46 datasets found
  1. Leading causes of death among teenagers aged 15-19 years in the United...

    • statista.com
    Updated Dec 13, 2024
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    Statista (2024). Leading causes of death among teenagers aged 15-19 years in the United States 2020-22 [Dataset]. https://www.statista.com/statistics/1017959/distribution-of-the-10-leading-causes-of-death-among-teenagers/
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    Dataset updated
    Dec 13, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of 2022, the third leading cause of death among teenagers aged 15 to 19 years in the United States was intentional self-harm or suicide, contributing around 17 percent of deaths among age group. The leading cause of death at that time was unintentional injuries, contributing to around 37.4 percent of deaths, while 21.8 percent of all deaths in this age group were due to assault or homicide. Cancer and heart disease, the overall leading causes of death in the United States, are also among the leading causes of death among U.S. teenagers. Adolescent suicide in the United States In 2021, around 22 percent of students in grades 9 to 12 reported that they had seriously considered attempting suicide in the past year. Female students were around twice as likely to report seriously considering suicide compared to male students. In 2022, Montana had the highest rate of suicides among U.S. teenagers with around 39 deaths per 100,000 teenagers, followed by South Dakota with a rate of 33 per 100,000. The states with the lowest death rates among adolescents are New York and New Jersey. Mental health treatment Suicidal thoughts are a clear symptom of mental health issues. Mental health issues are not rare among children and adolescents, and treatment for such issues has become increasingly accepted and accessible. In 2021, around 15 percent of boys and girls aged 5 to 17 years had received some form of mental health treatment in the past year. At that time, around 35 percent of youths aged 12 to 17 years in the United States who were receiving specialty mental health services were doing so because they had thought about killing themselves or had already tried to kill themselves.

  2. Leading causes of death among children aged 10-14 years in the United States...

    • statista.com
    Updated Dec 13, 2024
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    Statista (2024). Leading causes of death among children aged 10-14 years in the United States 2020-22 [Dataset]. https://www.statista.com/statistics/1017954/distribution-of-the-10-leading-causes-of-death-among-children-ten-to-fourteen/
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    Dataset updated
    Dec 13, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2022, the leading causes of death among children and adolescents in the United States aged 10 to 14 were unintentional injuries, intentional self-harm (suicide), and cancer. That year, unintentional injuries accounted for around 25 percent of all deaths among this age group. Leading causes of death among older teens Like those aged 10 to 14 years, the leading cause of death among older teenagers in the U.S. aged 15 to 19 years is unintentional injuries. In 2022, unintentional injuries accounted for around 37 percent of all deaths among older teens. However, unlike those aged 10 to 14, the second leading cause of death among teens aged 15 to 19 is assault or homicide. Sadly, the third leading cause of death among this age group is suicide, making suicide among the leading three causes of death for both age groups. Teen suicide Suicide remains a major problem among teenagers in the United States, as reflected in the leading causes of death among this age group. It was estimated that in 2021, around 22 percent of high school students in the U.S. considered attempting suicide in the past year, with this rate twice as high for girls than for boys. The states with the highest death rates due to suicide among adolescents aged 15 to 19 years are Montana, South Dakota, and New Mexico. In 2022, the death rate from suicide among this age group in Montana was 39 per 100,000 population. In comparison, New York, the state with the lowest rate, had just five suicide deaths among those aged 15 to 19 years per 100,000 population.

  3. Leading causes of death, total population, by age group

    • www150.statcan.gc.ca
    • ouvert.canada.ca
    • +1more
    Updated Feb 19, 2025
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    Government of Canada, Statistics Canada (2025). Leading causes of death, total population, by age group [Dataset]. http://doi.org/10.25318/1310039401-eng
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    Dataset updated
    Feb 19, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

