According to a March 2024 survey conducted in the United States, 32 percent of adults reported feeling that social media had neither a positive nor negative effect on their own mental health. Only seven percent of social media users said that online platforms had a very positive effect on their mental health, while 12 percent of users said it had a very negative impact. Furthermore, 22 percent of respondents said social media had a somewhat negative effect on their mental health. Is social media addictive? A 2023 survey of individuals between 11 and 59 years old in the United States found that over 73 percent of TikTok users agreed that the platform was addictive. Furthermore, nearly 27 percent of those surveyed reported experiencing negative psychological effects related to TikTok use. Users belonging to Generation Z were the most likely to say that TikTok is addictive, yet millennials felt the negative effects of using the app more so than Gen Z. In the U.S., it is also not uncommon for social media users to take breaks from using online platforms, and as of March 2024, over a third of adults in the country had done so. Following mental health-related content Although online users may be aware of the negative and addictive aspects of social media, it is also a useful tool for finding supportive content. In a global survey conducted in 2023, 32 percent of social media users followed therapists and mental health professionals on social media. Overall, 24 percent of respondents said that they followed people on social media if they had the same condition as they did. Between January 2020 and March 2023, British actress and model Cara Delevingne was the celebrity mental health activist with the highest growth in searches tying her name to the topic.

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.

According to a March 2024 survey conducted in the United States, more men than women considered that social media had positive effects on their mental health, with nine percent of male respondents reporting very positive effects, and 16 percent reporting somewhat positive effects. In comparison, only six percent and 15 percent of women reported that social networks affected them very positively or somewhat positively, respectively. A similar share of men and women considered that online networks did not have a negative or positive effect on them.

This data set is drawn from primarily Hispanic university students and assesses topics associated with social media use and mental health.

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.

According to a survey conducted in 2024, 44 percent of parents in the United States felt that social media was the one thing they thought most negatively impacted teenagers' mental health. Technology in general was regarded by 14 percent of those surveyed as the thing they thought most negatively impacted teens' mental health.

Citation

Rani, S.; Ahmed, K.; Subramani, S. From Posts to Knowledge: Annotating a Pandemic-Era Reddit Dataset to Navigate Mental Health Narratives. Appl. Sci. 2024, 14, 1547. https://doi.org/10.3390/app14041547

RMHD Our dataset, meticulously curated from Reddit, encompasses a comprehensive collection of posts from five key subreddits focused on mental health: r/anxiety, r/depression, r/mentalhealth, r/suicidewatch, and r/lonely. These subreddits were chosen for their rich, focused discussions on mental health issues, making them invaluable for research in this area.

The dataset spans from January 2019 through August 2022 and is systematically structured into folders by year. Within each yearly folder, the data is further segmented into monthly batches. Each month's data is compiled into five separate CSV files, corresponding to the selected subreddits.

Structure of Part A : Raw Data:Each CSV file in our dataset includes the following columns, providing a detailed view of the Reddit posts along with essential metadata: Author: The username of the Reddit post's author. Created_utc: The UTC timestamp of when the post was created. Score:The net score (upvotes minus downvotes) of the post. Selftext: The main text content of the post. **Subreddit: **The subreddit from which the post was sourced. Title: The title of the Reddit post. Timestamp:The local date and time when the post was created, converted from the UTC timestamp. This structured approach allows researchers to conduct detailed, time-based analyses and to easily access data from specific subreddits.

Structure of Part B : Labelled Data :Part B of our dataset, which includes a subset of 800 manually annotated posts, is structured differently to provide focused insights into the mental health discussions. The columns in Part B are as follows: Score: The net score (upvotes minus downvotes) of the post. Selftext:The main text content of the post. Subreddit: The subreddit from which the post was sourced. Title: The title of the Reddit post. Label: The assigned label indicating the identified root cause of mental health issues, based on our annotation process are : Drug and Alcohol , Early Life, Personality,Trauma and Stress

This annotation process brings additional depth to the dataset, allowing researchers to explore the underlying factors contributing to mental health issues.

The dataset, with a zipped size of approximately 1.68GB, is publicly available and serves as a rich resource for researchers interested in exploring the root causes of mental health issues as represented in social media discussions, particularly within the diverse conversations found on Reddit.

