), 2008–2014 (P2), 2015–2021 (P3).

  6. a

    Quality Education

    • senegal2-sdg.hub.arcgis.com
    • eswatini-1-sdg.hub.arcgis.com
    • +12more
    Updated Jul 1, 2022
    + more versions
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    arobby1971 (2022). Quality Education [Dataset]. https://senegal2-sdg.hub.arcgis.com/items/f7ac9c7f496b4995a79ed539bf3223d6
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    Dataset updated
    Jul 1, 2022
    Dataset authored and provided by
    arobby1971
    Area covered
    Description

    Goal 4Ensure inclusive and equitable quality education and promote lifelong learning opportunities for allTarget 4.1: By 2030, ensure that all girls and boys complete free, equitable and quality primary and secondary education leading to relevant and effective learning outcomesIndicator 4.1.1: Proportion of children and young people (a) in grades 2/3; (b) at the end of primary; and (c) at the end of lower secondary achieving at least a minimum proficiency level in (i) reading and (ii) mathematics, by sexSE_TOT_PRFL: Proportion of children and young people achieving a minimum proficiency level in reading and mathematics (%)Indicator 4.1.2: Completion rate (primary education, lower secondary education, upper secondary education)SE_TOT_CPLR: Completion rate, by sex, location, wealth quintile and education level (%)Target 4.2: By 2030, ensure that all girls and boys have access to quality early childhood development, care and pre-primary education so that they are ready for primary educationIndicator 4.2.1: Proportion of children aged 24-59 months who are developmentally on track in health, learning and psychosocial well-being, by sexiSE_DEV_ONTRK: Proportion of children aged 36−59 months who are developmentally on track in at least three of the following domains: literacy-numeracy, physical development, social-emotional development, and learning (% of children aged 36-59 months)Indicator 4.2.2: Participation rate in organized learning (one year before the official primary entry age), by sexSE_PRE_PARTN: Participation rate in organized learning (one year before the official primary entry age), by sex (%)Target 4.3: By 2030, ensure equal access for all women and men to affordable and quality technical, vocational and tertiary education, including universityIndicator 4.3.1: Participation rate of youth and adults in formal and non-formal education and training in the previous 12 months, by sexSE_ADT_EDUCTRN: Participation rate in formal and non-formal education and training, by sex (%)Target 4.4: By 2030, substantially increase the number of youth and adults who have relevant skills, including technical and vocational skills, for employment, decent jobs and entrepreneurshipIndicator 4.4.1: Proportion of youth and adults with information and communications technology (ICT) skills, by type of skillSE_ADT_ACTS: Proportion of youth and adults with information and communications technology (ICT) skills, by sex and type of skill (%)Target 4.5: By 2030, eliminate gender disparities in education and ensure equal access to all levels of education and vocational training for the vulnerable, including persons with disabilities, indigenous peoples and children in vulnerable situationsIndicator 4.5.1: Parity indices (female/male, rural/urban, bottom/top wealth quintile and others such as disability status, indigenous peoples and conflict-affected, as data become available) for all education indicators on this list that can be disaggregatedSE_GPI_PTNPRE: Gender parity index for participation rate in organized learning (one year before the official primary entry age), (ratio)SE_GPI_TCAQ: Gender parity index of trained teachers, by education level (ratio)SE_GPI_PART: Gender parity index for participation rate in formal and non-formal education and training (ratio)SE_GPI_ICTS: Gender parity index for youth/adults with information and communications technology (ICT) skills, by type of skill (ratio)SE_IMP_FPOF: Immigration status parity index for achieving at least a fixed level of proficiency in functional skills, by numeracy/literacy skills (ratio)SE_NAP_ACHI: Native parity index for achievement (ratio)SE_LGP_ACHI: Language test parity index for achievement (ratio)SE_TOT_GPI: Gender parity index for achievement (ratio)SE_TOT_SESPI: Low to high socio-economic parity status index for achievement (ratio)SE_TOT_RUPI: Rural to urban parity index for achievement (ratio)SE_ALP_CPLR: Adjusted location parity index for completion rate, by sex, location, wealth quintile and education levelSE_AWP_CPRA: Adjusted wealth parity index for completion rate, by sex, location, wealth quintile and education levelSE_AGP_CPRA: Adjusted gender parity index for completion rate, by sex, location, wealth quintile and education levelTarget 4.6: By 2030, ensure that all youth and a substantial proportion of adults, both men and women, achieve literacy and numeracyIndicator 4.6.1: Proportion of population in a given age group achieving at least a fixed level of proficiency in functional (a) literacy and (b) numeracy skills, by sexSE_ADT_FUNS: Proportion of population achieving at least a fixed level of proficiency in functional skills, by sex, age and type of skill (%)Target 4.7: By 2030, ensure that all learners acquire the knowledge and skills needed to promote sustainable development, including, among others, through education for sustainable development and sustainable lifestyles, human rights, gender equality, promotion of a culture of peace and non-violence, global citizenship and appreciation of cultural diversity and of culture’s contribution to sustainable developmentIndicator 4.7.1: Extent to which (i) global citizenship education and (ii) education for sustainable development are mainstreamed in (a) national education policies; (b) curricula; (c) teacher education; and (d) student assessmentTarget 4.a: Build and upgrade education facilities that are child, disability and gender sensitive and provide safe, non-violent, inclusive and effective learning environments for allIndicator 4.a.1: Proportion of schools offering basic services, by type of serviceSE_ACS_CMPTR: Schools with access to computers for pedagogical purposes, by education level (%)SE_ACS_H2O: Schools with access to basic drinking water, by education level (%)SE_ACS_ELECT: Schools with access to electricity, by education level (%)SE_ACC_HNDWSH: Schools with basic handwashing facilities, by education level (%)SE_ACS_INTNT: Schools with access to the internet for pedagogical purposes, by education level (%)SE_ACS_SANIT: Schools with access to access to single-sex basic sanitation, by education level (%)SE_INF_DSBL: Proportion of schools with access to adapted infrastructure and materials for students with disabilities, by education level (%)Target 4.b: By 2020, substantially expand globally the number of scholarships available to developing countries, in particular least developed countries, small island developing States and African countries, for enrolment in higher education, including vocational training and information and communications technology, technical, engineering and scientific programmes, in developed countries and other developing countriesIndicator 4.b.1: Volume of official development assistance flows for scholarships by sector and type of studyDC_TOF_SCHIPSL: Total official flows for scholarships, by recipient countries (millions of constant 2018 United States dollars)Target 4.c: By 2030, substantially increase the supply of qualified teachers, including through international cooperation for teacher training in developing countries, especially least developed countries and small island developing StatesIndicator 4.c.1: Proportion of teachers with the minimum required qualifications, by education leveliSE_TRA_GRDL: Proportion of teachers who have received at least the minimum organized teacher training (e.g. pedagogical training) pre-service or in-service required for teaching at the relevant level in a given country, by sex and education level (%)

