Reduced Serum Neuropeptide Y Levels as a Potential Neurobiological Marker for Problematic Media Use in School-Aged Children

Reduced Serum Neuropeptide Y Levels as a Potential Neurobiological Marker for Problematic Media Use in School-Aged Children | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Reduced Serum Neuropeptide Y Levels as a Potential Neurobiological Marker for Problematic Media Use in School-Aged Children Yasin Yıldız, Medeni Arpa, Tuğba Calaboğlu, Elif Göz Karadeniz, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9270342/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Introduction: The intensive integration of digital technologies into children's daily lives has introduced a novel behavioral pathology characterized as Problematic Media Use (PMU). Current diagnostic modalities predominantly rely on subjective psychometric scales. Hence, there is a critical need for objective biomarkers. This study aims to investigate the association between the severity of PMU and serum levels of Neuropeptide Y (NPY), a key mediator in stress regulation and reward circuitry. Methods A total of 80 children aged 5–11 years were enrolled in the study. PMU levels were assessed using the Problematic Media Use Scale (PMUS), and participants were stratified into three risk groups (low, moderate, and high risk) based on their scores. Serum NPY concentrations were quantified via ELISA. Results The mean PMUS score of the participants was 56.1 ± 22.9 (27–107). A significant decline in serum NPY levels was observed as PMU severity increased (p = 0.009). Correlation analysis revealed a moderate negative correlation between PMUS scores and NPY concentrations (r= -0.346, p = 0.002 $ ). In the multiple regression model, PMUS score, family income, and gender were identified as independent predictors of NPY levels (p < 0.001; adjusted R 2 = 0.185). Notably, the PMUS score demonstrated the strongest negative impact on NPY levels (β = -0.396). Conclusion This study provides early evidence demonstrating that problematic media use in children leads to the down-regulation of serum NPY levels. NPY emerges as a promising candidate for an objective biomarker in the diagnosis, screening, and therapeutic monitoring of digital addictions. Elucidating the biochemical pathways of NPY in larger longitudinal cohorts may establish a new standard in the clinical management of digital-era pathologies. Health sciences/Biomarkers Health sciences/Diseases Health sciences/Medical research Health sciences/Neurology Biological sciences/Neuroscience Problematic Media Use Neuropeptide Y Child Health Biomarker Figures Figure 1 Figure 2 INTRODUCTION The global integration of digital technologies has fundamentally transformed human interaction, learning, and entertainment. Within this emerging ecosystem, children and adolescents defined as "digital natives" engage in intensive interactions with internet-based platforms from the earliest stages of their developmental processes. The excessive and unregulated use of these platforms, particularly online gaming, has emerged as a significant public health concern [ 1 ]. Consequently, distinguishing between the "normative use" and "problematic use" of digital media products is of paramount importance. In clinical evaluation, defining problematic media use in a child should transcend mere "screen time duration" and focus on "excessive use impairing the child’s functionality." Prioritizing functional impairment is essential when assessing pediatric behavioral or developmental disorders, as it serves as the definitive boundary separating normal variations of behavior from pathological levels [ 2 ]. Similarly, updated guidelines by the American Academy of Pediatrics emphasize that digital media interactions should be evaluated not only by quantity or time spent but also by the quality of engagement. Thus, the concept of "Effective Use of Technology" has become a focal point in contemporary pediatric discourse. The transformation of digital technologies and the internet ecosystem into indispensable components of daily life has fundamentally altered information consumption and social interaction patterns, introducing a novel behavioral pathology categorized as "Problematic Media Use" (PMU). PMU is conceptualized as the uncontrolled and compulsive use of social media, video platforms, and smartphones to an extent that impairs an individual’s socio-psychological functionality [ 3 ]. Various methodologies are employed to delineate the spectrum ranging from functional/normative use to problematic engagement and full-scale addiction. Within the framework of digital-era pathologies, Internet Gaming Disorder (IGD) remains the only condition formally recognized by international health organizations. In the DSM-5-TR, IGD is categorized under Section III : Emerging Measures and Models, rather than as a formal diagnosis [ 4 ]. Conversely, the World Health Organization’s ICD-11 (International Classification of Diseases, 2022) has officially recognized "Gaming