The research team, led by Hyeyoon Jeong of the Department of Psychiatry at Korea University College of Medicine together with Woojeong Lee, Hyun-suk Yi of Gwangmyeong City Health Center, and senior author MoonSoo Lee, surveyed 1,485 adolescents in an urban Korean community. Of these, 198 were classified as out-of-school youth. Because school dropouts are rarely captured in routine school-based health surveys, most of what science knows about adolescent smartphone overdependence comes from in-school populations, leaving this group largely invisible to researchers and policy makers alike. The new study is among the first to quantify just how different their risk profile looks.

Problematic smartphone use, often abbreviated PSU, refers to a pattern of smartphone engagement marked by loss of control, preoccupation, withdrawal-like distress, and interference with daily functioning. In the study, participants completed the Korean Scale for Smartphone Addiction, or K-SAS, the national standard for measuring smartphone overdependence. The results were striking: 43.9 percent of out-of-school youth met criteria for PSU compared with 35.3 percent of their in-school peers. More importantly, the out-of-school group was disproportionately represented in the highest-risk category, meaning that when smartphone use goes wrong in this population, it tends to go seriously wrong. The researchers describe this as a “polarized” distribution, with out-of-school youth clustering at the extremes of the risk spectrum rather than spreading evenly across it.

Stress showed the same polarization. Using the Perceived Stress Scale, a ten-item instrument developed by Cohen and colleagues that asks respondents to rate how unpredictable, uncontrollable, and overloaded they find their lives, the team found that out-of-school youth exhibited substantially elevated stress overall, but with a bimodal pattern suggesting that some cope reasonably well while a large subgroup experiences overwhelming levels. This heterogeneity matters clinically, because uniform interventions may fail to reach the most distressed individuals within the group.

The mental health gap was even more dramatic than the smartphone gap. On the Mind EASY mental health screening instrument, a standardized tool used in Korean community settings, 25.8 percent of out-of-school youth showed broad mental health vulnerability compared with just 6.0 percent of in-school adolescents—a more than fourfold difference. The screening captured both internalizing problems, such as depression and anxiety, and externalizing problems, such as aggression and conduct difficulties. Previous research has consistently linked externalizing symptoms to behavioral addictions, and the current study reinforces that connection: externalizing problems emerged as one of the key correlates of smartphone overdependence in multivariable regression analysis.

That regression model is the analytical heart of the paper. By simultaneously adjusting for multiple variables, the researchers isolated the factors that independently predict smartphone overdependence. Four stood out: high perceived stress, difficulty adapting to school, externalizing behavioral problems, and smoking. Each of these points to a plausible causal pathway. Stress and negative emotions are thought to drive escape-oriented and mood-modifying phone use, a mechanism supported by network analyses showing that “escaping negative moods” bridges problematic smartphone use and depression. School adaptation difficulties may push adolescents out of institutional structures that ordinarily regulate daily routines and provide social connection, leaving the smartphone as the primary—and least supervised—source of stimulation and belonging. Smoking, meanwhile, marks a broader cluster of risk behaviors; prior Korean studies have shown that drinking, smoking, and smartphone overdependence jointly elevate risk of drug involvement among adolescents.

The researchers frame their findings through the theory of cumulative advantage and disadvantage, a life-course framework holding that small initial inequalities compound over time into large gaps in well-being. An adolescent who leaves school loses access to structured time, peer networks, adult mentorship, and school-based mental health services. In that vacuum, the smartphone becomes simultaneously a lifeline and a hazard: it is the main channel for social contact, entertainment, and even future employment searches, yet the very conditions of isolation and distress that follow dropping out make compulsive use more likely. The result is what the authors call a “digital disadvantage” layered on top of educational and psychological disadvantage.

International evidence supports the gravity of the situation. Systematic reviews of young people not in education, employment, or training—the so-called NEET population—have documented markedly elevated rates of mental disorder, and meta-analyses have linked loneliness to both internet and smartphone addiction in adolescents. Korean-specific studies add further context: out-of-school youth report higher stigma, lower life satisfaction, and greater depressive symptoms, with self-esteem acting as a key mediating factor. The new study extends this literature by treating smartphone use not as an isolated behavior but as part of an integrated psychosocial profile.

The measurement strategy deserves attention. Beyond the K-SAS and PSS-10, participants completed instruments assessing emotion regulation, drawing on the Gross and John framework that distinguishes cognitive reappraisal from expressive suppression, along with items on substance use and drug-related awareness. This breadth allowed the team to test whether deficits in emotion regulation—long implicated in the development of psychopathology following childhood adversity—also underpin problematic smartphone use. Meta-analytic evidence suggests they do: adolescents who rely on maladaptive strategies such as rumination and catastrophizing show higher rates of problematic use, while adaptive reappraisal appears protective. Emotion regulation deficits may thus represent a shared root cause connecting stress, externalizing behavior, and compulsive phone use in out-of-school youth.

