Introduction

Social Media Mental Health Statistics: Social media has many uses, but it often causes the most harm to younger users. Teens face significant mental health issues due to social media, and the COVID-19 pandemic made things worse by increasing screen time and social media use. This created more opportunities for teens to encounter online problems, worsening the situation.

Teens also use social media to find communities and interest groups, watch live streams, and support good causes. It’s important to US teens that they feel welcome and safe online. Despite some problems, social media offers many chances for connection and entertainment. We shall shed more light on the Social Media Mental Health Statistics through this article.

In a survey conducted in 2023, 32 percent of social media users followed therapists and mental health professionals for mental health content. One quarter of respondents said that they followed people on social media if they had the same condition as they did. Furthermore, 20 percent of social network users followed mental health advocates and brands for mental health content.

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

A novel large dataset of social media posts from users with one or multiple mental health conditions along with matched control users.

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.

According to a survey conducted in the United States in March 2024, 35 percent of adults reported that they had taken an extended break from social media because it was harming their mental health. Overall, 51 percent of respondents had never taken an extended break from social networks for mental health reasons.

The Impact of Social Media on Mental Health: A Comprehensive Literature Review Research Hypothesis

Our research hypothesis is that excessive social media use is associated with negative mental health outcomes, particularly depression, anxiety, and sleep disturbances. This hypothesis is based on the growing body of literature suggesting a link between social media use and mental health issues, particularly among adolescents and young adults. Data and Findings

This comprehensive literature review synthesized findings from numerous studies investigating the relationship between social media use and mental health. The data was gathered through a systematic search of major databases, including PubMed, PsycINFO, Scopus, and Web of Science. The search strategy employed a combination of keywords and Boolean operators to identify relevant studies, focusing on research published within the past 10 years.

The review revealed a complex and multifaceted relationship between social media use and mental health. While some studies suggested a positive association, the majority of research indicated a negative correlation, supporting our initial hypothesis.

Notable Findings:

• Increased risk of depression and anxiety: Multiple studies found a positive correlation between excessive social media use and depressive symptoms, including feelings of sadness, hopelessness, and low self-esteem. Similarly, social media use was linked to increased levels of anxiety, potentially due to social comparison, cyberbullying, and fear of missing out (FOMO). • Sleep disturbances: Excessive social media use can disrupt sleep patterns, leading to insomnia, reduced sleep quality, and shortened sleep duration. Sleep deprivation can further exacerbate mental health issues, including depression and anxiety. • Social isolation and loneliness: While social media platforms aim to connect individuals virtually, they can paradoxically contribute to increased feelings of loneliness and social isolation. Excessive social media use can lead to a decrease in face-to-face interactions, resulting in a sense of isolation. • Cyberbullying: Social media platforms can facilitate cyberbullying, which can have severe psychological consequences, including increased anxiety, depression, and suicidal ideation. • Body image concerns: Social media platforms often present idealized and unrealistic portrayals of physical appearance, which can contribute to body image concerns and dissatisfaction.

Dataset

This dataset was created by Ansh vajpai

Released under CC0: Public Domain

Contents

This dataset is structured as a graph, where nodes represent users and edges capture their interactions, including tweets, retweets, replies, and mentions. Each node provides detailed user attributes, such as unique ID, follower and following counts, and verification status, offering insights into each user's identity, role, and influence in the mental health discourse. The edges illustrate user interactions, highlighting engagement patterns and types of content that drive responses, such as tweet impressions. This interconnected structure enables sentiment analysis and public reaction studies, allowing researchers to explore engagement trends and identify the mental health topics that resonate most with users.

The dataset consists of three files: 1. Edges Data: Contains graph data essential for social network analysis, including fields for UserID (Source), UserID (Destination), Post/Tweet ID, and Date of Relationship. This file enables analysis of user connections without including tweet content, maintaining compliance with Twitter/X’s data-sharing policies. 2. Nodes Data: Offers user-specific details relevant to network analysis, including UserID, Account Creation Date, Follower and Following counts, Verified Status, and Date Joined Twitter. This file allows researchers to examine user behavior (e.g., identifying influential users or spam-like accounts) without direct reference to tweet content. 3. Twitter/X Content Data: This file contains only the raw tweet text as a single-column dataset, without associated user identifiers or metadata. By isolating the text, we ensure alignment with anonymization standards observed in similar published datasets, safeguarding user privacy in compliance with Twitter/X's data guidelines. This content is crucial for addressing the research focus on mental health discourse in social media. (References to prior Data in Brief publications involving Twitter/X data informed the dataset's structure.)

Context

This dataset explores the relationship between digital behavior and mental well-being among 100,000 individuals. It records how much time people spend on screens, use of social media (including TikTok), and how these habits may influence their sleep, stress, and mood levels.

It includes six numerical features, all clean and ready for analysis, making it ideal for machine learning tasks like regression or classification. The data enables researchers and analysts to investigate how modern digital lifestyles may impact mental health indicators in measurable ways.

