A March 2023 survey found that over half of teens in the United States accessed the internet to listen to music, as 65 percent of respondents between 13 and 17 years stated so. A further 59 percent said they went online to use social media, while 57 percent watched videos created by other people.

This statistic shows the results of a survey on the usage of the internet for school-related activities among teenagers in Germany in 2014, by age groups. During the survey period it was found that 50 percent of respondents aged between 18 and 19 years stated that they used the internet to talk about their homework with others.

In 2024, it was found that ** percent of respondents aged between 12 and 19 years stated that they used WhatsApp every day or several times a week. Instagram and TikTok usage remained mostly the same compared to 2023.

The 1989 English Church Census (SN:2842) found there had been a drastic drop in those, aged 15-19, attending the English church in the 1980's. The aim was to discover why they had left and what, if anything, could be done about it. A key finding was the importance of having people in church who understood teenagers, their values and their language.

In order to gauge the views of a wide range of teenage church attenders the sample of church teenagers was structured by denomination, churchmanship, environment and area. The denomination and churchmanship categories were based on an analysis of current teenage church attendance from the English Church Census. Churches were sampled in three areas (the North, South and London). Within these areas churches were sampled in four environments (city centre, suburb, council estate and rural).

Teenagers who were not regular churchgoers were contacted through secondary schools. Schools which agreed to take part in the survey were clustered in geographical areas close to responding churches.

The statistics shows the ways of spending time among teenagers in Italy in 2016, by activity and age group. As of the survey period, about **** percent of the 14 years old read books in their free time, while one percent of the respondents with the same age went to the cinema.

The purpose of this study was to assess both the school-level effects and the participant-level effects of Youth Crime Watch (YCW) programs. Abt Associates conducted a four-year impact evaluation of Youth Crime Watch (YCW) programs in three Florida school districts (Broward, Hillsborough, and Pinellas Counties). School-based YCW programs implement one or more of a variety of crime prevention activities, including youth patrol, in which YCW participants patrol their school campus and report misconduct and crime. The evaluation collected both School-Level Data (Part 1) and Student-Level Data (Part 2). The School-Level Data (Part 1) contain 9 years of data on 172 schools in the Broward, Hillsborough, and Pinellas school districts, beginning in the 1997-1998 school year and continuing through the 2005-2006 school year. A total of 103 middle schools and 69 high schools were included, yielding a total of 1,548 observations. These data provide panel data on reported incidents of crime and violence, major disciplinary actions, and school climate data across schools and over time. The Student-Level Data (Part 2) were collected between 2004 and 2007 and are comprised of two major components: (1) self-reported youth attitude and school activities survey data that were administered to a sample of students in middle schools in the Broward, Hillsborough, and Pinellas School Districts as part of a participant impact analysis, and (2) self-reported youth attitude and school activities survey data that were administered to a sample of YCW continuing middle school students and YCW high school students in the same three school districts as part of a process analysis. For Part 2, a total of 3,386 completed surveys were collected by the project staff including 1,319 "new YCW" student surveys, 1,581 "non-YCW" student surveys, and 486 "Pro" or "Process" student surveys. The 138 variables in the School-Level Data (Part 1) include Youth Crime Watch (YCW) program data, measures of crime and the level of school safety in a school, and other school characteristics. The 99 variables in the Student-Level Data (Part 2) include two groups of questions for assessing participant impact: (1) how the respondents felt about themselves, and (2) whether the respondent would report certain types of problems or crimes that they observed at the school. Part 2 also includes administrative variables and demographic/background information. Other variables in Part 2 pertain to the respondent's involvement in school-based extracurricular activities, involvement in community activities, attitudes toward school, attitudes about home environment, future education plans, attitudes toward the YCW advisor, attitudes about effects of YCW, participation in YCW, reasons for joining YCW, and reasons for remaining in YCW.