  7. f

    Time trends of rates per 100,000 inhabitants of years of life lost (YLL),...

    • plos.figshare.com
    xls
    Updated Nov 20, 2024
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    Erica Santos dos Reis; Wandklebson Silva Paz; Rosália Elen Santos Ramos; Caíque Jordan Nunes Ribeiro; Laiza Santos Biano; Márcio Bezerra-Santos; Camila Indiani de Oliveira; Michael Wheeler Lipscomb; Tatiana Rodrigues de Moura (2024). Time trends of rates per 100,000 inhabitants of years of life lost (YLL), years lived with disability (YLD) and disability-adjusted life years (DALY) by sex and regions, Brazil, 2001–2021. [Dataset]. http://doi.org/10.1371/journal.pntd.0012668.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Nov 20, 2024
    Dataset provided by
    PLOS Neglected Tropical Diseases
    Authors
    Erica Santos dos Reis; Wandklebson Silva Paz; Rosália Elen Santos Ramos; Caíque Jordan Nunes Ribeiro; Laiza Santos Biano; Márcio Bezerra-Santos; Camila Indiani de Oliveira; Michael Wheeler Lipscomb; Tatiana Rodrigues de Moura
    License

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

    Area covered
    Brazil
    Description

    Time trends of rates per 100,000 inhabitants of years of life lost (YLL), years lived with disability (YLD) and disability-adjusted life years (DALY) by sex and regions, Brazil, 2001–2021.

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

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(2023). Disabled People and Leisure, 1979 - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/88086592-1e06-50a1-9129-1194e4674346

Disabled People and Leisure, 1979 - Dataset - B2FIND

Explore at:
Dataset updated
Apr 26, 2023
Description

Abstract copyright UK Data Service and data collection copyright owner. The object of this study was to gain more knowledge about the role of PHAB (Physically Handicapped and Able-Bodied clubs) in the lives of the people involved, and to provide a basis for decisions about the best use of resources. Separate samples of physically-handicapped and able-bodied respondents allow comparisons between the two groups. Main Topics: Variables (1) Members of PHAB clubs: Length of membership, attendance, reasons for joining, attitudes towards club, activities with club, social networks, other memberships, frequency of outings, household composition, educational background, employment, travel. Physically handicapped members: disability, attitude to help, attitude to able-bodied members, use of wheelchair or walking aids, mobility allowance. Able-bodied members: attitude to physically handicapped people outside club, voluntary work. (2) Leaders' questionnaire When club started, committee membership, frequency of meetings, transport problems, leaders' attitude to mentally handicapped memers, current number of mentally handicapped members, activities at last four meetings, average attendance, leaders' sex and age, whether physically handicapped, proportion of members needing wheelchair. (3) Disabled People Main interests and ability to pursue them, holiday away from home in last four weeks, leisure time activities, membership of clubs, transport, whether heard of PHAB clubs, participation in courses away from home in last five years, holidays in last five years, participation in holidays arranged by Croydon Social Services Department, perception of leisure facilities in Croydon, nature of disability, use of wheelchair or walking aids, ability to get out alone, receipt of mobility allowance, attitude to help, details of spare time activities in last week, regular visitors during normal week, visitors in last week, social networks, marital status, sex, age, educational background, employment. Leaders of 50 clubs randomly selected were interviewed and provided separate lists of their physically-handicapped and able-bodied members ages over 15. Ten names were selected from each club. Names of recently `lapsed' able-bodied and physically-handicapped members were also provided by club leaders Face-to-face interview

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