This report presents findings from the third (wave 3) in a series of follow up reports to the 2017 Mental Health of Children and Young People (MHCYP) survey, conducted in 2022. The sample includes 2,866 of the children and young people who took part in the MHCYP 2017 survey. The mental health of children and young people aged 7 to 24 years living in England in 2022 is examined, as well as their household circumstances, and their experiences of education, employment and services and of life in their families and communities. Comparisons are made with 2017, 2020 (wave 1) and 2021 (wave 2), where possible, to monitor changes over time.

According to a survey conducted in 2024 in the United States, ** percent of teenagers stated that social media helped them with friendships, while ** percent said it helped them with confidence. Additionally, ** percent of U.S. teens felt that social media negatively affected their productivity, and ** percent said it affected the amount of sleep they had. As for mental health, one in * teens felt that social media hurt that aspect of their lives, and one in ** said it helped.

Please cite the following paper when using this dataset:

N. Thakur, “Five Years of COVID-19 Discourse on Instagram: A Labeled Instagram Dataset of Over Half a Million Posts for Multilingual Sentiment Analysis”, Proceedings of the 7th International Conference on Machine Learning and Natural Language Processing (MLNLP 2024), Chengdu, China, October 18-20, 2024 (Paper accepted for publication, Preprint available at: https://arxiv.org/abs/2410.03293)

Abstract

The outbreak of COVID-19 served as a catalyst for content creation and dissemination on social media platforms, as such platforms serve as virtual communities where people can connect and communicate with one another seamlessly. While there have been several works related to the mining and analysis of COVID-19-related posts on social media platforms such as Twitter (or X), YouTube, Facebook, and TikTok, there is still limited research that focuses on the public discourse on Instagram in this context. Furthermore, the prior works in this field have only focused on the development and analysis of datasets of Instagram posts published during the first few months of the outbreak. The work presented in this paper aims to address this research gap and presents a novel multilingual dataset of 500,153 Instagram posts about COVID-19 published between January 2020 and September 2024. This dataset contains Instagram posts in 161 different languages. After the development of this dataset, multilingual sentiment analysis was performed using VADER and twitter-xlm-roberta-base-sentiment. This process involved classifying each post as positive, negative, or neutral. The results of sentiment analysis are presented as a separate attribute in this dataset.

For each of these posts, the Post ID, Post Description, Date of publication, language code, full version of the language, and sentiment label are presented as separate attributes in the dataset.

The Instagram posts in this dataset are present in 161 different languages out of which the top 10 languages in terms of frequency are English (343041 posts), Spanish (30220 posts), Hindi (15832 posts), Portuguese (15779 posts), Indonesian (11491 posts), Tamil (9592 posts), Arabic (9416 posts), German (7822 posts), Italian (5162 posts), Turkish (4632 posts)

There are 535,021 distinct hashtags in this dataset with the top 10 hashtags in terms of frequency being #covid19 (169865 posts), #covid (132485 posts), #coronavirus (117518 posts), #covid_19 (104069 posts), #covidtesting (95095 posts), #coronavirusupdates (75439 posts), #corona (39416 posts), #healthcare (38975 posts), #staysafe (36740 posts), #coronavirusoutbreak (34567 posts)

The following is a description of the attributes present in this dataset - Post ID: Unique ID of each Instagram post - Post Description: Complete description of each post in the language in which it was originally published - Date: Date of publication in MM/DD/YYYY format - Language code: Language code (for example: “en”) that represents the language of the post as detected using the Google Translate API - Full Language: Full form of the language (for example: “English”) that represents the language of the post as detected using the Google Translate API - Sentiment: Results of sentiment analysis (using the preprocessed version of each post) where each post was classified as positive, negative, or neutral

Open Research Questions

This dataset is expected to be helpful for the investigation of the following research questions and even beyond:

• How does sentiment toward COVID-19 vary across different languages?
• How has public sentiment toward COVID-19 evolved from 2020 to the present?
• How do cultural differences affect social media discourse about COVID-19 across various languages?
• How has COVID-19 impacted mental health, as reflected in social media posts across different languages?
• How effective were public health campaigns in shifting public sentiment in different languages?
• What patterns of vaccine hesitancy or support are present in different languages?
• How did geopolitical events influence public sentiment about COVID-19 in multilingual social media discourse?
• What role does social media discourse play in shaping public behavior toward COVID-19 in different linguistic communities?
• How does the sentiment of minority or underrepresented languages compare to that of major world languages regarding COVID-19?
• What insights can be gained by comparing the sentiment of COVID-19 posts in widely spoken languages (e.g., English, Spanish) to those in less common languages?