The public health implications are considerable. Smartphone interventions designed for in-school adolescents typically operate through schools—classroom curricula, school counselors, parental notifications—all channels that by definition fail to reach young people who have left the education system. The authors argue for integrated community-based interventions delivered through health centers, welfare centers, and alternative education programs, combining stress management, behavioral health treatment including smoking cessation, and digital literacy rather than tackling smartphone use in isolation. Digital detox strategies have shown promise in broader reviews, but their effectiveness in marginalized populations remains largely untested.

There are, of course, limitations inherent to the design. The study is cross-sectional, meaning it captures associations at a single point in time and cannot establish whether problematic smartphone use precedes or follows school dropout, distress, or smoking. The sample of 198 out-of-school youth, though substantial for such a hard-to-reach group, is modest relative to the in-school comparison, and the findings from a single Korean urban community may not generalize to other cultural contexts. Longitudinal designs tracking adolescents through the process of leaving school will be needed to untangle the direction of these relationships.

Nevertheless, the scale of the disparities documented here—a 43.9 percent prevalence of problematic smartphone use, a more than fourfold elevation in broad mental health vulnerability, and a constellation of interacting risk factors—makes a compelling case that out-of-school youth constitute a distinct high-risk population that current screening and intervention systems systematically miss. As smartphones become the default infrastructure of adolescent social and emotional life, digital inequality is no longer merely a matter of access; it is a matter of how, and how destructively, the device is used. For young people already outside the classroom, that distinction may shape the entire trajectory of their transition to adulthood.

The study drew on two waves of data from adolescents aged 14 to 17, 51 percent of them boys, with an overall average age of 15.96 years and near-identical averages for boys (15.97) and girls (15.94). At the first time point, participants completed a cybervictimization subscale, reporting how often they had been insulted, threatened, excluded or humiliated through phones and online platforms. Later, at the second time point, the same adolescents completed standardized questionnaires measuring psychological distress — a state encompassing depressive, anxious and stress-related symptoms — fear of missing out, commonly abbreviated FoMO, and problematic smartphone use, a pattern that researchers define with addiction-like criteria: loss of control over use, persistent preoccupation with the device, and continued use despite damage to sleep, schoolwork or relationships. Because the design spans two time points, it allows researchers to test directionality in a way cross-sectional surveys cannot: when victimization measured first predicts phone problems measured second, the temporal arrow points from bullying toward the compulsive behavior rather than the reverse.

The significance of the question is hard to overstate. Cyberbullying is among the most intensively studied stressors of modern adolescence, and meta-analytic reviews synthesizing dozens of studies have tied it to depression, anxiety, self-harm, suicidal ideation and substance use, with girls often bearing a heavier psychological toll. Its relationship with problematic smartphone use, however, has received comparatively little attention — even though the smartphone is typically both the arena in which the abuse unfolds and the object adolescents reach for when they are hurting. Earlier research had connected peer victimization and cyberbullying to problematic internet use more broadly, and one Chinese study traced reciprocal longitudinal links between peer victimization and mobile phone addiction through depression. What remained unclear was whether cyberbullying victimization specifically forecasts problematic smartphone use over time, and whether the strength of that link differs between girls and boys. The new study was designed to close both gaps at once.

To explain the mechanism, the authors anchored their predictions in two complementary theories. General strain theory holds that mistreatment generates negative emotional states — anger, depression, anxiety — and that people cope with this strain in ways that can include escapist or excessive behavior. Compensatory internet use theory extends that logic to screens: the device becomes a coping tool, a means of regulating unpleasant emotions by escaping into apps, feeds and messaging. Fear of missing out adds a second, more socially tuned engine. Defined in the research literature as the apprehension that others are having rewarding experiences from which one is absent, FoMO binds distress to compulsive checking. A distressed teenager cannot simply log off, because staying offline feels like abandoning the social world — and, painfully, the very platforms where the humiliation occurred remain the primary windows into that world. The model therefore predicts a chain: victimization breeds distress, distress breeds FoMO, and both states push use from habitual to harmful.

