Gambling, Gaming, Shopping, and Social Media Addiction: The Role of Materialistic and Hedonic Values

Psychological predictors of the co-occurrence of problematic gaming, gambling, and social media use among adolescents

Back to table of contents Previous article Next article Clinical & ResearchFull AccessSpecial Report: Be Prepared to Address Technological Addictions in Psychiatric PracticePetros Levounis, M.D., M.A.Petros LevounisSearch for more papers by this author, M.D., M.A.Published Online:1 Feb 2022https://doi.org/10.1176/appi.pn.2022.2.4AbstractIn an ever-expanding high-tech environment, some individuals who are overly preoccupied with technology and online activity may need psychiatric help.iStock/DisobeyArtThough online technologies like interconnected computers and electronic messaging can trace their origins to the 1960s, the online world did not take off until the end of the 20th century with the advent of a public World Wide Web and the rise of the cellular phone. Since then, however, we have seen an explosion in online applications that have connected people across the globe in ways never imagined. Billions of text messages are sent across smartphones each day, keeping distant friends and family in touch, while consumers can find almost any product they need without leaving their house.The benefits offered by online technologies have become more evident since the COVID-19 pandemic began, as offices, schools, and health care centers transitioned to virtual services to continue operating under socially restrictive guidelines. Though this “new normal” has been imperfect, the ability to work, learn, and socialize remotely has mitigated many of the adverse impacts of this pandemic.But the seemingly endless bounty offered by online technology is not without risks. Just as happens with substances like alcohol or opioids, some people become so caught up in their virtual world that their real world—jobs, finances, relationships, physical health—begins to suffer. As smartphones and other modern devices become more and more integrated into all facets of life, understanding, identifying, and treating these technological addictions will become a significant aspect of psychiatric care.Medical Illness vs. Societal IllWhen conceptualizing technology-related addictions, we limit our scope to the people who exhibit a true medical disorder. Most people can use technologies for extended periods without ill effect. Parents, teachers, and doctors may bemoan that today’s youth are spending too much time online, but in most cases the children do not develop clinical problems. And although there is a growing consensus that social media is decreasing our civility and increasing tribalization, negative online behaviors are not necessarily indicative of an underlying disorder. The question of how online technologies are influencing our wellness, happiness, and creativity is extremely relevant, but let us leave that discussion for another day and invite the sociologists, philosophers, and policymakers to join the conversation.Cybersex: An All-Inclusive TermOnline PornographyOnline DatingSex ChatsSex WebcamsTeledildonicsFrom a psychiatric perspective, we are primarily concerned with those individuals who continue to be preoccupied with a technology despite experiencing internal preoccupation and external consequences. Just as with substance use disorders, people with a genuine technological addiction can develop tolerance and require greater time or intensity in their behavior to achieve the same effect. People with a technological addiction also think obsessively about their behavior when not online, and they experience withdrawal symptoms if they are shut out from their technology of choice.Only one technological addiction has been semi-officially recognized by APA as of DSM-5: internet gaming disorder is in Section III of our manual as a condition for further study. However, addiction specialists generally agree on seven major online behaviors of concern: internet gaming, online gambling, online shopping, cybersex, internet surfing, texting/emailing, and social media.Technology’s Seven DiscontentsInternet gaming disorder: Given its inclusion in the back pages of DSM-5 as well as in the most recent International Statistical Classification of Diseases (as gaming disorder), problematic gaming can be seen as the prototype disorder that can help professionals develop diagnostic criteria and treatment plans for other technological addictions. This disorder rose to prominence during the heyday of massive multiplayer online games like World of Warcraft, with stories of gamers losing themselves in their online world at the expense of real-world connections. Today, problematic gaming can occur on both high-performance computers and basic smartphones, as game developers have become more adept at keeping players in a psychological “flow state.” A game’s challenge rises concurrently with a player’s skill and experience, such that the player becomes neither bored nor anxious, encouraging (or rather forcing) longer play.Internet gambling disorder: While gambling disorder is recognized in DSM-5, the internet has broadened the opportunities for problematic gambling immensely. In addition to virtual recreations of casinos and racetracks, online gambling can be found in a range of fantasy sports leagues and brokerage firms that let people engage in wild and speculative trading of stocks and other investments like cryptocurrencies. Some online sites have even prospered by offering casino-like games without any tangible payoff; this has led some experts to reconceptualize addictive gambling not as a rewards-based disorder, but an irresistible attraction to the thrill of risking something of