All the Instagram posts that were collected during this data mining process to develop this dataset were publicly available on Instagram and did not require a user to log in to Instagram to view the same (at the time of writing this paper).

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Acadia Healthcare: Navigating the Mental Health Landscape (ACHC)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

A 2024 survey conducted in the United States found that social media was more harmful to teen girls' mental health than teen boys. Overall, ** percent of teen girls said online platforms hurt their mental health, compared to ** percent of teen boys. Additionally, half of teenage girls felt that social media negatively impacted their sleep, as did ** percent of teen boys.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Axsome's Common Stock (AXSM): A New Frontier in Mental Health Treatment?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

According to a survey conducted in June 2024 in the United States, 52 percent of respondents aged 65 years and over thought that social media platforms definitely should be required to display cigarette-style health messages on them, warning users of their association with mental health harm for adolescents. Overall, 44 percent of respondents aged between 45 and 64 years felt the same. In addition, 36 percent of respondents aged between 18 and 29 years thought that social networks definitely should be required to display cigarette-style health messages.

Instagram’s most popular post

              As of April 2024, the most popular post on Instagram was Lionel Messi and his teammates after winning the 2022 FIFA World Cup with Argentina, posted by the account @leomessi. Messi's post, which racked up over 61 million likes within a day, knocked off the reigning post, which was 'Photo of an Egg'. Originally posted in January 2021, 'Photo of an Egg' surpassed the world’s most popular Instagram post at that time, which was a photo by Kylie Jenner’s daughter totaling 18 million likes.
              After several cryptic posts published by the account, World Record Egg revealed itself to be a part of a mental health campaign aimed at the pressures of social media use.

              Instagram’s most popular accounts

              As of April 2024, the official Instagram account @instagram had the most followers of any account on the platform, with 672 million followers. Portuguese footballer Cristiano Ronaldo (@cristiano) was the most followed individual with 628 million followers, while Selena Gomez (@selenagomez) was the most followed woman on the platform with 429 million. Additionally, Inter Miami CF striker Lionel Messi (@leomessi) had a total of 502 million. Celebrities such as The Rock, Kylie Jenner, and Ariana Grande all had over 380 million followers each.

              Instagram influencers

              In the United States, the leading content category of Instagram influencers was lifestyle, with 15.25 percent of influencers creating lifestyle content in 2021. Music ranked in second place with 10.96 percent, followed by family with 8.24 percent. Having a large audience can be very lucrative: Instagram influencers in the United States, Canada and the United Kingdom with over 90,000 followers made around 1,221 US dollars per post.

              Instagram around the globe

              Instagram’s worldwide popularity continues to grow, and India is the leading country in terms of number of users, with over 362.9 million users as of January 2024. The United States had 169.65 million Instagram users and Brazil had 134.6 million users. The social media platform was also very popular in Indonesia and Turkey, with 100.9 and 57.1, respectively. As of January 2024, Instagram was the fourth most popular social network in the world, behind Facebook, YouTube and WhatsApp.

