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.

According to a survey conducted in the United Kingdom in May 2025, a total of 87 percent of respondents stated that social media had negatively affected their mental health. Of these respondents, one-in-ten young social media users said it had negatively impacted their mental health too many times to count.

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.

A 2024 survey conducted in the United States and the United Kingdom found that ** percent of male social media users had concerns about the impact of social media on young men’s health. Around ***** percent of those surveys disagreed with the idea that social media was effecting young men's health.

This is the second (wave 2) in a series of follow up reports to the Mental Health and Young People Survey (MHCYP) 2017, exploring the mental health of children and young people in February/March 2021, during the Coronavirus (COVID-19) pandemic and changes since 2017. Experiences of family life, education, and services during the COVID-19 pandemic are also examined. The sample for the Mental Health Survey for Children and Young People, 2021 (MHCYP 2021), wave 2 follow up was based on 3,667 children and young people who took part in the MHCYP 2017 survey, with both surveys also drawing on information collected from parents. Cross-sectional analyses are presented, addressing three primary aims: Aim 1: Comparing mental health between 2017 and 2021 – the likelihood of a mental disorder has been assessed against completion of the Strengths and Difficulties Questionnaire (SDQ) in both years in Topic 1 by various demographics. Aim 2: Describing life during the COVID-19 pandemic - Topic 2 examines the circumstances and experiences of children and young people in February/March 2021 and the preceding months, covering: COVID-19 infection and symptoms. Feelings about social media use. Family connectedness. Family functioning. Education, including missed days of schooling, access to resources, and support for those with Special Educational Needs and Disabilities (SEND). Changes in circumstances. How lockdown and restrictions have affected children and young people’s lives. Seeking help for mental health concerns. Aim 3: Present more detailed data on the mental health, circumstances and experiences of children and young people by ethnic group during the coronavirus pandemic (where sample sizes allow). The data is broken down by gender and age bands of 6 to 10 year olds and 11 to 16 year olds for all categories, and 17 to 22 years old for certain categories where a time series is available, as well as by whether a child is unlikely to have a mental health disorder, possibly has a mental health disorder and probably has a mental health disorder. This study was funded by the Department of Health and Social Care, commissioned by NHS Digital, and carried out by the Office for National Statistics, the National Centre for Social Research, University of Cambridge and University of Exeter.

People with mental health conditions have been identified as particularly vulnerable to poor mental health during the coronavirus disease 2019 (COVID-19) pandemic. However, why this population have faced these adverse effects, how they have experienced them and how they have coped remains under-explored. To explore how the COVID-19 pandemic affected the mental health of people with existing mental health conditions, and to identify coping strategies for positive mental health. Semi-structured qualitative interviews with 22 people with mental health conditions. Participants were purposively recruited via social media, study newsletters and third sector mental health organisations. Data were analysed using reflexive thematic analysis. Participants were aged 23–70 (mean age 43), predominantly female (59.1%) and of white ethnicity (68.2%). Fifty percent were unable to work due to illness and the most frequently reported mental health condition was depression. Five pandemic-related factors contributed to deteriorating mental health: (i) feeling safe but isolated at home; (ii) disruption to mental health services; (iii) cancelled plans and changed routines; (iv) uncertainty and lack of control; (v) rolling media coverage. Five coping strategies were identified for maintaining mental health: (i) previous experience of adversity; (ii) social comparison and accountability; (iii) engaging in hobbies and activities; (iv) staying connected with others; (v) perceived social support. Challenges were identified as a direct result of the pandemic and people with severe mental illnesses were particularly negatively affected. However, some found this period a time of respite, drew upon reserves of resilience and adapted their coping strategies to maintain positive well-being.

Background: The Coronavirus disease (COVID-19) has emphasised the critical need to investigate the mental well-being of healthcare professionals working during the pandemic. It has been highlighted that healthcare professionals display a higher prevalence of mental distress and research has largely focused on frontline professions. Social restrictions were enforced during the pandemic that caused rapid changes to the working environment (both clinically and remotely). The present study aims to examine the mental health of a variety of healthcare professionals, comparing overall mental wellbeing in both frontline and non-frontline professionals and the effect of the working environment on mental health outcomes.

