Problematic media use (PMU) reflects addiction-like media use that can negatively affect wellbeing. PMU includes preoccupation with media, use of media for mood regulation, increasing tolerance and withdrawal symptoms around media use, and media use interfering with family relationships (Domoff et al., 2019; Domoff et al., 2021; Kuss et al., 2014). Personal ownership of smartphones rapidly increases during the preadolescent years (The Common Sense Census: Media Use by Tweens and Teens, 2021), and PMU specific to smartphones has been documented in several studies of adolescents and young adults, with prevalence estimates ranging from 14 to 31% (Sohn et al., 2019).

The media content frequently accessed by preadolescents, including online video platforms and social media (The Common Sense Census: Media Use by Tweens and Teens, 2021), are highly engineered and persuasively designed to prolong engagement, with features such as intermittent reinforcement schedules for presenting highly enjoyable content and indicators of social approval (e.g., “likes”) (Franqueira et al., 2022; Griffiths, 2018; Kuss and Griffiths, 2017; Bringing Dark Patterns to Light: An FTC Workshop, 2022; Lindström et al., 2021). Importantly, a user’s interaction with online media is tailored using extremely sophisticated algorithms based on user-specific data to maximize the likelihood that the content presented is enticing (Bringing Dark Patterns to Light: An FTC Workshop, 2022). The design of online video platforms and social media have, in fact, been compared to slot machines (The Perfect Slot Machine, 2022), where rewards are anticipated but intermittent to prolong engagement (Lindström et al., 2021). Gaming apps, even those marketed as educational (Meyer et al., 2021), are also often persuasively designed with rewards that are “unlocked” with continued play. Online games popular with preadolescents also include virtual social networks that may increase a child’s affinity for mobile media use (Kuss and Griffiths, 2017). As presented in the Interaction of Person-Affect-Cognition-Execution (I-PACE) model for the development of internet use disorder (Brand et al., 2016), engaging with such rewarding content may train reactive and reward-seeking behavior that reinforces media use and may start a cycle of addiction-like behavior around media use. Preadolescents may be especially vulnerable to the persistent and highly accessible reward-based training that mobile media devices provide because neural networks that manage behavior and self-regulation do not fully mature until late adolescence (Strang et al., 2013; Klaczynski, 2004; Stevens, 2016). Importantly, such media use behaviors may be harmful to mental health. A meta-analysis of 18 studies that enrolled adolescents and young adults documented positive associations between problematic social media use and depression, anxiety, and stress (Shannon et al., 2022).

Few studies have investigated a potential genetic predisposition to addiction-like media use and all have been completed among adolescents or young adults with a focus on internet gaming disorders (Han et al., 2007; Lee et al., 2008; Montag et al., 2012; Jeong et al., 2017; Tereshchenko, 2023). Specifically, gene variants previously associated with internet gaming disorder or addiction include SNPs rs180097 (ANKK1) (Han et al., 2007), rs4680 (COMT) (Han et al., 2007), and rs1044396 (CHRNA4) (Montag et al., 2012; Jeong et al., 2017) and short/long variants of 5HTTLPR (Lee et al., 2008). In particular, each of these SNPs relates to addictive behaviors. rs1800497 (i.e., the Taq1A polymorphism) is in an exon of the ANKK1 gene (previously believed to be within the DRD2 gene) that impacts the dopamine receptor DRD2 (ANKK1, n.d.). The alternate allele (Taq1A1; a G > A variant) is associated with alcohol dependence (Smith et al., 2008) and other disorders of self-regulation including cocaine use (Blum et al., 1996) and overeating (Sun et al., 2017). COMT rs4680 results in a variant of catechol-O-methyltransferase (COMT), an enzyme that degrades catecholamines including dopamine (COMT, n.d.). The alternate allele (a G > A variant) results in greater instability and less enzymatic activity of COMT (COMT^L) (Chen et al., 2004) and has been associated with the risk of major depressive disorder in some (Bækken et al., 2008; Wang et al., 2016) but not a majority (Antypa et al., 2013) of studies. rs4680 may also relate to nicotine dependence (Choi and Shin, 2015) including among adolescents (O’Loughlin et al., 2014), although findings are not conclusive (Choi and Shin, 2015). CHRNA4 encodes the cholinergic receptor nicotinic alpha 4 subunit, a nicotinic acetylcholine receptor (CHRNA4, n.d.), and the alternate allele in rs1044396 (a G > A variant) has been related to less nicotine dependence (Feng et al., 2004). 5HTTLPR is a repeat polymorphism in the promotor region of SLC6A4, a gene that encodes the serotonin transporter (SLC6A4, n.d.). 5HTTLPR has two variants, a short and long version that differ in the number of 44-bp repeats in the promotor region (Heils et al., 2002), although extra-long variants have been reported (Goldman et al., 2010). The short-form variant relates to reduced serotonin transporter expression (SLC6A4, n.d.) and has been associated with an increased susceptibility to major depression and alcohol dependence (Oo et al., 2016), although findings are not conclusive (Goldman et al., 2010; Fratelli et al., 2020).

