Percentage of smartphone users by selected smartphone use habits in a typical day.

According to a survey of parents and children in the UK conducted in 2024, ** percent of children between 16 and 17 years old owned a smartphone, while ** percent of respondents aged between ***** and **** did not have a mobile phone.

Electronic devices available to children Mobile phones are not the only devices children are exposed to daily. At home, indeed, they have access to all kinds of electronic devices, such as TVs, gaming consoles, and radios. For instance, in 2020, ** percent of children had access to a smart TV, and ** percent had a game console. Furthermore, ** percent of children in the UK had access to a PC, laptop, or netbook with an internet connection. Children’s online activities British children perform many different activities online, with mobile phones being the most used devices to go online. Among the most recurring online activities were playing games and watching videos, especially on YouTube. Furthermore, children in the UK appear to spend quite some time on social media platforms, like TikTok and Snapchat, where they spend on average ** and ** minutes daily, respectively.

The survey charted the use of mobile phones in Finnish families and among children in particular. The archived material consists of family interviews conducted in 1997. Topics included the role of mobile communication in families and children's mobile phone use. The dataset consists of 31 interviews. The dataset is only available in Finnish.

Quantitative and qualitative data sets for 24 sites across Ghana, Malawi and South Africa:
a) SPSS dataset on young people’s use of mobile phones in Ghana, Malawi and South Africa.  4626 cases (young people aged 7-25 years): 1568 Ghana; 1544 Malawi; 1514 South Africa.  719 variables (+ 11 ‘navigation facilitators’) b) 1,620 Qualitative transcripts from interviews with people of diverse ages, 8y upwards: individual interviews [using either i.theme checklist or ii call register checklist]; focus group interviews [not all sites]: 50-80 transcripts for most sites.

This research project, which commenced in August 2012, explored how the rapid expansion of mobile phone usage is impacting on young lives in sub-Saharan Africa. It builds directly on our previous research on children’s mobility within which baseline quantitative data and preliminary qualitative information was collected on mobile phone usage (2006-2010) across 24 research sites, as an adjunct to our wider study of children’s physical mobility and access to services.

In this study our focus is specifically on mobile phones and we cover a much wider range of phone-related issues, including changes in gendered and age patterns of phone use over time; phone use in building social networks (for instance to support job search); impacts on education, livelihoods, health status, safety and surveillance, physical mobility and possible connections to migration, youth identity, and questions of exploitation and empowerment associated with mobile phones.

Mixed-method, participatory youth-centred studies have been conducted in the same 24 sites as in our earlier work across Ghana, Malawi and South Africa (urban, peri-urban, rural, remote rural, in two agro-ecological zones per country). We have built on the baseline data for 9-18 year-olds gathered in 2006-2010, through repeat and extended studies, but also included additional studies with 19-25 year-olds (to capture changing usage and its impacts as our initial cohort move into their 20s).

The number of smartphone users in the Philippines was forecast to increase between 2024 and 2029 by in total 5.6 million users (+7.29 percent). This overall increase does not happen continuously, notably not in 2026, 2027, 2028 and 2029. The smartphone user base is estimated to amount to 82.33 million users in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

This dataset has been artificially generated to mimic real-world user interactions within a mobile application. It contains 100,000 rows of data, each row of which represents a single event or action performed by a synthetic user. The dataset was designed to capture many of the attributes commonly tracked by app analytics platforms, such as device details, network information, user demographics, session data, and event-level interactions.

Key Features Included

User & Session Metadata

User ID: A unique integer identifier for each synthetic user. Session ID: Randomly generated session identifiers (e.g., S-123456), capturing the concept of user sessions. IP Address: Fake IP addresses generated via Faker to simulate different network origins. Timestamp: Randomized timestamps (within the last 30 days) indicating when each interaction occurred. Session Duration: An approximate measure (in seconds) of how long a user remained active. Device & Technical Details

Device OS & OS Version: Simulated operating systems (Android/iOS) with plausible version numbers. Device Model: Common phone models (e.g., “Samsung Galaxy S22,” “iPhone 14 Pro,” etc.). Screen Resolution: Typical screen resolutions found in smartphones (e.g., “1080x1920”). Network Type: Indicates whether the user was on Wi-Fi, 5G, 4G, or 3G. Location & Locale

Location Country & City: Random global locations generated using Faker. App Language: Represents the user’s app language setting (e.g., “en,” “es,” “fr,” etc.). User Properties

Battery Level: The phone’s battery level as a percentage (0–100). Memory Usage (MB): Approximate memory consumption at the time of the event. Subscription Status: Boolean flag indicating if the user is subscribed to a premium service. User Age: Random integer ranging from teenagers to seniors (13–80). Phone Number: Fake phone numbers generated via Faker. Push Enabled: Boolean flag indicating if the user has push notifications turned on. Event-Level Interactions

