The relationships between digital media use and mental health have been investigated by various researchers—predominantly psychologists, sociologists, anthropologists, and medical experts—especially since the mid-1990s, after the growth of the World Wide Web. A significant body of research has explored "overuse" phenomena, commonly known as "digital addictions", or "digital dependencies". These phenomena manifest differently in many societies and cultures. Some experts have investigated the benefits of moderate digital media use in various domains, including in mental health, and the treatment of mental health problems with novel technological solutions.

The delineation between beneficial and pathological use of digital media has not been established. There are no widely accepted diagnostic criteria, although some experts consider overuse a manifestation of underlying psychiatric disorders. The prevention and treatment of pathological digital media use is also not standardised, although guidelines for safer media use for children and families have been developed. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) and the International Classification of Diseases (ICD-11) do not include diagnoses for problematic internet use and problematic social media use; the ICD-11 include diagnosis for gaming disorder (commonly known as video game addiction), whereas the DSM-5 does not. Experts are still debating how and when to diagnose these conditions. The use of the term addiction to refer to these phenomena and diagnoses has also been questioned.

Digital media and screen time have changed how children think, interact and develop in positive and negative ways, but researchers are unsure about the existence of hypothesised causal links between digital media use and mental health outcomes. Those links appear to depend on the individual and the platforms they use. Several large technology firms have made commitments or announced strategies to try to reduce the risks of digital media use.

History and terminology

The relationship between digital technology and mental health has been investigated from many perspectives.[1][2][3] Benefits of digital media use in childhood and adolescent development have been found.[4] Concerns have been expressed by researchers, clinicians and the public in regard to apparent compulsive behaviours of digital media users, as correlations between technology overuse and mental health problems become apparent.[1][5][6]

Terminologies used to refer to compulsive digital-media-use behaviours are not standardised or universally recognised. They include "digital addiction", "digital dependence", "problematic use", or "overuse", often delineated by the digital media platform used or under study (such as problematic smartphone use or problematic internet use).[7] Unrestrained use of technological devices may affect developmental, social, mental and physical well-being and may result in symptoms akin to other psychological dependence syndromes, or behavioural addictions.[8][6] The focus on problematic technology use in research, particularly in relation to the behavioural addiction paradigm, is becoming more accepted, despite poor standardisation and conflicting research.[9]

Internet addiction has been proposed as a diagnosis since the mid-1990s,[10] and social media and its relation to addiction has been examined since 2009.[11] A 2018 Organisation for Economic Co-operation and Development (OECD) report noted the benefits of structured and limited internet use in children and adolescents for developmental and educational purposes, but that excessive use can have a negative impact on mental well-being. It also noted an overall 40% increase in internet use in school-age children between 2010 and 2015, and that different OECD nations had marked variations in rates of childhood technology use, as well as differences in the platforms used.[12]

The Diagnostic and Statistical Manual of Mental Disorders has not formally codified problematic digital media use in diagnostic categories, but it deemed internet gaming disorder to be a condition for further study in 2013.[13] Gaming disorder, commonly known as video game addiction, has been recognised in the ICD-11.[14][15] Different recommendations in the DSM and the ICD are due partly to the lack of expert consensus, the differences in emphasis in the classification manuals, as well as difficulties utilising animal models for behavioural addictions.[8]

The utility of the term addiction in relation to overuse of digital media has been questioned, in regard to its suitability to describe new, digitally mediated psychiatric categories, as opposed to overuse being a manifestation of other psychiatric disorders.[2][3] Usage of the term has also been criticised for drawing parallels with substance use behaviours. Careless use of the term may cause more problems—both downplaying the risks of harm in seriously affected people, as well as overstating risks of excessive, non-pathological use of digital media.[3] The evolution of terminology relating excessive digital media use to problematic use rather than addiction was encouraged by Panova and Carbonell, psychologists at Ramon Llull University, in a 2018 review.[16]

Due to the lack of recognition and consensus on the concepts used, diagnoses and treatments are difficult to standardise or develop. Heightened levels of public anxiety around new media (including social media, smartphones and video games) further obfuscate population-based assessments, as well as posing management dilemmas.[2] Radesky and Christakis, the 2019 editors of JAMA Paediatrics, published a review that investigated "concerns about health and developmental/behavioural risks of excessive media use for child cognitive, language, literacy, and social-emotional development."[17] Due to the ready availability of multiple technologies to children worldwide, the problem is bi-directional, as taking away digital devices may have a detrimental effect, in areas such as learning, family relationship dynamics, and overall development.[18]

Problematic use

Though associations have been observed between digital media use and mental health symptoms or diagnoses, causality has not been established; nuances and caveats published by researchers are often misunderstood by the general public, or misrepresented by the media.[3] Females are more likely to overuse social media, and males video games.[19] Following from this, problematic digital media use may not be singular constructs, may be delineated based on the digital platform used, or reappraised in terms of specific activities (rather than addiction to the digital medium).[20]

Screen time and mental health

Main articles: Screen time, Behavioral modernity, Evolutionary mismatch, Major depressive disorder, and Media multitasking

See also: Criticism of Facebook § Psychological/sociological effects, Digital Revolution, Evolutionary medicine, Evolutionary psychiatry, Social aspects of television, Social media and suicide, and Suicide in the United States

In addition to noting with evolutionary biologist George C. Williams in the development of evolutionary medicine that most chronic medical conditions are the consequence of evolutionary mismatches between a stateless environment of nomadic hunter-gatherer life in bands and contemporary human life in sedentary technologically modern state societies (e.g. WEIRD societies),[21] psychiatrist Randolph M. Nesse has argued that evolutionary mismatch is an important factor in the development of certain mental disorders.[22][23][24] In 1890, 1 percent of U.S. households owned at least one telephone, while a majority did by 1946 and 75 percent did by 1957.[25][26] In 1908, 1 percent of U.S. households owned at least one automobile, while 50 percent did by 1948 and 75 percent did by 1960.[27][26] In 1948, 1 percent of U.S. households owned at least one television while 75 percent did by 1955,[26] and by 1992, 60 percent of all U.S. households received cable television subscriptions.[28] In 1980, 1 percent of U.S. households owned at least one videocassette recorder while 75 percent did by 1992.[26] In 2000, a majority of U.S. households had at least one personal computer and internet access the following year.[29]

In 2002, a majority of U.S. survey respondents reported having a mobile phone.[30] In September and December 2006 respectively, Luxembourg and the Netherlands became the first countries to completely transition from analog to digital television, while the United States commenced its transition in 2008. In September 2007, a majority of U.S. survey respondents reported having broadband internet at home.[31] In January 2013, a majority of U.S. survey respondents reported owning a smartphone.[32] According to estimates from Nielsen Media Research, approximately 45.7 million U.S. households in 2006 (or approximately 40 percent of approximately 114.4 million) owned a dedicated home video game console,[33][34] and by 2015, 51 percent of U.S. households owned a dedicated home video game console according to an Entertainment Software Association annual industry report.[35][36]

A 2019 systematic map of reviews suggested associations between some types of potentially problematic internet use and psychiatric or behavioural problems such as depression, anxiety, hostility, aggression and attention deficit hyperactivity disorder (ADHD). The studies could not determine if causal relationships exist, reviewers emphasising the importance of future prospective study designs.[1] While overuse of digital media has been associated with depressive symptoms, digital media may also be utilized in some situations to improve mood.[37][38] Symptoms of ADHD have been positively correlated with digital media use in a large prospective study.[39] The ADHD symptom of hyperfocus may cause affected individuals to overuse video games, social media, or online chatting, however; the correlation between hyperfocus and problematic social media use is weak.[40] Being exposed to high amounts of social media can also affect body image, which can lead to eating disorders, depression and anxiety. There has been research done showing that 84 percent of participants exposed to pro-ED social media developed symptoms of an eating disorder, along with depression and anxiety. This study also showed that only 14 percent of the individuals experiencing symptoms received treatment. The common treatment barriers were not believing their symptoms were serious enough to seek help, or thinking they could just help themselves. These results show that majority of people who are affected by eating disorders by social media will not get the help they need to recover.[41] Additionally, diet-focused social media trends like "What I eat in a day" videos have been shown to have negative impacts on body image.[42]

A 2016 technical report by Chassiakos, Radesky, and Christakis identified benefits and concerns in adolescent mental health regarding digital media use. It showed that the manner of social media use was the key factor, rather than the amount of time engaged. A decline in well-being and life-satisfaction was found in older adolescents who passively consumed social media, but these were not apparent in those who were more actively engaged. The report also found a U-shaped curvilinear relationship in the amount of time spent on digital media, with risk of depression increasing at both the low and high ends of internet use.[4] A 2018 review into the Chinese social media platform WeChat found associations of self-reported mental health symptoms with excessive platform use. However, the motivations and usage patterns of WeChat users affected overall psychological health, rather than the amount of time spent using the platform.[6] In the United Kingdom, a study of 1,479 individuals aged 14–24 compared psychological benefits and problems for five large social media platforms: Facebook, Instagram, Snapchat, Twitter and YouTube. It concluded that YouTube was the only platform with a net positive rating "based on the 14 health and wellbeing-related questions", and the other platforms measured had net negative ratings, Instagram having the lowest rating. The study identified Instagram as having some positive effects including self-expression, self-identity, and community, but found that these were outweighed by the negative effects, specifically on sleep, body image, and "fear of missing out".[43]

A report published in Clinical Psychological Science in 2018 featured two cross-sectional surveys of 506,820 American high school students, and found that use of digital media was associated with higher rates of depressive symptoms and suicidality. They concluded that more time engaged with electronic devices, and less time on "non-screen activities" (such as in-person social interaction, sports/exercise, homework, and attending religious services) was correlated with depressive symptoms and suicide-related outcomes (suicidal ideation, plans, and attempts), especially among girls.[44] A later report in the same publication questioned the survey's research methodology, citing "inaccurate research measurements, negligible correlations between the main variables, [and] insufficient and inadequate statistical analyses".[45]

The relationship between bipolar disorder and technology use has been investigated in a singular survey of 84 participants for Computers in Human Behavior. The survey found marked variations in technology use based on self-reported mood states. The authors of the report then postulated that for patients with bipolar disorder, technology may be a "double-edged sword", with potential benefits and harms.[46]

Fear of missing out (FoMO) is a disruptive behavioral phenomenon that causes emotional stress. Studies show that the more social media accounts an individual has, the higher chance they have FoMO. There is a direct correlation between the number of accounts an individual has and the individual's levels of anxiety and depression.[47]

There is no significant link between ethnicity and FoMO/overall loneliness meaning anxiety and depression caused by FoMO from social media is consistent across the board for all ethnicities.[47]

A US study done in 2019 found an association between social media and depression in adolescence. Based on the upward social comparison, it may be that repeated exposure to idealized images lowers adolescents' self-esteem, triggers depression, and enhances depression over time. Furthermore, heavier users of social media with depression appear to be more negatively affected by their time spent on social media, potentially by the nature of information that they select (e.g., blog posts about self-esteem issues), consequently potentially maintaining and enhancing depression over time.[48]

In February 2019, experimental psychologists Amy Orben and Andrew K. Przybylski published a specification curve analysis of data from the Monitoring the Future survey, the Millennium Cohort Study, and the Youth Risk Behavior Surveillance System that included a total of 355,358 subjects in Nature Human Behaviour to examine the correlational evidence for negative effects of digital technology on adolescent well-being and found that digital technology use accounted for only 0.4% of the variance and that such a small change did not require public policy changes and that the weight given to digital screen time in scientific and public discourse is outsized.[49] In May 2019, Orben and Przybylski published a subsequent specification curve analysis in Psychological Science of three nationally representative samples from data sets including 17,247 subjects from the Republic of Ireland, the United States, and the United Kingdom including time-use diary studies and found little evidence for substantial negative associations for digital screen engagement and adolescent well-being and noted that correlations between retrospective self-reports and time diaries are too low for retrospective self-reports to be useful.[50]

In February 2020, Frontiers in Psychology published a commentary on Orben and Przybylski's May 2019 study from psychologists Jean Twenge, Andrew B. Blake, Jonathan Haidt, and W. Keith Campbell that noted that the conclusion of Orben and Przybylski's analysis that there is no meaningful link between screen time measured with time diaries and adolescent well-being made six analytical decisions (e.g. relying solely on linear correlations, primarily measuring participation in digital media activities rather than time spent, combining all types of screen time, not separating data by gender) that substantially reduced the size of the relationship and noted that the data sets Orben and Przybylski cite do demonstrate a clear and substantial relationship between depression and heavier usage of social media for girls (consistent with other research by Twenge and Haidt).[51]

In April 2020, Nature Human Behaviour published a response to Orben and Przybylski's February 2019 study from Twenge, Haidt, Thomas Joiner, and Campbell that noted that Orben and Przybylski likewise made six analytical decisions (e.g. only considering monotonic effects, combining all types of screen time and not separating data by gender, excluding hours-per-week items on non-television digital media such as social media, internet use, gaming, texting, and video chat) that lowered the effect sizes of their analysis, noting instead that all three of the datasets that they included in their analysis contained data that indicates that heavy use of social media is consistently associated with non-trivial negative mental health outcomes for girls, and considering the rising rates of depression, anxiety, self-harm, and suicide among girls in the United States and other countries that no other researchers have found a plausible alternative explanation for, Twenge et al. conclude instead that screen time research should not be dismissed in scientific and public discourse.[52]