  4. H

    Data from: Kids Count Data Center

    • dataverse.harvard.edu
    Updated Feb 23, 2011
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    Harvard Dataverse (2011). Kids Count Data Center [Dataset]. http://doi.org/10.7910/DVN/DLA2Q2
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 23, 2011
    Dataset provided by
    Harvard Dataverse
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Users can customize tables, graphs and maps on data related to children in a specific state or in the United States as a whole. Comparisons can be made between states. Background KIDS COUNT Data Center is part of the Annie E. Casey Foundation and serves to provide information on the status of children in America. The ten core indicators of interest under "Data by State" are: percent of low birth weight babies, infant mortality rate, child death rate, rate of teen deaths by accident, suicide and homicide, teen birth rate, percent of children living with parents who do not have full-time year-round employment, percent of teens who are high school drop outs, percent of teens not working and not in school, percent of children in poverty, and percent of families with children headed by a single parent. A number of other indicators, plus demographic and income information, are also included. "Data across States" is grouped into the following broad categories: demographics, education, economic well-being, family and community, health, safety and risk behaviors, and other. User Functionality Users can determine the view of the data- by table, line graph or map and can print or email the results. Data is available by state and across states. Data Across States allows users to access the raw data. Data is often present over a number of years. For a number of indicators under "Data Across States," users can view results by age, gender/ sex, or race/ ethnicity. Data Notes KIDS COUNT started in 1990. The most recent year of data is 2009 (or 2008 depending on the state, with some data available from 2010). Data is available on the national and state level, and for some states, at the county and city level.

  5. Talking with teenagers about drugs

    • datasets.ai
    • open.canada.ca
    • +1more
    21
    Updated Aug 27, 2024
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    Health Canada | Santé Canada (2024). Talking with teenagers about drugs [Dataset]. https://datasets.ai/datasets/0ed3f484-658b-4204-9408-66e10942c9f6
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    21Available download formats
    Dataset updated
    Aug 27, 2024
    Dataset provided by
    Health Canadahttp://www.hc-sc.gc.ca/
    Authors
    Health Canada | Santé Canada
    Description

    Between illegal substances and prescription medications it may be hard to know where to start talking about drugs. But drugs can be dangerous and some teenagers are not aware of all the risks. Start the conversation early and give information before your teen needs to ask.

  6. s

    Social Media Addiction Statistics Amongst Teenagers

    • searchlogistics.com
    Updated Apr 1, 2025
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    (2025). Social Media Addiction Statistics Amongst Teenagers [Dataset]. https://www.searchlogistics.com/learn/statistics/social-media-addiction-statistics/
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    Dataset updated
    Apr 1, 2025
    License

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

    Description

    Teenagers are the 2nd largest group of people affected by social media addiction. Teens ages 13 to 18 years old spend a significant amount of their free time on social media with an average of 3 hours a day.

  7. Mortality rates, by age group

    • www150.statcan.gc.ca
    • open.canada.ca
    Updated Dec 4, 2024
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    Government of Canada, Statistics Canada (2024). Mortality rates, by age group [Dataset]. http://doi.org/10.25318/1310071001-eng
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    Dataset updated
    Dec 4, 2024
    Dataset provided by
    Government of Canadahttp://www.gg.ca/
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Number of deaths and mortality rates, by age group, sex, and place of residence, 1991 to most recent year.

  8. Teen pregnancy, by pregnancy outcomes, females aged 15 to 19

    • www150.statcan.gc.ca
    • open.canada.ca
    • +3more
    Updated Apr 10, 2007
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    Government of Canada, Statistics Canada (2007). Teen pregnancy, by pregnancy outcomes, females aged 15 to 19 [Dataset]. http://doi.org/10.25318/1310016601-eng
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    Dataset updated
    Apr 10, 2007
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Number of teen pregnancies and rates per 1,000 females, by pregnancy outcome (live births, induced abortions, or fetal loss), by age groups 15 to 17 years and 18 to 19 years, 1998 to 2000.