Method: A cross-sectional mixed methods design, conducted through an online questionnaire. Demographic information was optional but participants were required to complete: (a) Patient Health Questionnaire, (b) Generalised Anxiety Disorder, (c) Perceived Stress Scale, and (d) Copenhagen Burnout Inventory. The questionnaire included one open-ended question regarding challenges experienced working during the pandemic.

Procedure:
Upon ethical approval the online questionnaire was advertised for six weeks from 1st May 2021 to 12th June 2021 to maximise the total number of respondents able to partake. The survey was hosted on the survey platform “Online Surveys”. It was not possible to determine a response rate because identifying how many people had received the link was unattainable information. The advert for the study was placed on social media platforms (WhatsApp, Instagram, Facebook and Twitter) and shared through emails.

Participants were recruited through the researchers’ existing professional networks and they shared the advertisement and link to questionnaire with colleagues. The information page explained the purpose of the study, eligibility criteria, procedure, costs and benefits of partaking and data storage. Participants were made aware on the information page that completing and submitting the questionnaire indicated their informed consent. It was not possible to submit complete questionnaires unless blank responses were optional demographic data. Participants were informed that completed questionnaires could not be withdrawn due to anonymity.

The questionnaire consisted of four sections: demographic data, mental health information and the four psychometric tools, PHQ-9, GAD-7, PSS-10 and CBI. Due to the sensitive nature of this research, only the psychometric measures required an answer for each question, thus all demographic information was optional to encourage participant contentment. Once participants had completed the questionnaire and submitted, they were automatically taken to a debrief page. This revealed the hypothesis of the questionnaire and rationalised why it was necessary to conceal this prior to completion. Participants were signposted to mental health charities and a self-referral form for psychological support. Participants could contact the researcher via email to express an interest in the results. It was explained that findings would be analysed using descriptive statistics to investigate any correlations or patterns in the responses. Data collected was stored electronically, on a password protected laptop. It will be kept for three years and then destroyed.

Instruments: PHQ-9, GAD-7, PSS-10 and CBI.

Other questions included:

Thank you for considering taking part in the questionnaire! Please remember by completing and submitting the questionnaire you are giving your informed consent to participate in this study.

Demographic:

Gender: please select one of the following:

Male Female Non-binary Prefer not to answer

Age: what is your age?

Open question: Prefer not to answer

What is your current region in the UK?

South West, East of England, South East, East Midlands, Yorkshire and the Humber, North West, West Midlands, North East, London, Scotland, Wales, Northern Ireland Prefer not to answer

Ethnicity: please select one of the following:

White English, Welsh, Scottish, Northern Irish or British Irish Gypsy or Irish Traveller Any other White background Mixed or Multiple ethnic groups White and Black Caribbean White and Black African White and Asian Any other Mixed or Multiple ethnic background Asian or Asian British Indian Pakistani Bangladeshi Chinese Any other Asian background Black, African, Caribbean or Black British African Caribbean Any other Black, African or Caribbean background Other ethnic group Arab Option for other please specify Prefer not to answer

Employment/environment:

What was your employment status in 2020 prior to COVID-19 pandemic?

Please select the option that best applies. Employed Self-employed Unpaid work (homemaker/carer) Out of work and looking for work Out of work but not currently looking for work Student Volunteer Retired Unable to work Prefer not to answer Option for other please specify

What is your current employment status?

Please tick the option that best applies. Employed Self-employed Unpaid work (homemaker/carer) Out of work and looking for work Out of work but not currently looking for work Student Volunteer Retired Unable to work Prefer not to answer Option for other please specify

What is your healthcare profession/helping profession?

Please state your job title. Open question

How often did you work from home before the COVID-19 pandemic?

Not at all, rarely, some, most, everyday Option for N/A

How often did you work from home during the first UK national lockdown for COVID-19?

Not at all, rarely, some, most, everyday Option for N/A

How often did you work from home during the second UK national lockdown during COVID-19?

Not at all, rarely, some, most, everyday Option for N/A

How often have you worked from home during the third UK national lockdown during COVID-19?

Not at all, rarely, some, most, everyday Option for N/A

How often are you currently working from home during the COVID-19 pandemic?