A systematic examination of reviews, published in 2019, concluded that evidence, although of mainly low to moderate quality, showed an association of screen time with a variety of health problems including: "adiposity, unhealthy diet, depressive symptoms and quality of life". They also concluded that moderate use of digital media may have benefits for young people in terms of social integration, a curvilinear relationship found with both depressive symptoms and overall well-being.[5]

A research study done on urban adolescents in China revealed that more than a quarter of adolescents in China were exposed to over 2 hours of screen time per day. They found that screen time and physical activity was independently associated with mental health. Specifically, an increase in screen time and decrease in physical activity contributed to an additional risk for mental health productivity by increasing depressive anxiety symptoms and life dissatisfaction.[53]

A 2017 UK large-scale study of the "Goldilocks hypothesis"—of avoiding both too much and too little digital media use[54]—was described as the "best quality" evidence to date by experts and non-government organisations (NGOs) reporting to a 2018 UK parliamentary committee. That study concluded that modest digital media use may have few adverse affects, and some positive associations in terms of well-being.[55]

A study by The Lancet Child & Adolescent Health in 2019 showed a relationship between social media use by girls and an increase in their exposure to bullying, reduction in sleep and exercise.[56]

Social media can be harmful especially to pre-teens and teenagers who are still growing and discovering their bodies. In a peer reviewed article titled "The Paradox of Tik Tok Anti-Pro Anorexia Videos: How Social Media Can Promote Non-Suicidal Self-Injury and Anorexia" writers stated the impact that TikTok has on this generation especially since the beginning of COVID-19. While the exposure of anorexic bodies can be harmful to adolescents, writers claim that it could be helpful to talk about it. It appears that videos showing thinner bodies got more exposure, likes, and engagement than the videos showing bodies with a bigger frame.[57]

ADHD

Main articles: Attention deficit hyperactivity disorder, Like button, and Suicide in the United States § Health or Disability

See also: Criticism of Facebook § Facebook addiction, Facebook like button, Human multitasking, Law of effect, Mobile phones and driving safety, Problematic smartphone use, Problematic social media use, and Texting while driving

In September 2014, Developmental Psychology published a meta-analysis of 45 studies investigating the relationship between media use and ADHD-related behaviors in children and adolescents and found a small but significant relationship between media use and ADHD-related behaviors.[58] In March 2016, Frontiers in Psychology published a survey of 457 post-secondary student Facebook users (following a face validity pilot of another 47 post-secondary student Facebook users) at a large university in North America showing that the severity of ADHD symptoms had a statistically significant positive correlation with Facebook usage while driving a motor vehicle and that impulses to use Facebook while driving were more potent among male users than female users.[59] In June 2018, Children and Youth Services Review published a regression analysis of 283 adolescent Facebook users in the Piedmont and Lombardy regions of Northern Italy (that replicated previous findings among adult users) showing that adolescents reporting higher ADHD symptoms positively predicted Facebook addiction, persistent negative attitudes about the past and that the future is predetermined and not influenced by present actions, and orientation against achieving future goals, with ADHD symptoms additionally increasing the manifestation of the proposed category of psychological dependence known as "problematic social media use."[60]

In April 2015, the Pew Research Center published a survey of 1,060 U.S. teenagers ages 13 to 17 who reported that nearly three-quarters of them either owned or had access to a smartphone, 92 percent went online daily with 24 percent saying they went online "almost constantly."[61] Citing Centers for Disease Control data showing that nearly one-fourth of all deaths in the United States in 2014 for people ages 15 to 24 were in motor vehicle accidents, psychiatrist Randolph M. Nesse has noted that fear of dangers in operating a motor vehicle cannot have a prewired learning module, and along with evolutionary biologist George C. Williams and psychiatrist Isaac Marks, Nesse has noted that people with systematically deficient fear responses to various adaptive phobias (e.g. basophobia, ophidiophobia, arachnophobia) are more temperamentally careless and more likely to receive unintentional injuries that are potentially fatal, and Marks, Williams, and Nesse have proposed that such deficient phobia should be classified as "hypophobia" due to its selfish genetic consequences.[62][63][64][65]

In July 2018, the Journal of the American Medical Association published a two-month longitudinal cohort survey of 3,051 U.S. teenagers ages 15 and 16 (recruited at 10 different Los Angeles County, California secondary schools by convenience sampling) self-reporting engagement in 14 different modern digital media activities at high-frequency. 2,587 had no significant symptoms of ADHD at baseline with a mean number of 3.62 modern digital media activities used at high-frequency and each additional activity used frequently at baseline positively correlating with a significantly higher frequency of ADHD symptoms at follow-ups. Of the 495 who reported no high-frequency digital media activities at baseline had a 4.6% mean rate of having ADHD symptoms at follow-ups, while the 114 who reported 7 high-frequency activities had a 9.5% mean rate and the 51 with 14 high-frequency activities had a 10.5% mean rate (indicating a statistically significant but modest association between higher frequency of digital media use and subsequent symptoms of ADHD).[66][67][68] In October 2018, PNAS USA published a systematic review of four decades of research on the relationship between children and adolescents' screen media use and ADHD-related behaviors and concluded that a statistically small relationship between children's media use and ADHD-related behaviors exists.[69]

In April 2019, PLOS One published the results of a longitudinal birth cohort study of screen-time use reported by parents of 2,322 children in Canada at ages 3 and 5 and found that compared to children with less than 30 minutes per day of screen-time, children with more than 2 hours of screen-time per day had a 7.7-fold increased risk of meeting criteria for ADHD.[70] In January 2020, the Italian Journal of Pediatrics published a cross-sectional study of 1,897 children from ages 3 through 6 attending 42 kindergartens in Wuxi, China that also found that children exposed to more than 1 hour of screen-time per day were at increased risk for the development of ADHD and noted its similarity to a finding relating screen-time and the development of autism (ASD).[71] In November 2020, Infant Behavior and Development published a study of 120 3-year-old children with or without family histories of ASD or ADHD (20 with ASD, 14 with ADHD, and 86 for comparison) examining the relationship between screen time, behavioral outcomes, and expressive/receptive language development that found that higher screen time was associated with lower expressive/receptive language scores across comparison groups and that screen time was associated with behavioral phenotype, not family history of ASD or ADHD.[72]

In November 1999, Biological Psychiatry published a literature review by psychiatrists Joseph Biederman and Thomas Spencer on the pathophysiology of ADHD that found the average heritability estimate of ADHD from twin studies to be 0.8,[73] while a subsequent family, twin, and adoption studies literature review published in Molecular Psychiatry in April 2019 by psychologists Stephen Faraone and Henrik Larsson that found an average heritability estimate of 0.74.[74] Additionally, Randolph M. Nesse has argued that the 5:1 male-to-female sex ratio in the epidemiology of ADHD suggests that ADHD may be the end of a continuum where males are overrepresented at the tails, citing clinical psychologist Simon Baron-Cohen's suggestion for the sex ratio in the epidemiology of autism as an analogue.[75][76][77]

In the journal Globalization and Health Article number: Vol 17(48) (2021) Shauai et al. published a study titled Influences of digital media use on children and adolescents with ADHD during COVID-19 pandemic. They explored the influence of digital media on the core symptoms, emotional state, life events, learning motivation, executive function (EF), and family environment of children and adolescents diagnosed with ADHD. They included participants age 8 to 16 who met the criteria for ADHD and included a group who had problematic digital media use (PDMU) and a group who met the ADHD criteria who did not have PDMU. The study analyzed the differences between the groups in ADHD symptoms, EF, anxiety, and depression, stress from life events, learning motivation, and family environment were compared respectively. The research concluded that the ADHD children with PDMU displayed more severe symptoms, negative emotions, impairments in executive functioning, difficulties in family functioning, pressure from life events, and a lower learning motivation than those who did not have PMDU. The research suggested that for children and adolescents who struggle with ADHD, it is essential to supervise digital media usage and increase physical exercise for better management of core symptoms and other associated difficulties associated with ADHD.[78]

Researchers Siddharth Sagar, Dr. Navin Kumarhttp published a study in Psychology and Education Vol.58 No.4 (2021) titled Usages of Social Media and Symptoms of Attention Deficit Hyperactivity Disorder (ADHD): A Cross-Sectional Study. The study aimed to empirically test the association between social media usage and ADHD. They hypothesized that social media users will significantly differ in demographic variables such as age, gender, and education and that ADHD would be significantly associated with social media usage. The study did suggest that ADHD is significantly associated with addictive or excessive social media use and that addictive social media use was associated with being female, being a young individual, and with undergraduate-aged individuals. They further concluded that individuals with high social media usage have higher incidences[spelling?] of ADHD in comparison to average or low-frequency users. They suggest this may be due to social media being an ideal outlet for constant touching, fidgeting, and frequent shifts from one activity to another when bored or feeling inattentive. These are common ADHD behaviors (American Psychiatric Association, 2013). [79]

Autism

Main articles: Autism spectrum, Suicide in the United States § Health or Disability, and Video game addiction

See also: Evolutionary psychiatry § Autism spectrum disorder (ASD), PC bang, and Video games in the United States

In February 2017, PLOS One published a systematic review of 35 studies examining the prevalence of physical activity and sedentary behaviors and their potential correlates among children with autism spectrum disorder (ASD) and found that 15 reported physical activity prevalence, 10 reported physical activity correlates, 18 reported sedentary behavior prevalence, and 10 reported sedentary behavior correlates, and age was consistently inversely associated with physical activity, but noted that all but one of the studies were classified as having high risk of selection bias and that more research was needed to consistently identify the correlates of the behaviors.[80] In September 2017, Scientific Reports published a meta-analysis of 15 epidemiological studies totaling 49,937,078 participants including 1,045,538 with ASD used a random effects model to examine associations between obesity, overweight, and ASD and found that while the prevalence of overweight participants with ASD was not significantly different from the control group, the prevalence of obesity was significantly higher among ASD participants than the control group.[81]

In April 2018, Child and Adolescent Psychiatric Clinics of North America published a study of data from the American Academy of Child and Adolescent Psychiatry that found that children with ASD surveyed spent 4.5 hours more per day on screen time than typically developing peers, that children with ASD spent most of their free time on screen time as compared with 18% of typically developing peers, and that children with ASD played video games 1 hour more per day than typically developing peers and tended to prefer video games over television. Conversely, more than half of children with ASD surveyed had never played with a friend over electronic media, with only 15% engaging with friends in this way on a weekly basis and 64% using electronic media primarily non-socially (e.g. to play video games alone or with strangers, or surfing gaming web sites).[82]

In October 2018, Evidence-Based Mental Health published a meta-analysis of 47 data sets using a random effects model to examine associations between sleep problems and ASD on 14 subjective and 14 objective sleep parameters and found that as compared with control groups, ASD participants differed significantly on 10 of the 14 subjective parameters and 7 of the 14 objective parameters.[83] In November 2018, the Journal of Autism and Developmental Disorders published a study examining associations between environmental factors physical activity and screen time among 1,380 children with ASD and 1,411 children without ASD and found that the absence of a bedroom television and neighborhood support for children without ASD were associated with physical activity, while a bedroom television and no parental limits on screen time was associated with screen time for children with ASD.[84]

In May 2019, Behavioral Sciences published an online parental survey of 327 children with ASD that found that children with ASD mostly use television and after conducting 13 in-person interviews with parents the researchers concluded that screen media usage by children with ASD should be supervised.[85] In November 2020, Infant Behavior and Development published a study of 120 3-year-old children with or without family histories of ASD or ADHD (20 with ASD, 14 with ADHD, and 86 for comparison) examining the relationship between screen time, behavioral outcomes, and expressive/receptive language development that found that higher screen time was associated with lower expressive/receptive language scores across comparison groups and that screen time was associated with behavioral phenotype, not family history of ASD or ADHD.[72]

In February 2021, Frontiers in Psychiatry published a study of 101 children with ASD and 57 children without ASD to examine the relationship between screen time of children with ASD and their development quotients and found that screen time for children with ASD was longer among children with ASD (3.34 ± 2.64 hours) than children without (0.91 ± 0.93 hours) and screen time for children with ASD was positively correlated with the Childhood Autism Rating Scale.[86]

Insomnia

Main articles: Insomnia and Screen time § Sleep

See also: Circadian rhythm, Circadian rhythm sleep disorder, Light effects on circadian rhythm, Obesity, and Obesity in the United States

In August 2018, Sleep Medicine Reviews published a meta-analysis performed by psychiatrists Wai Sze Chan, Meredith P. Levsen, and Christina S. McCrae of 67 studies published since 2008 that found that multilevel random effects models showed that the odds of being obese among those who had an insomnia diagnosis was not significantly greater than the odds of being obese and not receiving an insomnia diagnosis, while a small but significant cross-sectional correlation was found between insomnia symptoms and body mass index, longitudinal data was limited to three studies that showed that developing insomnia symptoms in the future among the obese was not significantly greater than among the non-obese, finding the research to be inconclusive.[87]

In May 2019, Sleep Medicine published a study of 2,865 U.S. adolescents at the age 15 follow-up of the Fragile Families and Child Wellbeing Study who completed surveys quantifying personal sleep duration and insomnia symptoms, screen time use of social messaging, web surfing, television or movie watching, and gaming, and depressive systems and the researchers constructed a multiple mediation model while controlling for depressive symptoms at age 9 to identify associations between age 15 screen time, sleep, and depressive symptoms, and found through structural equation modeling that the association for social messaging, web surfing, and television and movie watching, the three sleep variables fully mediated the positive association between screen time and depressive symptoms while for gaming the sleep variables only accounted for 38.5% of the association between gaming and depressive symptoms.[88]