value.Online shopping disorder: This category includes traditional purchase shopping as well as auction shopping, which adds some of the thrill of gambling. As with gambling, problematic shopping was around in the brick-and-mortar days, but the online experience has exacerbated the risks by shrinking the path to purchase. This four-step model posits that consumers go through a period of awareness (there’s a new product out), consideration (that might be good for me), conversion (I’m going to the store this weekend to buy it), and evaluation (I like it and will tell my friends) with each purchase. With endless advertising, boundless product reviews, and time-limited flash sales, the internet has made this cycle near instantaneous. As with addictive substances (think tobacco, intravenous heroin, or alprazolam), the quicker the onset of action, the greater the addictiveness of the drug or the behavior.Cybersex: Though internet pornography springs to mind when thinking about cybersex, this disorder also includes more active and social behaviors like adult webcams, sex chats, and even unhealthy online dating. The current frontier in this field is teledildonics, a form of virtual sex in which webcam viewers can remotely control sexual stimulation devices used by the host. As with shopping or gambling, sex addiction is not new, but online technologies have let people explore sexuality with far more accessibility, affordability, and anonymity than ever before, which may be of particular concern with younger individuals.Internet surfing and infobesity: While people have joked that no one has yet found the end of the internet, the vast amount of online information can lead to a pair of related problems. The first is the classic journey of surfing from one webpage to the next via hyperlinks or search engines, as a user’s momentary interests distract from a prespecified task. Soon, people find they wasted hours of potential productivity going down online rabbit holes. On the other hand, people who stay focused on a task while online can find themselves experiencing information overload, or “infobesity.” In this proposed disorder, users find so much information on their topic of interest that they don’t know how to sort through it all and proceed, leading to a state of productive paralysis.Texting/email addiction: Communication is an important component of human behavior, and it’s undeniable that texts and emails have become a preferred tool for keeping in touch with friends, family, and coworkers. In some instances, though, the time devoted to online chatting and the content of communication become unhealthy, with sexting and cyberbullying being two prominent examples.Social media addiction: It may be appropriate to end the list with social media since this topic may have the fuzziest delineation between healthy and unhealthy use. Many people believe if social media apps like Facebook or Twitter disappeared altogether, the world would be much improved. As previously noted, however, debates on the repercussions of the social media era are somewhat beyond the scope of everyday clinical psychiatry. The relevant issue is whether patients are experiencing significant symptoms and consequences due to their social media use. As social media is still a rapidly evolving space, identifying addictive use is difficult, but one strong warning sign could be extended passive use of social media, where one is more voyeur than active participant. Another red flag may be related to FOMO, or the “fear of missing out” on the latest news developments or the fabulous lives of others, as a person’s driving factor in social media use.Diagnostic Dilemmas: All for One or One for All?In examining the above list, one can see that these (proposed) disorders have not arisen from the depths of the World Wide Web; most of these online behaviors have addictive reflections in the real world. Our professional great grandparents Emil Kraepelin and Eugene Bleuler, for example, described compulsive shopping disorder more than a century ago, while accounts of compulsive gambling or sex addiction are older still. Even some problematic elements of social media use, such as obsessive following of photos and videos from influencers, resemble the problems seen a generation ago among youth who obsessed over fashion magazines. Given these connections, some might wonder whether we need to establish a class of technological addictions; perhaps it is better to incorporate these problems into existing frameworks of behavioral addictions—for instance, making internet gambling disorder a subtype or specifier of gambling disorder.But while the base behaviors are similar, conducting these behaviors through a digital intermediary can alter many fundamental aspects of the disorder. In gambling disorder, for instance, individuals are diagnosed who meet a minimum set of criteria over the previous 12-month span, reflecting that gambling episodes are often sporadic and not always financially ruinous. With online gambling, the same at-risk individual now has 24/7 access to casinos, and the symptoms for diagnosis of a disorder might emerge in a couple of months or even weeks. Likewise, many people engage in cybersex specifically to experience “online dissociation,” which makes the psychology of the disorder quite different from that of those who have real-world sexual dysfunction.Another option floated by some professionals is to develop broad diagnostic criteria based on platforms, such as internet addiction or smartphone addiction. There is certainly a rationale for this. Consider online gaming: While the ability to maintain gamers in a “flow state” contributes to addictive gaming, developers also increasingly entice gamers with elements