Not at all, rarely, some, most, everyday Option for N/A

Mental health:

How would you describe your mental health leading up to the COVID-19 pandemic?

Excellent, Very good, Good, Fair, Poor

How would you describe your mental health during the COVID-19 pandemic?

Excellent, Very good, Good, Fair, Poor

What have been the main challenges working as a healthcare professional/helping profession during COVID-19 pandemic? Open question

Data analysis: Firstly, any missing data was checked by the researcher and noted in the results section. The data was then analysed using a statistical software package called Statistical Package for the Social Sciences version 28 (SPSS-28). Descriptive statistics were collected to organise and summarise the data, and a correlation coefficient describes the strength and direction of the relationship between two variables. Inferential statistics were used to determine whether the effects were statistically significant. Responses to the open-ended question were coded and examined for key themes and patterns utilising the Braun and Clarke (2006) thematic analysis approach.

Ethical considerations: The study was approved by the Health Science, Engineering and Technology Ethical Committee with Delegated Authority at the University of Hertfordshire.

The potential benefits and risks of partaking in the research were contemplated and presented on the information page to promote informed consent. Precautions to prevent harm to participants included eligibility criteria, excluding those under eighteen years older or experiencing mental health distress. As the questionnaire was based around employment and the working environment, another exclusion involved experiencing a recent job change which caused upset.

An anonymous questionnaire and optional input of demographic data fostered the participants’ right to autonomy, privacy and respect. Specific employment and organisation or company information were not collected to protect confidentiality. Although participants were initially deceived regarding the hypotheses, they were provided with accurate information about the purpose of the study. Deceit was appropriate to collect unbiased information and participants were subsequently informed of the hypotheses on the debrief page.

Previous studies have demonstrated the advantages of physical behaviour such as physical activity and sleep on mental health and provided an association between virtual behaviour, such as social media use and screen time, and mental health problems. Here, physical behaviour is defined as the data related to the person in the physical real world such as physical activity, sleep, and virtual behaviour is defined as behaviour involving the internet such as social networks, general web browsing, and instant messaging. We believe that a person's physical or virtual behaviour individually may not be the best indicator of their mental health. Current datasets do not include data on both physical and virtual behaviours. Therefore, we seek to run a data collection study that collects both physical and virtual behaviours. Additionally, we investigate if machine learning models that include both physical and virtual behaviour can better predict mental health. This study is conducted by using data collected via a custom-made app. This app is made to run in the background of a user's smartphone collecting physical activity, sleep, location, and audio inferences passively. Additionally, it offers users an ecological momentary assessment (EMA) platform where they may log information about their feelings and other significant occurrences through the Warwick-Edinburgh Mental Wellbeing survey. This will provide us with a ground truth to evaluate our models. We also collect social media data through Instagram and YouTube logs sent by the participants at the end of the study.

ISBN Reference: 1-4039-8637-1 Summary This report first describes the prevalence of mental disorders among 5- to 16-year olds in 2004 and notes any changes since the previous survey in 1999. It then provides profiles of children in each of the main disorder categories (emotional, conduct, hyperkinetic and autistic spectrum disorders) and , where the sample size permits, profiles subgroups within these categories. The final chapters examine the characteristics of children with multiple disorders and present a selection of analyses for Scotland. Causal relationships should not be assumed for any of the results presented in this report.

The Adult Psychiatric Morbidity Survey, 2014: Special Licence Access (APMS 2014) is the fourth survey of psychiatric morbidity in adults living in private households. It was carried out by the National Centre for Social Research (NatCen Social Research) in collaboration with the University of Leicester, and was commissioned by NHS Digital. Users should note that the 2014 survey is subject to more restrictive Special Licence access conditions than previous surveys in the series.

The main aim of the survey series is to collect data on poor mental health among adults (aged 16 and over) living in private households in England. The specific objectives are:

• to estimate the prevalence of psychiatric morbidity according to diagnostic category in the adult household population of England. The survey includes assessment of common mental disorders, psychosis, autism, substance misuse and dependency, and suicidal thoughts, attempts and self-harm;
• to screen for attention-deficit/hyperactivity disorder (ADHD), post-traumatic stress disorder (PTSD), bipolar disorder and personality disorders;
• to examine trends in the psychiatric disorders included in previous survey years (1993, 2000, and 2007).
• to identify the nature and extent of social disadvantage associated with mental illness;.
• to gauge the level and nature of treatment and service use in relation to mental health problems, with an emphasis on primary care;
• to collect data on key current and lifetime factors that might be associated with mental health problems, such as the experience of stressful life events, abusive relationships, and work stress.
• to collect data on factors that might protect against poor mental health, such as social support networks and neighbourhood cohesion.