In November 2019, Psychiatry Research published a study of a nationally representative sample of 14,603 U.S. adolescents aged 14–18 years from the 2017 Youth Risk Behavior Survey examining the association between excessive screen time and behaviors and insufficient sleep among adolescents using a logistic regression with insufficient sleep and the excessive screen time behaviors as the outcome and explanatory variables respectively and found that the odds for adolescents engaging in excessive screen time behaviors to be receiving insufficient sleep (controlling for all other predictors) was 1.34 times higher than adolescents not engaging in excessive screen time behaviors, with 74.8% of adolescents in the survey receiving less than 8 hours of sleep on an average school night and 43% engaging in excessive screen behaviors.[89]

In December 2019, Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity published a survey of a sample of 6,419 adults in Mexico from the 2016 National Health and Nutrition Survey in self-reported differences in sleep duration, insomnia symptoms, television screen time, total screen time, degree of physical activity with body mass index used to categorize participants and found that of the 39% and 37% of participants categorized as overweight and obese respectively, television screen time, total screen time, sleep duration, and physical activity were significantly correlated with being overweight or obese, with Obese II and Obese III participants spending 30 minutes on average more than normal weight participants in front of any screen and Obese II reporting 30 minutes less sleep on average and Obese III less likely to engage in physical activity.[90]

In February 2020, Sleep Medicine Reviews published a systematic review of 31 studies examining associations between screen time or movement behaviors (sedentary vs. physical activity) and sleep outcomes in children younger than 5 years following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and that performed a Grading of Recommendations Assessment, Development and Evaluation with subjects stratified by age and found that screen time is associated with poorer sleep outcomes for children under the age of 5, with meta-analysis only confirming poor sleep outcomes among children under 2 years while for movement behaviors evidence was mixed but that physical activity and outdoor play among children 1–4 were favorably associated.[91]

NPD

Main articles: Narcissistic personality disorder, Dark triad, and Like button

See also: Criticism of Facebook § Narcissism, Facebook like button, Fear of missing out, Law of effect, Malignant narcissism, Mass shootings in the United States § Contributing factors, Microblogging, Objectification, Reblogging, Selfie, Slacktivism, Tokenism, Virtue signalling, and White savior

In July 2018, a meta-analysis published in Psychology of Popular Media found that grandiose narcissism positively correlated with time spent on social media, frequency of status updates, number of friends or followers, and frequency of posting self-portrait digital photographs,[92] while a meta-analysis published in the Journal of Personality in April 2018 found that the positive correlation between grandiose narcissism and social networking service usage was replicated across platforms (including Facebook and Twitter).[93] In March 2020, the Journal of Adult Development published a regression discontinuity analysis of 254 Millennial Facebook users investigating differences in narcissism and Facebook usage between the age cohorts born from 1977 to 1990 and from 1991 to 2000 and found that the later born Millennials scored significantly higher on both.[94] In June 2020, Addictive Behaviors published a systematic review finding a consistent, positive, and significant correlation between grandiose narcissism and problematic social media use.[95] Also in 2018, social psychologist Jonathan Haidt and FIRE President Greg Lukianoff noted in The Coddling of the American Mind that former Facebook president Sean Parker stated in a 2017 interview that the Facebook like button was consciously designed to prime users receiving likes to feel a dopamine rush as part of a "social-validation feedback loop".[96]

"Conspicuous compassion" is the practice of publicly donating large sums of money to charity to enhance the social prestige of the donor, and is sometimes described as a type of conspicuous consumption.[97][98] Jonathan Haidt and Greg Lukianoff argued that microaggression training on college campuses in the United States has led to a call-out culture and a climate of self-censorship due to fear of shaming by virtue signalling social media mobs with users who are often anonymous and tend to deindividuate as a consequence.[99] Citing February 2017 Pew Research Center survey data showing that critical Facebook postings expressing "indignant disagreement" were twice as likely to receive likes, comments, or shares (along with a similar finding for Twitter posts published in PNAS USA in July 2017),[100][101] Haidt and Tobias Rose-Stockwell cited the phrase "moral grandstanding" in The Atlantic in December 2019 to describe how having an audience on social media forums converts much of its interpersonal communication into a public performance.[102]

Following the murder of George Floyd in May 2020 and the subsequent protests in his name, Civiqs and YouGov/Economist polls showed that while net support for Black Lives Matter among White Americans increased from −4 points to +10 points in early June 2020 (with 43 percent in support) it fell to −6 points by early August 2020,[103] and by April 2021, further Civiqs polls showed that support for Black Lives Matter among White Americans had reverted to roughly its level of support prior to George Floyd's murder (37 percent in favor and 49 percent opposed).[104] In a February 2021 interview on Firing Line, journalist Charles M. Blow criticized a minority of young white protestors in the George Floyd protests in the United States whom he argued were using the protests for their own personal growth to substitute for social rites of passage (e.g. prom) and summertime social gatherings (e.g. attending movie theaters or concerts) that were precluded by COVID-19 lockdowns and social distancing measures, noting that as lockdowns began to be relaxed and removed, support for Black Lives Matter among whites began to decline.[105]

In February 2021, Psychological Medicine published a survey reviewing 14,785 publicly reported murders in English language news worldwide between 1900 and 2019 compiled in a database by psychiatrists at the New York State Psychiatric Institute and the Columbia University Irving Medical Center that found that of the 1,315 personal-cause mass murders (i.e. driven by personal motivations and not occurring within the context of war, state-sponsored or group-sponsored terrorism, gang activity, or organized crime) only 11 percent of mass murderers and only 8 percent of mass shooters had a "serious mental illness" (e.g. schizophrenia, bipolar disorder, major depressive disorder), that mass shootings have become more common than other forms of mass murder since 1970 (with 73 percent occurring in the United States alone), and that mass shooters in the United States were more likely to have legal histories, to engage in recreational drug use or alcohol abuse, and to display non-psychotic psychiatric or neurologic symptoms.[106][107][108]

Survey coauthor psychiatrist Paul S. Appelbaum argued that the data from the survey indicated that "difficulty coping with life events seem more useful foci for prevention [of mass shootings] and policy than an emphasis on serious mental illness",[109] while psychiatrist Ronald W. Pies has suggested that psychopathology should be understood as a three-gradation continuum of mental, behavioral and emotional disturbance with most mass shooters falling into a middle category of "persistent emotional disturbance".[110] In 2015, psychiatrists James L. Knoll and George D. Annas noted that the tendency of most media attention following mass shootings on mental health leads to sociocultural factors being comparatively overlooked.[111] Instead, Knoll and Annas cite research by social psychologists Jean Twenge and W. Keith Campbell on narcissism and social rejection in the personal histories of mass shooters, as well as cognitive scientist Steven Pinker's suggestion in The Better Angels of Our Nature (2011) that further reductions in human violence may be dependent upon reducing human narcissism.[112][113]

Proposed diagnostic categories

See also: Internet addiction disorder, Internet sex addiction, Nomophobia, Problematic smartphone use, Problematic social media use, and Video game addiction

Gaming disorder has been considered by the DSM-5 task force as warranting further study (as the subset internet gaming disorder), and was included in the ICD-11.[13] Concerns have been raised by Aarseth and colleagues over this inclusion, particularly in regard to stigmatisation of heavy gamers.[114]

Christakis has asserted that internet addiction may be "a 21st century epidemic".[115] In 2018, he commented that childhood Internet overuse may be a form of "uncontrolled experiment[s] on ... children".[116] International estimates of the prevalence of internet overuse have varied considerably, with marked variations by nation. A 2014 meta-analysis of 31 nations yielded an overall worldwide prevalence of six percent.[117] A different perspective in 2018 by Musetti and colleagues reappraised the internet in terms of its necessity and ubiquity in modern society, as a social environment, rather than a tool, thereby calling for the reformulation of the internet addiction model.[118]

Some medical and behavioural scientists recommend adding a diagnosis of "social media addiction" (or similar) to the next Diagnostic and Statistical Manual of Mental Disorders update.[119][120][6] A 2015 review concluded there was a probable link between basic psychological needs and social media addiction. "Social network site users seek feedback, and they get it from hundreds of people—instantly. It could be argued that the platforms are designed to get users 'hooked'."[121]

Internet sex addiction, also known as cybersex addiction, has been proposed as a sexual addiction characterised by virtual internet sexual activity that causes serious negative consequences to one's physical, mental, social, and/or financial well-being.[122][123] It may be considered a form of problematic internet use.[124]

Related phenomena

Luckia Games, an online gambling provider
Luckia Games, an online gambling provider

Online problem gambling

Main article: Online gambling § Problem gambling

A 2015 review found evidence of higher rates of mental health comorbidities, as well as higher amounts of substance use, among internet gamblers, compared to non-internet gamblers. Causation, however, has not been established. The review postulates that there may be differences in the cohorts between internet and land-based problem gamblers.[125]

Cyberbullying

Main article: Cyberbullying

Cyberbullying, bullying or harassment using social media or other electronic means, has been shown to have effects on mental health. Victims may have lower self-esteem, increased suicidal ideation, decreased motivation for usual hobbies, and a variety of emotional responses, including being scared, frustrated, angry, anxious or depressed. These victims may also begin to distance themselves from friends and family members.[126]

According to the EU Kids Online project, the incidence of cyberbullying across seven European countries in children aged 8–16 increased from 8% to 12% between 2010 and 2014. Similar increases were shown in the United States and Brazil.[127]

Media multitasking

Main article: Media multitasking

Concurrent use of multiple digital media streams, commonly known as media multitasking, has been shown to be associated with depressive symptoms, social anxiety, impulsivity, sensation seeking, lower perceived social success and neuroticism.[128] A 2018 review found that while the literature is sparse and inconclusive, overall, heavy media multitaskers also have poorer performance in several cognitive domains.[129] One of the authors commented that the data does not "unambiguously show that media multitasking causes a change in attention and memory", therefore it is possible to argue that it is inefficient to multitask on digital media.[130]

Assessment and treatment

Rigorous, evidence-based assessment of problematic digital media use is yet to be comprehensively established. This is due partially to a lack of consensus around the various constructs and lack of standardization of treatments.[131] The American Academy of Pediatrics (AAP) has developed a Family Media Plan, intending to help parents assess and structure their family's use of electronic devices and media more safely. It recommends limiting entertainment screen time to two hours or less per day.[132][133] The Canadian Paediatric Society produced a similar guideline. Ferguson, a psychologist, has criticised these and other national guidelines for not being evidence-based.[134] Other experts, cited in a 2017 UNICEF Office of Research literature review, have recommended addressing potential underlying problems rather than arbitrarily enforcing screen time limits.[3]

Different methodologies for assessing pathological internet use have been developed, mostly self-report questionnaires, but none have been universally recognised as a gold standard.[135] For gaming disorder, both the American Psychiatric Association[136] and the World Health Organization (through the ICD-11)[14] have released diagnostic criteria.

There is some limited evidence of the effectiveness of cognitive behavioral therapy and family-based interventions for treatment. In randomised controlled trials, medications have not been shown to be effective.[131] A 2016 study of 901 adolescents suggested mindfulness may assist in preventing and treating problematic internet use.[137] A 2019 UK parliamentary report deemed parental engagement, awareness and support to be essential in developing "digital resilience" for young people, and to identify and manage the risks of harm online.[55] Treatment centers have proliferated in some countries, and China and South Korea have treated digital dependence as a public health crisis, opening 300 and 190 centers nationwide, respectively.[138] Other countries have also opened treatment centers.[139][140]

NGOs, support and advocacy groups provide resources to people overusing digital media, with or without codified diagnoses,[141][142] including the American Academy of Child and Adolescent Psychiatry.[143][144]

A 2022 study outlines the mechanisms by which media-transmitted stressors affect mental well-being. Authors suggest a common denominator related to problems with the media's construction of reality is increased uncertainty, which leads to defensive responses and chronic stress in predisposed individuals.[145]

Mental health benefits

Smartphones and other digital devices are ubiquitous in many societies.
Smartphones and other digital devices are ubiquitous in many societies.