Dataset Applications

• Quantify how screen‑time, TikTok use, or multi‑platform engagement statistically relate to stress, sleep loss, and mood.
• Train regression or classification models that forecast stress level or mood score from real‑time digital‑usage metrics.
• Feed user‑specific data into recommender systems that suggest screen‑time caps or bedtime routines to improve mental health.
• Provide evidence for guidelines on youth screen‑time limits and platform moderation based on observed stress‑sleep trade‑offs.
• Serve as a teaching dataset for EDA, feature engineering, and model evaluation in data‑science or psychology curricula.
• Evaluate app interventions (e.g., screen‑time nudges) by comparing predicted versus actual post‑intervention stress or mood shifts.
• Cluster individuals into digital‑behavior personas (e.g., “heavy late‑night scrollers”) to tailor mental‑health resources.
• Generate synthetic time‑series scenarios (what‑if reductions in TikTok hours) to estimate downstream impacts on sleep and stress.
• Use engineered features (ratio of TikTok hours to total screen‑time, etc.) in broader wellbeing models that include diet or exercise data.
• Assess whether mental‑health prediction models remain accurate and unbiased across different screen‑time or platform‑use segments. # Column Descriptions
• screen_time_hours – Daily total screen usage in hours across all devices.
• social_media_platforms_used – Number of different social media platforms used per day.
• hours_on_TikTok – Time spent on TikTok daily, in hours.
• sleep_hours – Average number of sleep hours per night.
• stress_level – Stress intensity reported on a scale from 1 (low) to 10 (high).
• mood_score – Self-rated mood on a scale from 2 (poor) to 10 (excell # Inspiration This dataset was inspired by growing concerns about how screen time and social media affect mental health. It enables analysis of the links between digital habits, stress, sleep, and mood—encouraging data-driven solutions for healthier online behavior and emotional well-being. # Ethically Mined Data: This dataset has been ethically mined and synthetically generated without collecting any personally identifiable information. All values are artificial but statistically realistic, allowing safe use in academic, research, and public health projects while fully respecting user privacy and data ethics.

According to a survey conducted in England in 2021, **** percent of young people with a likelihood of probable mental disorder agreed to the statement that the number of likes, comments or shares they get on social media has an impact on their mood. While **** percent of respondents with probable mental disorder agreed that they spent more time on social media then they meant to.

Dehydrated tweets about COVID-19 in Spanish and English languages. Reddit Mental Health dataset extracted of subreddits as r\mentalhealth, r\anxiety or r\depression

The state of Colorado currently lacks research that looks at the impact of various life stressors on individuals’ emotional well-being, specifically mental disorders, physical health conditions, social media usage, and employment status. This influences the ability of policies to combat the current rising mental health crisis and maximize people’s emotional well-being, making it crucial to gain a better understanding of these factors. The need for this research has been further exacerbated with the rise of the pandemic, as social media usage, changes in employment, and mental and physical health are more volatile than normal. This research study had 55 participants through the use of an anonymous survey sent to residents of Colorado ages 18 and older to analyze and visualize how emotional well-being is affected by these four life stressors. Conducting linear regressions, correlation tests, and plotting our results showed that employment status was the most statistically significant factor in an individual’s emotional well-being, followed by the prevalence of mental disorders. In turn, we recommend that policymakers and other stakeholders in Colorado actively work to combat the negative effects of volatile employment and mental disorders, which will ultimately better the emotional well-being of their citizens.

Explore the psychological impact of social media's 'perfect life' ideal. This research uncovers how online pressure affects well-being, particularly for Gen Z.

According to a survey conducted in the United States in February 2023, 47 percent of Millennials who were using social media said that it had a very or somewhat positive effect on their mental health. Overall, Generation X, those born between 1965 and 1981, were most likely to say that social media had a very or somewhat negative impact on their mental health, with 41 percent feeling this way.

Suicide is not only an individual phenomenon, but it is also influenced by social and environmental factors. With the high suicide rate and the abundance of social media data in South Korea, we have studied the potential of this new medium for predicting completed suicide at the population level. We tested two social media variables (suicide-related and dysphoria-related weblog entries) along with classical social, economic and meteorological variables as predictors of suicide over 3 years (2008 through 2010). Both social media variables were powerfully associated with suicide frequency. The suicide variable displayed high variability and was reactive to celebrity suicide events, while the dysphoria variable showed longer secular trends, with lower variability. We interpret these as reflections of social affect and social mood, respectively. In the final multivariate model, the two social media variables, especially the dysphoria variable, displaced two classical economic predictors – consumer price index and unemployment rate. The prediction model developed with the 2-year training data set (2008 through 2009) was validated in the data for 2010 and was robust in a sensitivity analysis controlling for celebrity suicide effects. These results indicate that social media data may be of value in national suicide forecasting and prevention.

According to an online survey conducted in January 2023, 51 percent of adults in the United States felt the responsibility to protect children from social media harm fell upon parents. Overall, one in five respondents stated that the impact of social media on children's mental health was the responsibility of social media companies, and five percent said social media users were responsible for protecting kids from potential social media harm.

According to a survey conducted in March 2024 among adults from the United States, more women than men reported that they had taken an extended break from social media due to negative effects on mental health, accounting for 37 percent of female respondents, compared to 33 percent of male respondents. An equal share of men and women reported never taking a break from online networks for this reason, with 51 percent of respondents of each gender.

IH416 - Impact of social media on your mental health for those aged 18 years and over who used social media. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Impact of social media on your mental health for those aged 18 years and over who used social media...