  9. Leading causes of death among children and teens aged 1-19 U.S. 2020-2021

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Leading causes of death among children and teens aged 1-19 U.S. 2020-2021 [Dataset]. https://www.statista.com/statistics/1384047/leading-causes-of-death-for-children-and-teens-us/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Over the last few years, gun violence in the United States has become an increasingly deadly public health crisis. In 2021, firearms were the leading cause of death for children and adolescents aged one to 19 years old for a second year in a row in the United States, with ***** deaths from firearms, which accounted for more deaths than car crashes and other diseases in that year. This is an increase from the previous year, when there were ***** deaths from firearms. Gun violence in the U.S. Along with a rise in gun-related deaths, the United States has been experiencing an overall increase in gun violence, including mass shootings, school shootings, and gun homicides. Not surprisingly, the United States has also reported in increase in gun sales, with the unit sales for firearms reaching a new high in recent years. A uniquely American problem Despite the rise of gun violence and gun-related deaths, guns remain easily accessible in the United States and gun control has become a divisive issue throughout the nation. However, gun control proponents often call attention to the uniquely American phenomenon of school shootings. Since 2018, the annual number of incidents involving firearms at K-12 schools in the U.S. reached over *** in each year, while similar incidents in other countries with strict gun laws are exceptionally rare.

  10. g

    Population aged 25 to 59 years who had some relationship with their mother...

    • gimi9.com
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    Population aged 25 to 59 years who had some relationship with their mother or did not maintain it because they were deceased according to the level of education of the mother when she was a teenager and at risk of poverty. Canary Islands. 2022 | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_5b53e70b67cc94daf41822d3871cd27c2b60ff6f/
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    Area covered
    Canary Islands
    Description

    This table provides data from 2022 on the estimated population aged 25 to 59 years who had some relationship with their mother or did not maintain it because they died in the Canary Islands by level of education of the mother when she was a teenager and risk of poverty.

  11. u

    Talking with teenagers about drugs - Catalogue - Canadian Urban Data...

    • data.urbandatacentre.ca
    • beta.data.urbandatacentre.ca
    Updated Oct 1, 2024
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    (2024). Talking with teenagers about drugs - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://data.urbandatacentre.ca/dataset/gov-canada-0ed3f484-658b-4204-9408-66e10942c9f6
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    Dataset updated
    Oct 1, 2024
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Area covered
    Canada
    Description

    Between illegal substances and prescription medications it may be hard to know where to start talking about drugs. But drugs can be dangerous and some teenagers are not aware of all the risks. Start the conversation early and give information before your teen needs to ask.

  12. f

    Datasheet1_Analysis of early and treatment related deaths among children and...

    • frontiersin.figshare.com
    • datasetcatalog.nlm.nih.gov
    pdf
    Updated Oct 17, 2024
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    Katarzyna Pawińska-Wąsikowska; Małgorzata Czogała; Karolina Bukowska-Strakova; Marta Surman; Monika Rygielska; Teofila Książek; Beata Sadowska; Agnieszka Pac; Jolanta Skalska-Sadowska; Magdalena Samborska; Jacek Wachowiak; Małgorzata Ciebiera; Radosław Chaber; Renata Tomaszewska; Tomasz Szczepański; Karolina Zielezińska; Tomasz Urasiński; Anna Rodziewicz-Konarska; Krzysztof Kałwak; Marta Kozłowska; Ninela Irga-Jaworska; Barbara Sikorska-Fic; Bartosz Chyżyński; Paweł Łaguna; Katarzyna Muszyńska-Rosłan; Maryna Krawczuk-Rybak; Paulina Deleszkiewicz; Katarzyna Drabko; Katarzyna Bobeff; Wojciech Młynarski; Agnieszka Chodała-Grzywacz; Grażyna Karolczyk; Katarzyna Mycko; Wanda Badowska; Natalia Bartoszewicz; Jan Styczyński; Katarzyna Machnik; Weronika Stolpa; Agnieszka Mizia-Malarz; Walentyna Balwierz; Szymon Skoczeń (2024). Datasheet1_Analysis of early and treatment related deaths among children and adolescents with acute myeloid leukemia in Poland: 2005–2023.pdf [Dataset]. http://doi.org/10.3389/fped.2024.1482720.s001
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    pdfAvailable download formats
    Dataset updated
    Oct 17, 2024
    Dataset provided by
    Frontiers
    Authors
    Katarzyna Pawińska-Wąsikowska; Małgorzata Czogała; Karolina Bukowska-Strakova; Marta Surman; Monika Rygielska; Teofila Książek; Beata Sadowska; Agnieszka Pac; Jolanta Skalska-Sadowska; Magdalena Samborska; Jacek Wachowiak; Małgorzata Ciebiera; Radosław Chaber; Renata Tomaszewska; Tomasz Szczepański; Karolina Zielezińska; Tomasz Urasiński; Anna Rodziewicz-Konarska; Krzysztof Kałwak; Marta Kozłowska; Ninela Irga-Jaworska; Barbara Sikorska-Fic; Bartosz Chyżyński; Paweł Łaguna; Katarzyna Muszyńska-Rosłan; Maryna Krawczuk-Rybak; Paulina Deleszkiewicz; Katarzyna Drabko; Katarzyna Bobeff; Wojciech Młynarski; Agnieszka Chodała-Grzywacz; Grażyna Karolczyk; Katarzyna Mycko; Wanda Badowska; Natalia Bartoszewicz; Jan Styczyński; Katarzyna Machnik; Weronika Stolpa; Agnieszka Mizia-Malarz; Walentyna Balwierz; Szymon Skoczeń
    License