Individuals with mental illness can develop social connections over social media, that may foster a sense of social inclusion in online communities.[4] People with mental illness may share personal stories in a perceived safer space, as well as gaining peer support for developing coping strategies.[4]

People with mental illness are likely to report avoiding stigma and gaining further insight into their mental health condition by using social media. This comes with the risk of unhealthy influences, misinformation, and delayed access to traditional mental health outlets.[4]

Other benefits include connections to supportive online communities, including illness or disability specific communities, as well as the LGBTQIA community. Young cancer patients have reported an improvement in their coping abilities due to their participation in an online community.[146] The uses of social media for healthcare communication include providing reducing stigma and facilitating dialogue between patients and between patients and health professionals.[147]

Furthermore, in children, the educational benefits of digital media use are well established.[4]

According to the American Addiction Centers, apps like TikTok are also helpful for its users to share their stories of recovery, celebrating milestones, and cheering on others on the path to recovery. Hashtags such as, #sober, #mentalhealthawareness, and #soberlife are helping to destigmatize sobriety.[148]

Other disciplines

Digital anthropology

Daniel Miller from University College London has contributed to the study of digital anthropology, especially ethnographic research on the use and consequences of social media and smartphones as part of the everyday life of ordinary people around the world. He notes the effects of social media are very specific to individual locations and cultures. He contends "a layperson might dismiss these stories as superficial. But the anthropologist takes them seriously, empathetically exploring each use of digital technologies in terms of the wider social and cultural context."[149]

Digital anthropology is a developing field which studies the relationship between humans and digital-era technology. It aims to consider arguments in terms of ethical and societal scopes, rather than simply observing technological changes.[150] Brian Solis, a digital analyst and anthropologist, stated in 2018, "we've become digital addicts: it's time to take control of technology and not let tech control us".[151]

Digital sociology

Digital sociology explores how people utilise digital media using several research methodologies, including surveys, interviews, focus groups, and ethnographic research. It intersects with digital anthropology, and studies cultural geography. It also investigates longstanding concerns, and contexts around young people's overuse of "these technologies, their access to online pornography, cyber bullying or online sexual predation".[152]

A 2012 cross-sectional sociological study in Turkey showed differences in patterns of internet use that related to levels of religiosity in 2,698 subjects. With increasing religiosity, negative attitudes towards internet use increased. Highly religious people showed different motivations for internet use, predominantly searching for information.[153] A study of 1,296 Malaysian adolescent students found an inverse relationship between religiosity and internet addiction tendency in females, but not males.[154]

A 2018 review published in Nature considered that young people may have different experiences online, depending on their socio-economic background, noting lower-income youths may spend up to three hours more per day using digital devices, compared to higher-income youths.[155] They theorised that lower-income youths, who are already vulnerable to mental illness, may be more passive in their online engagements, being more susceptible to negative feedback online, with difficulty self-regulating their digital media use. It concluded that this may be a new form of digital divide between at-risk young people and other young people, pre-existing risks of mental illness becoming amplified among the already vulnerable population.[155]

Neuroscience

Dar Meshi and colleagues noted in 2015 that "[n]euroscientists are beginning to capitalise on the ubiquity of social media use to gain novel insights about social cognitive processes".[156] A 2018 neuroscientific review published in Nature found the density of the amygdala, a brain region involved in emotional processing, is related to the size of both offline and online social networks in adolescents. They considered that this and other evidence "suggests an important interplay between actual social experiences, both offline and online, and brain development". The authors postulated that social media may have benefits, namely social connections with other people, as well as managing impressions people have of other people such as "reputation building, impression management, and online self-presentation". It identified "adolescence [as] a tipping point in development for how social media can influence their self-concept and expectations of self and others", and called for further study into the neuroscience behind digital media use and brain development in adolescence.[157] Although brain-imaging modalities are under study, neuroscientific findings in individual studies often fail to be replicated in future studies, similar to other behavioural addictions; as of 2017, the exact biological or neural processes that could lead to excessive digital media use are unknown.[3]

Impact on cognition

There is research and development about the cognitive impacts of smartphones and digital technology. A group reported that, contrary to widespread belief, scientific evidence doesn't show that these technologies harm biological cognitive abilities and that they instead only change predominant ways of cognition – such as a reduced need to remember facts or conduct mathematical calculations by pen and paper outside contemporary schools. However, some activities – like reading novels – that require long focused attention-spans and don't feature ongoing rewarding stimulation may become more challenging in general.[158][159] How extensive online media usage impacts cognitive development in youth is under investigation[160] and impacts may substantially vary by the way and which technologies are being used – such as which and how digital media platforms are being used – and how these are designed. Impacts may vary to a degree such studies have not yet taken into account and may be modulatable by the design, choice and use of technologies and platforms, including by the users themselves.

Measured results of the study
Measured results of the study

A study suggests that in children aged 8–12 during two years, time digital gaming or watching digital videos can be positively correlated with measures intelligence, albeit correlations with overall screen time (including social media, socializing and TV) were not investigated and 'time gaming' did not differentiate between categories of video games (e.g. shares of games' platform and genre), and digital videos did not differentiate between categories of videos.[161][162]

Impact on social life

Worldwide adolescent loneliness in contemporary schools and depression increased substantially after 2012 and a study found this to be associated with smartphone access and Internet use.[163][164] However, smartphone and Internet technologies also have potentials and implemented use-cases for positive impacts on social life which is inextricably linked to mental health.

Digital mental health care

"Wellmind", a United Kingdom National Health Service smartphone application
"Wellmind", a United Kingdom National Health Service smartphone application

Digital technologies have also provided opportunities for delivery of mental health care online; benefits have been found with computerised cognitive behavioural therapy for depression and anxiety.[165] Research of digital health interventions in young people is preliminary, with a meta-review unable to draw firm conclusions because of problems in research methodology.[166] Potential benefits according to one review include "the flexibility, interactivity, and spontaneous nature of mobile communications ... in encouraging persistent and continual access to care outside clinical settings".[167] Mindfulness based online intervention has been shown to have small to moderate benefits on mental health. The greatest effect size was found for the reduction of psychological stress. Benefits were also found regarding depression, anxiety, and well-being.[168] Smartphone applications have proliferated in many mental health domains, with "demonstrably effective" recommendations listed in a 2016 review encouraging cognitive behavioural therapy, addressing both anxiety and mood. The review did however call for more randomised controlled trials to validate the effectiveness of their recommendations when delivered by digital apps.[165]

The Lancet commission on global mental health and sustainability report from 2018 evaluated both benefits and harms of technology. It considered the roles of technologies in mental health, particularly in public education; patient screening; treatment; training and supervision; and system improvement.[169] A study in 2019 published in Front Psychiatry in the National Center for Biotechnology Information states that despite proliferation of many mental health apps there has been no "equivalent proliferation of scientific evidence for their effectiveness."[170]

Steve Blumenfield and Jeff Levin-Scherz, writing in the Harvard Business Review, claim that "most published studies show telephonic mental health care is as effective as in-person care in treating depression, anxiety and obsessive-compulsive disorder." The also cite a 2020 study done with the Veterans Administration as evidence of this as well.[171]

Industry and government

Several technology firms have implemented changes intending to mitigate the adverse effects of excessive use of their platforms, and in Japan, China and South Korea legislative and/or regulatory governmental efforts have been enacted to address the interrelated issues.

In December 2017, Facebook admitted passive consumption of social media could be harmful to mental health, although they said active engagement can have a positive effect. In January 2018, the platform made major changes to increase user engagement.[172] In January 2019, Facebook's then head of global affairs, Nick Clegg, responding to criticisms of Facebook and mental health concerns, stated they would do "whatever it takes to make this environment safer online especially for youngsters". Facebook admitted "heavy responsibilities" to the global community, and invited regulation by governments.[173] In 2018 Facebook and Instagram announced new tools that they asserted may assist with overuse of their products.[174] In 2019, Instagram, which has been investigated specifically in one study in terms of addiction,[175] began testing a platform change in Canada to hide the number of "likes" and views that photos and videos received in an effort to create a "less pressurised" environment.[176] It then continued this trial in Australia, Italy, Ireland, Japan, Brazil and New Zealand[177] before extending the experiment globally in November of that year. The platform also developed artificial intelligence to counter cyberbullying.[178]

China's Ministry of Culture has enacted several public health efforts from as early as 2006 to address gaming and internet-related disorders. In 2007, an "Online Game Anti-Addiction System" was implemented for minors, restricting their use to 3 hours or less per day. The ministry also proposed a "Comprehensive Prevention Program Plan for Minors' Online Gaming Addiction" in 2013, to promulgate research, particularly on diagnostic methods and interventions.[179] China's Ministry of Education in 2018 announced that new regulations would be introduced to further limit the amount of time spent by minors in online games.[180][181] In response, Tencent, the owner of WeChat and the world's largest video game publisher, restricted the amount of time that children could spend playing one of its online games, to one hour per day for children 12 and under, and two hours per day for children aged 13–18.[182]

In 2018, Alphabet Inc. released an update for Android smartphones, including a dashboard app enabling users to set timers on application use.[183] Apple Inc. purchased a third-party application and then incorporated it in iOS 12 to measure "screen time".[184] Journalists have questioned the functionality of these products for users and parents, as well as the companies' motivations for introducing them.[183][185] Alphabet has also invested in a mental health specialist, Quartet, which uses machine learning to collaborate and coordinate digital delivery of mental health care.[186]

South Korea has eight government ministries responsible for public health efforts in relation to internet and gaming disorders, a review article published in Prevention Science in 2018 stating that the "region is unique in that its government has been at the forefront of prevention efforts, particularly in contrast to the United States, Western Europe, and Oceania."[179] Efforts are coordinated by the Ministry of Science and ICT, and include awareness campaigns, educational interventions, youth counseling centres, and promoting healthy online culture.[179]

Two institutional investors in Apple Inc., JANA Partners LLC and the California State Teachers' Retirement System (CalSTRS), stated in 2018 that they "believe[d] both the content and the amount of time spent on phones need to be tailored to youths". They called on Apple Inc. to act before regulators and consumers potentially force them to do so.[187][188] Apple Inc. responded that they have, "always looked out for kids, and [they] work hard to create powerful products that inspire, entertain, and educate children while also helping parents protect them online". The firm is planning new features that they asserted may allow them to play a pioneering role in regard to young people's health.[189]

Japan's Ministry of Internal Affairs and Communications coordinates Japanese public health efforts in relation to problematic internet use and gaming disorder. Legislatively, the Act on Development of an Environment that Provides Safe and Secure Internet Use for Young People was enacted in 2008, to promote public awareness campaigns, and support NGOs to teach young people safe internet use skills.[179]