derived from gambling (loot boxes that offer prizes of varying rarity) and shopping (releasing a game for free but incorporating microtransactions to unlock bonuses or cosmetic upgrades) arenas. Likewise, many online gambling sites have taken to gamifying their experience (for instance, by enabling players to level up their casino avatar the more they play) or adding sexual elements to separate themselves from physical casinos.However, individuals have different motivations and gratifications when conducting each of these online activities. While gambling can be seen as a thrill of risking something of value, shopping is done for the thrill of acquiring something of value. In addition, data suggest that certain demographics may be at elevated risk of different addictions. Online gaming addiction occurs more frequently in men, while social media addiction is more likely to afflict women; texting addiction is seen more often in young adults, while shopping addiction is more common in older adults. Understanding these differences will help professionals develop more robust screening tools and treatment strategies.How Do I know If My Patient Is Addicted to Technology?For classic substances of misuse, we can reasonably look at well-validated scales, screening instruments, and diagnostic criteria to identify people who might be experiencing an addiction. But when it comes to digital devices, we mostly are at a loss. One factor we can be confident about is that time spent online is not a reliable indicator of a problem. Being routinely engaged with social media is a requirement for many corporate jobs, while competitive gaming and/or online streaming of games has become a popular pastime and money maker. How can psychiatrists distinguish a healthy, though time-consuming, habit from an unhealthy psychiatric condition?As noted above, the seven proposed technological addictions are largely unique entities with distinct risk factors and motivations, but at times they share some thematic elements such as thrill seeking, escapism, and financial ramifications. Therefore, the work carried out to define online gaming disorder can provide a framework for diagnosing other technological addictions. Under the current DSM-5 entry, online gaming disorder is likely present if someone meets five of the following nine symptom criteria over a 12-month period:Being preoccupied with video games.Experiencing withdrawal symptoms when video games are inaccessible.Requiring more and more playing time to gain the same level of satisfaction.Being unable to cut down on game playing despite efforts to do so.Giving up other activities to play more frequently.Deceiving family members about how much time is spent gaming.Using video games to alleviate negative moods.Jeopardizing jobs or relationships due to gaming.Continuing to play video games despite knowledge of adverse consequences.When considering whether patients might have a technological addiction, consider whether their online activities may be related to another psychiatric diagnosis. As Robert Glick, M.D., director of the Center for Psychoanalytic Training and Research at Columbia University from 1997 to 2007 taught us, “the chief complaint is often nothing more than a dysfunctional solution to a yet unidentified problem.” The problematic engagement with technology may be a coping mechanism, maladaptive behavior, or a self-medication for an underlying psychiatric condition. Since online gaming disorder became recognized, many families have jumped on it to explain problems in their children, when emergent depression, bipolar disorder, or schizophrenia is the true diagnosis. Having an external culprit like video games or social media is a less stigmatizing—and thus more easily accepted—problem than a psychiatric illness for many.Treatment Options and Goals: How to Manage a Modern NecessityJust as the diagnostic criteria for the seven proposed technological addictions remain a work in progress, the guidance on how to treat patients with such a disorder remains so as well. The best advice currently is to rely on what works well across the broad addiction sphere: providing patients an integrated treatment that incorporates addiction psychotherapy, pharmacological treatment of other psychiatric disorders, and possibly mutual-help (otherwise known as 12-step) facilitation.Counseling GuidanceBe empathic and curious.Educate about problematic use and addiction.Advise.Follow up.Refer, if necessary.Source: National Institute on Alcohol Abuse and Alcoholism, NIAAA.NIH.gov.The first approach should be professional assessment and counseling, which many general psychiatrists should be prepared to take on themselves. As with substance use disorders and other behavioral addictions, educating and counseling patients about their technological addiction is based on empathy, curiosity, and nonjudgmental support. That a proposed disorder is not yet codified in text does not disqualify someone from having a legitimate psychiatric concern.After initial assessment and counseling, motivational interviewing and cognitive-behavioral therapy that includes mindfulness techniques may be an effective strategy in the management of many technological addictions. Furthermore, peer support groups are now available for all the technological addictions listed.Some psychiatrists may wonder whether patients with a technological addiction should be discouraged from using technology-based treatment such as internet-based cognitive-behavioral therapy or online 12-step programs, since this may potentially keep their problem front and center. To that, one could argue that our field uses opioids to treat opioid use disorder and nicotine patches for smoking cessation, so we have successfully