Adolescence is a unique developmental period, characterized by physical and emotional growth and significant maturation of cognitive and social skills. For individuals with Autism Spectrum Disorder (ASD), it is also a vulnerable period as cognitive and social skills can deteriorate. Circumscribed interests (CIs), idiosyncratic areas of intense interest and focus, are a core symptom of ASD that may be associated with social development. Yet, relatively little is known about the expression of CIs in adolescents with ASD. Many studies investigating CIs have used images depicting items of special interest; however, it is not clear how images should be customized for adolescent studies. The goal of this study was to gain insight into the types of images that may be appropriate for studies of CIs in adolescents with ASD. To this end, we used a mixed methods design that included, 1) one-on-one interviews with 10 adolescents (4 with ASD and 6 TD), to identify categories of images that were High Autism Interest (‘HAI’) or High Typically Developing Interest (‘HTD’), and 2) an online survey taken by fifty-three adolescents with ASD (42 male) and 135 typically developing (TD) adolescents (55 male) who rated how much they liked 105 ‘HAI’ and ‘HTD’ images. Although we found a significant interaction between ‘HAI’ and ‘HTD’ categories and diagnosis, neither group significantly preferred one category over the other, and only one individual category ('Celebrities') showed a significant group effect, favored by TD adolescents. Males significantly preferred ‘HAI’ images relative to females, and TD adolescents significantly preferred images with social content relative to adolescents with ASD. Our findings suggest that studies investigating affective or neural responses to CI-related stimuli in adolescents should consider that stereotypical ASD interests (e.g. trains, gadgets) may not accurately represent individual adolescents with ASD, many of whom show interests that overlap with TD adolescents (e.g. video games).

The Basque Youth Observatory is an instrument of the Basque Government that allows to have a global and permanent vision of the situation and evolution of the youth world that allows to evaluate the impact of the actions carried out in the CAPV by the different administrations in the field of youth.The Basque Youth Observatory regularly publishes more than 100 statistical indicators that can be consulted in euskadi.eus, along with other research and reports. Statistics are provided in various formats (csv, excel).

Between 2018 and 2019, nearly ** percent of students between the ages of eight and ** surveyed in Costa Rica said they used the internet to watch video content, making it the most popular online activity among this segment of the population. Meanwhile, online shopping was the least popular web activity among children and teens in the Central American country, with less than ** percent of respondents stating to purchase over the internet.

Dataset Description:

This dataset captures the real-world online behavior of teenagers, focusing on e-safety awareness, cybersecurity risks, and device interactions. The data was collected from network activity logs and e-safety monitoring systems across various educational institutions and households in Texas and California. Spanning from January 2017 to October 2024, this dataset includes interactions with social media platforms, educational websites, and other online services, providing an in-depth look at teenage online activities in urban and suburban settings. The dataset is anonymized to protect user privacy and contains real incidents of network threats, security breaches, and cybersecurity behavior patterns observed in teenagers.

Use Cases:

Predicting e-safety awareness and online behavior patterns. Detecting malware exposure risk and cybersecurity vulnerabilities. Analyzing online habits related to social media and internet consumption. Evaluating cybersecurity behaviors like password strength, VPN usage, and phishing attempts. Features Overview:

S.No Feature Name Description 1 Device Type The type of device used during the online session (Mobile, Laptop, Tablet, Desktop, etc.) 2 Malware Detection Whether malware was detected on the device during the session (Yes/No) 3 Phishing Attempts Number of phishing attempts experienced during online activity 4 Social Media Usage Frequency of social media usage (Low, Medium, High) 5 VPN Usage Whether a VPN was used during the session (Yes/No) 6 Cyberbullying Reports Number of reported cyberbullying incidents 7 Parental Control Alerts Number of alerts triggered by parental control software 8 Firewall Logs Number of blocked or allowed network connections by the firewall 9 Login Attempts Number of login attempts during the session 10 Download Risk Risk level associated with downloaded files (Low, Medium, High) 11 Password Strength Strength of the passwords used (Weak, Moderate, Strong) 12 Data Breach Notifications Number of alerts regarding compromised personal information 13 Online Purchase Risk Risk level of online purchases made (Low, Medium, High) 14 Education Content Usage Frequency of engagement with educational content (Low, Medium, High) 15 Age Group Age category of the teenager (Under 13, 13-16, 17-19) 16 Geolocation Location of network access (US, EU, etc.) 17 Public Network Usage Whether the online activity occurred over a public network (Yes/No) 18 Network Type Type of network connection (WiFi, Cellular, etc.) 19 Hours Online Total hours spent online during the session 20 Website Visits Number of websites visited per hour during the session 21 Peer Interactions Level of peer-to-peer interactions during online activity 22 Risky Website Visits Whether visits to risky websites occurred (Yes/No) 23 Cloud Service Usage Whether cloud services were accessed during the session (Yes/No) 24 Unencrypted Traffic Whether unencrypted network traffic was accessed during the session (Yes/No) 25 Ad Clicks Whether online advertisements were clicked during the session (Yes/No) 26 Insecure Login Attempts Number of insecure login attempts made (e.g., over unencrypted networks) Potential Research and Machine Learning Applications:

Cybersecurity and anomaly detection models. Predictive modeling for e-safety awareness and risk behaviors. Time-series analysis of internet consumption and security threat trends. Behavioral clustering and pattern recognition in teenage online activity. Data Collection Method: The data was collected through collaboration with local schools and cybersecurity monitoring agencies. Real-time network monitoring systems captured interactions across different online platforms. All personally identifiable information (PII) was anonymized to ensure privacy, making the dataset ideal for public use in research and machine learning tasks.

This dataset provides a rich foundation for studying teenage online behavior patterns and developing predictive models for cybersecurity awareness and risk mitigation. Researchers and data scientists can use this data to create models that better understand online behavior, identify security risks, and design interventions to improve e-safety for teenagers.

411 adolescents born in 1978 or 1979 in two socioeconomically different cities are included in the study. Collection of the material has occurred three times for each youth, at 15, 17 and 20 years of age. 103 boys and 106 girls in Uppsala, and 90 boys and 112 girls in Trollhättan participated in the study.

In Part 1 of the longitudinal study, adolescents were examined at 15, 17 and 20.5 years of age. Lifestyle factors such as nutrition, physical activity, smoking and alcohol habits were studied to later be able to determine whether these are associated with health problems in adulthood such as cardiovascular disease, obesity, osteoporosis, diabetes and cancer. The idea is also to analyze whether differences in adolescents’ socio-economic background correlates with lifestyle factors, health and development of disease in adulthood.

Serum and in some cases whole blood from 15, 17 and 20.5 years of age are stored in Uppsala Biobank, in addition to measurement data and questionnaire responses.

There is an opportunity to continue with Part 2 of the study, since the adolescents are now more than 35 years old.

Purpose:

Prospective study of adolescent health, nutrition and physical activity and its importance for future morbidity.

Seattle Parks and Recreation Teen Life Centers locations. SPR Teen Life Centers are locations where the parks department provides a safe space for teen activities.

Financial overview and grant giving statistics of Jenkintown Youth Activities

This study examines how adolescent leisure activity networks relate to subjective well-being (SWB) using Statistics Korea’s 2019 Time Use Survey. The analysis includes 241 high-SWB and 241 low-SWB adolescents, assessing network density, inclusiveness, average distance, isolated nodes, degree centrality, and cohesion through NetMiner 4.0, with descriptive statistics processed in SPSS ver. 25.0. The results show clear differences in leisure activity networks. High-SWB adolescents engaged in more social activities and sports, while low-SWB adolescents participated in fewer, more solitary activities. High-SWB networks were diverse and well-connected, whereas low-SWB networks were more fragmented. Screen-based activities also played different roles: supporting social connections in high-SWB adolescents but reinforcing isolation in low-SWB adolescents. This study visually highlights that leisure participation varies by SWB level. The findings suggest that promoting diverse and interactive leisure activities can improve adolescent well-being, offering insights for policy and intervention programs.

This dataset presents statistical data on individuals participating in various activities within youth and sports institutions in the State of Qatar. The data is organized by activity type, age group, nationality (Qatari and Non-Qatari), and gender. Activity categories include cultural, scientific, artistic, social, environmental, technological, sports, and heritage-related fields.The dataset offers valuable insights into participation patterns across demographic segments, supporting the planning and evaluation of youth development programs. It is useful for policymakers, researchers, and organizations involved in cultural and sports programming.

