11 datasets found
  1. f

    S3 Text -

    • plos.figshare.com
    zip
    Updated Oct 9, 2023
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    Alinafe Chisalunda; Wingston Felix Ng’ambi; Nesto Salia Tarimo; Ndaziona Peter Kwanjo Banda; Adamson Sinjani Muula; Johnstone Kumwenda; Alinane Linda Nyondo-Mipando (2023). S3 Text - [Dataset]. http://doi.org/10.1371/journal.pgph.0002367.s003
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    zipAvailable download formats
    Dataset updated
    Oct 9, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Alinafe Chisalunda; Wingston Felix Ng’ambi; Nesto Salia Tarimo; Ndaziona Peter Kwanjo Banda; Adamson Sinjani Muula; Johnstone Kumwenda; Alinane Linda Nyondo-Mipando
    License

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

    Description

    A. In-depth interview guide for patients. B. Guardian in-depth interview guide for qualitative data. (ZIP)

  2. d

    Statistics Canada, 2024, \"HART - 2021 Census of Canada - Selected...

    • search.dataone.org
    • borealisdata.ca
    Updated Oct 30, 2024
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    Statistics Canada (2024). Statistics Canada, 2024, \"HART - 2021 Census of Canada - Selected Characteristics of Households led by Older Adults for Housing Need - Canada, all provinces and territories, at the Census Division (CD), and Census Metropolitan Area (CMA) level [custom tabulation] [Dataset]. http://doi.org/10.5683/SP3/CTSYFE
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    Dataset updated
    Oct 30, 2024
    Dataset provided by
    Borealis
    Authors
    Statistics Canada
    Area covered
    Canada
    Description

    Housing Assessment Resource Tools (HART) This dataset contains 2 tables and 5 files which draw upon data from the 2021 Census of Canada. The tables are a custom order and contain data pertaining to older adults and housing need. The 2 tables have 6 dimensions in common and 1 dimension that is unique to each table. Table 1's unique dimension is the "Ethnicity / Indigeneity status" dimension which contains data fields related to visible minority and Indigenous identity within the population in private households. Table 2's unique dimension is "Structural type of dwelling and Period of Construction" which contains data fields relating to the structural type and period of construction of the dwelling. Each of the two tables is then split into multiple files based on geography. Table 1 has two files: Table 1.1 includes Canada, Provinces and Territories (14 geographies), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); and Table 1.2 includes Canada and the CMAs of Canada (44). Table 2 has three files: Table 2.1 includes Canada, Provinces and Territories (14), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); Table 2.2 includes Canada and the CMAs of Canada excluding Ontario and Quebec (20 geographies); and Table 2.3 includes Canada and the CMAs of Canada that are in Ontario and Quebec (25 geographies). The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and data fields: Geography: - Country of Canada as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia) as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), as a whole as well as all census divisions (CDs) within the 3 territories - All 43 census metropolitan areas (CMAs) in Canada Data Quality and Suppression: - The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. - Area suppression is used to replace all income characteristic data with an 'x' for geographic areas with populations and/or number of households below a specific threshold. If a tabulation contains quantitative income data (e.g., total income, wages), qualitative data based on income concepts (e.g., low income before tax status) or derived data based on quantitative income variables (e.g., indexes) for individuals, families or households, then the following rule applies: income characteristic data are replaced with an 'x' for areas where the population is less than 250 or where the number of private households is less than 40. Source: Statistics Canada - When showing count data, Statistics Canada employs random rounding in order to reduce the possibility of identifying individuals within the tabulations. Random rounding transforms all raw counts to random rounded counts. Reducing the possibility of identifying individuals within the tabulations becomes pertinent for very small (sub)populations. All counts are rounded to a base of 5, meaning they will end in either 0 or 5. The random rounding algorithm controls the results and rounds the unit value of the count according to a predetermined frequency. Counts ending in 0 or 5 are not changed. Universe: Full Universe: Population aged 55 years and over in owner and tenant households with household total income greater than zero in non-reserve non-farm private dwellings. Definition of Households examined for Core Housing Need: Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances. Data Fields: Table 1: Age / Gender (12) 1. Total – Population 55 years and over 2. Men+ 3. Women+ 4. 55 to 64 years 5. Men+ 6. Women+ 7. 65+ years 8. Men+ 9. Women+ 10. 85+ 11. Men+ 12. Women+ Housing indicators (13) 1. Total – Private Households by core housing need status 2. Households below one standard only...