gone down this road before. The rise of online peer support and recovery groups has been extremely helpful in addiction treatment (even more so during the pandemic), as individuals now can connect with others in a comforting and, if desired, truly anonymous manner.When it comes to medications, things get tricky, as no medications are approved for any behavioral addiction, technology based or otherwise. The optimal use of medications for most patients is in the management of common psychiatric comorbidities like depression or anxiety, which have been shown to worsen the problematic behavior. If you think a patient might need some medication assistance, there are a few options to consider, but caution is warranted as the evidence is very limited. Patients with internet gambling or internet shopping disorder, who have an impulsivity-driven technological addiction, might respond to naltrexone, which has moderate evidence of efficacy in non-internet gambling disorder. Patients with a compulsive technological addiction like cybersex may benefit from selective serotonin reuptake inhibitors (SSRIs), which are first-line medications for obsessive-compulsive spectrum disorders; SSRIs also decrease libido as a side effect, which may be an additional benefit for treating cybersex addiction. Finally, methylphenidate might help manage problematic internet surfing, based on some limited evidence in studies among people with attention-deficit/hyperactivity disorder.ConclusionThough data on the prevalence of technological addictions are sparse, most people use computers, tablets, and smartphones regularly with great benefits and no serious adverse consequences. Research on the phenomenology and nosology of these illnesses will help us further elucidate the distinction between problematic and nonproblematic use of technology, especially in children and young adults. Another area of new research will involve emerging technologies. By the time clinicians get a firmer grasp of today’s ailments, the technology of tomorrow—such as virtual reality and smart devices powered by artificial intelligence—will be commonplace enough to bring about a host of new problems. Finally, we will need to be ready to guide our patients, our colleagues, and the general public on how to best handle technology with an eye on maximizing its enormous potential for fulfillment, gratification, and happiness while minimizing its significant risks for dissatisfaction, misery, and despair. ■Disclosure statement:The author receives revenue from APA Publishing but has no other financial conflicts to disclose.Petros Levounis, M.D., M.A., is a professor and chair of the Department of Psychiatry and associate dean at Rutgers New Jersey Medical School and chief of service at University Hospital in Newark, N.J. He is co-editor with James Sherer, M.D., of Technological Addictions from APA Publishing. 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Purpose of ReviewThe COVID-19 pandemic changed people’s lifestyles and such changed lifestyles included the potential of increasing addictive behaviors. The present systematic review and meta-analysis aimed to estimate the prevalence of different behavioral addictions (i.e., internet addiction, smartphone addiction, gaming addiction, social media addiction, food addiction, exercise addiction, gambling addiction, and shopping addiction) both overall and separately.Recent FindingsFour databases (PubMed, Scopus, ISI Web of Knowledge, and ProQuest) were searched. Peer-reviewed papers published in English between December 2019 and July 2022 were reviewed and analyzed. Search terms were selected using PECO-S criteria: population (no limitation in participants’ characteristics), exposure (COVID-19 pandemic), comparison (healthy populations), outcome (frequency or prevalence of behavioral addiction), and study design (observational study). A total of 94 studies with 237,657 participants from 40 different countries (mean age 25.02 years; 57.41% females). The overall prevalence of behavioral addiction irrespective of addiction type (after correcting for publication bias) was 11.1% (95% CI: 5.4 to 16.8%). The prevalence rates for each separate behavioral addiction (after correcting for publication bias) were 10.6% for internet addiction, 30.7% for smartphone addiction, 5.3% for gaming addiction, 15.1% for social media addiction, 21% for food addiction, 9.4% for sex addiction, 7% for exercise addiction, 7.2% for gambling addiction, and 7.2% for shopping addiction. In the lockdown periods, prevalence of food addiction, gaming addiction, and social media addiction was higher compared to non-lockdown periods. Smartphone and social media addiction was associated with methodological quality of studies (i.e., the higher the risk of boas, the higher the prevalence rate). Other associated factors of social media addiction were the percentage of female participants, mean age of participants, percentage of individuals using the internet in country, and developing status of country. The percentage of individuals in the population using the internet was associated with all the prevalence of behavioral addiction overall and the prevalence of sex addiction and gambling addiction. Gaming addiction prevalence was associated with data collection method (online vs. other methods) that is gaming addiction prevalence was much lower using online methods to collect the data.SummaryBehavioral addictions appeared to be potential health issues during the COVID-19 pandemic. Healthcare providers and government authorities should foster some campaigns that assist people in coping with stress during COVID-19 pandemics to prevent them from developing behavioral addictions during COVID-19 and subsequent pandemics.