Most people seek to establish romantic or intimate relationships in life, including people with mental health problems. However, this has been a neglected topic in mental health practice and research. This study aimed to investigate views of mental health and social care staff about the appropriateness of helping service users with romantic relationships, barriers to doing this, and suggestions for useful ways to support this. An online survey comprising both closed, multiple response and free-text questions was circulated to mental health organisations across the U.K. via social media, professional networks and use of snowballing sampling. A total of 63 responses were received. Quantitative data were analysed using descriptive statistics, and are reported as frequencies and percentages. Qualitative data were interpreted using thematic analysis, using an inductive approach. Although most participants reported that ‘finding a relationship’ conversations were appropriate in their job role, many barriers to supporting service users were identified, including: a lack of training; concerns about professional boundaries; concerns about service user capacity and vulnerability; and concerns about being intrusive. Participant suggestions for future support included educating service users on safe dating behaviours, and practical interventions such as assisting service users to use dating sites and engage with social activities to develop social skills and meet others. Staff were willing to help service users seek an intimate relationship but may need specific training or guidance to facilitate this confidently and safely. This study elucidates the need for further research in this area, particularly in understanding service user perspectives, and in developing resources to support staff in this work.

IntroductionThe digital “revolution” brings along consequences at the individual level, consequences in terms of mental health, both positive and negative. Therefore, the purpose of the meta-analysis presented in this work is to investigate, in the adult population, the associated factors (psychological distress, anxiety, depression, stress, burnout, loneliness and social isolation, insomnia, and psychological well-being (PWB)) by means of digital technology represented by Artificial Intelligence (AI), remote work (RW), smartphone, social media (SM), and smart technologies used in tourism (STT).MethodsThe meta-analysis was performed between June 2020–June 2024, and the protocol was registered in the PROSPERO database (CRD42024560285). Forty-seven papers involving a total of 36,100 participants were included in the meta-analysis. Standard meta-analytic procedures were applied, and correlation coefficients (r) were used as measures of effect size.ResultsThe highest positive value of the effect was obtained for the association between PWB and the use of the digital environment (AI, RW, and STT) r = 0.435, and the highest negative effect value was obtained for the association between burnout and the use of the digital environment (AI and RW) r = −0.478. The moderation analysis further clarified the role of contextual variables.Discussion/ConclusionThis meta-analysis highlights that digital technologies have both positive and negative effects on adult mental health, reflecting the complex impact of the digital environment.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/search, CRD42024560285.

Social networks and friendship groups are important factors related to the development of health risk and health promoting behaviours, mental health and wellbeing, educational attainment, and positive social engagement in adolescence and early adulthood.

The MRC/CSO Social and Public Health Sciences Unit has been studying adolescent social networks and health in the West of Scotland for several decades. The Teenage Friends and Lifestyles (1995), Peers and Levels of Stress (2006), and Adolescent Lifestyles in Contemporary Europe (2011) studies have been a rich source of information on the health needs of Scotland's younger citizens and have helped to identify how risk factors have changed over time.

Net4Health will continue from the previous studies and aims to understand how peer and social network influences on adolescent health operate in the West of Scotland today, and how these influences have changed, particularly in relation to mental health and wellbeing and within changing digital social environments. It is hoped that this study will provide information that will inform the appropriate design of social network interventions to improve health and wellbeing.

The Net4Health project involves collecting social network and health data from adolescents attending secondary schools in Scotland. Net4Health builds upon previous networks and health research conducted in the Social and Public Health Sciences Unit (SPHSU). It aims to study the change in adolescent health behaviours and outcomes comparing the 2020s to previous decades, how peer-, school-, and family-level determinants of health outcomes have changed, and explore mechanisms through which interventions could improve health outcomes. It will also explore novel methods for collecting data relating to the relational aspects of adolescent health.