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

    Area covered
    Poland
    Description

    BackgroundA personalised approach to the treatment of acute myeloid leukemia (AML) in children and adolescents, as well as the development of supportive therapies, has significantly improved survival. Despite this, some patients still die before starting treatment or in an early phase of therapy before achieving remission. The study analysed the frequency, clinical features and risk factors for early deaths (ED) and treatment related deaths (TRD) of children and adolescents with AML.MethodsFrom January 2005 to November 2023, 646 children with AML treated in the centers of the Polish Pediatric Leukemia and Lymphoma Study Group according to three subsequent therapeutic protocols were evaluated: AML-BFM 2004 Interim (385 children), AML-BFM 2012 Registry (131 children) and AML-BFM 2019 (130 children).ResultsOut of 646 children, early death occurred in 30 children, including 15 girls. The median age was 10.7 years (1 day to 18 years). More than half of the patients (53%) were diagnosed with acute myelomonocytic leukemia (M5) and 13% with acute promyelocytic leukemia (M3). The ED rate for the three consecutive AML-BFM protocols was 4.9% vs. 5.3% vs. 3.1%, respectively. In 19 patients, death occurred before the 15th day of treatment, in 11 between the 15th and 42nd day. The most common cause of death before the 15th day (ED15) was leukostasis and bleeding, whereas between the 15th and 42nd day (ED15-42), infections, mainly bacterial sepsis. A significant association was found between ED15 and high leukocyte count (>10 × 109/L), M3 leukemia (p 

  13. Maternal, Child, and Adolescent Health Needs Assessment, 2023-2024

    • data.sfgov.org
    • catalog.data.gov
    csv, xlsx, xml
    Updated Aug 5, 2025
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    SF Department of Public Health (2025). Maternal, Child, and Adolescent Health Needs Assessment, 2023-2024 [Dataset]. https://data.sfgov.org/Health-and-Social-Services/Maternal-Child-and-Adolescent-Health-Needs-Assessm/iqtk-etij
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    xlsx, csv, xmlAvailable download formats
    Dataset updated
    Aug 5, 2025
    Dataset provided by
    San Francisco Department of Public Health
    Authors
    SF Department of Public Health
    Description

    SUMMARY This table contains data about women, ages 15 to 50, pregnant people, infants, children, and youths, up to age 24. It contains information about a wide range of health topics, including medical conditions, nutrition, dehydration, oral health, mental health, safety, access to health care, and basic needs, like housing. Local, county-level prevalence rates, time trends, and health disparities about national public health priorities, including preterm birth, infant death, childhood obesity, adolescent depression and substance use, and high blood pressure, diabetes, and kidney disease in young adults.

    The population data is from the 2023-2024 San Francisco Maternal Child and Adolescent Health needs assessment and is published on the Open Data Portal to share with community partners, plan services, and promote health.