This study examined the relationship between social media addiction, game addiction and family functions in adolescents. Respondent of this study is 762 students studying at four different high schools of the province of İstanbul. In the study, Pearson Moment Correlation Coefficient was found to determine the level of relationships between social media addiction, game addiction and family functions in adolescents. The effects of social media addiction and game addiction in adolescents on family functions were examined with regression analysis technique. When the relationships between social media addiction, game addiction and family functions in adolescents were examined, a positive relationship was found between social media and game addiction, while a positive significant relationship was found between both social media and game addiction and unhealthy family functions. In addition, it was also concluded that social media addiction and game addiction in adolescents were significant predictors of all subdimensions of family functions.

The purpose of this article is to identify possible relationships among Russian-speaking schoolchildren between: video game addiction, smartphone addiction, social media addiction, aggression, anxiety, depression, procrastination, daily gaming duration, and sleep problems. The basis of this empirical study was the results of online testing of 310 schoolchildren ages 10-17 (mean age M = 14.3 years, SD = 1.9). Used: the APA questionnaire on video game addiction, a short version of the questionnaire on smartphone addiction (author V.P. Sheynov), the questionnaire on social media addiction (authors V.P. Sheynov, A.S. Devitsyn), a short version of the questionnaire on procrastination (authors V.P. Sheynov, A.S. Devitsyn), the Russianlanguage version of the Hospital Anxiety and Depression Scale (adapted by M.A. Morozova et al.). Positive correlations were found among Russian-speaking schoolchildren between: video game addiction, smartphone addiction, social media addiction, aggression, anxiety, depression, procrastination, duration of daily video game playing, and sleep problems. With age, schoolchildren of both sexes show higher rates of social media addiction, smartphone addiction, aggression, anxiety, depression, and procrastination. At ages 10-17, boys have significantly higher rates of video game addiction and daily video game playing than girls, and their rates increase with age. Girls have higher rates of social media and smartphone addiction, anxiety, and procrastination than boys. Aggression is also more pronounced in girls, especially in schoolgirls ages 10-13. Boys and girls suffer equally from depression and sleep problems. The obtained results have theoretical significance. In particular, they show that video game addiction, smartphone addiction and social media addiction form a triune concept (construct) that can be defined as the “Problem Complex of Digital Addictions”, which includes smartphone addiction, social media addiction and video game addiction with their positive relationships with each other and positive relationships with such problematic personality traits as aggression, anxiety, depression, procrastination, sleep problems and duration of daily video game playing.