No studies have assessed if preadolescents with these genetic risk factors may be more susceptible to the rewarding effects of digital media and, in turn, be more prone to developing addiction-like media use behaviors. Therefore, the goal of this study was to leverage existing genetic data to examine the associations between previously documented genetic risk factors for internet addiction and problematic media use among 9-to-12-year-old children. It was hypothesized that children with SNPs reflective of a greater risk for addiction (e.g., the presence of the Taq1A1 allele in rs180097) or depression (e.g., variants in rs4680) would demonstrate greater PMU.

The mean age of children in the analytic sample (n = 180) was 10.9 (SD 1.2) years, 43.9% of children were female, and most (90.0%) were identified by the parent as white, non-Hispanic. Families were largely from a higher socioeconomic status (Table 1). Children averaged 18.1 (SD 12.1) h per week of non-school-related screen media use, and nearly all (92.2%) of children used a touchscreen tablet or smartphone in the past month. The median PMU was 2.22 (IQR: 1.78, 2.78) which reflects a median response of rarely (2) to sometimes (3) across the nine scale items. Children’s leisure screen time per week was moderately correlated to PMU (Pearson’s r for log-transformed PMU and total screen time = 0.27; p < 0.001). The distribution of genotypes is presented in Table 2. Mean leisure screen media use per week was unrelated to rs1800497, rs4680, or rs1044396 genotype (all ANOVA p-values >0.117). Median PMU differed by rs1800497 genotype, which was of borderline statistical significance (Kruskal–Wallis p = 0.054; Figure 1) but did not differ by rs4680 (p = 0.917) or rs1044396 genotype (p = 0.944).

In adjusted regression models (Table 3), there was an additive association between the number of Taq1A1 alleles and greater PMU. Specifically, adjusted geometric mean PMU scores were 8.6% (95% CI: 0.8, 16.3%) greater for each additional copy of the Taq1A1 allele (p = 0.030; R² = 5.2%) and were 2.13 for homozygous low-risk (n = 99), 2.31 for heterozygous (n = 70), and 2.58 for homozygous high-risk (n = 11) children. A dominant (p = 0.041; R² = 4.9%) model was also supported by the data, although the additive model had a slightly better fit (Table 3). A recessive model was not statistically related to PMU (p = 0.209; R² = 3.5%).

No other allele variants were statistically associated with PMU at the p < 0.05 level. Findings were consistent when limiting the analysis to children of European descent, although the additive model for rs1800497 was not statistically significant (p = 0.097) and the dominant model for rs1800497 was borderline significant (p = 0.055) in this subset (Supplementary Table 1). In particular, post-hoc tests for an interaction between rs1800497 genotype and European ancestry were not statistically significant in the full dataset for the additive or dominant models (p-for-interaction = 0.273 and 0.858, respectively).

In this preliminary study of 180 9-to-12-year-olds, rs1800497 (i.e., the Taq1A polymorphism) was positively associated with more severe PMU as measured with a validated scale appropriate for youth. This finding aligns with that of Han et al. (2007), where the rs1800497 alternate allele was more frequent among excessive internet video game players (n = 79) than age-matched controls (n = 75) in a study of male adolescents. This is the second study to suggest that rs1800497 relates to more addictive-like media use behaviors and the first to examine this association among preadolescents. Findings are important to understand the neurological mechanisms underlying the development of PMU and if some children may be more susceptible to PMU because of a genetic risk factor.

The alternate allele (A1) of rs1800497 results in a decreased density and binding potential of DRD2 in the striatum in humans and this association follows an additive model (Ritchie and Noble, 2003; Jönsson et al., 1999; Pohjalainen et al., 1998; Gluskin and Mickey, 2016). As stated by Blum et al. (1996) and Blum et al. (2000), a dampened responsivity to dopamine likely contributes to a reward deficiency syndrome that increases the risk of addictive, impulsive, and compulsive behaviors. The media contemporary preadolescents engage with is highly engineered to be persuasive and to prolong user engagement (Franqueira et al., 2022; Griffiths, 2018; Kuss and Griffiths, 2017; Bringing Dark Patterns to Light: An FTC Workshop, 2022; Lindström et al., 2021), which can result in compulsive use of mobile devices (Soror et al., 2015). Social media itself can be uniquely rewarding. Sherman et al. found heightened activity in reward networks of the brain when adolescents viewed photographs with many “likes” (Sherman et al., 2016) or when “liking” photographs from others (Sherman et al., 2018) using a simulated Instagram platform. Thus, it is feasible that those with reward deficiency syndrome may be most prone to develop PMU because of the rewarding nature of contemporary screen media. Unfortunately, our study did not measure children’s media use on the different device types or platforms, and we cannot test whether rs1800497 is related to the use of more (e.g., social media) vs. less (e.g., watching TV shows) persuasively engineered media.