See also

References

  1. ^ a b c Dickson K, Richardson M, Kwan I, MacDowall W, Burchett H, Stansfield C, et al. (2018). Screen-based activities and children and young people's mental health: A Systematic Map of Reviews (PDF). Department of Health Reviews Facility. EPPI-Centre, Social Science Research Unit, UCL Institute of Education, University College London. ISBN 978-1-911-605-13-3. Archived (PDF) from the original on 11 February 2019. Retrieved 15 May 2019.
  2. ^ a b c Ryding FC, Kaye LK (2018). ""Internet Addiction": a Conceptual Minefield". International Journal of Mental Health and Addiction. 16 (1): 225–232. doi:10.1007/s11469-017-9811-6. PMC 5814538. PMID 29491771.
  3. ^ a b c d e f Kardefelt-Winther D (1 February 2017). "How does the time children spend using digital technology impact their mental well-being, social relationships and physical activity? – An evidence-focused literature review" (PDF). UNICEF Office of Research – Innocenti. UNICEF Office of Research. Archived (PDF) from the original on 5 July 2019. Retrieved 12 May 2019.
  4. ^ a b c d e f Reid Chassiakos YL, Radesky J, Christakis D, Moreno MA, Cross C (November 2016). "Children and Adolescents and Digital Media". Pediatrics. 138 (5): e20162593. doi:10.1542/peds.2016-2593. PMID 27940795.
  5. ^ a b Stiglic N, Viner RM (January 2019). "Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews". BMJ Open. 9 (1): e023191. doi:10.1136/bmjopen-2018-023191. PMC 6326346. PMID 30606703.
  6. ^ a b c d Montag C, Becker B, Gan C (2018). "The Multipurpose Application WeChat: A Review on Recent Research". Frontiers in Psychology. 9: 2247. doi:10.3389/fpsyg.2018.02247. PMC 6297283. PMID 30618894.
  7. ^ Stiglic N, Viner RM (January 2019). "Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews". BMJ Open. 9 (1): e023191. doi:10.1136/bmjopen-2018-023191. PMC 6326346. PMID 30606703.
     • Beales K, MacDonald F, Bartlett V, Bowden-Jones H (2017). Are we all addicts now? : digital dependence. Liverpool: Liverpool University Press. ISBN 978-1-78694-081-0. OCLC 988053669.
     • Pantic I (October 2014). "Online social networking and mental health". Cyberpsychology, Behavior and Social Networking. 17 (10): 652–657. doi:10.1089/cyber.2014.0070. PMC 4183915. PMID 25192305.
     • Kuss DJ, Griffiths MD (March 2017). "Social Networking Sites and Addiction: Ten Lessons Learned". International Journal of Environmental Research and Public Health. 14 (3): 311. doi:10.3390/ijerph14030311. PMC 5369147. PMID 28304359.
     • Sigman A. "The Impact of Screen Media on Children: A Eurovision For Parliament" (PDF). Steiner Education Australia (reprint of original speech). Archived (PDF) from the original on 17 March 2019. Retrieved 10 January 2019.
  8. ^ a b Grant JE, Chamberlain SR (August 2016). "Expanding the definition of addiction: DSM-5 vs. ICD-11". CNS Spectrums. 21 (4): 300–303. doi:10.1017/S1092852916000183. PMC 5328289. PMID 27151528.
  9. ^ Ellis DA (1 August 2019). "Are smartphones really that bad? Improving the psychological measurement of technology-related behaviors". Computers in Human Behavior. 97: 60–66. doi:10.1016/j.chb.2019.03.006. ISSN 0747-5632. S2CID 150864248. Archived from the original on 9 February 2020. Retrieved 31 January 2020.
  10. ^ Young K (27 February 1998). Caught in the net: how to recognize the signs of Internet addiction—and a winning strategy for recovery. New York, New York: Wiley. ISBN 978-0-471-19159-9. OCLC 38130573.
  11. ^ La Barbera D, La Paglia F, Valsavoia R (2009). "Social network and addiction". Studies in Health Technology and Informatics. 144: 33–36. PMID 19592725.
  12. ^ Cornford K (2018). "Children & Young People's Mental Health in the Digital Age" (PDF). OECD.org. Archived (PDF) from the original on 11 January 2019. Retrieved 22 March 2019.
  13. ^ a b Parekh R. "Internet Gaming". The American Psychiatric Association. Archived from the original on 26 May 2019. Retrieved 10 May 2019.
  14. ^ a b "Gaming disorder". Gaming disorder. World Health Organization. September 2018. Archived from the original on 6 February 2019. Retrieved 10 May 2019.
  15. ^ "ICD-11 – Mortality and Morbidity Statistics". icd.who.int. Archived from the original on 1 August 2018. Retrieved 11 May 2019.
  16. ^ Panova T, Carbonell X (June 2018). "Is smartphone addiction really an addiction?". Journal of Behavioral Addictions. 7 (2): 252–259. doi:10.1556/2006.7.2018.49. PMC 6174603. PMID 29895183.
  17. ^ Radesky JS, Christakis DA (October 2016). "Increased Screen Time: Implications for Early Childhood Development and Behavior". Pediatric Clinics of North America. 63 (5): 827–839. doi:10.1016/j.pcl.2016.06.006. PMID 27565361.
  18. ^ Hsin C (2014). "The Influence of Young Children's Use of Technology on Their Learning: A Review". Journal of Educational Technology & Society. 17 (4): 85–99. JSTOR jeductechsoci.17.4.85.
     • Gordo López AJ, Contreras PP, Cassidy P (1 August 2015). "The [not so] new digital family: disciplinary functions of representations of children and technology". Feminism & Psychology. 25 (3): 326–346. doi:10.1177/0959353514562805. S2CID 146174524.
     • Subrahmanyam K, Kraut RE, Greenfield PM, Gross EF (22 September 2000). "The impact of home computer use on children's activities and development". The Future of Children. 10 (2): 123–144. doi:10.2307/1602692. JSTOR 1602692. PMID 11255703.
  19. ^ Hawi N, Samaha M (August 2019). "Identifying commonalities and differences in personality characteristics of internet and social media addiction profiles: traits, self-esteem, and self-construal". Behaviour & Information Technology. 38 (2): 110–119. doi:10.1080/0144929X.2018.1515984. S2CID 59523874. Archived from the original on 20 October 2021. Retrieved 12 May 2019.
     • Kuss DJ, Griffiths MD (March 2017). "Social Networking Sites and Addiction: Ten Lessons Learned". International Journal of Environmental Research and Public Health. 14 (3): 311. doi:10.3390/ijerph14030311. PMC 5369147. PMID 28304359.
     • Paulus FW, Ohmann S, von Gontard A, Popow C (July 2018). "Internet gaming disorder in children and adolescents: a systematic review". Developmental Medicine and Child Neurology. 60 (7): 645–659. doi:10.1111/dmcn.13754. PMID 29633243. S2CID 205070702.
  20. ^ Hawi N, Samaha M (August 2019). "Identifying commonalities and differences in personality characteristics of internet and social media addiction profiles: traits, self-esteem, and self-construal". Behaviour & Information Technology. 38 (2): 110–119. doi:10.1080/0144929X.2018.1515984. S2CID 59523874. Archived from the original on 20 October 2021. Retrieved 12 May 2019.
     • Paulus FW, Ohmann S, von Gontard A, Popow C (July 2018). "Internet gaming disorder in children and adolescents: a systematic review". Developmental Medicine and Child Neurology. 60 (7): 645–659. doi:10.1111/dmcn.13754. PMID 29633243. S2CID 205070702.
  21. ^ Nesse, Randolph; Williams, George C. (1994). Why We Get Sick: The New Science of Darwinian Medicine. New York: Vintage Books. p. 9. ISBN 978-0679746744.
  22. ^ Nesse, Randolph M. (2005). "32. Evolutionary Psychology and Mental Health". In Buss, David M. (ed.). The Handbook of Evolutionary Psychology (1st ed.). Hoboken, NJ: Wiley. pp. 904–905. ISBN 978-0471264033.
  23. ^ Nesse, Randolph M. (2016) [2005]. "43. Evolutionary Psychology and Mental Health". In Buss, David M. (ed.). The Handbook of Evolutionary Psychology, Volume 2: Integrations (2nd ed.). Hoboken, NJ: Wiley. pp. 1008–1009. ISBN 978-1118755808.
  24. ^ Nesse, Randolph (2019). Good Reasons for Bad Feelings: Insights from the Frontier of Evolutionary Psychiatry. Dutton. pp. 31–36. ISBN 978-1101985663.
  25. ^ Putnam, Robert D. (2000). Bowling Alone: The Collapse and Revival of American Community. New York: Simon & Schuster. p. 167. ISBN 978-0684832838.
  26. ^ a b c d Putnam, Robert D. (2000). Bowling Alone: The Collapse and Revival of American Community. New York: Simon & Schuster. p. 217. ISBN 978-0684832838.
  27. ^ Statistical Abstract of the United States: 1955 (PDF) (Report). Statistical Abstract of the United States (76 ed.). U.S. Census Bureau. 1955. p. 554. Archived (PDF) from the original on 16 September 2021. Retrieved 29 June 2021.
  28. ^ "The Rise of Cable Television". Encyclopedia.com. Archived from the original on 25 August 2021. Retrieved 14 June 2021.
  29. ^ File, Thom (May 2013). Computer and Internet Use in the United States (PDF) (Report). Current Population Survey Reports. Washington, D.C.: U.S. Census Bureau. Archived (PDF) from the original on 3 July 2019. Retrieved 11 February 2020.
  30. ^ Tuckel, Peter; O'Neill, Harry (2005). Ownership and Usage Patterns of Cell Phones: 2000–2005 (PDF) (Report). JSM Proceedings, Survey Research Methods Section. Alexandria, VA: American Statistical Association. p. 4002. Archived (PDF) from the original on 16 August 2021. Retrieved 25 September 2020.
  31. ^ "Demographics of Internet and Home Broadband Usage in the United States". Pew Research Center. 7 April 2021. Archived from the original on 30 August 2021. Retrieved 19 May 2021.
  32. ^ "Demographics of Mobile Device Ownership and Adoption in the United States". Pew Research Center. 7 April 2021. Archived from the original on 3 September 2019. Retrieved 19 May 2021.
  33. ^ Arendt, Susan (5 March 2007). "Game Consoles in 41% of Homes". WIRED. Condé Nast. Archived from the original on 9 July 2021. Retrieved 29 June 2021.
  34. ^ Statistical Abstract of the United States: 2008 (PDF) (Report). Statistical Abstract of the United States (127 ed.). U.S. Census Bureau. 30 December 2007. p. 52. Archived (PDF) from the original on 9 July 2021. Retrieved 29 June 2021.
  35. ^ North, Dale (14 April 2015). "155M Americans play video games, and 80% of households own a gaming device". VentureBeat. Archived from the original on 9 July 2021. Retrieved 29 June 2021.
  36. ^ 2015 Essential Facts About the Computer and Video Game Industry (Report). Essential Facts About the Computer and Video Game Industry. Vol. 2015. Entertainment Software Association. Archived from the original on 1 May 2020. Retrieved 29 June 2021.
  37. ^ Hoge E, Bickham D, Cantor J (November 2017). "Digital Media, Anxiety, and Depression in Children". Pediatrics. 140 (Suppl 2): S76–S80. doi:10.1542/peds.2016-1758G. PMID 29093037.
  38. ^ Elhai JD, Dvorak RD, Levine JC, Hall BJ (January 2017). "Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology". Journal of Affective Disorders. 207: 251–259. doi:10.1016/j.jad.2016.08.030. PMID 27736736. S2CID 205642153.
  39. ^ Krull K (19 February 2019). "Attention deficit hyperactivity disorder in children and adolescents, clinical features and diagnosis". UpToDate.com. UpToDate. Archived from the original on 1 April 2019. Retrieved 23 March 2019.
  40. ^ Kooij JJ, Bijlenga D, Salerno L, Jaeschke R, Bitter I, Balázs J, et al. (February 2019). "Updated European Consensus Statement on diagnosis and treatment of adult ADHD". European Psychiatry. 56: 14–34. doi:10.1016/j.eurpsy.2018.11.001. PMID 30453134.
  41. ^ Fitzsimmons-Craft EE, Krauss MJ, Costello SJ, Floyd GM, Wilfley DE, Cavazos-Rehg PA (December 2020). "Adolescents and young adults engaged with pro-eating disorder social media: eating disorder and comorbid psychopathology, health care utilization, treatment barriers, and opinions on harnessing technology for treatment". Eating and Weight Disorders. 25 (6): 1681–1692. doi:10.1007/s40519-019-00808-3. PMC 7195229. PMID 31679144.
  42. ^ Kato, Brooke (31 July 2020). "This dangerous TikTok trend could lead to eating disorders, experts say". New York Post. Archived from the original on 10 June 2021. Retrieved 29 July 2021.
  43. ^ "#StatusOfMind – Social media and young people's mental health and wellbeing" (PDF). Royal Society for Public Health. Archived from the original (PDF) on 25 November 2018. Retrieved 10 January 2019.
  44. ^ Twenge JM, Joiner TE, Rogers ML, Martin GN (2018). "Increases in Depressive Symptoms, Suicide-Related Outcomes, and Suicide Rates Among U.S. Adolescents After 2010 and Links to Increased New Media Screen Time". Clinical Psychological Science. 6 (1): 3–17. doi:10.1177/2167702617723376. S2CID 148724233.
  45. ^ Ophir Y, Lipshits-Braziler Y, Rosenberg H (May 2019). "New-Media Screen Time is Not (Necessarily) Linked to Depression: Comments on Twenge, Joiner, Rogers, and Martin (2018)". Clinical Psychological Science. 8 (2): 374–378. doi:10.1177/2167702619849412. S2CID 189987879.