Event Type: The action taken by the user (e.g., “click,” “view,” “scroll,” “like,” “share,” etc.). Event Target: The UI element or screen component interacted with (e.g., “home_page_banner,” “search_bar,” “notification_popup”). Event Value: A numeric field indicating additional context for the event (e.g., intensity, count, rating). App Version: Simulated version identifier for the mobile application (e.g., “4.2.8”). Data Quality & “Noise” To better approximate real-world data, 1% of all fields have been intentionally “corrupted” or altered:

Typos and Misspellings: Random single-character edits, e.g., “Andro1d” instead of “Android.” Missing Values: Some cells might be blank (None) to reflect dropped or unrecorded data. Random String Injections: Occasional random alphanumeric strings inserted where they don’t belong. These intentional discrepancies can help data scientists practice data cleaning, outlier detection, and data wrangling techniques.

Usage & Applications

Data Cleaning & Preprocessing: Ideal for practicing how to handle missing values, inconsistent data, and noise in a realistic scenario. Analytics & Visualization: Demonstrate user interaction funnels, session durations, usage by device/OS, etc. Machine Learning & Modeling: Suitable for building classification or clustering models (e.g., user segmentation, event classification). Simulation for Feature Engineering: Experiment with deriving new features (e.g., session frequency, average battery drain, etc.).

Important Notes & Disclaimer

Synthetic Data: All entries (users, device info, IPs, phone numbers, etc.) are artificially generated and do not correspond to real individuals. Privacy & Compliance: Since no real personal data is present, there are no direct privacy concerns. However, always handle synthetic data ethically.

The survey charted late teens' use of mobile phones in Finland. The archived data consist of interviews conducted with late teens (aged around 16-19) between 2000 and 2002. Topics covered the use of mobile phones with friends, in everyday life and in school. The dataset comprises 38 interviews. The dataset is only available in Finnish.

Problematic mobile phone use is a growing concern among youth athletes, with potential negative impacts on their wellbeing and performance. This article presents “Get Smart About Smartphones,” a group workshop intervention designed to address such behaviours. Grounded in the Theory of Planned Behaviour, the workshop targets athletes’ attitudes, subjective norms, and perceived behavioural control through fun, interactive activities tailored to their sporting context. The structure, content, and delivery of the intervention are described in detail. Practical recommendations are offered for sport psychologists, coaches, schools, and parents interested in implementing this programme with youth athletes to support healthier phone habits.

A randomized, behavioral trial examining whether HIV-infected youth ages 15 to 24 receiving cell phone support with study funded phone plans demonstrated improved ART adherence and viral control during the 24 week intervention and 24 week post-intervention periods, compared to controls. Participants were randomized to either the intervention or control group. Intervention group participants received Monday through Friday cell phone support from an Adherence Facilitator, including reminders, assessment of barriers to adherence, problem solving and referrals to services. Control group participants completed all on-study evaluations, except intervention exit interviews.

YouTube, Instagram and Snapchat are the most popular online platforms among teens. Fully 95% of teens have access to a smartphone, and 45% say they are online 'almost constantly

this dataset has all you need to know about apps that are more popular among teens

This video series provides three scenarios that highlight best practices to help inform those working to administer the National Youth in Transition Database (NYTD) survey. Providing young people with a variety of ways to take the survey may help a state increase the survey completion rate. Different states may have different practices, so it is important to research how your state administers the NYTD survey to stay in compliance with your state’s practices. Scenario 2 demonstrates administering the NYTD survey over the telephone. Metadata-only record linking to the original dataset. Open original dataset below.

The survey charted young boys' use of mobile phones in Finland. The archived data consist of interviews conducted with young boys (aged around 14-16) in 1999. Topics covered the use of mobile phones with friends, in everyday life and in school. The dataset comprises 36 interviews. The dataset is only available in Finnish.

This project investigated the experiences of New York City youth ages 16-24 who were at high risk for gun violence (e.g., carried a gun, been shot or shot at). Youth participants were recruited from three neighborhoods with historically high rates of gun violence when compared to the city as a whole--Brownsville (Brooklyn), Morrisania (Bronx), and East Harlem (Manhattan). This study explores the complex confluence of individual, situational, and environmental factors that influence youth gun acquisition and use. This study is part of a broader effort to build an evidence-based foundation for individual and community interventions, and policies that will more effectively support these young people and prevent youth gun violence. Through interviews with 330 youth, this study seeks to answer these questions: What are the reasons young people carry guns? How do young people talk about having and using guns? What are young people's social networks like, and what roles do guns play in thesenetworks? Interviews covered the following topics: neighborhood perceptions; perceptions of and experiences with the police, gangs, guns, and violence; substance use; criminal history; and demographics: race, gender, age, legal status, relationship status, living situation, location, number of children, drug use, and education.