Social media addiction among youths is becoming a pressing public mental health issue in contemporary society due to the devastating consequences on individuals (i.e., perpetrator and victim) and society. This study, therefore, examined the prevalence, pathways to social media addiction, and predictive factors of social media addiction among Ghanaian youths. The present study used a cross-sectional survey design. A total of 488 participants were conveniently selected to respond to measures on social media addiction, gaming disorder, internet gaming disorder, smartphone application-based addiction, nomophobia, stress, anxiety, and depression. Linear regression and Hayes’ PROCESS macro were used to analyze the data. The findings revealed the prevalence rates of social media addiction (12.3%), gaming disorder (3.7%), internet gaming disorder (3.1%), smartphone application-based addiction (29.1%), nomophobia (49.6%), stress (26%), anxiety (62.1%), and depression (49%). There was a direct effect of smartphone application-based addiction on social media addiction and indirect effects through gaming disorder and nomophobia. Also, smartphone application-based addiction had direct effects on gaming disorder, internet gaming disorder, nomophobia, stress, anxiety, and depression. However, there was no direct effect of internet gaming disorder, stress, anxiety, and depression on social media addiction. Furthermore, smartphone application-based addiction and nomophobia (specifically, “losing connectedness” and “giving up convenience”) significantly predicted social media addiction among the youths in general. Among females, the predictive factors were smartphone application-based addiction, and nomophobia, specifically “losing connectedness” and “not being able to access information,” while smartphone application-based addiction, anxiety, and nomophobia, specifically “giving up convenience,” were the predictive factors for males. Smartphone application-based addiction and nomophobia play significant roles in social media addiction, and there are at least three pathways to social media addiction among youths. Therefore, counselors and health professionals need to develop educational and preventive programs that focus on digital literacy and healthy technology use among youths.

Although previous meta-analyses were conducted to quantitatively synthesize the relation between problematic social media (SM) use and mental health, they focused on Facebook addiction. The purpose of this meta-analysis is to examine this relation by extending the research scope via the inclusion of studies examining problematic use of all platforms. One hundred and thirty-three independent samples (N =244,676) were identified. As expected, the mean correlations between problematic SM use and well-being are negative, while those between problematic SM use and distress are positive. Life satisfaction and self-esteem are commonly used to represent well-being, while depression and loneliness are usually used to indicate distress. The mean correlations of problematic SM use with life satisfaction and self-esteem are small, whereas those of problematic SM use with depression and loneliness are moderate. The moderating effects of publication status, instruments, platforms and mean age are not significant. The magnitude of the correlations between problematic SM use and mental health indicators can generalize across most moderator conditions.

Latent classes of gaming disorder symptoms by gender: associations with problematic social media use, psychosomatic symptoms, bullying, and social support in adolescents.

SummaryIntroductionGambling, especially when problematic, has been observed to have a significant impact on mental health, social relationships, and well-being in general. Social isolation and problematic social media use (PSMU) have also been identified as risk factors affecting psychological well-being, with a potential link to gambling that may intensify the impact on well-being, especially among adolescents. However, the interaction between these factors remains poorly explored, especially in younger populations. This study aims to investigate the effects of social isolation and problematic social media use on psychological well-being in a sample of adolescents, focusing on how these factors interact and influence well-being according to different engagement in gambling.MethodsWe analyzed data from the 2021/2022 Italian Health Behaviour in School-aged Children study in Tuscany Region. A cross-sectional study was conducted on 1,265 Tuscan adolescents aged 15-17 years, divided into three groups according to gambling behavior: non-gamblers, occasional gamblers and problem gamblers. Participants completed self-report questionnaires to assess well-being, social isolation, and PSMU. Data were analyzed using clustering methods, descriptive statistics, and path analysis to explore the relationships among these variables.ResultsThe study identified three distinct groups of gamblers: non-gamblers (74.3%), casual gamblers (10.0%) and problem gamblers (15,7%). Contrary to expectations, problem gamblers reported the highest well-being scores, suggesting potential compensatory mechanisms or subjective perceptions masking underlying vulnerabilities. Social isolation had a negative impact on well-being in all groups, with the strongest effects observed in casual gamers. Problematic social media use did not show significant differences between groups, but was associated with lower well-being in all groups. An unexpected positive interaction between social isolation and PSMU was found in problem gamblers, indicating a unique reinforcing relationship in this group.DiscussionThe results highlight the complex interaction between gambling behavior, social isolation, and problematic social media use in influencing adolescents’ well-being. While social isolation consistently reduced well-being, problematic gamblers showed higher well-being scores, potentially due to developmental factors or maladaptive coping mechanisms.ConclusionThe study emphasizes the need for further research to better understand these relationships, particularly in the context of online gambling and social media use, to provide targeted interventions for at-risk adolescents.