    For more information see:

  14. Maternal, Child, and Adolescent Health Homepage
  15. Maternal, Child, and Adolescent Health Reports

    HOW THE DATASET IS CREATED The Maternal, Child, and Adolescent Health (MCAH) Needs Assessment for San Francisco included review of a wide range of citywide population data covering a ten-year span, from 2014 to 2023. Data from over 83,000 birth records, 59,000 death records, 261,000 emergency room visits, 66,000 hospital admissions, and 90,000 newborn screening discharges were gathered, along with citywide data from child welfare records, health screenings in childcare and schools, DMV records of first-time drivers, school surveys, and a state-run mailed survey of recent births (California Department of Public Health MIHA survey). The datasets provided information about approximately 700 health conditions. Each health condition was described in terms of the number of people affected or cases, and the rate affected, stratified by age, sex, race-ethnicity, insurance status, zip code, and time period.

    Rates were calculated by dividing the number of people or events by the population group estimate (e.g., total births or census estimates), then multiplying by 100 or 1,000 depending on the measure. Each rate was presented with its 95% confidence interval to support users to compare any two rates, either between groups or over time. Two rates differ “significantly” if their 95% confidence intervals do not overlap.

    The present dataset summarizes the group-level results for any age-, sex-, race-, insurance-, zip code-, and/or period-specific group that included at least 20 people or cases.

    Causes of death, health conditions that affected over 1000 people in the time frame, problems that got worse over time, and health disparities by insurance, race-ethnicity and/or zip code were flagged for the MCAH Needs Assessment.

    UPDATE PROCESS The dataset will be updated manually, bi-annually, each December and June.

    HOW TO USE THIS DATASET Population data from the MCAH needs assessment are shared in several formats, including aggregated datasets on DataSF.gov, downloadable PDF summary reports by age group, interactive online visualizations, data tables, trend graphs, and maps. Information about each variable is available in a linked data dictionary. The definition of each numerator and denominator depends on data source, life stage, and time. Health conditions may not be directly comparable across life stage, if the numerator definition includes age- or pregnancy-specific diagnosis codes (e.g. diabetes hospitalization).

    For small groups or rare conditions, consider combining time periods and/or groups. Data are suppressed if fewer than 20 cases happened in the group and period.

    Group-specific rates are available if the matched group-specific census estimates (denominator) were available. Census estimates are only available for selected age-sex-race-, age-sex-zip code-, or age-sex-insurance-specific groups. Hospital records reflect what each clinician documented as relevant for the hospital encounter. No diagnosis does not rule out the presence of a condition unnoticed. Hospital and ER visit data reflect how many people had the condition vs. unknown. Rates may not be directly comparable across time and place, because data collection protocol may not be complete or standardized across data entry staff, time, and place.

    Multiple statistical comparisons may lead to false positives. Some statistically significant results may be significant only by chance. Observational data do not support causal inference and are only meant to flag topics for deeper discussion and investigation. Consider alternative explanations for the data, including chance and potential sources of error.

  • s

    Social Media Addiction Statistics Amongst Young Adults

    • searchlogistics.com
    Updated Apr 1, 2025
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    (2025). Social Media Addiction Statistics Amongst Young Adults [Dataset]. https://www.searchlogistics.com/learn/statistics/social-media-addiction-statistics/
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    Dataset updated
    Apr 1, 2025
    License

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

    Description

    90% of people aged 18-29 use social media in some form. 15% of people aged 23-38 admit that they are addicted to social media.

  • d

    Challenges Faced by Teenage Programmers in Software Development

    • dataone.org
    Updated Nov 8, 2023
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    Sadhu, Harshith (2023). Challenges Faced by Teenage Programmers in Software Development [Dataset]. http://doi.org/10.7910/DVN/97PY1K
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Sadhu, Harshith
    Description

    As software has become an integral part of society, many teenage programmers have taken their hand at creating software applications, such as websites or video games. However, since programming is not such an easy concept to master, many developers have been left struggling in their coding journeys As indicated in the current body of literature, many professionals have struggled with marketing, creating applications for multiple platforms, and garnering enough project sponsorship. Although these studies were great in that they described the common issues, they did not cover the teenage population, hence leading me to investigate the most common obstacles of software development amongst the teenage population and how they can resolve these challenges. To investigate this topic, a 2 part study was conducted which surveyed teenagers on their most challenging programming obstacles and which interviewed industry level professionals for solutions/advice for these challenges. It was then revealed that teenagers faced some of the same issues as industry level professionals, such as cross platform integration and brainstorming unique application purposes, however, they were unique in that they had issues managing their school work with their development time. With the completion of this study, the obstacles of the teenage population were finally uncovered and teenage programmers are now able to refer back to the advice given within the study to further their software journeys.