Primary Care Networks were created in July 2019 to provide accessible and integrated primary, mental health, and community care for patients. The PCN contract is a Directed Enhanced Service and aims to increase the primary care workforce by 26,000 by 2024. The bulk of the PCN workforce consists of Direct Patient Care staff, funded by the Additional Roles Reimbursement Scheme (ARRS), and each PCN has the flexibility and autonomy to determine which roles are required to meet the specific needs of their local populations. Initially, recruitment focused on clinical pharmacists and social prescribing link workers, with more roles being included over subsequent years. Information about the PCN workforce is provided directly by each PCN, and recorded in the National Workforce Reporting Service (NWRS) which is the same system that is used to collect information about the general practice workforce. This report includes England, Integrated Care Board (ICB), Sub-ICB Location and PCN-level figures for Clinical Directors, Direct Patient Care Workers and Admin/Non-Clinical staff working in PCNs on 31 January 2024. The level of detail in the information that we can collect about each individual varies, as there are different ways that individuals can be contracted to work for their PCN. Some staff work directly for the PCN, including Clinical Directors, administrative workers, and some Direct Patient Care staff. These individuals may have been newly recruited to the PCN, or could be staff transferring some or all of their working hours from a general practice or other organisation. Alternatively, an individual may be employed by a member organisation within the PCN – such as a hospital trust or charity – and deployed to work for the PCN. In both cases, details about the staff member, including the hours worked for the PCN, are recorded in the NWRS. However, in some cases, a role – for example a physiotherapist – is not staffed permanently by a specific individual. Instead, the working hours are covered by a group of physiotherapists, employed by another organisation such as the local ICB, and deployed to the PCN as a “contracted service,” which up until the September 2020 release were referred to in this publication series as “pooled resource”. In these cases, the providing organisation holds a contract with the PCN to deliver the physiotherapy service and supplies appropriately qualified staff, possibly on a rota’d basis. Where the healthcare provision is covered by a contracted service of this nature, it is not possible to identify the separate individuals working within the PCN and in these cases, the PCN provides us with information about the average weekly working hours covered by that “contracted service”. This means that although we can calculate proxy full-time equivalent (FTE) figures relating to the service, no information about headcount or workforce characteristics can be inferred. This means that headcount figures presented in the accompanying Bulletin do not include provision from these “contracted services.” The completeness and coverage of PCN workforce data is constantly improving and more PCNs are using the new NWRS. We now believe data quality is sufficient to warrant monthly collections and publications, and as such, monthly publications have commenced from January 2023. We are working continually to improve our publications and we welcome feedback from all users by email to: PrimaryCareWorkforce@nhs.net. Links to other publications presenting healthcare workforce information can be found under Related Links.

Adult Coloring Book Market size was valued at USD 150 Million in 2023 and is projected to reach USD 350 Million by 2031, growing at a CAGR of 10 % during the forecast period 2024-2031.

Global Adult Coloring Book Market Drivers

The market drivers for the Adult Coloring Book Market can be influenced by various factors. These may include:

Stress Relief and Relaxation: Many adults use coloring books as a way to unwind, reduce stress, and practice mindfulness.

Growing Awareness of Mental Health: There is increasing recognition of mental health issues, and coloring books are seen as a therapeutic tool that can help with anxiety and depression.

Art Therapy: The rise of art therapy as a legitimate form of psychological treatment has driven interest in adult coloring books.

Digital Detox: As people seek to reduce screen time, they are turning to analog activities like coloring for entertainment and relaxation.

Creative Expression: Adults are looking for ways to express their creativity, and coloring books provide an accessible outlet for artistic expression.

Social Media Influence: Platforms like Instagram and Pinterest have popularized adult coloring books, with many users sharing their completed pages and contributing to trends.

Celebrity and Influencer Endorsements: Recommendations from well-known personalities can boost the popularity of adult coloring books.

Gift-Giving: Adult coloring books are popular gifts, contributing to seasonal spikes, especially around holidays.

Publishing Innovations: The release of high-quality, themed, and artist-specific coloring books has invigorated consumer interest.

There continues to be a growing trend of people caring more about their health and well-being, benefitting the Health and Wellness Spas industry. Wellness tourism has provided the industry with an expansive market of inbound clients attracted by spa towns and cities that have invested in contemporary and luxury spa businesses. However, over the five years through 2024-25, industry revenue is anticipated to decline at a compound annual rate of 1.6% to £7.9 billion. Spas suffered a sharp downturn in revenue in 2020-21 following the COVID-19 outbreak, which led to temporary closures of spas and social distancing restrictions. Following a strong resurgence in spa attendance in the two years through 2022-23 owing to the easing of lockdown restrictions and pent-up demand, revenue has continued to grow and is expected to climb by 4% in 2024-25, supported by an almost complete recovery in international tourist numbers. Spas fluctuate with consumer trends. Disposable incomes and consumer confidence are still struggling in 2024-25 because of high inflation and the cost of living that's been weighing on individuals since 2022-23. The cost-of-living crisis is a heaby burden on consumer confidence and on revenue growth, as individuals are more frugal. Spas are increasingly competing against each other by marketing all-inclusive packages, couple retreats and group sessions to attract younger demographics. However, the most profitable markets remain in the highest income quintiles who are less afflicted. Over the five years through 2029-30, industry revenue is anticipated to grow at a compound annual rate of 3.2% to reach £9.3 billion. Rising living costs will persist in the short term, limiting industry growth. Spas will have to keep contending with a skills shortage due to the introduction of a points-based immigration system in January 2021, which is likely to drive wage growth. Nonetheless, consumers are expected to become increasingly concerned about their physical and psychological wellbeing, relying on spas to relieve stress and anxiety.

