According to a 2023 survey conducted in the United States, teenagers spent an average of 4.8 hours every day on social media platforms. Girls spent 5.3 hours on social networks daily, compared to 4.4 hours for boys. YouTube and TikTok were the most popular online networks among those aged 13 to 19, with 1.9 and 1.5 hours of average daily engagement, respectively. The most used platform for girls was TikTok, while the most used platform for boys was YouTube. Are teens constantly connected to social media? YouTube, TikTok, Instagram and Snapchat are the most attractive and time-consuming platforms for young internet users. A survey conducted in the U.S. in 2023 found that 62 percent of teenagers were almost constantly connected to Instagram, and 17 percent were almost constantly connected to TikTok. Overall, 71 percent of teens used YouTube daily, and 47 percent used Snapchat daily. Furthermore, YouTube had a 93 percent reach among American teens in 2023, down from 95 percent in 2022. Teens and their internet devices For younger generations especially, social media is mostly accessed via mobile devices, and almost all teenagers in the United States have smartphone access. A 2023 survey conducted in the U.S. found that 92 percent of teens aged 13 to 14 years had access to a smartphone at home, as well as 97 percent of those aged 15 to 17. Additionally, U.S. girls were slightly more likely than their male counterparts to have access to a smartphone.

In 2024, children in the United Kingdom spent an average of *** minutes per day on TikTok. This was followed by Instagram, as children in the UK reported using the app for an average of ** minutes daily. Children in the UK aged between four and 18 years also used Facebook for ** minutes a day on average in the measured period. Mobile ownership and usage among UK children In 2021, around ** percent of kids aged between eight and 11 years in the UK owned a smartphone, while children aged between five and seven having access to their own device were approximately ** percent. Mobile phones were also the second most popular devices used to access the web by children aged between eight and 11 years, as tablet computers were still the most popular option for users aged between three and 11 years. Children were not immune to the popularity acquired by short video format content in 2020 and 2021, spending an average of ** minutes per day engaging with TikTok, as well as over ** minutes on the YouTube app in 2021. Children data protection In 2021, ** percent of U.S. parents and ** percent of UK parents reported being slightly concerned with their children’s device usage habits. While the share of parents reporting to be very or extremely concerned was considerably smaller, children are considered among the most vulnerable digital audiences and need additional attention when it comes to data and privacy protection. According to a study conducted during the first quarter of 2022, ** percent of children’s apps hosted in the Google Play Store and ** percent of apps hosted in the Apple App Store transmitted users’ locations to advertisers. Additionally, ** percent of kids’ apps were found to collect persistent identifiers, such as users’ IP addresses, which could potentially lead to Children’s Online Privacy Protection Act (COPPA) violations in the United States. In the United Kingdom, companies have to take into account several obligations when considering online environments for children, including an age-appropriate design and avoiding sharing children’s data.

This dataset was originally collected for a data science and machine learning project that aimed at investigating the potential correlation between the amount of time an individual spends on social media and the impact it has on their mental health.

The project involves conducting a survey to collect data, organizing the data, and using machine learning techniques to create a predictive model that can determine whether a person should seek professional help based on their answers to the survey questions.

This project was completed as part of a Statistics course at a university, and the team is currently in the process of writing a report and completing a paper that summarizes and discusses the findings in relation to other research on the topic.

The following is the Google Colab link to the project, done on Jupyter Notebook -

https://colab.research.google.com/drive/1p7P6lL1QUw1TtyUD1odNR4M6TVJK7IYN

The following is the GitHub Repository of the project -

https://github.com/daerkns/social-media-and-mental-health

Libraries used for the Project -

Pandas
Numpy
Matplotlib
Seaborn
Sci-kit Learn

As of February 2025, the average daily social media usage of internet users worldwide amounted to 141 minutes per day, down from 143 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of 3 hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just 2 hours and 16 minutes. Global social media usage Currently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively. People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events and friends. Global impact of social media Social media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general. During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased polarization in politics, and heightened everyday distractions.