Methodologically, the team estimated a longitudinal mediation framework, the standard design for testing whether an effect travels through intermediate variables. In this architecture, cyberbullying victimization is the predictor, psychological distress and FoMO are parallel mediators assessed at the second time point, and problematic smartphone use is the outcome. The indirect pathways were tested with bootstrapping, the resampling procedure recommended for mediation analysis, and model quality was evaluated with fit statistics drawn from the structural equation modeling literature the authors cite, including the comparative fit index and the root mean square error of approximation. To probe gender differences, the researchers compared the strength of each path across boys and girls, asking whether the links from victimization to distress, from victimization to FoMO, and from both states to smartphone problems differed systematically by sex. This combination of longitudinal ordering, parallel mediation and gender comparison is what gives the study its explanatory leverage over earlier cross-sectional work.

The results followed the predicted script. Adolescents who reported more cybervictimization at the first wave showed significantly higher psychological distress and stronger fear of missing out at the second wave, and both of those states, in turn, predicted more problematic smartphone use. The total effect of being cyberbullied on later phone problems was thus carried substantially by two indirect routes: an emotional-pain route in which victimization bred distress that sought relief in the device, and a social-vigilance route in which victimization bred FoMO that drove compulsive monitoring. Critically, the gender comparisons showed that the associations of cyberbullying victimization with psychological distress, with FoMO, and with problematic smartphone use were all stronger for girls than for boys. In the authors’ reading, distress and FoMO are pivotal mechanisms linking victimization to problematic phone use — and they are especially decisive among female victims, for whom each step of the cascade runs steeper.

Why would girls be more vulnerable? The authors and the broader literature point to converging explanations. Research on self-construal suggests that girls more often define themselves through relationships, so social exclusion and online humiliation strike closer to the core of identity. Studies of interpersonal dependence find that reliance on relationships is tied to depression more strongly in women than in men, and analyses of adolescent samples show that the psychological aftermath of cyber and traditional bullying — psychological symptoms, self-harm, suicidality — is consistently heavier for girls. Girls also tend to invest more heavily in the social media environments where victimization happens, which raises the emotional price of disengaging. When the social world is both the source of injury and the repository of identity, the fear of missing out stops being a personality quirk and becomes a rational response to a threatened self — one that keeps a girl’s thumb hovering over the screen long after the attack has ended.

The FoMO pathway deserves particular attention because it contains a paradox that adults often misread. After being bullied online, many victims keep returning to the platforms where the abuse occurred — checking whether humiliating content has spread, who has viewed it, what the comment sections say, whether the attack has resumed. Each check briefly resolves uncertainty, and that fleeting relief reinforces the checking loop, in much the way anxiety-driven compulsions strengthen with repetition. Prior two-wave panel research has found that FoMO and problematic smartphone use feed each other bidirectionally, and survey work across countries has repeatedly linked depression and anxiety to problematic phone use through FoMO. In the victim’s daily life, the smartphone becomes simultaneously the weapon and the refuge: the medium of the attack and the only place to monitor, and perhaps manage, its aftermath. That duality helps explain why victims’ phone use escalates rather than collapses, and why simple screen-time limits so often fail.

The practical implications cut against simple solutions. Confiscating phones does nothing to dismantle the emotional machinery driving the behavior; distress and FoMO will find another outlet. The authors instead argue for prevention and intervention strategies that reduce emotional distress and fear of missing out among cyberbullying victims — school counseling and cognitive-behavioral support for the distress pathway, alongside efforts to loosen adolescents’ conviction that constant connection is socially mandatory for the FoMO pathway. Evidence-based anti-bullying programs that improve school climate remain the first line of defense, since preventing victimization prevents everything downstream. The study also carries a diagnostic message for adults: a sudden escalation in phone use after signs of online victimization is not mere defiance or addiction in isolation, but a barometer of unprocessed social pain, and in girls it may be the loudest such signal. The work was conducted within a project on AI-powered identification and intervention for adolescent cyberbullying funded by the Shandong Provincial Natural Science Foundation (grant ZR2025QC792).

The authors are candid about limits. Two measurement waves cannot fully rule out reciprocal effects, all data came from adolescent self-reports, and the sample was drawn from China, so cultural context may shape both bullying dynamics and smartphone norms; replication across regions and longer time spans remains necessary. Boys were affected too — the pathways ran in the same direction, only less steeply — so the gender finding concerns magnitude rather than absence. The research was reviewed and approved by an institutional ethics committee, and it arrives at a moment when adolescents’ social lives have migrated almost entirely onto devices and clinicians increasingly confront problematic smartphone use as a standalone complaint. Its central reframing is quietly consequential: compulsive phone use after cyberbullying is less a technology problem than an emotional one, and among girls the signal is louder. Treat the pain, the authors suggest, and the grip of the screen may begin to loosen.