This study did not find an association between PMU and rs4680 or rs1044396. rs4680 affects the stability of catechol-O-methyltransferase and the degradation of dopamine, suggesting that once introduced, dopamine is available in the synapses longer for those with COMT of low enzymatic activity (COMT^L) (Chen et al., 2004). A previous case–control study of Asian male adolescents found a greater frequency of the allele encoding COMT^L among excessive internet game players (0.329) versus the control group (0.233) (Han et al., 2007). Regarding rs1044396, differing findings were reported in two previous studies examining rs1044396 and internet addiction, where the alternate (Montag et al., 2012) or reference (Jeong et al., 2017) allele related to greater internet addiction in two separate studies. This current study did not define cases with PMU and the overall mean value of PMU was low. It is possible that rs4680 or rs1044396 affects the severity or persistence of a media-based disorder once established but is not involved in the early development of that disorder. Conversely, the previous findings could have been confounded by comorbid mental health conditions (Lee et al., 2008; Ha et al., 2006).

Children’s total leisure screen media use per week was positively correlated with PMU in this current study. Screen time did not consider time spent on mobile devices specifically, and a direct test of persuasive media use and PMU is not possible in our study. However, 92.2% of preadolescents in the study used a mobile device in the past month, suggesting mobile device use was common. Screen time was unrelated to rs1044396 genotype, however, suggesting that the association with PMU is not fully dependent on total screen use quantity. Indeed, PMU captures many elements of problematic use including screen use to regulate negative mood. Longitudinal studies are needed to understand how a genetic risk for addiction relates to PMU considering the trajectories of screen use quantity and quality over time. That information is needed to best inform preventive interventions and guidance for parents and youth.

PMU was measured with a validated scale based on the nine DSM-V criteria for internet gaming disorder (Domoff et al., 2019). Importantly, this PMU measure is not specific to device type, which is an important consideration as preadolescent children frequently access online media via multiple devices including smartphones and touchscreen tablets (The Common Sense Census: Media Use by Tweens and Teens, 2021). However, measuring PMU in preadolescents is relatively new and thresholds to define clinically relevant PMU do not yet exist. Problematic smartphone use, defined as answering yes to at least six items of the 9-item Social Media Disorder Scale, was consistently related to lower mental, school, and social wellbeing in a study among 154,981 adolescents across 29 countries (Boer et al., 2020). That scale was also designed based on clinical criteria of addiction and scale items are similar to PMU items, suggesting that increased PMU may similarly relate to wellbeing among adolescents. The mean PMU was below 3 in this current study or a mean response of “sometimes” to each scale item. Additional studies are needed to understand how rs1800497 may affect PMU at more extreme levels, and if that genetic risk increases with age.

Strengths of this study include the collection of genetic data along with PMU among a sample of preadolescents. As a limitation, PMU and child media use were parent-reported and may be biased. This sample included children with lower levels of media use than national norms (The Common Sense Census: Media Use by Tweens and Teens, 2021), and the sample excluded children taking medications for attention disorders. Thus, included children were at a relatively low risk of developing more severe PMU. The sample was mostly white, non-Hispanic of higher socioeconomic status, limiting the generalizability of study findings. There were a limited number of preadolescents with two copies of the Taq1A1 allele (n = 11), which limits inference. The borderline findings among the subset of children with European ancestry may particularly be affected by a small sample size. We further did not measure comorbid mental health conditions that may confound reported associations. The goal of this study was not to conduct a genome-wide association study, but instead to test specific candidate SNPs as informed by the literature that suggests screen time may impact dopaminergic neural pathways.

In summary, this study found a positive, additive association between rs1800497, the Taq1A polymorphism, and more severe PMU among a sample of preadolescents. The effect size was small, and results need to be replicated in more diverse samples. Future studies should additionally include confirmation of PMU based on clinical criteria versus solely relying on parent reports Regardless, findings support that a neurological mechanism related to a reward deficiency may make some children more prone to developing addiction-like media use behaviors.