Disorder" (6C.51) as a distinct clinical entity [ 5 ]. Diagnosis is established by the presence of at least five out of nine criteria over a 12-month period (preoccupation, withdrawal, tolerance, unsuccessful attempts to control, loss of interest, continued use despite problems, deception, escape, and jeopardy or loss) [ 6 ]. Furthermore, various psychometric instruments have been developed for conditions such as Problematic Smartphone Use, Problematic Social Media Use, Online Buying, and Online Gambling [ 7 – 11 ]. However, these scales rely heavily on self-reported data and subjective scoring systems. Consequently, the diagnosis of digital technology-related disorders is currently predicated on subjective data derived from survey responses and individual observations. The potential for social desirability bias or inaccurate self-reporting remains a significant limitation. Therefore, there is an exigent need for objective biomarkers to enhance diagnostic accuracy and clinical monitoring in digital-related pathologies. Neuropeptide Y (NPY) is highly expressed within the central nervous system, particularly in the hippocampus, cortex, and hypothalamus. It is co-released with classical neurotransmitters, such as GABA and other inhibitory mediators. The expression of its two primary receptor subtypes, Y1 and Y2, has been documented in the frontal cortex, lateral septum, paraventricular nucleus (PVN), lateral hypothalamus, amygdala, hippocampus, and the nucleus tractus solitarius [ 12 ]. NPY modulates diverse physiological and pathophysiological processes, including food intake, fear and anxiety, learning and memory, depression, post-traumatic stress, and the processing of pain and pruritus [ 13 ]. Furthermore, NPY may support neuronal health and function by stimulating the release of nerve growth factors, mitigating neuroinflammation, and inducing both autophagy and neurogenesis [ 14 ]. Extensive research suggests a robust association between various forms of addiction and NPY signaling. The Nucleus Accumbens (NAc) regulates reward-related behaviors, and the mesolimbic dopamine system plays a pivotal role in the reinforcing effects of addictive substances [ 15 ]. Repeated administration of psychotomimetic agents, such as methamphetamine and cocaine, reversibly reduces NPY expression at both peptide and mRNA levels within the NAc [ 16 ]. Notably, alcohol-preferring rats exhibit lower NPY levels across several brain regions compared to non-preferring counterparts [ 17 ]. Consequently, significant alterations in NPY levels have been demonstrated in various forms of psychogenic addiction. Similar to classical substance use disorders, Problematic Media Use should be conceptualized within the spectrum of behavioral addictions, characterized by the chronic and excessive stimulation of dopaminergic neurons in the mesolimbic reward system [ 18 ]. In the context of excessive exposure to digital technologies, diagnostic criteria for disorders other than Internet Gaming Disorder remain inadequately defined, and psychometric assessments may lack sufficient reliability. Building upon this evidence, the objective of our study is to evaluate excessive digital media exposure through an objective laboratory parameter. To this end, we quantified serum NPY levels in children with Problematic Media Use. METHODS Study Design and Setting This study was designed as a descriptive, quantitative research to investigate the correlation between Problematic Media Use and serum Neuropeptide Y levels. The research was conducted at the Department of Pediatrics, Faculty of Medicine, Recep Tayyip Erdogan University. The study population consisted of healthy children of both genders, aged 5–11 years, who presented to the outpatient clinic for routine follow-up or screening and required blood sampling for clinical indications. The study was carried out between May and October 2025. Inclusion criteria were defined as being between the ages of 5 and 11 years and providing informed consent for participation. Exclusion criteria were strictly established to eliminate potential confounding factors affecting the central nervous system or NPY levels: Presence of chronic neurological disorders or developmental delays. Diagnosed neurodevelopmental conditions, including Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD). Known genetic syndromes. Chronic medication use, particularly agents with potential CNS activity (e.g., antiepileptics, antihistamines, atomoxetine, and methylphenidate). The study was conducted in accordance with the Helsinki Declaration, and written informed consent was obtained from all participants and/or their legal guardians. After obtaining consent from participants who met the eligibility criteria, they were asked to complete an epidemiological data form (demographic information form) and the “Problem Media Use Scale” (PMUS). Sample Size Determination The sample size for this study was calculated using G*Power software (version 3.1.9.4), based on Cohen’s standardized effect size