The study recruited 386 participants initially, but after screening for data quality, 238 valid responses were retained for analysis. The final sample had a mean age of 20.34 years with a standard deviation of 2.14, and was composed of 44.1 percent female and 54.2 percent male respondents. Participants completed three validated instruments: the Game Addiction Scale (GAS), which measures problematic gaming across dimensions such as salience, tolerance, mood modification, and conflict; the Barratt Impulsiveness Scale Short Form (BIS-11-SF), a widely used measure of trait impulsivity covering attentional, motor, and non-planning impulsiveness; and the FoMO Scale, which captures the anxious apprehension that others might be having rewarding experiences from which one is absent. Turkish-language versions of all three scales were used, each previously validated for the local population.

The analytical centerpiece of the study was path analysis, a form of structural equation modeling that allows researchers to test multiple direct and indirect relationships simultaneously within a single theoretical model. Rather than asking whether each variable predicts gaming addiction in isolation, path analysis maps a system of pathways, estimating both the direct effect of one variable on another and the cascading effects that travel through intermediate variables. The researchers evaluated model fit using conventional criteria established in the structural equation modeling literature, and the resulting model showed generally acceptable fit indices while explaining 21 percent of the variance in gaming addiction scores.

Three direct associations emerged as statistically significant. Impulsivity showed a positive association with gaming addiction (β = 0.25, p < .001), as did gaming duration (β = 0.26, p < .001) and the number of games played (β = 0.16, p = .010). In practical terms, participants who reported higher trait impulsivity, longer hours spent gaming, and a more diverse gaming repertoire tended to score higher on the addiction scale. The similarity in the standardized coefficients for impulsivity and gaming duration is notable: it suggests that who the player is, in terms of self-regulatory disposition, matters roughly as much as how much the player actually plays.

The most intriguing finding, however, concerned what did not appear as a direct pathway. Fear of missing out, often blamed in popular commentary as a direct driver of compulsive digital behavior, showed no significant direct association with gaming addiction in this model (β = 0.09, p = .113). Yet FoMO was not irrelevant. The analysis revealed a significant indirect association: FoMO predicted gaming addiction through impulsivity, with an indirect effect of β = 0.06 and a 95 percent confidence interval of 0.018 to 0.112, which excludes zero. In other words, young adults who experience stronger fear of missing out tend to display higher impulsivity, and that elevated impulsivity in turn is associated with greater gaming addiction risk.

This mediating role of impulsivity aligns with a growing body of theoretical work on behavioral addictions. The Interaction of Person-Affect-Cognition-Execution (I-PACE) model, developed by Brand and colleagues to explain the development and maintenance of specific internet-use disorders, proposes that addictive behaviors arise from an interplay between predisposing personal characteristics, affective responses, cognitive appraisals, and executive control functions. Within that framework, FoMO can be understood as an affective-motivational state that erodes self-control, making impulsive action more likely, while impulsivity functions as the proximal self-regulatory weakness that translates emotional pressure into excessive behavior. The Turkish study’s path model provides cross-sectional statistical support for precisely this kind of chained mechanism.

The second indirect pathway involved gaming habits rather than personality. The number of games played showed a significant indirect association with gaming addiction through gaming duration (β = 0.10, 95 percent confidence interval 0.038 to 0.158). This suggests that gaming diversity, the sheer variety of titles and genres a player engages with, does not directly translate into addiction risk on its own; instead, it appears to operate by extending total play time. A player who moves across multiple games may simply accumulate more hours, and it is those hours that carry the association with problematic play. This finding echoes earlier research by Donati and colleagues, who reported that the number of video-game genres played was associated with pathological gaming in male adolescents, and it adds nuance to debates about whether versatility in gaming is a risk factor or merely a correlate.

The role of gaming duration itself deserves attention. A large-scale international study by Pontes and colleagues has examined the interplay between time spent gaming and disordered gaming, contributing to an ongoing debate about whether screen time is a cause, a consequence, or a benign correlate of gaming disorder. The Turkish findings position duration as the strongest single direct predictor in the model (β = 0.26), consistent with the view that sheer exposure is a meaningful component of risk, while the diversity finding implies that the composition of that exposure, spread across many games, matters chiefly through its effect on total time.

The study’s authors are careful to flag the limits of their design. Because the data are cross-sectional, collected at a single point in time, the model cannot establish causal direction. It is possible that impulsivity drives gaming addiction, but also that heavy gaming erodes self-control over time, or that both share an underlying cause. The sample, drawn from young adults in Türkiye and trimmed to 238 valid responses, may not generalize to other age groups, cultures, or gaming platforms, and the reliance on self-report questionnaires introduces the usual possibility of biased recall and social desirability effects. The 21 percent of variance explained, while respectable for a psychological model, also means that nearly four-fifths of the differences in gaming addiction scores remain unaccounted for by the variables studied.

Even with those caveats, the research carries practical implications. If FoMO feeds gaming addiction indirectly by amplifying impulsivity, interventions that strengthen self-regulatory capacity, such as cognitive-behavioral approaches targeting impulse control, may be more effective than campaigns that simply warn about the fear of missing out. Likewise, the finding that gaming diversity operates through duration suggests that monitoring total play time, rather than the number of titles played, is the more meaningful behavioral marker for parents, clinicians, and educators. Gaming disorder is now recognized in the ICD-11 following a clinical and public health case made by researchers including Rumpf and colleagues, and studies like this one help map the psychological terrain that precedes diagnosis. For the millions of young adults who game daily, the message from Trabzon is subtle but clear: the anxiety of being left out does not itself doom a player, but when it wears down the brakes of self-control, the hours can quietly begin to add up.

Subject of Research: Associations among impulsivity, fear of missing out, gaming habits, and gaming addiction in young adults

Article Title: Exploring gaming addiction: Associations with impulsivity, FoMO, and gaming habits

Article References: Gudek, B., & Bahcekapili, E. (2026). Exploring gaming addiction: Associations with impulsivity, FoMO, and gaming habits. Current Psychology, 45(19), Article 1561. https://doi.org/10.1007/s12144-026-10107-7

Image Credits: AI Generated

DOI: 10.1007/s12144-026-10107-7

Keywords: gaming addiction, FoMO, impulsivity, gaming duration, path analysis, young adults, behavioral addiction, self-regulation, Game Addiction Scale, structural equation modeling, gaming habits, Current Psychology