This study was conducted as a descriptive and cross‐sectional study to examine the effects of game addiction and social media addiction on the lifestyle of Turkish adolescents. The study was conducted between May to June 2022, involved 1116 adolescents in the 13−18 age group receiving education in three high schools situated in the Western region of Turkey. Data were collected online with the Descriptive Information Form, Game Addiction Scale Short Form for Adolescents (GAS), Social Media Addiction Scale for Adolescents (SMAS), and Adolescent Lifestyle Profile Scale (ALP). Mean, percentage, t test, analysis of variance and linear regression analysis were used for analyzing data. There was a statistically significant difference between the presence of social media accounts and smartphones, duration of having social media account, average time spent daily on social media accounts and virtual games, social media use characteristics for the last 6 months, interests of influencers followed on social media, affection by influencers, and effect of social media on daily life and the mean scores on GAS, SMAS, and ALP. It was determined that game addiction and social media addiction explained 61.8% of the lifestyles of adolescents and significantly affected them. In addition, social media use characteristics, game addiction, and social media addiction explain and significantly predict the lifestyle of adolescents at a rate of 62.8%. The results of the study reveal that game addiction and social media addiction is a significant predictor of Turkish adolescents' lifestyle. It can be recommended to provide trainings that shed light on the importance of efficient use of technology to adolescents and their parents and to evaluate the effectiveness of these trainings.

Social media addiction has undergone a remarkable transformation among regular users, but limited research has been conducted on exploring the antecedents of addiction. The purpose of this study is to investigate the relationship between continuance intention and addiction. Moreover, it investigates the moderating role of satisfaction and trust on the relationship between continuance intention and addiction. The developed conceptual model suggests that continuance intention is the antecedent of addiction, while satisfaction and trust act as moderators between continuance intention and addiction. The antecedents of continuance intention are emotional, informational, social, and hedonic values. A survey was conducted to collect data from 572 voluntary participants, and the analysis was performed using SPSS and AMOS. The statistical result showed the effects of emotional, informational, and hedonic values on Facebook use continuance intention, but the effect of social value was not supported. Results also confirmed a significant effect of continuance intention on Facebook addiction. Additionally, it confirmed the moderating role of satisfaction on the impact of continuance intention on Facebook addiction, but the moderating role of trust was not supported. The results of this study provide insight for Facebook users, managers, and policymakers regarding treatment and intervention for Facebook addiction. It discusses several theoretical and practical implications. In this research, we proposed a new model based on extending the associations between perceived value and continuance behaviours theory.

Addiction aux jeux (d’argent et vidéo) et état de santé des joueurs : une revue critique de la littérature

BackgroundTo examine the associations of problematic and excessive social media use (SMU) with dietary behaviours of adolescents.MethodsWe analysed the 2017/2018 Health Behaviour in School-aged Children survey data, involving 222,865 adolescents (51.8% girls) from 41 countries. A dietary intake score was derived using consumption of fruits, vegetables, sweets, and sugary soft-drinks. Breakfast intake was categorised as daily or non-daily. Excessive SMU assessed how often respondents had online contact through social media, and problematic SMU was assessed through symptoms of addiction.ResultsRegression analyses showed that adolescents reporting problematic SMU had 54% lower odds in boys (OR 0.46; 95% CI 0.42–0.51) and 64% lower odds in girls (OR 0.36; 0.33–0.40) of reporting good dietary intake compared with poor intake. Excessive SMU was also associated with lower odds of reporting good dietary intake. Problematic SMU associated inversely with daily fruit and vegetable intake, while excessive SMU was positively associated with daily fruit and vegetable intake across sex. Both types of SMU were linked to increased intake of sweets and sugary drinks and decreased breakfast consumption.ConclusionsProblematic SMU was associated with poor dietary habits, while excessive SMU showed mixed findings. Prospective research is warranted to understand the causal mechanisms.ImpactProblematic and excessive social media use (SMU) was associated with poor dietary habits with problematic SMU being more detrimental than excessive SMU.This research contributes to the literature by demonstrating that problematic and excessive SMU correlate differently with adolescent dietary habits, highlighting the need for targeted approaches to promote healthier eating.Adolescents should be encouraged to use social media responsibly, while social media companies should promote local fresh food options to enhance healthy dietary habits.