conventions. According to Cohen (1992), effect sizes are categorized as small (0.10), medium (0.25), and large (0.40). To achieve a statistical power of 95% (1-beta = 0.95) with a medium effect size of 0.25 and a Type I error rate (alpha) of 0.05, the minimum required sample size was determined to be 78 participants. Data Collection Instruments *Sociodemographic Data Form A descriptive form was developed by the researchers based on current literature [ 11 ] to collect participants' characteristics. This form included items regarding chronological age, parental educational attainment, household income levels, and residential location. *Problematic Media Use Scale (PMUS) The Problematic Media Use Scale (PMUS) was originally developed by Domoff et al. in 2017 to assess screen dependency across all visual media modalities in children aged 4–11 years. The scale items were constructed based on the diagnostic criteria for Internet Gaming Disorder as outlined in the DSM-5. Items are scored on a 5-point Likert-type scale ranging from 1 (never) to 5 (always), with a maximum attainable score of 105. The instrument exists in both short (9-item) and long (27-item) versions; higher total scores indicate increased severity of problematic use. The scale is proxy-reported by parents based on their observations of the child's behaviors. Rather than focusing on a specific digital device, the PMUS aims to detect problematic use or "screen dependency" encompassing various visual media platforms, including television, computers, tablets, and smartphones. The internal consistency (Cronbach’s alpha) of the original scale was reported as 0.97 for the long form and 0.93 for the short form [ 19 ]. The Turkish adaptation and validation study was conducted and published by Furuncu and Öztürk in 2020 [ 11 ]. In the present study, the 27-item long form was utilized. Following data collection, participants were stratified into three risk groups (low, moderate, and high risk) based on their total PMUS scores. Biochemical analysis Serum samples remaining after routine biochemical analyses were used in the study. The collected serum samples were stored at − 20°C until the time of analysis. During the study period, all samples were thawed at once and analyzed in batches. Serum Neuropeptide Y levels were measured using the enzyme-linked immunosorbent assay (ELISA) method in accordance with the manufacturer’s instructions (Cat. No.: E-EL-H1893, Elabscience, Houston, USA). The kit manufacturer specifies the analytical sensitivity of the kit as 18.75 pg/mL and the measurement range as 31.25–2000 pg/mL. Statistical analysis All statistical analyses were performed using IBM SPSS Statistics for Windows, Version 29.0 (IBM Corp., Armonk, NY, USA). The normality of continuous variables was verified with the Shapiro–Wilk test and confirmed by visual inspection of histograms and Q‑Q plots. Since our data distributed normally, the continuous variables were presented as mean ± standard deviation. Categorical variables were reported as n (%). Comparisons between two independent groups were evaluated using the Independent‑Samples t test, and the corresponding effect size was expressed as Cohen’s d. Associations between categorical variables were examined using the chi‑square (χ²) test, and the magnitude of association was expressed as Phi (φ) or Cramer’s V, as appropriate effect size. Relationships between variables were assessed using Pearson’s correlation analysis. Correlation strength was reported through the correlation coefficient (r). In addition, partial correlation analysis was conducted to control for the potential effects of age and sex. Participants were stratified into tertiles according to PMUS total scores (low, moderate, and high problematic media use). Differences in mean NPY levels among tertile groups were compared using ANOVA following the verification of homogeneity of variances with Levene’s test. When overall significance was observed, Tukey’s post‑hoc test was applied for pairwise comparisons. A linear trend analysis was also performed within the ANOVA model across the ordered tertiles. Effect sizes for ANOVA and trend analyses were reported as eta‑squared (η²). To identify independent predictors of serum NPY levels, multiple linear regression analysis using the forced‑entry (enter) method was performed and NPY level was entered as the dependent variable, while PMUS total score, sex, child age, mother’s age, residential area (urban/rural), and parental education level were included simultaneously as independent variables based on theoretical and biological relevance. The overall model fit was expressed by the coefficient of determination (R² and adjusted R²), while the relative contribution of each covariate was represented by its standardized beta coefficient (β) and the change‑in‑R² value. Multicollinearity was checked using the variance inflation factor (VIF). All statistical tests were two‑tailed, and a p‑value < 0.05 was considered statistically significant. Ethics Our study