  3. f

    Quality of life varied by demographic and behavioral characteristics.

    • plos.figshare.com
    xls
    Updated Oct 9, 2023
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    Alinafe Chisalunda; Wingston Felix Ng’ambi; Nesto Salia Tarimo; Ndaziona Peter Kwanjo Banda; Adamson Sinjani Muula; Johnstone Kumwenda; Alinane Linda Nyondo-Mipando (2023). Quality of life varied by demographic and behavioral characteristics. [Dataset]. http://doi.org/10.1371/journal.pgph.0002367.t004
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    xlsAvailable download formats
    Dataset updated
    Oct 9, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Alinafe Chisalunda; Wingston Felix Ng’ambi; Nesto Salia Tarimo; Ndaziona Peter Kwanjo Banda; Adamson Sinjani Muula; Johnstone Kumwenda; Alinane Linda Nyondo-Mipando
    License

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

    Description

    Quality of life varied by demographic and behavioral characteristics.

  4. Comparison of mean scores by activity.

    • plos.figshare.com
    xls
    Updated Jan 9, 2025
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    Anubhuti Shukla; Sriha Yalamanchi; Guillermo Tamayo-Cabeza; Amanda Albright; Zachary A. Weber; April D. Newton (2025). Comparison of mean scores by activity. [Dataset]. http://doi.org/10.1371/journal.pone.0313492.t004
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    xlsAvailable download formats
    Dataset updated
    Jan 9, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Anubhuti Shukla; Sriha Yalamanchi; Guillermo Tamayo-Cabeza; Amanda Albright; Zachary A. Weber; April D. Newton
    License

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

    Description

    BackgroundDisproportionate access to healthcare services among the Lesbian, Gay, Bisexual, Transgender, Queer or Questioning and others (LGBTQ+) population can be partially attributed to the lack of cultural competence among healthcare providers. The aim of this study was to evaluate the impact of an interprofessional model in improving cultural competence and clinical preparedness among dental and pharmacy students for providing LGBTQ+ specific care.MethodologyThis study is a retrospective observational study which used a novel interprofessional model of three different LGBTQ+ focused educational interventions within a group of dental and pharmacy students. The study used pre- and post-surveys, Assessment of Interprofessional Team Collaboration Scale (AITCS-II) and the Team Observed Structured Clinical Encounter (TOSCE) evaluations to assess the effectiveness of the interventions. Descriptive statistics, Fisher’s exact test, Wilcoxon signed-rank test, Welch test, Kruskal-Wallis Test, and pairwise Wilcox Test were employed to analyze quantitative data while qualitative insights were gathered from evaluator comments and student feedback.ResultsThe study evaluated cultural competence among 154 dental and pharmacy students revealing improved cultural humility post-intervention, particularly for dental students although not statistically significant (p>0.05). Students participating in multiple interventions had higher mean scores, but the differences were not significant (p>0.05). Significant differences were found among interprofessional teams of students in the domains of roles and responsibilities (p = 0.039) and patient centered approach (p = 0.039). No significant differences were found in individual scores participation in the teams (p = 0.018). Students also provided positive feedback on the program’s impact on their understanding of LGBTQ+ health issues and inclusive care.ConclusionThis program was a novel intervention aimed at improving cultural competence for health professional students in an interprofessional environment Further research in the direction can be useful in creating replicable programs.

  5. f

    Assessment of quality of life among persons with type II diabetes mellitus.

    • plos.figshare.com
    xls
    Updated Oct 9, 2023
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    Alinafe Chisalunda; Wingston Felix Ng’ambi; Nesto Salia Tarimo; Ndaziona Peter Kwanjo Banda; Adamson Sinjani Muula; Johnstone Kumwenda; Alinane Linda Nyondo-Mipando (2023). Assessment of quality of life among persons with type II diabetes mellitus. [Dataset]. http://doi.org/10.1371/journal.pgph.0002367.t003
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    xlsAvailable download formats
    Dataset updated
    Oct 9, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Alinafe Chisalunda; Wingston Felix Ng’ambi; Nesto Salia Tarimo; Ndaziona Peter Kwanjo Banda; Adamson Sinjani Muula; Johnstone Kumwenda; Alinane Linda Nyondo-Mipando
    License

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

    Description

    Assessment of quality of life among persons with type II diabetes mellitus.