BackgroundSexual and gender minority (SGM) individuals experience minority stress, especially when they lack social support. SGM young adults may turn to social media in search of a supportive community; however, social media use can become problematic when it interferes with functioning. Problematic social media use may be associated with experiences of minority stress among SGM young adults.ObjectiveThe objective of this study is to examine the associations among social media use, SGM-related internalized stigma, emotional social support, and depressive symptoms in SGM young adults.MethodsParticipants were SGM young adults who were regular (≥4 days per week) social media users (N=302) and had enrolled in Facebook smoking cessation interventions. As part of a baseline assessment, participants self-reported problematic social media use (characterized by salience, tolerance, and withdrawal-like experiences; adapted from the Facebook Addiction Scale), hours of social media use per week, internalized SGM stigma, perceived emotional social support, and depressive symptoms. Pearson correlations tested bivariate associations among problematic social media use, hours of social media use, internalized SGM stigma, perceived emotional social support, and depressive symptoms. Multiple linear regression examined the associations between the aforementioned variables and problematic social media use and was adjusted for gender identity.ResultsA total of 302 SGM young adults were included in the analyses (assigned female at birth: 218/302, 72.2%; non-Hispanic White: 188/302, 62.3%; age: mean 21.9 years, SD 2.2 years). The sexual identity composition of the sample was 59.3% (179/302) bisexual and/or pansexual, 17.2% (52/302) gay, 16.9% (51/302) lesbian, and 6.6% (20/302) other. The gender identity composition of the sample was 61.3% (185/302) cisgender; 24.2% (73/302) genderqueer, fluid, nonbinary, or other; and 14.6% (44/302) transgender. Problematic social media use averaged 2.53 (SD 0.94) on a 5-point scale, with a median of 17 hours of social media use per week (approximately 2.5 h per day). Participants with greater problematic social media use had greater internalized SGM stigma (r=0.22; P<.001) and depressive symptoms (r=0.22; P<.001) and lower perceived emotional social support (r=−0.15; P=.007). Greater internalized SGM stigma remained was significantly associated with greater problematic social media use after accounting for the time spent on social media and other correlates (P<.001). In addition, participants with greater depressive symptoms had marginally greater problematic social media use (P=.05). In sum, signs of problematic social media use were more likely to occur among SGM young adults who had internalized SGM stigma and depressive symptoms.ConclusionsTaken together, problematic social media use among SGM young adults was associated with negative psychological experiences, including internalized stigma, low social support, and depressive symptoms. SGM young adults experiencing minority stress may be at risk for problematic social media use.

Gambling disorder is the only behavioral addiction recognized as a clinical disorder in DSM-5, and Internet gaming disorder is included as a condition requiring further research. ICD-11 categorizes gambling and gaming disorders as disorders due to addictive behaviors. Additional behavioral addictions may include compulsive sexual behavior disorder, compulsive buying-shopping disorder, and problematic use of social media. This narrative review summarizes the current state of knowledge regarding these five (potential) disorders due to addictive behaviors. All five (potential) disorders are clinically relevant and prevalent. Behavioral addictions frequently co-occur with other mental and behavioral problems, such as depression, anxiety, and attention deficit hyperactivity disorder. Validated diagnostic instruments exist, with empirical support varying across conditions. No medications have approved indications from regulatory bodies for behavioral addictions, and cognitive-behavioral therapy has the most empirical support for efficacious treatment. Given that behavioral addictions are prevalent, frequently co-occur with psychiatric disorders, may often go undiagnosed and untreated, and have been linked to poorer treatment outcomes, active screening and treatment are indicated. Public health considerations should be expanded, and impacts of modern technologies should be investigated more intensively. Treatment optimization involving pharmacotherapy, psychotherapy, neuromodulation, and their combination warrants additional investigation.