11 datasets found
  1. Share of U.S. adolescents with substance use disorders 2018-2019, by gender

    • statista.com
    Updated Nov 29, 2023
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    Statista (2023). Share of U.S. adolescents with substance use disorders 2018-2019, by gender [Dataset]. https://www.statista.com/statistics/1351722/substance-use-disorders-among-us-adolescents-by-gender/
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    Dataset updated
    Nov 29, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2018 - 2019
    Area covered
    United States
    Description

    From 2018 to 2019, around 4.4 percent of female adolescents aged 12 to 17 years in the United States reported having a substance use disorder during the past year. This statistic illustrates the percentage of adolescents in the U.S. with substance use disorders from 2018 to 2019, by gender.

  2. f

    Descriptive statistics for predictors, outcomes, and hypothesized moderators...

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Sabra L. Katz-Wise; Vishnudas Sarda; S. Bryn Austin; Sion Kim Harris (2023). Descriptive statistics for predictors, outcomes, and hypothesized moderators for Waves 1–5 (N = 30). [Dataset]. http://doi.org/10.1371/journal.pone.0250500.t002
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Sabra L. Katz-Wise; Vishnudas Sarda; S. Bryn Austin; Sion Kim Harris
    License

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

    Description

    Descriptive statistics for predictors, outcomes, and hypothesized moderators for Waves 1–5 (N = 30).

  3. f

    Table_2_Past Year Cannabis Use Among Norwegian Adolescents: Time Trends...

    • frontiersin.figshare.com
    docx
    Updated Jun 1, 2023
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    Ove Heradstveit; Sondre Aasen Nilsen; Kyrre Breivik; Anders Bakken; Thomas Haug; Kristian Hartveit; Kjell Morten Stormark (2023). Table_2_Past Year Cannabis Use Among Norwegian Adolescents: Time Trends Based on the Ungdata Surveys 2010–2019.DOCX [Dataset]. http://doi.org/10.3389/fpsyt.2021.627479.s002
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Frontiers
    Authors
    Ove Heradstveit; Sondre Aasen Nilsen; Kyrre Breivik; Anders Bakken; Thomas Haug; Kristian Hartveit; Kjell Morten Stormark
    License

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

    Description

    Aims: To describe trends in cannabis use from 2010 to 2019 among Norwegian adolescents and relate these to individual- and municipal-level variables.Design: Data from nationwide repeated cross-sectional surveys collected in 2010–2013 (T1), 2014–2016 (T2), and 2017–2019 (T3) were used to describe secular trends in proportions of adolescent cannabis use.Setting: Cross-sectional surveys in 410 of the total 428 municipalities of Norway.Participants: A total of 628,678 survey responses from adolescents aged ~13–19 years of age, in which 566,912 survey responses were eligible for analyses, representing data from 340 municipalities.Measurements: Respondent's past year cannabis use, time, gender, school grade, municipality, geographical location, and municipality population.Findings: Boys reported overall higher cannabis use, with ~2:1 gender ratio for any past year cannabis use and a 3:1 gender ratio for frequent cannabis use. Adolescents in Eastern Norway reported higher cannabis use compared with other areas in the country, and adolescents from municipalities with a higher population size reported higher rates of cannabis use than smaller municipalities. A gradual increase in cannabis use from T1 to T3 was found in Eastern Norway and in the largest municipalities. More generally, proportions of past year cannabis use showed a marked increase from T2 to T3 across genders, grade/age groups, geographical location, and municipality population, with few exceptions.Conclusions: Our findings indicate that proportions of past year cannabis use have increased among Norwegian adolescents in recent years. Preventive interventions to hinder initiation of cannabis use, as well as measures to address frequent cannabis use among Norwegian adolescents, are needed.

  4. f

    Gender classification definitions of participants and proportions, weighted...

    • plos.figshare.com
    xls
    Updated Jun 15, 2023
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    Wit Wichaidit; Natnita Mattawanon; Witchaya Somboonmark; Nattaphorn Prodtongsom; Virasakdi Chongsuvivatwong; Sawitri Assanangkornchai (2023). Gender classification definitions of participants and proportions, weighted percent ± standard error (SE) (n = 21,323 participants). [Dataset]. http://doi.org/10.1371/journal.pone.0287130.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 15, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Wit Wichaidit; Natnita Mattawanon; Witchaya Somboonmark; Nattaphorn Prodtongsom; Virasakdi Chongsuvivatwong; Sawitri Assanangkornchai
    License

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

    Description

    Gender classification definitions of participants and proportions, weighted percent ± standard error (SE) (n = 21,323 participants).

  5. d

    Young people are admitted to the new juvenile restraint facility according...

    • data.gov.tw
    csv
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    Department of Statistics, Young people are admitted to the new juvenile restraint facility according to the type of drug, the number of observation and restraint, and gender (statistics). [Dataset]. https://data.gov.tw/en/datasets/39441
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    csvAvailable download formats
    Dataset authored and provided by
    Department of Statistics
    License

    https://data.gov.tw/licensehttps://data.gov.tw/license

    Description

    The number of people admitted to the new adolescent rehabilitation center is categorized by the type of drugs, frequency of drug use, and gender.

  6. f

    a. Prevalence (weighted percent ± SE) of past-year exposure to violence...