Downloads of Add Health require submission of the following information, which is shared with the original producer of Add Health: supervisor name, supervisor email, and reason for download. A Data Guide for this study is available as a web page and for download. The National Longitudinal Study of Adolescent to Adult Health (Add Health), 1994-2018 [Public Use] is a longitudinal study of a nationally representative sample of U.S. adolescents in grades 7 through 12 during the 1994-1995 school year. The Add Health cohort was followed into young adulthood with four in-home interviews, the most recent conducted in 2008 when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents' social, economic, psychological, and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships. Add Health Wave I data collection took place between September 1994 and December 1995, and included both an in-school questionnaire and in-home interview. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12, and gathered information on social and demographic characteristics of adolescent respondents, education and occupation of parents, household structure, expectations for the future, self-esteem, health status, risk behaviors, friendships, and school-year extracurricular activities. All students listed on a sample school's roster were eligible for selection into the core in-home interview sample. In-home interviews included topics such as health status, health-facility utilization, nutrition, peer networks, decision-making processes, family composition and dynamics, educational aspirations and expectations, employment experience, romantic and sexual partnerships, substance use, and criminal activities. A parent, preferably the resident mother, of each adolescent respondent interviewed in Wave I was also asked to complete an interviewer-assisted questionnaire covering topics such as inheritable health conditions, marriages and marriage-like relationships, neighborhood characteristics, involvement in volunteer, civic, and school activities, health-affecting behaviors, education and employment, household income and economic assistance, parent-adolescent communication and interaction, parent's familiarity with the adolescent's friends and friends' parents. Add Health data collection recommenced for Wave II from April to August 1996, and included almost 15,000 follow-up in-home interviews with adolescents from Wave I. Interview questions were generally similar to Wave I, but also included questions about sun exposure and more detailed nutrition questions. Respondents were asked to report their height and weight during the course of the interview, and were also weighed and measured by the interviewer. From August 2001 to April 2002, Wave III data were collected through in-home interviews with 15,170 Wave I respondents (now 18 to 26 years old), as well as interviews with their partners. Respondents were administered survey questions designed to obtain information about family, relationships, sexual experiences, childbearing, and educational histories, labor force involvement, civic participation, religion and spirituality, mental health, health insurance, illness, delinquency and violence, gambling, substance abuse, and involvement with the criminal justice system. High School Transcript Release Forms were also collected at Wave III, and these data comprise the Education Data component of the Add Health study. Wave IV in-home interviews were conducted in 2008 and 2009 when the original Wave I respondents were 24 to 32 years old. Longitudinal survey data were collected on the social, economic, psychological, and health circumstances of respondents, as well as longitudinal geographic data. Survey questions were expanded on educational transitions, economic status and financial resources and strains, sleep patterns and sleep quality, eating habits and nutrition, illnesses and medications, physical activities, emotional content and quality of current or most recent romantic/cohabiting/marriage relationships, and maltreatment during childhood by caregivers. Dates and circumstances of key life events occurring in young adulthood were also recorded, including a complete marriage and cohabitation history, full

Number and percentage of youth who participated in sedentary activities, by age group and sex, for 2004 only.

The Basque Youth Observatory is an instrument of the Basque Government that allows to have a global and permanent vision of the situation and evolution of the youth world that allows to evaluate the impact of the actions carried out in the CAPV by the different administrations in the field of youth.The Basque Youth Observatory regularly publishes more than 100 statistical indicators that can be consulted in euskadi.eus, along with other research and reports. Statistics are provided in various formats (csv, excel).

This study examines how adolescent leisure activity networks relate to subjective well-being (SWB) using Statistics Korea’s 2019 Time Use Survey. The analysis includes 241 high-SWB and 241 low-SWB adolescents, assessing network density, inclusiveness, average distance, isolated nodes, degree centrality, and cohesion through NetMiner 4.0, with descriptive statistics processed in SPSS ver. 25.0. The results show clear differences in leisure activity networks. High-SWB adolescents engaged in more social activities and sports, while low-SWB adolescents participated in fewer, more solitary activities. High-SWB networks were diverse and well-connected, whereas low-SWB networks were more fragmented. Screen-based activities also played different roles: supporting social connections in high-SWB adolescents but reinforcing isolation in low-SWB adolescents. This study visually highlights that leisure participation varies by SWB level. The findings suggest that promoting diverse and interactive leisure activities can improve adolescent well-being, offering insights for policy and intervention programs.