This statistic shows the results of a survey on the share of teenagers who owned an internet enabled mobile phone or a mobile internet data flatrate in Germany in 2014. The survey found that 73 percent of adolescent mobile phone and smartphone owners stated to have a data flatrate for their device.

ABSTRACT The relationship of adolescents with time, how they conceptualize it and use it, has been the focus of numerous studies. The impact of information and communication technologies, diving in the virtual world and the access to the new world offered by the internet have affected this relationship. This is the main purpose of this article: watch this question in the light of the results of a survey of 481 adolescents from Rio de Janeiro. We started showing some teenage concepts and highlighting approaches on the relationship with time in this period of life. Then, we show the conceptual approaches of time on the internet made by authors such as Lèvy, Jenkins and Prensky. In the survey questionnaire one of the requirements was to agree or disagree, justifying the answer, with the statement “The internet really occupies my time.” Most teenagers of the sample agreed with the statement, with reasons related to escaping from reality, the isolation of social life and cognitive effects such as decreased reading and the unreliability of the internet as a research source. Adolescents of this “touch generation” always on the cell phone, connected to the internet, who have evolved in the use of digital technologies of interaction for integration, measure time in a new way. It is the responsibility of education knowing how to deal with this teens and it is the responsibility of institutions that train teachers to prepare them for this fascinating challenge of educating them.

The survey charted young girls' use of mobile phones in Finland. The archived data consist of interviews conducted with young girls (aged around 13-16) in 1999. Topics covered the use of mobile phones with friends, in everyday life and in school. The dataset comprises 28 interviews. The dataset is only available in Finnish.

ObjectivesObesity is an increasing public health problem affecting young people. The causes of obesity are multi-factorial among Chinese youth including lack of physical activity and poor eating habits. The use of an internet curriculum and cell phone reminders and texting may be an innovative means of increasing follow up and compliance with obese teens. The objectives of this study were to determine the feasibility of using an adapted internet curriculum and existing nutritional program along with cell phone follow up for obese Chinese teens.Design and MethodsThis was a randomized controlled study involving obese teens receiving care at a paediatric obesity clinic of a tertiary care hospital in Hong Kong. Forty-eight subjects aged 12 to 18 years were randomized into three groups. The control group received usual care visits with a physician in the obesity clinic every three months. The first intervention (IT) group received usual care visits every three months plus a 12-week internet-based curriculum with cell phone calls/texts reminders. The second intervention group received usual care visits every three months plus four nutritional counselling sessions.ResultsThe use of the internet-based curriculum was shown to be feasible as evidenced by the high recruitment rate, internet log-in rate, compliance with completing the curriculum and responses to phone reminders. No significant differences in weight were found between IT, sLMP and control groups.ConclusionAn internet-based curriculum with cell phone reminders as a supplement to usual care of obesity is feasible. Further study is required to determine whether an internet plus text intervention can be both an effective and a cost-effective adjunct to changing weight in obese youth.Trial RegistrationChinese Clinical Trial Registry ChiCTR-TRC-12002624

The survey charted the use of mobile phones in Finnish families and among children in particular. The archived data consist of family interviews conducted in 2000 and 2001. Topics included the role of mobile communication in families and children's mobile phone use. The dataset comprises 33 interviews. The dataset is only available in Finnish.

Temporal trends of smartphone use in South Korean adolescent in youth risk behavior survey.

IntroductionRising rates of adolescent overdose deaths attributed to counterfeit prescription drugs purchased using social media have drawn national attention to how these platforms might influence substance use. Research suggests a significant relationship exists between exposure to substance-related social media content and use of drugs and alcohol, but most studies are cross-sectional and limited by recall bias. This study used an ecological momentary assessment (EMA) protocol to collect longitudinal data on social media use and online drug-related exposures associated with youth substance use.MethodsParticipants, aged 12–23, receiving mental health treatment from a U.S. community-based hospital, joined a six-week, smartphone-based EMA protocol. Each day, participants completed a modified CRAFFT screen for daily substance use and a survey on substance-related online content exposure, and input data from their smartphone screen time reports. Analyses employed mixed effects logistic regression models to explore relationships between substance-related online exposures, substance and social media use.ResultsData was obtained from 25 youth, predominantly white non-Hispanic/Latinx (56.0%) and female (64.0%). Participants had significantly higher odds of substance use on days when exposed to substance-related digital content posted by peers (OR: 19.6). They were also more likely to report these exposures (OR: 7.7) and use substances (OR: 29.6) on days when Snapchat was one of their most frequently used smartphone applications.DiscussionOur results support existing concerns about specific social media platforms being potential mediators of youth substance use. Future EMA studies in larger cohorts should explore the role of social media platforms in substance procurement.