This data set belongs to:Beyens, I., Pouwels, J. L., van Driel, I. I., Keijsers, L., & Valkenburg, P. M. (2020). The effect of social media on well-being differs from adolescent to adolescent. Scientific Reports. doi:10.1038/s41598-020-67727-7The design, sampling and analysis plan of the study are available on the Open Science Framework (OSF) at https://osf.io/nhks2.For more information, please contact the authors at i.beyens@uva.nl or info@project-awesome.nl.

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.

This database is comprised of 951 participants who provided self-report data online in their school classrooms. The data was collected in 2016 and 2017. The dataset is comprised of 509 males (54%) and 442 females (46%). Their ages ranged from 12 to 16 years (M = 13.69, SD = 0.72). Seven participants did not report their age. The majority were born in Australia (N = 849, 89%). The next most common countries of birth were China (N = 24, 2.5%), the UK (N = 23, 2.4%), and the USA (N = 9, 0.9%). Data were drawn from students at five Australian independent secondary schools. The data contains item responses for the Spence Children’s Anxiety Scale (SCAS; Spence, 1998) which is comprised of 44 items. The Social media question asked about frequency of use with the question “How often do you use social media?”. The response options ranged from constantly to once a week or less. Items measuring Fear of Missing Out were included and incorporated the following five questions based on the APS Stress and Wellbeing in Australia Survey (APS, 2015). These were “When I have a good time it is important for me to share the details online; I am afraid that I will miss out on something if I don’t stay connected to my online social networks; I feel worried and uncomfortable when I can’t access my social media accounts; I find it difficult to relax or sleep after spending time on social networking sites; I feel my brain burnout with the constant connectivity of social media. Internal consistency for this measure was α = .81. Self compassion was measured using the 12-item short-form of the Self-Compassion Scale (SCS-SF; Raes et al., 2011). The data set has the option of downloading an excel file (composed of two worksheet tabs) or CSV files 1) Data and 2) Variable labels. References: Australian Psychological Society. (2015). Stress and wellbeing in Australia survey. https://www.headsup.org.au/docs/default-source/default-document-library/stress-and-wellbeing-in-australia-report.pdf?sfvrsn=7f08274d_4 Raes, F., Pommier, E., Neff, K. D., & Van Gucht, D. (2011). Construction and factorial validation of a short form of the self-compassion scale. Clinical Psychology and Psychotherapy, 18(3), 250-255. https://doi.org/10.1002/cpp.702 Spence, S. H. (1998). A measure of anxiety symptoms among children. Behaviour Research and Therapy, 36(5), 545-566. https://doi.org/10.1016/S0005-7967(98)00034-5

Introduction: Social media has become an integrated part of daily life, with an estimated 3 billion social media users worldwide. Adolescents and young adults are the most active users of social media. Research on social media has grown rapidly, with the potential association of social media use and mental health and well-being becoming a polarized and much-studied subject. The current body of knowledge on this theme is complex and difficult-to-follow. The current paper presents a scoping review of the published literature in the research field of social media use and its association with mental health and well-being among adolescents.Methods and Analysis: First, relevant databases were searched for eligible studies with a vast range of relevant search terms for social media use and mental health and well-being over the past five years. Identified studies were screened thoroughly and included or excluded based on prior established criteria. Data from the included studies were extracted and summarized according to the previously published study protocol.Results: Among the 79 studies that met our inclusion criteria, the vast majority (94%) were quantitative, with a cross-sectional design (57%) being the most common study design. Several studies focused on different aspects of mental health, with depression (29%) being the most studied aspect. Almost half of the included studies focused on use of non-specified social network sites (43%). Of specified social media, Facebook (39%) was the most studied social network site. The most used approach to measuring social media use was frequency and duration (56%). Participants of both genders were included in most studies (92%) but seldom examined as an explanatory variable. 77% of the included studies had social media use as the independent variable.Conclusion: The findings from the current scoping review revealed that about 3/4 of the included studies focused on social media and some aspect of pathology. Focus on the potential association between social media use and positive outcomes seems to be rarer in the current literature. Amongst the included studies, few separated between different forms of (inter)actions on social media, which are likely to be differentially associated with mental health and well-being outcomes.