According to Cognitive Market Research, the global Direct to consumer DNA Testing Marketsize will be USD 2151.2 million in 2024. It will expand at a compound annual growth rate (CAGR) of 25.00% from 2024 to 2031.

North America held the major market of more than 40% of the global revenue with a market size of USD 860.88 million in 2024 and will grow at a compound annual growth rate (CAGR) of 23.2% from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 645.36 million.
Asia Pacific held a market of around 23% of the global revenue with a market size of USD 494.78 million in 2024 and will grow at a compound annual growth rate (CAGR) of 27.0% from 2024 to 2031.
Latin America's market will have more than 5% of the global revenue with a market size of USD 107.56 million in 2024 and will grow at a compound annual growth rate (CAGR) of 24.4% from 2024 to 2031.
Middle East and Africa are the major markets of around 2% of the global revenue with a market size of USD 43.02 million in 2024 and will grow at a compound annual growth rate (CAGR) of 24.7% from 2024 to 2031.
The Targeted Analysisheld the highest direct-to-consumer DNA Testing Market revenue share in 2024.

Market Dynamics of Direct to consumer DNA Testing Market

Key Drivers of Direct to consumer DNA Testing Market

Increase Trend Toward Direct-to-consumer Genetic Testing Boosting the Market Growth

The public understanding and acceptance of genetic testing are steadily increasing. A national survey found that awareness has increased dramatically in the United States, and a social media survey found that 47% of users are familiar with the direct-to-consumer concept. Across many sectors, there is an apparent rise in customers seeking customized products & experiences, with a rising willingness to pay for the identification & addressing of unique needs. Customers are trying to express willingness to undergo testing & pay for genetic testing services. According to a recent survey conducted in the United States with a sample size of 2,000 people, 33% said they would be willing to pay for and use the advice provided by a direct-to-consumer genetic testing company.

Rise in the Occurrence of Chronic Disorders to Drive Market Growth

Direct-to-consumer genetic tests offer information about a genetic inclination towards a spectrum of disorders such as heart ailments, mental illness, diabetes, and Alzheimer's. In addition to this, DTC genetic testing also offers information pertaining to genetic aspects that can affect the body reaction of the consumer to a particular diet, pharmaceutical drugs, alcohol, and caffeine. Apparently, the tests also impart information about the genes that are related to eye color, athletic performance, and forms of male baldness. All these factors above are anticipated to accelerate the growth of the direct-to-consumer (DTC) genetic testing market over the years to come.

Restraint Factors of Direct to consumer DNA Testing Market

Privacy Concerns to Restrict the Market Growth

More than 65% of individuals are willing to use home direct-to-consumer genetic testing services. Privacy is one of the main concerns, especially the potential sharing of data with third parties, including pharmaceutical and insurance companies and consumer health. Almost all the respondents willing to use the service have concerns about a company owning their DNA profiles. In submitting a sample for processing, individuals provide sensitive information about themselves and family members with whom they share a genetic link. Leakage of such data could negatively impact these individuals across various areas, including employment prospects, relationships, and insurance premiums. Cyber security breaches, database password & service hacking, Human error, or oversight by data custodians pose a risk.

Impact of COVID-19 on the Direct to consumer DNA Testing Market

During the COVID-19 pandemic, widespread diagnostic and serological (immunity) testing is critical in containing the disease, easing stay-at-home measures, and informing policies for economic recovery. Most diagnostic and serological tests are provided by healthcare providers who interface with the healthcare system. However, several companies have begun to offer COVID-19 testing on a direct-to-consumer (DTC) basis, which means that the test is initiated by a consumer rather tha...