  • f

    Data from: Relationship between social skills, stress, age, sex, school type...

    • scielo.figshare.com
    • datasetcatalog.nlm.nih.gov
    jpeg
    Updated May 30, 2023
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    Sheila Francisca Machado; Sérgio Henrique de Souza Alves; Patrícia Fagundes Caetano (2023). Relationship between social skills, stress, age, sex, school type and school grade in adolescents [Dataset]. http://doi.org/10.6084/m9.figshare.14307491.v1
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    jpegAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    SciELO journals
    Authors
    Sheila Francisca Machado; Sérgio Henrique de Souza Alves; Patrícia Fagundes Caetano
    License

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

    Description

    Abstract During adolescence many changes occur in adolescent life. They have to develop social skills, behaviors that composes the repertoire of an individual to respond the social demands adequately. They face some situations that can cause stress, which is the reaction of the body to restore its balance after going through stressor situation. The present study aimed to investigate the correlation of social skills and stress variables: sex, age, type of school attended and grade. For this was used Psychological tests ESA (Stress Scale for Adolescents) and IHSA-Del-Prette(Inventory of Social Skills for Adolescents). The obtained results permit to conclude that there is a correlation between stress and the variables gender, age and type of school attended, as well as between the emission of social skills and the type of school attended. The hypothesis that the female students had more social skills than the students was not confirmed, nor it was confirmed that men have more difficulties in issuing the answers than women.

  • f

    Data_Sheet_1_The Causes of Death and Their Influence in Life Expectancy of...

    • frontiersin.figshare.com
    pdf
    Updated Jun 6, 2023
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    Juanjuan Liang; Yuanze Du; Xiang Qu; Changrong Ke; Guipeng Yi; Mi Liu; Juncheng Lyu; Yanfeng Ren; Jie Xing; Chunping Wang; Shiwei Liu (2023). Data_Sheet_1_The Causes of Death and Their Influence in Life Expectancy of Children Aged 5–14 Years in Low- and Middle-Income Countries From 1990 to 2019.pdf [Dataset]. http://doi.org/10.3389/fped.2022.829201.s001
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    pdfAvailable download formats
    Dataset updated
    Jun 6, 2023
    Dataset provided by
    Frontiers
    Authors
    Juanjuan Liang; Yuanze Du; Xiang Qu; Changrong Ke; Guipeng Yi; Mi Liu; Juncheng Lyu; Yanfeng Ren; Jie Xing; Chunping Wang; Shiwei Liu
    License

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

    Description

    IntroductionAlthough child and adolescent health is the core of the global health agenda, the cause of death and its expected contribution to life expectancy (LE) among those aged 5–14 are under-researched across countries, especially in low- and middle-income countries (LMICs).MethodsDeath rates per 10 years age group including a 5–14-year-old group were calculated by the formula, which used the population and the number of deaths segmented by the cause of death and gender from the 2019 Global Burden of Disease (GBD) study. LE and cause-eliminated LE in 10-year intervals were calculated by using life tables.ResultsIn 2019, the global mortality rate for children and adolescents aged 5–14 years was 0.522 (0.476–0.575) per 1,000, and its LF was 71.377 years. In different-income regions, considerable heterogeneity remains in the ranking of cause of death aged 5–14 years. The top three causes of death in low-income countries (LICs) are enteric infections [0.141 (0.098–0.201) per 1,000], other infectious diseases [0.103 (0.073–0.148) per 1,000], and neglected tropical diseases and malaria [0.102 (0.054–0.172) per 1,000]. Eliminating these mortality rates can increase the life expectancy of the 5–14 age group by 0.085, 0.062, and 0.061 years, respectively. The top three causes of death in upper-middle income countries (upper MICs) are unintentional injuries [0.066 (0.061–0.072) per 1,000], neoplasm [0.046 (0.041–0.050) per 1,000], and transport injuries [0.045 (0.041–0.049) per 1,000]. Eliminating these mortality rates can increase the life expectancy of the 5–14 age group by 0.045, 0.031, and 0.030 years, respectively.ConclusionThe mortality rate for children and adolescents aged 5–14 years among LMICs remains high. Considerable heterogeneity was observed in the main causes of death among regions. According to the main causes of death at 5–14 years old in different regions and countries at different economic levels, governments should put their priority in tailoring their own strategies to decrease preventable mortality.