was approved by the Non-Interventional Ethics Committee of Recep Tayyip Erdoğan University (Date: June 18, 2025, No. 2025/264) and the Rize Provincial Health Directorate (Date: July 23, 2024, No. E-64960800-799-249332101). RESULTS The mean age of the 80 patients included in the study was 7.9 ± 0.19 years (5–11). The proportion of female patients was 56.3% (n = 45). The epidemiological data of the participants are presented in Table 1 . Table 1 Epidemiological data of the participants Mean age of participants (mean/sd) 7,9 ± 0,19 (5–11) years Mean age of mothers (mean/sd) 27,2 ± 3,1 (25–41) years Mean age of fathers (mean/sd) 32,3 ± 4,4 (29–48) years n % n % Sex Girl 45 56,3 Father's education level Elementary 10 12,5 Boy 35 43,7 Middle school 16 20,0 Residential area Village 8 10,0 High school 34 42,5 Town 16 20,0 College 20 25,0 City 56 70,0 Mother's education level Elementary 16 20,0 Parents' employment status Dad works 50 62,5 Middle school 12 15,0 Neither of them 1 1,3 High school 36 45,0 Mom works 22 27,5 College 16 20,0 Both of them 7 8,8 Family Income Under $ 500 5 6,3 Device most frequently used Tablet 20 25,0 500–750 $ 39 48,8 Mobile phone 37 46,3 750–1000 $ 28 35,0 TV 18 22,5 1000–1500 $ 4 5,0 Game console 5 6,3 Over $ 1500 4 5,0 Results from the problem media use survey indicate that participants’ average scores were 56.1 ± 22.9 (27–107), and participants were divided into three groups based on their scores (participants were ranked from lowest to highest score). The sociodemographic and clinical characteristics of the participants are summarized in Table 2 according to the tertiles of the PMUS total scores. Father’s age differed significantly between the high‑ and moderate‑PMUS groups after post‑hoc correction (p = 0.039), indicating slightly older paternal age in children with severe problematic media use. Mother’s age showed a marginal trend but did not reach statistical significance (p = 0.062). No significant group differences were observed for sex distribution, family income, residential area (urban/rural), parental employment status, addiction type, or parental education level (p > 0.05 for all). Serum NPY levels were quantified across the three risk groups as follows: 91.13 ± 27.91 ng/mL in the low-risk group, 73.08 ± 29.83 ng/mL in the moderate-risk group, and 72.03 ± 17.58 ng/mL in the high-risk group (Fig. 1 ). A one-way analysis of variance (ANOVA) revealed that these differences between groups were statistically significant (F(2,77) = 5.055, p = 0.009). The linear trend analysis indicated a significant decreasing trend in NPY concentrations with increasing PMUS scores (F(1,77) = 9.772, p = 0.002), with no deviation from linearity (p = 0.562). The effect size (η² = 0.116, 95% CI [0.009–0.243]) indicates a moderate magnitude of effect, suggesting that higher levels of problematic media use are associated with lower circulating NPY, pointing to a possible downregulation of stress-related neuropeptide systems. Effect‑size estimates indicated the strongest difference for NPY (η² = 0.116), followed by father’s age (η² = 0.086). Table 2 Comparison of Sociodemographic and Clinical Characteristics Across PMUS Tertile Groups Low (n = 27) Moderate (n = 27) High (n = 26) p value effect size Mean ± SD; n (%) Mean ± SD; n (%) Mean ± SD; n (%) PMUS Total Score 33 ± 4 52 ± 6 85 ± 12 NPY (pg/mL) 174.8 ± 71 156.7 ± 62 121.5 ± 50 0.009 0.116 Chid age (year) 8 ± 2 8 ± 2 8 ± 2 0.279 0.033 Mother's age (year) 37 ± 5 38 ± 4 40 ± 6 0.062 0.070 Father's age (year) 42 ± 6 41 ± 5 46 ± 10 0.031 0.086 Sex Female 18 (66.7) 15 (55.6) 12 (46.2) 0.321 0.169 Male 9 (33.3) 12 (44.4) 14 (53.8) Family Income 1.000 $ 11 (40.7) 16 (59.3) 9 (34.6) Residential area Rural 11 (40.7) 7 (25.9) 6 (23.1) 0.318 0.169 Urban 16 (59.3) 20 (74.1) 20 (76.9) Parental employment status Father 17 (63) 21 (77.8) 20 (76.9) 0.394 0.153 Mother 10 (37) 6 (22.2) 6 (23.1) Device most frequently used Tablet 5 (18.5) 7 (25.9) 8 (30.8) 0.337 0.207 Mobile Phone 11 (40.7) 12 (44.4) 14 (53.8) Television 10 (37) 6 (22.2) 2 (7.7) Computer 1 (3.7) 2 (7.4) 2 (7.7) Mother’s education level Primary School 4 (14.8) 5 (18.5) 7 (26.9) 0.644 0.163 Secondary School 4 (14.8) 3 (11.1) 5 (19.2) High School 11 (40.7) 14 (51.9) 11 (42.3) University 8 (29.6) 5 (18.5) 3 (11.5) Father’s education level Primary School 5 (18.5) 2 (7.4) 3 (11.5) 0.188 0.234 Secondary School 5 (18.5) 8 (29.6) 3 (11.5) High School 10 (37) 8 (29.6) 16 (61.5) University 7 (25.9) 9 (33.3) 4 (15.4) Multiple linear regression analysis was performed to identify independent predictors of NPY levels. The overall model was statistically significant (p < 0.001; adjusted R² = 0.185). Among the variables entered into the model, problematic media use score, family income, and sex emerged as significant independent predictors of NPY concentration. Specifically, the PMUS total score demonstrated a significant negative association with NPY levels (β= − 0.396, t= − 3.596, p < 0.001), indicating that higher problem media use was related to lower circulating