  46. ^ Matthews M, Murnane E, Snyder J, Guha S, Chang P, Doherty G, Gay G (1 October 2017). "The double-edged sword: A mixed methods study of the interplay between bipolar disorder and technology use". Computers in Human Behavior. 75: 288–300. doi:10.1016/j.chb.2017.05.009. Archived from the original on 19 March 2020. Retrieved 4 December 2019.
  47. ^ a b Barry CT, Sidoti CL, Briggs SM, Reiter SR, Lindsey RA (December 2017). "Adolescent social media use and mental health from adolescent and parent perspectives". Journal of Adolescence. 61: 1–11. doi:10.1016/j.adolescence.2017.08.005. PMID 28886571.
  48. ^ Boers E, Afzali MH, Newton N, Conrod P (July 2019). "Association of Screen Time and Depression in Adolescence". JAMA Pediatrics. 173 (9): 853–859. doi:10.1001/jamapediatrics.2019.1759. PMC 6632122. PMID 31305878.
  49. ^ Orben, Amy; Przybylski, Andrew K. (2019). "The association between adolescent well-being and digital technology use". Nature Human Behaviour. Springer Nature Publishing. 3 (2): 173–182. doi:10.1038/s41562-018-0506-1. PMID 30944443. S2CID 58006454. Archived from the original on 23 April 2021. Retrieved 12 June 2021.
  50. ^ Orban, Amy; Przybylski, Andrew K. (2019). "Screens, Teens, and Psychological Well-Being: Evidence From Three Time-Use-Diary Studies". Psychological Science. SAGE Publications. 30 (5): 682–696. doi:10.1177/0956797619830329. PMC 6512056. PMID 30939250.
  51. ^ Twenge, Jean M.; Blake, Andrew B.; Haidt, Jonathan; Campbell, W. Keith (18 February 2020). "Commentary: Screens, Teens, and Psychological Well-Being: Evidence From Three Time-Use-Diary Studies". Frontiers in Psychology. Frontiers Media. 11: 181. doi:10.3389/fpsyg.2020.00181. PMC 7040178. PMID 32132949.
  52. ^ Twenge, Jean; Haidt, Jonathan; Joiner, Thomas E.; Campbell, W. Keith (2020). "Underestimating digital media harm". Nature Human Behaviour. Springer Nature Publishing. 4 (4): 346–348. doi:10.1038/s41562-020-0839-4. PMID 32303719. S2CID 215804486. Archived from the original on 8 August 2021. Retrieved 13 June 2021.
  53. ^ Cao H, Qian Q, Weng T, Yuan C, Sun Y, Wang H, Tao F (October 2011). "Screen time, physical activity and mental health among urban adolescents in China". Preventive Medicine. Special Section: Epidemiology, Risk, and Causation. 53 (4–5): 316–20. doi:10.1016/j.ypmed.2011.09.002. PMID 21933680. S2CID 39903719.
  54. ^ Przybylski AK, Weinstein N (February 2017). "A Large-Scale Test of the Goldilocks Hypothesis" (PDF). Psychological Science. 28 (2): 204–215. doi:10.1177/0956797616678438. PMID 28085574. S2CID 9669390. Archived (PDF) from the original on 19 July 2018. Retrieved 24 June 2019.
  55. ^ a b "Impact of social media and screen-use on young people's health" (PDF). House of Commons Science and Technology Committee. 31 January 2019. Archived (PDF) from the original on 20 July 2020. Retrieved 12 May 2019.
  56. ^ "Social Media Use May Harm Teens' Mental Health By Disrupting Positive Activities, Study Says". 13 August 2019. Archived from the original on 11 March 2021. Retrieved 17 December 2020.
  57. ^ Logrieco, G.; Marchili, M. R.; Roversi, M.; Villani, A. (2021). "The Paradox of Tik Tok Anti-Pro-Anorexia Videos: How Social Media Can Promote Non-Suicidal Self-Injury and Anorexia". International Journal of Environmental Research and Public Health. 18 (3): 1041. doi:10.3390/ijerph18031041. PMC 7908222. PMID 33503927.
  58. ^ Nikkelen, Sanne W.C.; Valkenburg, Patti M.; Huizinga, Mariette; Bushman, Brad J. (2014). "Media use and ADHD-related behaviors in children and adolescents: A meta-analysis". Developmental Psychology. American Psychological Association. 50 (9): 2228–41. doi:10.1037/a0037318. PMID 24999762. Archived from the original on 20 October 2021. Retrieved 13 June 2021.
  59. ^ Turel, Ofir; Bechara, Antoine (2016). "Social Networking Site Use While Driving: ADHD and the Mediating Roles of Stress, Self-Esteem and Craving". Frontiers in Psychology. Frontiers Media. 7: 455. doi:10.3389/fpsyg.2016.00455. PMC 4812103. PMID 27065923.
  60. ^ Settanni, Michele; Marengo, Davide; Fabris, Matteo Angelo; Longobardi, Claudio (2018). "The interplay between ADHD symptoms and time perspective in addictive social media use: A study of adolescent Facebook users". Children and Youth Services Review. Elsevier. 89: 165–170. doi:10.1016/j.childyouth.2018.04.031. S2CID 149795392. Archived from the original on 11 July 2020. Retrieved 10 June 2021.
  61. ^ Lenhart, Amanda (9 April 2015). "Teens, Social Media & Technology Overview 2015". Pew Research Center. Archived from the original on 10 June 2021. Retrieved 8 July 2020.
  62. ^ Nesse, Randolph; Williams, George C. (1994). Why We Get Sick: The New Science of Darwinian Medicine. New York: Vintage Books. pp. 212–214. ISBN 978-0679746744.
  63. ^ Nesse, Randolph M. (2005). "32. Evolutionary Psychology and Mental Health". In Buss, David M. (ed.). The Handbook of Evolutionary Psychology (1st ed.). Hoboken, NJ: Wiley. pp. 911–913. ISBN 978-0471264033.
  64. ^ Nesse, Randolph M. (2016) [2005]. "43. Evolutionary Psychology and Mental Health". In Buss, David M. (ed.). The Handbook of Evolutionary Psychology, Volume 2: Integrations (2nd ed.). Hoboken, NJ: Wiley. p. 1014. ISBN 978-1118755808.
  65. ^ Nesse, Randolph (2019). Good Reasons for Bad Feelings: Insights from the Frontier of Evolutionary Psychiatry. Dutton. pp. 64–76. ISBN 978-1101985663.
  66. ^ Ra, Chaelin K.; Cho, Junhan; Stone, Matthew D.; De La Cerda, Julianne; Goldenson, Nicholas I.; Moroney, Elizabeth; Tung, Irene; Lee, Steve S.; Leventhal, Adam M. (17 July 2018). "Association of Digital Media Use With Subsequent Symptoms of Attention-Deficit/Hyperactivity Disorder Among Adolescents". JAMA. American Medical Association. 320 (3): 255–263. doi:10.1001/jama.2018.8931. PMC 6553065. PMID 30027248. Archived from the original on 10 June 2021. Retrieved 8 July 2020.
  67. ^ Chatterjee, Rhitu (17 July 2018). "More Screen Time For Teens Linked To ADHD Symptoms". Morning Edition. NPR. Archived from the original on 10 June 2021. Retrieved 8 July 2020.
  68. ^ Clopton, Jennifer (20 November 2018). "ADHD Rising in the U.S., but Why?". WebMD. Internet Brands. Archived from the original on 10 June 2021. Retrieved 8 July 2020.
  69. ^ Beyens, Ine; Valkenburg, Patti M.; Piotrowski, Jessica Taylor (2 October 2018). "Screen media use and ADHD-related behaviors: Four decades of research". PNAS USA. National Academy of Sciences. 115 (40): 9875–9881. doi:10.1073/pnas.1611611114. PMC 6176582. PMID 30275318.
  70. ^ Tamana, Sukhpreet K.; Ezeugwu, Victor; Chikuma, Joyce; Lefebvre, Diana L.; Azad, Meghan B.; Moraes, Theo J.; Subbarao, Padmaja; Becker, Allan B.; Turvey, Stuart E.; Sears, Malcolm R.; Dick, Bruce D.; Carson, Valerie; Rasmussen, Carmen; Pei, Jacqueline; Mandhane, Piush J. (17 April 2019). "Screen-time is associated with inattention problems in preschoolers: Results from the CHILD birth cohort study". PLOS One. PLOS. 14 (4): e0213995. Bibcode:2019PLoSO..1413995T. doi:10.1371/journal.pone.0213995. PMC 6469768. PMID 30995220.
  71. ^ Xie, Guodong; Deng, Qianye; Cao, Jing; Chang, Qing (2020). "Digital screen time and its effect on preschoolers' behavior in China: results from a cross-sectional study". Italian Journal of Pediatrics. Springer Nature. 46 (9): 9. doi:10.1186/s13052-020-0776-x. PMC 6979375. PMID 31973770.
  72. ^ a b Hill, Monique Moore; Gangi, Devon; Miller, Meghan; Rafi, Sabrina Mohamed; Ozonoff, Sally (2020). "Screen time in 36-month-olds at increased likelihood for ASD and ADHD". Infant Behavior and Development. Elsevier. 61: 101484. doi:10.1016/j.infbeh.2020.101484. PMC 7736468. PMID 32871326.
  73. ^ Biederman, Joseph; Spencer, Thomas (1999). "Attention-deficit/hyperactivity disorder (adhd) as a noradrenergic disorder". Biological Psychiatry. Elsevier. 46 (9): 1234–1242. doi:10.1016/S0006-3223(99)00192-4. PMID 10560028. S2CID 45497168. Archived from the original on 20 October 2021. Retrieved 9 July 2020.
  74. ^ Faraone, Stephen V.; Larsson, Henrik (2019). "Genetics of attention deficit hyperactivity disorder". Molecular Psychiatry. Nature Research. 24 (4): 562–575. doi:10.1038/s41380-018-0070-0. PMC 6477889. PMID 29892054.
  75. ^ Baron-Cohen, Simon (2002). "The extreme male brain theory of autism". Trends in Cognitive Sciences. Elsevier. 6 (6): 248–254. doi:10.1016/S1364-6613(02)01904-6. PMID 12039606. S2CID 8098723. Archived from the original on 3 July 2013. Retrieved 9 July 2020.
  76. ^ Nesse, Randolph M. (2005). "32. Evolutionary Psychology and Mental Health". In Buss, David M. (ed.). The Handbook of Evolutionary Psychology (1st ed.). Hoboken, NJ: Wiley. p. 918. ISBN 978-0471264033.
  77. ^ Nesse, Randolph M. (2016) [2005]. "43. Evolutionary Psychology and Mental Health". In Buss, David M. (ed.). The Handbook of Evolutionary Psychology, Volume 2: Integrations (2nd ed.). Hoboken, NJ: Wiley. p. 1019. ISBN 978-1118755808.
  78. ^ Shuai, Lan; He, Shan; Zheng, Hong; Wang, Zhouye; Qiu, Meihui; Xia, Weiping; Cao, Xuan; Lu, Lu; Zhang, Jinsong (2021). "Influences of digital media use on children and adolescents with ADHD during COVID-19 pandemic". Globalization and Health. 17 (1): 48. doi:10.1186/s12992-021-00699-z. PMC 8054232. PMID 33874977.
  79. ^ "Vol. 58 No. 4 (2021): Volume 58 No. 4 (2021) | Psychology and Education Journal". Archived from the original on 20 October 2021. Retrieved 3 October 2021.
  80. ^ Jones, Rachel A.; Downing, Katherine; Rinehart, Nicole J.; Barnett, Lisa M.; May, Tamara; McGillivray, Jane A.; Papadopoulos, Nicole V.; Skouteris, Helen; Timperio, Anna; Hinkley, Trina (2017). "Physical activity, sedentary behavior and their correlates in children with Autism Spectrum Disorder: A systematic review". PLOS One. PLOS. 12 (2): e0172482. Bibcode:2017PLoSO..1272482J. doi:10.1371/journal.pone.0172482. PMC 5330469. PMID 28245224.
  81. ^ Zheng, Zhen; Li, Shiping; Zhao, Fengyan; Wang, Yan; Huang, Lan; Huang, Jinglan; Zou, Rong; Qu, Yi; Mu, Dezhi (2017). "Association among obesity, overweight and autism spectrum disorder: a systematic review and meta-analysis". Scientific Reports. Nature Portfolio. 7 (11697): 11697. Bibcode:2017NatSR...711697Z. doi:10.1038/s41598-017-12003-4. PMC 5601947. PMID 28916794.
  82. ^ Gwynette, McLeod Frampton; Sidhu, Shawn S.; Ceranoglu, Tolga Atilla (2018). "Electronic Screen Media Use in Youth With Autism Spectrum Disorder". Child and Adolescent Psychiatric Clinics of North America. 27 (2): 203–219. doi:10.1016/j.chc.2017.11.013. PMID 29502747. Archived from the original on 20 October 2021. Retrieved 27 June 2021.
  83. ^ Díaz-Román, Amparo; Zhang, Junhua; Delorme, Richard; Beggiato, Anita; Cortese, Samuele (2018). "Sleep in youth with autism spectrum disorders: systematic review and meta-analysis of subjective and objective studies". Evidence-Based Mental Health. BMJ. 21 (4): 146–154. doi:10.1136/ebmental-2018-300037. PMID 30361331. S2CID 53103694. Archived from the original on 27 June 2021. Retrieved 26 June 2021.
  84. ^ Healy, Seán; Garcia, Jeanette M.; Haegele, Justin A. (2020). "Environmental Factors Associated with Physical Activity and Screen Time Among Children With and Without Autism Spectrum Disorder". Journal of Autism and Developmental Disorders. Springer Science+Business Media. 50 (5): 1572–1579. doi:10.1007/s10803-018-3818-0. PMID 30446873. S2CID 53568482. Archived from the original on 27 June 2021. Retrieved 26 June 2021.
  85. ^ Stiller, Anja; Weber, Jan; Strube, Finja; Mößle, Thomas (2019). "Caregiver Reports of Screen Time Use of Children with Autism Spectrum Disorder: A Qualitative Study". Behavioral Sciences. MDPI. 9 (5): 56. doi:10.3390/bs9050056. PMC 6562753. PMID 31121966.
  86. ^ Dong, Han-Yu; Wang, Bing; Li, Hong-Hua; Yue, Xiao-Jing; Jia, Fei-Yong (2021). "Correlation Between Screen Time and Autistic Symptoms as Well as Development Quotients in Children With Autism Spectrum Disorder". Frontiers in Psychiatry. Frontiers Media. 12: 619994. doi:10.3389/fpsyt.2021.619994. PMC 7920949. PMID 33664683.
  87. ^ Chan, Wai Sze; Levesen, Meredith P.; McCrae, Christina S. (2018). "A meta-analysis of associations between obesity and insomnia diagnosis and symptoms". Sleep Medicine Reviews. Elsevier. 40: 170–182. doi:10.1016/j.smrv.2017.12.004. PMID 29366543. S2CID 1135275. Archived from the original on 24 June 2021. Retrieved 21 June 2021.
  88. ^ Li, Xian; Buxton, Orfeu M.; Lee, Soomi; Chang, Anne-Marie; Berger, Lawrence M.; Hale, Lauren (2019). "Sleep mediates the association between adolescent screen time and depressive symptoms". Sleep Medicine. Elsevier. 57: 51–60. doi:10.1016/j.sleep.2019.01.029. PMC 6511486. PMID 30897456.