How much time do people spend on social media?

              As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in
              the U.S. was just two hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively.
              People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general.
              During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.

The four datasets 'phone', 'game', 'social', and 'video' are the processed datasets that are used as input files for the Mplus models (but then in .csv instead of .dat format). The dataset 'phone' contains all data related to the main analyses of daytime, pre-bedtime and post-bedtime smartphone use. The datasets 'game', 'social', and 'video' represent the data related to the exploratory analyses for game app, social media app, and video player app use, respectively. The dataset 'timeframes' contains information about respondents' bedtime and wake-up time, which is required to calculate the three timeframes (daytime, pre-bedtime, and post-bedtime).------------------The materials used, including the R and Mplus syntaxes (https://osf.io/tpj98/) and the preregistration of the current study (https://osf.io/kxw2h/) can be found on OSF. For more information, please contact the authors via t.siebers@uva.nl or info@project-awesome.nl.

This dataset is designed to analyze mental health patterns in teenagers, focusing on stress levels using anonymized data from social media activity, surveys, and wearable devices. It consists of 5000 entries and 11 columns, each capturing different aspects of the user's daily behavior and well-being. The goal is to detect correlations between factors like social media usage, physical activity, sleep patterns, and stress levels. This dataset can be useful for research on adolescent mental health, early stress detection, and preventive care.

As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.

              Teens and social media

              As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
              Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.

This data set belongs to:Beyens, I., Pouwels, J. L., van Driel, I. I., Keijsers, L., & Valkenburg, P. M. (2024). Social media use and adolescents' well-being: Developing a typology of person-specific effect patterns. Communication Research, 51(6), 691-716. https://doi.org/10.1177/00936502211038196More information about the study is available on the Open Science Framework (OSF), including the preregistration of the design and sampling plan (https://osf.io/327cx), the preregistration of the hypotheses and analysis plan (https://osf.io/692h7), and all syntax files (https://osf.io/nf32w).For more information, please contact the authors at i.beyens@uva.nl or info@project-awesome.nl.

We surveyed 1,257 12- to 18-year-old adolescents attending 52 schools in urban or suburban areas of Argentina. We recorded the daily exposure to various screen-based activities, including video- and online-gaming, social media, TV or streaming. Screen time and device type in the hour before bedtime, sleep patterns during weekdays and weekends, somnolence (Pediatric Daytime Sleepiness Scale score), and grades in language and mathematics were also assessed.

The codebook, preregistration, and syntaxes can be found on the Open Science Framework (OSF) at https://osf.io/fzp7d/. For more information, please contact the authors via t.siebers@uva.nl or info@project-awesome.nl.

This data set belongs to:Valkenburg, P. M., Beyens, I., Pouwels, J. L., van Driel, I. I., & Keijsers, L. (2021).Social media browsing and adolescent well-being: Challenging the “Passive Social Media Use Hypothesis” Journal of Computer-Mediated Communication https://doi.org/10.1093/jcmc/zmab015The preregistration of the design and sampling plan of the study (https://osf.io/327cx) and the preregistration of the hypotheses and analysis plan (https://osf.io/eahrx/) are available on the Open Science Framework (OSF).For more information, please contact the authors at p.m.valkenburg@uva.nl or info@project-awesome.nl.

This data is on what and how undergraduate students of Covenant University, Nigeria use the social media. A survey was carried out among 2,798 undergraduate students. A close ended questionnaire was the instrument for data collection. These data indicate that they mainly use the social media for personal communication, information search, entertainment, academic as well as non-academic purposes. They use the social media for private messaging, socialization and sharing of ideas with their families, friends, colleagues and lecturers. These respondents are of the opinion that the paramount benefit they have derived from using the social media is freedom of expression as the social media provide the platforms for them to do so. The respondents spend at least an hour or two every day using the social media.