  6. f

    Assessment of quality of life based on comorbidities and complications.

    • plos.figshare.com
    xls
    Updated Oct 9, 2023
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    Alinafe Chisalunda; Wingston Felix Ng’ambi; Nesto Salia Tarimo; Ndaziona Peter Kwanjo Banda; Adamson Sinjani Muula; Johnstone Kumwenda; Alinane Linda Nyondo-Mipando (2023). Assessment of quality of life based on comorbidities and complications. [Dataset]. http://doi.org/10.1371/journal.pgph.0002367.t005
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    xlsAvailable download formats
    Dataset updated
    Oct 9, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Alinafe Chisalunda; Wingston Felix Ng’ambi; Nesto Salia Tarimo; Ndaziona Peter Kwanjo Banda; Adamson Sinjani Muula; Johnstone Kumwenda; Alinane Linda Nyondo-Mipando
    License

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

    Description

    Assessment of quality of life based on comorbidities and complications.

  7. f

    Response category and scores of MDQoL-17 questions [12].

    • figshare.com
    • plos.figshare.com
    xls
    Updated Oct 9, 2023
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    Alinafe Chisalunda; Wingston Felix Ng’ambi; Nesto Salia Tarimo; Ndaziona Peter Kwanjo Banda; Adamson Sinjani Muula; Johnstone Kumwenda; Alinane Linda Nyondo-Mipando (2023). Response category and scores of MDQoL-17 questions [12]. [Dataset]. http://doi.org/10.1371/journal.pgph.0002367.t001
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    xlsAvailable download formats
    Dataset updated
    Oct 9, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Alinafe Chisalunda; Wingston Felix Ng’ambi; Nesto Salia Tarimo; Ndaziona Peter Kwanjo Banda; Adamson Sinjani Muula; Johnstone Kumwenda; Alinane Linda Nyondo-Mipando
    License

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

    Description

    Response category and scores of MDQoL-17 questions [12].

  8. Main characteristics of participants.

    • plos.figshare.com
    xls
    Updated Jan 3, 2025
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    Florencia Saposnik; Dr. Mark Norman (2025). Main characteristics of participants. [Dataset]. http://doi.org/10.1371/journal.pmen.0000109.t001
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    xlsAvailable download formats
    Dataset updated
    Jan 3, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Florencia Saposnik; Dr. Mark Norman
    License

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

    Description

    This study examined the experiences of Canadian undergraduate students accessing mental healthcare between November 2022 to February 2023. We specifically assessed the impact of social determinants of health (i.e., gender, socioeconomic status, immigration status, English as a second language). Participants were recruited through social media platforms and by undergraduate program administrators at Canadian universities. Participants were asked to provide demographic information, answer questions about their experiences accessing mental healthcare, and to complete the mental health continuum short form (MHC-SF). Descriptive statistics and linear regression models were used to assess the association between MHC-SF and social determinants of health (e.g.: demographics, language, immigration status). Of 1098 students invited to participate, 365 participants completed the study (completion rate: 33.2%). Their mean age (SD) was 21.4 (4.6) years; 73.6% were female and 45.7% identified as non-White. Overall, the mean (SD) MHC-SF score of participants was 2.36 (0.99) out of 5. Students with low SES had lower MHC-SF scores (mean 2.08 vs 2.45; p = 0.003). The multivariable analysis showed that low SES (β -0.36; 95%CI: -0.60 to -0.12) and female gender (β -0.29; 95%CI: -0.58 to -0.012) were associated with lower MHC-SF scores. Additionally, being White was associated with higher MHC-SF scores (β -0.29; 95%CI: -0.44 to 0.54). Age, English as a second language, and immigration status were not significant predictors of mental health. High levels of stress, negative perceptions of the mental healthcare system, and limited access were the more common reported themes in the qualitative analysis. In our cohort, university students from across Canada had low MHC scores. Social determinants of health (e.g., low SES, being non-White, and identifying as a woman) were independent predictors of low MCH scores. Further studies are needed to identify specific groups at higher risk as well as strategies to overcome the suboptimal mental health among Canadian students.