  89. ^ Baiden, Philip; Tadeo, Savarra K.; Peters, Kersley E. (2019). "The association between excessive screen-time behaviors and insufficient sleep among adolescents: Findings from the 2017 youth risk behavior surveillance system". Psychiatry Research. Elsevier. 281 (112586): 112586. doi:10.1016/j.psychres.2019.112586. PMID 31629305. S2CID 203462333. Archived from the original on 24 June 2021. Retrieved 21 June 2021.
  90. ^ Kolovos, Spyros; Jimenez-Moreno, Aura Cecilia; Pinedo-Villanueva, Rafael; Cassidy, Sophie; Zavala, Gerardo A. (2021). "Association of sleep, screen time and physical activity with overweight and obesity in Mexico". Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity. Springer Science+Business Media. 26 (1): 169–179. doi:10.1007/s40519-019-00841-2. PMC 7895770. PMID 31893356.
  91. ^ Janssen, Xanne; Martin, Anne; Hughes, Adrienne R.; Hill, Catherine M.; Kotronoulas, Grigorios; Hesketh, Kathryn R. (2020). "Associations of screen time, sedentary time and physical activity with sleep in under 5s: A systematic review and meta-analysis". Sleep Medicine Reviews. Elsevier. 49 (101226): 101226. doi:10.1016/j.smrv.2019.101226. PMC 7034412. PMID 31778942.
  92. ^ McCain, Jessica L.; Campbell, W. Keith (2018). "Narcissism and Social Media Use: A Meta-Analytic Review". Psychology of Popular Media Culture. American Psychological Association. 7 (3): 308–327. doi:10.1037/ppm0000137. S2CID 152057114. Archived from the original on 20 October 2021. Retrieved 9 June 2020.
  93. ^ Gnambs, Timo; Appel, Markus (2018). "Narcissism and Social Networking Behavior: A Meta-Analysis". Journal of Personality. Wiley-Blackwell. 86 (2): 200–212. doi:10.1111/jopy.12305. PMID 28170106.
  94. ^ Brailovskaia, Julia; Bierhoff, Hans-Werner (2020). "The Narcissistic Millennial Generation: A Study of Personality Traits and Online Behavior on Facebook". Journal of Adult Development. Springer Science+Business Media. 27 (1): 23–35. doi:10.1007/s10804-018-9321-1. S2CID 149564334.
  95. ^ Casale, Silvia; Banchi, Vanessa (2020). "Narcissism and problematic social media use: A systematic literature review". Addictive Behaviors Reports. Elsevier. 11: 100252. doi:10.1016/j.abrep.2020.100252. PMC 7244927. PMID 32467841.
  96. ^ Lukianoff, Greg; Haidt, Jonathan (2018). The Coddling of the American Mind: How Good Intentions and Bad Ideas Are Setting Up a Generation for Failure. New York: Penguin Press. p. 147. ISBN 978-0735224896.
  97. ^ West, Patrick (2004). Conspicuous Compassion: Why Sometimes It Really Is Cruel To Be Kind. London: Civitas, Institute for the Study of Civil Society. ISBN 978-1903386347.
  98. ^ Payton, Robert L.; Moody, Michael P. (2008). Understanding Philanthropy: Its Meaning and Mission. p. 137. ISBN 978-0253000132.
  99. ^ Lukianoff, Greg; Haidt, Jonathan (2018). The Coddling of the American Mind: How Good Intentions and Bad Ideas Are Setting Up a Generation for Failure. New York: Penguin Press. pp. 71–73. ISBN 978-0735224896.
  100. ^ "Critical posts get more likes, comments, and shares than other posts". Pew Research Center. 21 February 2017. Archived from the original on 3 September 2021. Retrieved 1 September 2021.
  101. ^ Brady, William J.; Wills, Julian A.; Jost, John T.; Tucker, Joshua A.; Van Bavel, Jay J. (11 July 2017). "Emotion shapes the diffusion of moralized content in social networks". PNAS USA. National Academy of Sciences. 114 (28): 7313–7318. doi:10.1073/pnas.1618923114. PMC 5514704. PMID 28652356.
  102. ^ Haidt, Jonathan; Rose-Stockwell, Tobias (2019). "The Dark Psychology of Social Networks". The Atlantic. Vol. 324, no. 6. Emerson Collective. pp. 57–60. Archived from the original on 28 August 2021. Retrieved 11 June 2020.
  103. ^ Tesler, Michael (19 August 2020). "Support For Black Lives Matter Surged During Protests, But Is Waning Among White Americans". FiveThirtyEight. Archived from the original on 8 September 2021. Retrieved 2 September 2021.
  104. ^ Samuels, Alex (13 April 2021). "How Views On Black Lives Matter Have Changed – And Why That Makes Police Reform So Hard". FiveThirtyEight. Archived from the original on 6 September 2021. Retrieved 2 September 2021.
  105. ^ Blow, Charles M. (5 February 2021). "Charles Blow". Firing Line (Interview). Interviewed by Margaret Hoover. WNET. Archived from the original on 3 September 2021. Retrieved 2 September 2021.
  106. ^ Brucato, Gary; Appelbaum, Paul S.; Hesson, Hannah; Shea, Eileen A.; Dishy, Gabriella; Lee, Kathryn; Pia, Tyler; Syed, Faizan; Villalobos, Alexandra; Wall, Melanie M.; Lieberman, Jeffrey A.; Girgis, Ragy R. (2021). "Psychotic symptoms in mass shootings v. mass murders not involving firearms: findings from the Columbia mass murder database". Psychological Medicine. Cambridge University Press: 1–9. doi:10.1017/S0033291721000076. PMID 33595428. S2CID 231944742. Archived from the original on 17 August 2021. Retrieved 16 August 2021.
  107. ^ Preidt, Robert (25 February 2021). "Mental Illness Not a Factor in Most Mass Shootings". WebMD. Internet Brands. Archived from the original on 17 August 2021. Retrieved 16 August 2021.
  108. ^ Ramsland, Katherine (26 February 2021). "Is There a Link Between Madness and Mass Murder?". Psychology Today. Sussex Publishers. Retrieved 16 August 2021.
  109. ^ "Researchers Issue First Report on Mass Shootings from the Columbia Mass Murder Database". Columbia University Irving Medical Center. 18 February 2021. Archived from the original on 17 August 2021. Retrieved 17 August 2021.
  110. ^ Pies, Ronald W. (17 February 2020). "Mass Shooters and the Psychopathology Spectrum". Psychiatric Times. MJH Associates. Archived from the original on 17 August 2021. Retrieved 17 August 2021.
  111. ^ Knoll, James L.; Annas, George D. (2015). "4. Mass Shootings and Mental Illness". In Gold, Liza H.; Simon, Robert I. (eds.). Gun Violence and Mental Illness. New York: American Psychiatric Association. pp. 91–94. ISBN 978-1585624980. Archived from the original on 4 September 2021. Retrieved 19 August 2021.
  112. ^ Twenge, Jean; Campbell, W. Keith (2010). The Narcissism Epidemic: Living in the Age of Entitlement. New York: Atria Publishing Group. pp. 199–200. ISBN 978-1416575993.
  113. ^ Pinker, Steven (2011). The Better Angels of Our Nature: Why Violence Has Declined. New York: Penguin Books. pp. 519–521. ISBN 978-0143122012.
  114. ^ Aarseth E, Bean AM, Boonen H, Colder Carras M, Coulson M, Das D, et al. (September 2017). "Scholars' open debate paper on the World Health Organization ICD-11 Gaming Disorder proposal". Journal of Behavioral Addictions. 6 (3): 267–270. doi:10.1556/2006.5.2016.088. PMC 5700734. PMID 28033714.
  115. ^ Christakis DA (October 2010). "Internet addiction: a 21st century epidemic?". BMC Medicine. 8 (1): 61. doi:10.1186/1741-7015-8-61. PMC 2972229. PMID 20955578.
  116. ^ Cooper A (9 December 2018). "Groundbreaking study examines effects of screen time on kids". 60 Minutes Canada. CBS News. Archived from the original on 11 December 2018. Retrieved 12 December 2018.
  117. ^ Cheng C, Li AY (December 2014). "Internet addiction prevalence and quality of (real) life: a meta-analysis of 31 nations across seven world regions". Cyberpsychology, Behavior and Social Networking. 17 (12): 755–760. doi:10.1089/cyber.2014.0317. PMC 4267764. PMID 25489876.
  118. ^ Musetti A, Corsano P (18 April 2018). "The Internet Is Not a Tool: Reappraising the Model for Internet-Addiction Disorder Based on the Constraints and Opportunities of the Digital Environment". Frontiers in Psychology. 9: 558. doi:10.3389/fpsyg.2018.00558. PMC 5915628. PMID 29720954.
  119. ^ Pantic I (October 2014). "Online social networking and mental health". Cyberpsychology, Behavior and Social Networking. 17 (10): 652–7. doi:10.1089/cyber.2014.0070. PMC 4183915. PMID 25192305.
  120. ^ van den Eijnden RJ, Lemmens JS, Valkenburg PM (1 August 2016). "The Social Media Disorder Scale". Computers in Human Behavior. 61: 478–487. doi:10.1016/j.chb.2016.03.038.
  121. ^ Andreassen CS (1 June 2015). "Online Social Network Site Addiction: A Comprehensive Review" (PDF). Current Addiction Reports. 2 (2): 175–184. doi:10.1007/s40429-015-0056-9. ISSN 2196-2952. S2CID 145799241. Archived (PDF) from the original on 27 August 2017.
  122. ^ Stein DJ, Hollander E, Rothbaum BO (31 August 2009). Textbook of Anxiety Disorders. Washington, DC: American Psychiatric Publishing. p. 359. ISBN 978-1-58562-254-2. Archived from the original on 11 October 2013. Retrieved 24 April 2010.
  123. ^ Parashar A, Varma A (April 2007). "Behavior and substance addictions: is the world ready for a new category in the DSM-V?". CNS Spectrums. 12 (4): 257, author reply 258–9. doi:10.1017/S109285290002099X. PMID 17503551.
  124. ^ Griffiths M (November 2001). "Sex on the internet: Observations and implications for internet sex addiction". The Journal of Sex Research. 38 (4): 333–342. doi:10.1080/00224490109552104. S2CID 144522990. Archived from the original on 20 October 2021. Retrieved 2 April 2013.
  125. ^ Gainsbury SM (2015). "Online Gambling Addiction: the Relationship Between Internet Gambling and Disordered Gambling". Current Addiction Reports. 2 (2): 185–193. doi:10.1007/s40429-015-0057-8. PMC 4610999. PMID 26500834.
  126. ^  • Hinduja S, Patchin JW (2008). "Cyberbullying: An Exploratory Analysis of Factors Related to Offending and Victimization". Deviant Behavior. 29 (2): 129–156. doi:10.1080/01639620701457816. S2CID 144024729.
     • Hinduja S, Patchin JW (October 2007). "Offline consequences of online victimization: School violence and delinquency". Journal of School Violence. 6 (3): 89–112. doi:10.1300/J202v06n03_06. S2CID 143016237.
     • Hinduja S, Patchin JW (2009). Bullying beyond the schoolyard: Preventing and responding to cyberbullying. Thousand Oaks, CA: Corwin Press. ISBN 978-1-4129-6689-4.
     • Hinduja S, Patchin JW (2006). "Bullies move beyond the schoolyard: A preliminary look at cyberbullying". Youth Violence and Juvenile Justice. 4 (2): 148–169. doi:10.1177/1541204006286288. S2CID 145357837.
  127. ^ Almuneef M, Anton-Erxleben K, Burton P (14 November 2016). Ending the torment : tackling bullying from the schoolyard to cyberspace. United Nations. Office of the Special Representative of the Secretary-General on Violence against Children. New York: United Nations Publications. p. 116. ISBN 978-9-2110-1344-3. OCLC 982286456.
  128. ^ Uncapher MR, Lin L, Rosen LD, Kirkorian HL, Baron NS, Bailey K, et al. (November 2017). "Media Multitasking and Cognitive, Psychological, Neural, and Learning Differences". Pediatrics. 140 (Suppl 2): S62–S66. doi:10.1542/peds.2016-1758D. PMC 5658797. PMID 29093034.
  129. ^ Uncapher MR, Wagner AD (October 2018). "Minds and brains of media multitaskers: Current findings and future directions". Proceedings of the National Academy of Sciences of the United States of America. 115 (40): 9889–9896. doi:10.1073/pnas.1611612115. PMC 6176627. PMID 30275312.
  130. ^ Huber J (29 October 2018). "How does media multitasking affect the mind?". Scope. Archived from the original on 31 May 2019. Retrieved 31 May 2019.
  131. ^ a b Zajac K, Ginley MK, Chang R, Petry NM (December 2017). "Treatments for Internet gaming disorder and Internet addiction: A systematic review". Psychology of Addictive Behaviors. 31 (8): 979–994. doi:10.1037/adb0000315. PMC 5714660. PMID 28921996.
  132. ^ "How to Make a Family Media Use Plan". HealthyChildren.org. Archived from the original on 6 June 2019. Retrieved 6 June 2019.
  133. ^ Korioth T (12 December 2018). "Family Media Plan helps parents set boundaries for kids". AAP News. Archived from the original on 9 January 2019. Retrieved 9 January 2019.
  134. ^ Ferguson CJ, Beresin E (1 June 2017). "Social science's curious war with pop culture and how it was lost: The media violence debate and the risks it holds for social science". Preventive Medicine. 99: 69–76. doi:10.1016/j.ypmed.2017.02.009. ISSN 0091-7435. PMID 28212816.
  135. ^ Shaw M, Black DW (2008). "Internet addiction: definition, assessment, epidemiology and clinical management". CNS Drugs. 22 (5): 353–365. doi:10.2165/00023210-200822050-00001. PMID 18399706. S2CID 1699090.
  136. ^ Petry NM, Rehbein F, Gentile DA, Lemmens JS, Rumpf HJ, Mößle T, et al. (September 2014). "An international consensus for assessing Internet gaming disorder using the new DSM-5 approach". Addiction. 109 (9): 1399–1406. doi:10.1111/add.12457. PMID 24456155.