This survey charted the gambling, social media usage and subjective well-being of young people aged 15-25 years in the United States. The study was conducted as part of the "Problem Gambling and Social Media: Social Psychological Study on Youth Behaviour in Online Gaming Communities" research project. The aim of the project was to analyse how young social media users evaluate, adopt and share gambling-related online content and how online group processes affect their gambling and gambling-related attitudes. FSD's holdings also include two other datasets that were collected using a nearly identical questionnaire (FSD3399 and FSD3400). Data for the research project have been collected in Finland, the United States, Spain, and South Korea. First, the respondents were asked which social media services they used (e.g. Facebook, YouTube, Instagram, discussion forums, online casinos) and how often. Topics that the respondents discussed on gambling-related social media were charted more closely, and they were asked, for example, whether the discussion usually related to instructions or tips on gambling or to problem gambling and recovering from problem gambling. Some questions on the respondents' social media activity were also presented, for instance, how often they saw gambling-related advertising online, how often they changed their most important social media passwords, and how often they uploaded pictures of themselves on social media. The respondents were asked whether they had ever been harassed online or had been the victim of a crime on the Internet in the past three years (e.g. defamation, identity theft, fraud, sexual harassment). The respondents' identity bubbles on social media were surveyed by using the IBR scale (Identity Bubble Reinforcement Scale). The respondents were asked, for instance, whether they thought they could be themselves on social media and whether they only interacted with people similar to them on social media. Additionally, the CIUS scale (Compulsive Internet Use) was used to examine problems related to Internet use. Questions focused on, for example, whether the respondents found it difficult to stop using the Internet when they were online, whether people close to them said they should use the Internet less, and whether they felt restless, frustrated or irritated when they couldn't use the Internet. In the next section of the questionnaire, the respondents were randomly assigned to two groups for a vignette experiment. Respondents in the test group were told they belong to Group C because they had answered the earlier questions in a similar manner to others in the group. Those in the control group were given no information on the group. The respondents were presented with different gambling-related social media scenarios, and they were asked to evaluate the contents of the gambling-related messages by "liking" or "disliking" the message or by not reacting to it at all. Each respondent was shown four different gambling messages with different contents. Three factors were manipulated in the scenarios (2x2x2 design): expressed stance of the message on gambling (positive or negative), narrative perspective of the message (experience-driven first-person narration or fact-driven third-person narration) and majority opinion of other respondents on the message (positively or negatively biased distribution of likes or dislikes). For Group C, the majority opinion was seemingly provided by other Group C members, whereas for the control group the majority opinion was seemingly provided by other respondents. Additionally, the respondents' attitudes towards the message were surveyed with statements regarding, for instance, how likely they would find the message interesting or share it on social media. Next, the respondents' attitudes towards gambling were charted by using the ATGS scale (Attitudes Towards Gambling Scale). They were asked, for example, whether people should have the right to gamble whenever they want, whether most people who gamble do so sensibly and whether it would be better if gambling was banned altogether. The respondents' gambling habits were examined by using the SOGS scale (South Oaks Gambling Screen), and they were asked, for instance, which types of gambling they had done in the past 12 months (played slot machines, visited an online casino, bet on lotteries etc.), whether the people close to them had gambling problems, and whether they had borrowed money to gamble or to pay gambling debts. In addition, the respondents' alcohol consumption was surveyed with a few questions from the AUDITC scale (The Alcohol Use Disorders Identification Test), and they were asked whether they had used various drugs for recreational purposes (e.g. cannabis, LSD, amphetamine, opioids) and which online resources they had used to purchases these drugs (e.g. Facebook, Instagram, Craigslist). The respondents' subjective well-being and social relationships were examined next. The respondents were asked how happy they were in general and how satisfied they were with their economic situation and life in general. They were also asked how well the single statement "I have high self-esteem" from the SISE scale (Single-item Self-esteem Scale) described them. The three statements on lacking companionship, feeling left out and feeling isolated from the LONE scale (Three-item Loneliness Scale) were also included in the survey. Feelings of belonging to different groups or communities (e.g. family, friends, neighbourhood, parish/religious community) were charted, and the 12-item GHQ scale (General Health Questionnaire) was used to survey the respondents' recent mental health. Questions included, for example, whether the respondents had been able to concentrate on what they were doing, had felt they couldn't overcome their difficulties, and had been losing confidence in themselves. Finally, the respondents' sense of control over the events in their lives was examined with the MASTERY scale (Sense of Mastery Scale), with questions focusing on, for instance, whether they thought they had little control over the things that happen to them and whether they often felt helpless in dealing with the problems of life. The respondents' impulsivity was surveyed by using the EIS scale (Eysenck Impulsivity Scale) and their willingness to delay gratification was surveyed with the GRATIF scale (Delay of Gratification). Background variables included the respondent's gender, age, country of birth (own and parents') level of education, type of municipality of residence, household composition, disposable income, possible financial problems, and economic activity and occupational status.