  • A

    VitalStats

    • data.amerigeoss.org
    query tool
    Updated Jul 26, 2019
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    United States (2019). VitalStats [Dataset]. https://data.amerigeoss.org/is/dataset/vitalstats
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    query toolAvailable download formats
    Dataset updated
    Jul 26, 2019
    Dataset provided by
    United States
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Description

    Interactive online tool for creating and manipulating tables based on birth and perinatal (fetal and infant death) data files. Tabulated data can be graphed or mapped within VitalStats or exported to Excel for further analysis.

  • g

    Population aged 25 to 59 years who had some relationship with their father...

    • gimi9.com
    + more versions
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    Population aged 25 to 59 years who had some relationship with their father or did not maintain it because they were deceased according to the father's level of education when he was a teenager and level of education. Canary Islands. 2018 | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_114f06b846f6227d28612531f1ecabefd61c1af8
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    Area covered
    Canary Islands
    Description

    This table provides data from 2018 on the estimated population aged 25 to 59 years who had some relationship with their father or did not maintain it because they were deceased in the Canary Islands by level of education of the father when he was a teenager and level of education.

  • S

    Social Media Addiction Statistics

    • searchlogistics.com
    Updated Apr 1, 2025
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    Search Logistics (2025). Social Media Addiction Statistics [Dataset]. https://www.searchlogistics.com/learn/statistics/social-media-addiction-statistics/
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    Dataset updated
    Apr 1, 2025
    Dataset authored and provided by
    Search Logistics
    License

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

    Description

    In this post, I'll give you all the social media addiction statistics you need to be aware of to moderate your social media use.

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    Statista (2024). Leading causes of death among teenagers aged 15-19 years in the United States 2020-22 [Dataset]. https://www.statista.com/statistics/1017959/distribution-of-the-10-leading-causes-of-death-among-teenagers/
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    Leading causes of death among teenagers aged 15-19 years in the United States 2020-22

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    3 scholarly articles cite this dataset (View in Google Scholar)
    Dataset updated
    Dec 13, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of 2022, the third leading cause of death among teenagers aged 15 to 19 years in the United States was intentional self-harm or suicide, contributing around 17 percent of deaths among age group. The leading cause of death at that time was unintentional injuries, contributing to around 37.4 percent of deaths, while 21.8 percent of all deaths in this age group were due to assault or homicide. Cancer and heart disease, the overall leading causes of death in the United States, are also among the leading causes of death among U.S. teenagers. Adolescent suicide in the United States In 2021, around 22 percent of students in grades 9 to 12 reported that they had seriously considered attempting suicide in the past year. Female students were around twice as likely to report seriously considering suicide compared to male students. In 2022, Montana had the highest rate of suicides among U.S. teenagers with around 39 deaths per 100,000 teenagers, followed by South Dakota with a rate of 33 per 100,000. The states with the lowest death rates among adolescents are New York and New Jersey. Mental health treatment Suicidal thoughts are a clear symptom of mental health issues. Mental health issues are not rare among children and adolescents, and treatment for such issues has become increasingly accepted and accessible. In 2021, around 15 percent of boys and girls aged 5 to 17 years had received some form of mental health treatment in the past year. At that time, around 35 percent of youths aged 12 to 17 years in the United States who were receiving specialty mental health services were doing so because they had thought about killing themselves or had already tried to kill themselves.

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