  137. ^ Gámez-Guadix M, Calvete E (1 December 2016). "Assessing the Relationship between Mindful Awareness and Problematic Internet Use among Adolescents". Mindfulness. 7 (6): 1281–1288. doi:10.1007/s12671-016-0566-0. S2CID 148514937.
  138. ^ Sharma MK, Palanichamy TS (February 2018). "Psychosocial interventions for technological addictions". Indian Journal of Psychiatry. 60 (Suppl 4): S541–S545. doi:10.4103/psychiatry.IndianJPsychiatry_40_18. PMC 5844169. PMID 29540928. Archived from the original on 16 October 2019. Retrieved 18 April 2020.
  139. ^ Kuss DJ, Griffiths MD (September 2011). "Online social networking and addiction – a review of the psychological literature". International Journal of Environmental Research and Public Health. 8 (9): 3528–3552. doi:10.3390/ijerph8093528. PMC 3194102. PMID 22016701.
  140. ^ Romano M, Osborne LA, Truzoli R, Reed P (7 February 2013). "Differential psychological impact of Internet exposure on Internet addicts". PLOS One. 8 (2): e55162. Bibcode:2013PLoSO...855162R. doi:10.1371/journal.pone.0055162. PMC 3567114. PMID 23408958.
  141. ^ "Hooked on Social Media? Help From Adults with ADHD". ADDitude. ADDitude Magazine. 23 November 2016. Archived from the original on 15 December 2018. Retrieved 13 December 2018.
  142. ^ "ADHD and Learning Disabilities Directory: ADD Coaches, Organizers, Doctors, Schools, Camps". directory.additudemag.com. Archived from the original on 9 January 2019. Retrieved 9 January 2019.
  143. ^ "Resources Online". ADHD Australia. Archived from the original on 9 January 2019. Retrieved 9 January 2019.
  144. ^ "ADHD Resource Center". www.aacap.org. Archived from the original on 9 January 2019. Retrieved 9 January 2019.
  145. ^ Kesner, Ladislav; Horáček, Jiří (2022). "Global Adversities, the Media, and Mental Health". Frontiers in Psychiatry. 12: 809239. doi:10.3389/fpsyt.2021.809239. ISSN 1664-0640. PMC 8785246. PMID 35082704.
  146. ^ See, for example, patients of "Stop Cancer" (Halasartan), as cited in: Ben-Aharon, Irit; Goshen-Lago, Tal; Fontana, Elisa; Smyth, Elizabeth; Guren, Marianne; Caballero, Carmela; Lordick, Florian (1 June 2019). "Social networks for young patients with cancer: the time for system agility". The Lancet Oncology. 20 (6): 765. doi:10.1016/S1470-2045(19)30346-8. ISSN 1470-2045. PMID 31162090. S2CID 174808947. Archived from the original on 20 October 2021. Retrieved 6 June 2021.
  147. ^ Moorhead, S. Anne (22 August 2017). "Social Media for Healthcare Communication". Oxford Research Encyclopedia of Communication. doi:10.1093/acrefore/9780190228613.013.335. ISBN 978-0-19-022861-3. Archived from the original on 6 June 2021. Retrieved 6 June 2021.
  148. ^ Schwartzbach, Kevin (13 December 2019). "TikTok and Recovery on Social Media". American Addiction Centers. Archived from the original on 3 October 2021. Retrieved 3 October 2021.
  149. ^ Miller D. "The Anthropology of Social Media". Scientific American Blog Network. Archived from the original on 15 December 2018. Retrieved 13 December 2018.
  150. ^ Miller D (28 August 2018). "Digital Anthropology". Cambridge Encyclopedia of Anthropology. doi:10.29164/18digital. Archived from the original on 30 December 2018. Retrieved 7 January 2019.
  151. ^ Solis B (28 March 2018). "We've Become Digital Addicts: It's Time to Take Control of Technology and Not Let Tech Control Us". Medium. Archived from the original on 30 December 2018. Retrieved 6 January 2019.
  152. ^ Lupton D (1 August 2012). "Digital Sociology: An Introduction" (PDF). ses.library.usyd.edu.au. Archived (PDF) from the original on 13 April 2015. Retrieved 8 January 2019.
  153. ^ Sanaktekin OH (20 December 2011). "The Effects of Religiosity on Internet Consumption". Information, Communication & Society. 16 (10): 1553–1573. doi:10.1080/1369118x.2012.722663. S2CID 143260457.
  154. ^ Charlton JP, Soh PC, Ang PH, Chew KW (1 December 2013). "Religiosity, Adolescent Internet Usage Motives and Addiction". Information, Communication & Society. 16 (10): 1619–1638. doi:10.1080/1369118X.2012.735251. ISSN 1369-118X. S2CID 142545433.
  155. ^ a b Odgers C (February 2018). "Smartphones are bad for some teens, not all". Nature. 554 (7693): 432–434. Bibcode:2018Natur.554..432O. doi:10.1038/d41586-018-02109-8. PMC 6121807. PMID 29469108.
  156. ^ Meshi D, Tamir DI, Heekeren HR (December 2015). "The Emerging Neuroscience of Social Media" (PDF). Trends in Cognitive Sciences. 19 (12): 771–782. doi:10.1016/j.tics.2015.09.004. PMID 26578288. S2CID 3674598. Archived (PDF) from the original on 12 July 2018. Retrieved 14 January 2019.
  157. ^ Crone EA, Konijn EA (February 2018). "Media use and brain development during adolescence". Nature Communications. 9 (1): 588. Bibcode:2018NatCo...9..588C. doi:10.1038/s41467-018-03126-x. PMC 5821838. PMID 29467362.
  158. ^ "Smart technology is not making us dumber: study". phys.org. Archived from the original on 14 August 2021. Retrieved 14 August 2021.
  159. ^ Cecutti, Lorenzo; Chemero, Anthony; Lee, Spike W. S. (1 July 2021). "Technology may change cognition without necessarily harming it". Nature Human Behaviour. 5 (8): 973–975. doi:10.1038/s41562-021-01162-0. ISSN 2397-3374. PMID 34211150. S2CID 235709853. Archived from the original on 20 October 2021. Retrieved 14 August 2021.
  160. ^ Firth, Joseph; Torous, John; Stubbs, Brendon; Firth, Josh A.; Steiner, Genevieve Z.; Smith, Lee; Alvarez-Jimenez, Mario; Gleeson, John; Vancampfort, Davy; Armitage, Christopher J.; Sarris, Jerome (2019). "The "online brain": how the Internet may be changing our cognition". World Psychiatry. 18 (2): 119–129. doi:10.1002/wps.20617. ISSN 2051-5545. PMC 6502424. PMID 31059635.
  161. ^ "Video games can boost children's intelligence: study". Karolinska Institutet. Retrieved 24 June 2022.
  162. ^ Sauce, Bruno; Liebherr, Magnus; Judd, Nicholas; Klingberg, Torkel (11 May 2022). "The impact of digital media on children's intelligence while controlling for genetic differences in cognition and socioeconomic background". Scientific Reports. 12 (1): 7720. doi:10.1038/s41598-022-11341-2. ISSN 2045-2322. PMC 9095723. PMID 35545630.
  163. ^ "Teens around the world are lonelier than a decade ago. The reason may be smartphones". Washington Post. Archived from the original on 3 August 2021. Retrieved 14 August 2021.
  164. ^ Twenge, Jean M.; Haidt, Jonathan; Blake, Andrew B.; McAllister, Cooper; Lemon, Hannah; Le Roy, Astrid (20 July 2021). "Worldwide increases in adolescent loneliness". Journal of Adolescence. 93: 257–269. doi:10.1016/j.adolescence.2021.06.006. ISSN 0140-1971. PMID 34294429. S2CID 236197751. Archived from the original on 14 August 2021. Retrieved 23 August 2021.
  165. ^ a b Bakker D, Kazantzis N, Rickwood D, Rickard N (March 2016). "Mental Health Smartphone Apps: Review and Evidence-Based Recommendations for Future Developments". JMIR Mental Health. 3 (1): e7. doi:10.2196/mental.4984. PMC 4795320. PMID 26932350.
  166. ^ Hollis C, Falconer CJ, Martin JL, Whittington C, Stockton S, Glazebrook C, Davies EB (April 2017). "Annual Research Review: Digital health interventions for children and young people with mental health problems – a systematic and meta-review" (PDF). Journal of Child Psychology and Psychiatry, and Allied Disciplines. 58 (4): 474–503. doi:10.1111/jcpp.12663. PMID 27943285. S2CID 42082911. Archived (PDF) from the original on 20 July 2018. Retrieved 13 July 2019.
  167. ^ Seko Y, Kidd S, Wiljer D, McKenzie K (September 2014). "Youth mental health interventions via mobile phones: a scoping review". Cyberpsychology, Behavior and Social Networking. 17 (9): 591–602. doi:10.1089/cyber.2014.0078. PMID 25007383.
  168. ^ Spijkerman MP, Pots WT, Bohlmeijer ET (April 2016). "Effectiveness of online mindfulness-based interventions in improving mental health: A review and meta-analysis of randomised controlled trials". Clinical Psychology Review. 45: 102–114. doi:10.1016/j.cpr.2016.03.009. PMID 27111302.
  169. ^ Patel V, Saxena S, Lund C, Thornicroft G, Baingana F, Bolton P, et al. (October 2018). "The Lancet Commission on global mental health and sustainable development". The Lancet. 392 (10157): 1553–1598. doi:10.1016/S0140-6736(18)31612-X. PMID 30314863. S2CID 52976414. Archived from the original on 20 October 2021. Retrieved 17 January 2019.
  170. ^ Marshall JM, Dunstan DA, Bartik W (5 November 2019). "The Digital Psychiatrist: In Search of Evidence-Based Apps for Anxiety and Depression". Front Psychiatry. 10 (831): 831. doi:10.3389/fpsyt.2019.00831. PMC 6872533. PMID 31803083.
  171. ^ Blumenfield S, Levin-Scherz J (3 December 2020). "Digital Tools Are Revolutionizing Mental Health Care in the U.S." Harvard Business Review. Archived from the original on 25 December 2020. Retrieved 28 December 2020.
  172. ^ Levin S (15 December 2017). "Facebook admits it poses mental health risk – but says using site more can help". The Guardian. Archived from the original on 14 January 2019. Retrieved 15 January 2019.
  173. ^ Rajan A (28 January 2019). "Can Nick Clegg help Facebook grow up?". BBC News. Archived from the original on 28 February 2019. Retrieved 27 February 2019.
  174. ^ Booth C (1 August 2018). "Facebook and Instagram officially announce new tools to fight social media addiction". The Next Web. Archived from the original on 4 April 2019. Retrieved 19 December 2018.
  175. ^ Kircaburun K, Griffiths MD (March 2018). "Instagram addiction and the Big Five of personality: The mediating role of self-liking". Journal of Behavioral Addictions. 7 (1): 158–170. doi:10.1556/2006.7.2018.15. PMC 6035031. PMID 29461086.
  176. ^ Shaban H (1 May 2019). "Here's why Instagram is going to hide your 'likes'". The Washington Post. Archived from the original on 5 May 2019. Retrieved 1 May 2019.
  177. ^ Robertson H (18 July 2019). "Instagram hides 'likes' from more users". Yahoo! News. Agence France-Presse. Archived from the original on 11 August 2019. Retrieved 11 August 2019.
  178. ^ Steinmetz K (8 July 2018). "Inside Instagram's War on Bullying". Time. Archived from the original on 28 July 2019. Retrieved 7 August 2019.
  179. ^ a b c d King DL, Delfabbro PH, Doh YY, Wu AM, Kuss DJ, Pallesen S, et al. (February 2018). "Policy and Prevention Approaches for Disordered and Hazardous Gaming and Internet Use: an International Perspective" (PDF). Prevention Science. 19 (2): 233–249. doi:10.1007/s11121-017-0813-1. PMID 28677089. S2CID 28853252. Archived (PDF) from the original on 20 October 2021. Retrieved 29 September 2019.
  180. ^ "State data to limit China child gamers". BBC News. 6 September 2018. Archived from the original on 2 October 2019. Retrieved 18 September 2019.
  181. ^ "A new notice from China's Ministry of Education, and its impact on games". Niko. Niko Partners. 30 August 2018. Archived from the original on 20 September 2019. Retrieved 18 September 2019.
  182. ^ Webb K (7 November 2018). "Video game addiction has sparked a culture war in China – and it's having huge repercussions for the world's biggest video game maker". Business Insider Australia. Archived from the original on 20 September 2019. Retrieved 18 September 2019.
  183. ^ a b Haig M (10 May 2018). "Google wants to cure our phone addiction. How about that for irony? | Matt Haig". The Guardian. ISSN 0261-3077. Archived from the original on 11 January 2019. Retrieved 10 January 2019.
  184. ^ Ceres P (25 September 2018). "How to Use Apple's Screen Time Controls on iOS 12". Wired. ISSN 1059-1028. Archived from the original on 17 December 2018. Retrieved 13 December 2018.
  185. ^ Haller S (27 August 2018). "Warning: Apple's new Screen Time could allow your child to watch NC-17 movies". USA Today. Archived from the original on 10 January 2019. Retrieved 10 January 2019.
  186. ^ "Google invests in mental health specialist Quartet to expand machine learning team". Healthcare IT News. 4 January 2018. Archived from the original on 5 October 2019. Retrieved 6 October 2019.
  187. ^ Benoit D (7 January 2018). "iPhones and Children Are a Toxic Pair, Say Two Big Apple Investors". WSJ.com. Archived from the original on 8 January 2019. Retrieved 8 January 2019.
  188. ^ "New Letter From JANA Partners and Calstrs to Apple Inc". thinkdifferentlyaboutkids.com. JANA Partners LLC. 4 June 2018. Archived from the original on 5 January 2019.
  189. ^ Musil S. "Apple vows new parental controls amid child addiction fears". CNET. Archived from the original on 9 January 2019. Retrieved 9 January 2019.

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