BackgroundSeveral large-scale studies and reviews have reported both negative and positive associations of social media use with well-being, suggesting that the findings are more complex and need more nuanced study. Moreover, there is little or no exploration of how social media use in adolescence influences flourishing, a more all-encompassing construct beyond well-being, including six sub-domains (i.e., happiness, meaning and purpose, physical and mental health, character, close social relationships, and financial stability). This paper aims to fill this gap by understanding how adolescents might flourish through social media activities by fulfilling the basic needs pointed out by the Self-Determination Theory, i.e., relatedness, autonomy, and competence.MethodsThe study is drawn on cross-sectional data collected from 1,429 Swiss adolescents (58.8% females, Mage = 15.84, SDage = 0.83) as part of the HappyB project in Spring 2022. Self-reported measures included the Harvard Adolescent Flourishing scale, positive and negative online social experiences, self-disclosure on social media, and social media inspiration. Control variables included, among others, self-esteem, ill-being, and personality.ResultsAfter applying Bonferroni’s correction, results of the hierarchical regression analyses showed that positive social media experiences (β = 0.112, p < 0.001) and social media inspirations from others (β = 0.072, p < 0.001) and for others (β = 0.060, p = 0.003) were positively associated with flourishing. Flourishing was inversely associated with negative social media experiences (β = −0.076, p < 0.001). Among covariates, self-esteem (β = 0.350, p < 0.001), ill-being (β = −0.252, p < 0.001), perceived school environment (β = 0.138, p < 0.001), self-reported level of physical activity (β =0.109, p < 0.001), and perceived socio-economic status (β = −0.059, p = 0.001) were all related to flourishing. In contrast, gender, high school year, age, perceived stress, and personality (extraversion and neuroticism) were not.ConclusionUsing a well-being framework to investigate social media use in adolescents is needed to go beyond the ill-being perspective. Our results align with the needs pointed out by the Self-Determination Theory. Carrying out social media activities in a way that promotes—rather than diminishes—flourishing should be included as an additional good habit influencing adolescents’ development. We suggest that interventions aiming to foster adolescents’ flourishing should include curricula aiming to promote a good use of social media through positive online social relationships and inspirational contents.

Participant characteristics: 13 to 20 years old students.

Number of participants: 197.

Year of the study: 2023.

Place of the study: Vanuatu.

The open anonymized dataset can also be found on https://doi.org/10.5281/zenodo.15074015" target="_blank" rel="noopener">Wattelez, G., Amon, K., Nedjar-Guerre, A., Forsyth, R., Peralta, L., Urvoy, M.-J., Caillaud, C., & Galy, O. (2025). Exploring the Digital Health Landscape: How adolescents living in urban and rural Vanuatu use online platforms to access health information (anonymized version of the dataset and supplementary tables) (2.0.0) [Data set]. Zenodo.