  9. LGBTQ+ inclusivity in climate and curriculum at the educational institution....

    • plos.figshare.com
    xls
    Updated Jan 9, 2025
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    Anubhuti Shukla; Sriha Yalamanchi; Guillermo Tamayo-Cabeza; Amanda Albright; Zachary A. Weber; April D. Newton (2025). LGBTQ+ inclusivity in climate and curriculum at the educational institution. [Dataset]. http://doi.org/10.1371/journal.pone.0313492.t002
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    xlsAvailable download formats
    Dataset updated
    Jan 9, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Anubhuti Shukla; Sriha Yalamanchi; Guillermo Tamayo-Cabeza; Amanda Albright; Zachary A. Weber; April D. Newton
    License

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

    Description

    LGBTQ+ inclusivity in climate and curriculum at the educational institution.

  10. Physical activity level results.

    • plos.figshare.com
    xls
    Updated Nov 13, 2025
    + more versions
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    Moayad Subahi; Fahda Alshaikh; Eyad Dahlawi; Feras Zafar; Tamim Alsulimany; Nawaf Alnefaie; Abdulrahman Almalki (2025). Physical activity level results. [Dataset]. http://doi.org/10.1371/journal.pone.0336663.t002
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    xlsAvailable download formats
    Dataset updated
    Nov 13, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Moayad Subahi; Fahda Alshaikh; Eyad Dahlawi; Feras Zafar; Tamim Alsulimany; Nawaf Alnefaie; Abdulrahman Almalki
    License

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

    Description

    Knee osteoarthritis (KOA) is a prevalent condition that reduces physical function and quality of life. Physical activity is foundational to KOA management; however, patient engagement and perceptions of treatment remain underexplored, particularly in Middle Eastern populations. This study evaluated physical activity (PA) levels among individuals with KOA and explored their perceptions, awareness, and experiences with management strategies, especially physical therapy. A sequential explanatory mixed-methods design was employed. Quantitative data were collected using the International Physical Activity Questionnaire-Short Form (IPAQ-SF) from 60 adults with physician-diagnosed KOA (mean age 55.5 ± 6.4 years; 50% female) recruited from clinics and community programs in Saudi Arabia. Semi-structured interviews with 24 purposively selected participants further explored experiences and perceptions. Descriptive statistics summarized quantitative data, and thematic analysis guided qualitative interpretation. Ninety percent of participants recorded low PA levels (≤600 MET-min/week), with only 10% achieving moderate or high activity levels. Qualitative themes revealed multiple barriers including emotional distress, logistical difficulties, and misconceptions about KOA as well as facilitators such as family support and patient education. Integration of findings highlighted how contextual and psychosocial factors influence PA engagement. Adults with KOA in this study reported markedly low levels of PA, shaped by cultural, psychological, and environmental factors. Our findings highlight the importance of addressing these barriers through patient-centred education and improved access to physical therapy.

  11. Descriptive statistics of the participants background characteristics in the...

    • plos.figshare.com
    bin
    Updated Aug 4, 2023
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    Supritha Aithal; Vicky Karkou; Stergios Makris; Themis Karaminis; Joanne Powell (2023). Descriptive statistics of the participants background characteristics in the DMP intervention and standard care groups, separated by teacher/parent status. [Dataset]. http://doi.org/10.1371/journal.pone.0288626.t001
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    binAvailable download formats
    Dataset updated
    Aug 4, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Supritha Aithal; Vicky Karkou; Stergios Makris; Themis Karaminis; Joanne Powell
    License

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

    Description

    Descriptive statistics of the participants background characteristics in the DMP intervention and standard care groups, separated by teacher/parent status.

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

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Alinafe Chisalunda; Wingston Felix Ng’ambi; Nesto Salia Tarimo; Ndaziona Peter Kwanjo Banda; Adamson Sinjani Muula; Johnstone Kumwenda; Alinane Linda Nyondo-Mipando (2023). S3 Text - [Dataset]. http://doi.org/10.1371/journal.pgph.0002367.s003

S3 Text -

Related Article
Explore at:
zipAvailable download formats
Dataset updated
Oct 9, 2023
Dataset provided by
PLOS Global Public Health
Authors
Alinafe Chisalunda; Wingston Felix Ng’ambi; Nesto Salia Tarimo; Ndaziona Peter Kwanjo Banda; Adamson Sinjani Muula; Johnstone Kumwenda; Alinane Linda Nyondo-Mipando
License

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

Description

A. In-depth interview guide for patients. B. Guardian in-depth interview guide for qualitative data. (ZIP)

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