    • plos.figshare.com
    xls
    Updated Jun 15, 2023
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    Wit Wichaidit; Natnita Mattawanon; Witchaya Somboonmark; Nattaphorn Prodtongsom; Virasakdi Chongsuvivatwong; Sawitri Assanangkornchai (2023). a. Prevalence (weighted percent ± SE) of past-year exposure to violence among the participants, part 1. [Dataset]. http://doi.org/10.1371/journal.pone.0287130.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 15, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Wit Wichaidit; Natnita Mattawanon; Witchaya Somboonmark; Nattaphorn Prodtongsom; Virasakdi Chongsuvivatwong; Sawitri Assanangkornchai
    License

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

    Description

    b. Prevalence (weighted percent ± SE) of past-year exposure to violence among the participants, part 2.

  7. f

    a. Characteristics of study participants, weighted percent ± SE unless...

    • figshare.com
    • plos.figshare.com
    xls
    Updated Jun 15, 2023
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    Wit Wichaidit; Natnita Mattawanon; Witchaya Somboonmark; Nattaphorn Prodtongsom; Virasakdi Chongsuvivatwong; Sawitri Assanangkornchai (2023). a. Characteristics of study participants, weighted percent ± SE unless otherwise noted, part 1 (n = 21,323 participants) (ROW PERCENTS). [Dataset]. http://doi.org/10.1371/journal.pone.0287130.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 15, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Wit Wichaidit; Natnita Mattawanon; Witchaya Somboonmark; Nattaphorn Prodtongsom; Virasakdi Chongsuvivatwong; Sawitri Assanangkornchai
    License

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

    Description

    b. Characteristics of study participants, weighted percent ± SE unless otherwise noted, part 2 (n = 21,323 participants).

  8. f

    Anonymized data set.

    • plos.figshare.com
    txt
    Updated Jun 15, 2023
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    Wit Wichaidit; Natnita Mattawanon; Witchaya Somboonmark; Nattaphorn Prodtongsom; Virasakdi Chongsuvivatwong; Sawitri Assanangkornchai (2023). Anonymized data set. [Dataset]. http://doi.org/10.1371/journal.pone.0287130.s001
    Explore at:
    txtAvailable download formats
    Dataset updated
    Jun 15, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Wit Wichaidit; Natnita Mattawanon; Witchaya Somboonmark; Nattaphorn Prodtongsom; Virasakdi Chongsuvivatwong; Sawitri Assanangkornchai
    License

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

    Description

    Anonymized data set to replicate the study findings. (CSV)

  9. f

    R Codes.

    • plos.figshare.com
    txt
    Updated Jun 15, 2023
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    Wit Wichaidit; Natnita Mattawanon; Witchaya Somboonmark; Nattaphorn Prodtongsom; Virasakdi Chongsuvivatwong; Sawitri Assanangkornchai (2023). R Codes. [Dataset]. http://doi.org/10.1371/journal.pone.0287130.s002
    Explore at:
    txtAvailable download formats
    Dataset updated
    Jun 15, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Wit Wichaidit; Natnita Mattawanon; Witchaya Somboonmark; Nattaphorn Prodtongsom; Virasakdi Chongsuvivatwong; Sawitri Assanangkornchai
    License

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

    Description

    Codes for data analyses, text file with annotations. (TXT)

  10. f

    Demographics (N = 412).

    • plos.figshare.com
    xls
    Updated Jun 11, 2023
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    Karen Kwaning; Mitchell Wong; Kulwant Dosanjh; Christopher Biely; Rebecca Dudovitz (2023). Demographics (N = 412). [Dataset]. http://doi.org/10.1371/journal.pone.0251332.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 11, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Karen Kwaning; Mitchell Wong; Kulwant Dosanjh; Christopher Biely; Rebecca Dudovitz
    License

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

    Description

    Demographics (N = 412).

  11. f

    Estimated percent of associations between gender stigma awareness and risky...

    • figshare.com
    xls
    Updated Jun 4, 2023
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    Karen Kwaning; Mitchell Wong; Kulwant Dosanjh; Christopher Biely; Rebecca Dudovitz (2023). Estimated percent of associations between gender stigma awareness and risky health behaviors mediated by school disengagement. [Dataset]. http://doi.org/10.1371/journal.pone.0251332.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Karen Kwaning; Mitchell Wong; Kulwant Dosanjh; Christopher Biely; Rebecca Dudovitz
    License

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

    Description

    Estimated percent of associations between gender stigma awareness and risky health behaviors mediated by school disengagement.

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    Learn how you can add new datasets to our index.

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Statista (2023). Share of U.S. adolescents with substance use disorders 2018-2019, by gender [Dataset]. https://www.statista.com/statistics/1351722/substance-use-disorders-among-us-adolescents-by-gender/
Organization logo

Share of U.S. adolescents with substance use disorders 2018-2019, by gender

Explore at:
Dataset updated
Nov 29, 2023
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2018 - 2019
Area covered
United States
Description

From 2018 to 2019, around 4.4 percent of female adolescents aged 12 to 17 years in the United States reported having a substance use disorder during the past year. This statistic illustrates the percentage of adolescents in the U.S. with substance use disorders from 2018 to 2019, by gender.

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