Net4Health will involve documentary analysis of school policies and structures, surveys with school year groups; and in a subset of schools: qualitative network interviews with pupils and teachers, and wearable device assessment of movement and use of space.

BackgroundNon-medical prescribing by pharmacists, nurses, and other professionals has been introduced over recent decades to address staff shortages and the growing demand for mental health services globally. However, most of the emerging evidence concerning the contribution and impact of non-medical prescribing focuses on nurses, despite the expanding role of pharmacists.AimThe study aimed to explore in depth the factors influencing implementation and delivery of pharmacist non-medical prescribing services for patients with mental illness in community-based settings across the UK.MethodRemote semi-structured interviews were conducted with pharmacist independent prescribers across the UK between January and June 2024. Participants were recruited using purposive sampling through the research team’s professional networks and social media platforms, with data transcribed and analysed thematically.Results20 pharmacist prescribers were interviewed, including six from general practice and seven from specialist mental health care. Four main themes, including insecurity, training/education, ambiguity, and workload management were identified. Lack of confidence in prescribing was reported by most participants – general practice based pharmacists cited challenges related to a lack of confidence in managing patients with mental health illness, whereas those in specialist services identified difficulties with risk management. Concerns about training and education were frequently raised by participants, including inadequacies in the undergraduate pharmacy curriculum and non-medical prescribing courses in preparing them for key elements of practice related to mental health care such as assessing patients with mental illness. Pharmacist prescribers also reported challenges with workload management and role clarity. While pharmacists anecdotally perceived high patient satisfaction with the care they provided, this was not reported to be formally evaluated.ConclusionSeveral factors were identified that influenced successful implementation and delivery of pharmacist prescribing services for patients with mental illness in community care. Improved education and training in mental health along with a clearer definition of the pharmacist prescribing role may support optimal service delivery. Future work evaluating pharmacist prescribing should explore the viewpoints of patients and carers in order to develop holistic improvement recommendations driven by key stakeholders.

The Adult Psychiatric Morbidity Survey, 2007 (APMS 2007) is the third survey of psychiatric morbidity in adults living in private households. The main aim of the survey was to collect data on poor mental health among adults aged 16 and over living in private households in England.

The specific objectives of the survey were:

• to estimate the prevalence of psychiatric morbidity according to diagnostic category in the adult household population of England. The survey included assessment of common mental disorders; psychosis; borderline and antisocial personality disorder; Asperger syndrome, substance misuse and dependency; and suicidal thoughts, attempts and self-harm
• to screen for characteristics of eating disorder, attention deficit hyperactivity disorder, posttraumatic stress disorder, and problem gambling
• to examine trends in the psychiatric disorders that have been included in previous survey years (1993 and 2000)
• to identify the nature and extent of social disadvantage associated with mental illness
• to gauge the level and nature of service use in relation to mental health problems, with an emphasis on primary care
• to collect data on key current and lifetime factors that might be associated with mental health problems, such as experience of stressful life events, abusive relationships, and work stress
• to collect data on factors that might be protective against poor mental health, such as social support networks and neighbourhood cohesion

According to a survey conducted in June 2024, ** percent of adults in the United Kingdom stated that social media platforms definitely should be required to display cigarette‑style health messages, warning that they are associated with significant mental health harms for adolescents. Under ********** respondents felt that they definitely should not.

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 30 November 2023. 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.

According to a survey conducted in June 2024, ** percent of women and ** percent of men stated that social media platforms probably should be required to display cigarette‑style health messages, warning that they are associated with significant mental health harms for adolescents.

Using a small-scale descriptive network analysis approach, this study highlights the importance of stakeholder networks for identifying valuable stakeholders and the management of existing stakeholders in the context of mental health not-for-profit services. We extract network data from the social media brand pages of three health service organizations from the U.S., U.K., and Australia, to visually map networks of 579 social media brand pages (represented by nodes), connected by 5,600 edges. This network data is analyzed using a collection of popular graph analysis techniques to assess the differences in the way each of the service organizations manage stakeholder networks. We also compare node meta-information against basic topology measures to emphasize the importance of effectively managing relationships with stakeholders who have large external audiences. Implications and future research directions are also discussed.

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.