NPY values. Conversely, higher family income was positively associated with NPY (β = 0.265, t = 2.560, p = 0.013), and male sex contributed to higher NPY levels (β = 0.253, t = 2.334, p = 0.022). The child age, father’s age, and residential setting (urban/rural) did not significantly predict NPY after adjusting them for the other variables (p > 0.05 for all). No multicollinearity issues were observed (VIF = 1.039–1.177). Collectively, these findings indicate that the increase in problematic media use was independently associated with a decrease in serum NPY levels, even after controlling for demographic and socioeconomic factors (Table 3 ). Table 3 Multiple Linear Regression for Independent Predictors of NPY Levels Constant B SE (B) β (Std) t p VIF 149,910 48,216 3,109 0,003 PMUS Total Score -1,123 0,312 -0,396 -3,596 < 0,001 1,177 Sex (Male) 32,984 14,130 0,253 2,334 0,022 1,143 Family Income (High) 34,378 13,430 0,265 2,560 0,013 1,039 Child Age (years) 2,189 3,995 0,057 0,548 0,586 1,058 Father’s Age (years) 0,386 0,945 0,044 0,408 0,684 1,137 Residential Area (Urban) 0,603 15,137 0,004 0,040 0,968 1,120 Model Statistics: R² = 0.247; Adjusted R² = 0.185; F(6, 73) = 3.997, p = 0.002 Of the total participants, 45 (56.3%) were girls and 35 (43.8%) were boys. Mean NPY levels were 142.4 ± 46.1 pg/mL in girls and 162.5 ± 82.7 pg/mL in boys, and this difference was not statistically significant (p = 0.179, Cohen’s d = 0.305), representing a small- to- moderate effect size in favor of males. In contrast, the PMUS total score was significantly higher in boys (61.9 ± 25.7) than in girls (51.6 ± 19.7) (p = 0.046, Cohen’s d = 0.456), indicating that boys exhibited a greater degree of problematic media use with a medium effect size. While serum NPY concentrations tended to be higher in male participants, the inverse pattern was observed for media‑related behavioral risk, suggesting that increasing problematic media use in boys was not accompanied by corresponding elevations in NPY levels. Pearson’s correlation analysis revealed a significant negative relationship between NPY levels and the PMUS (r = − 0.346, p = 0.002). This indicates that higher levels of problematic media use were associated with lower circulating NPY concentrations. The correlation strength was of moderate magnitude, suggesting a meaningful but not strong inverse link between behavioral media dependence and this neuropeptidergic parameter. The combined findings indicate a consistent association between increased problematic media use and decreased serum NPY levels in school-age children. Despite the limited impact of sociodemographic and environmental factors, such as parental education, residential area, and family income, the behavioral burden, as reflected in higher PMUS scores, was identified as the primary factor influencing NPY variation (adjusted R² = 0.185). The negative association was supported by both tertile-based group comparisons and multiple regression models, and further confirmed by a moderate inverse correlation between NPY and PMUS scores (r= -0.346, p = 0.002). Despite the fact that male subjects presented slightly elevated NPY levels, they also demonstrated considerably higher PMUS scores, indicating that neuropeptidergic stress regulation mechanisms do not mitigate behavioral risk within this setting. Overall, these results point towards a potential biochemical mechanism underlying children's problematic media use, with increased engagement in digital media potentially associated with a reduction in stress-related neuropeptide systems. DISCUSSION The diagnosis of disorders arising from excessive exposure to digital technologies currently relies predominantly on psychometric scales and structured surveys. However, there is an exigent clinical need for objective evidence to categorize the severity of these conditions, monitor treatment responses, and facilitate longitudinal patient follow-up. In our study, which aimed to identify a potential biochemical surrogate for screen exposure, we demonstrated a significant inverse relationship between the severity of Problematic Media Use and serum Neuropeptide Y levels. Psychological addiction is characterized by the persistent need to engage in a substance or behavior due to emotional reinforcement, despite its potential adverse consequences. It often serves as a maladaptive coping mechanism utilized to manage negative affectivity, such as anxiety and stress [ 20 , 21 ]. Commonly consumed substances, including alcohol, nicotine, and caffeine, modulate mood and cognition by altering dopaminergic pathways within the brain's reward circuitry [ 22 ]. In the context of PMU, the "variable-ratio reinforcement" schedules inherent to digital platforms induce continuous stimulation of the NAc. This process leads to the maladaptive sensitization of the reward system and a subsequent reduction in dopamine receptor density within the ventral striatum [ 23 , 24 ]. This neurotransmitter imbalance manifesting as impulsivity, anhedonia, and a pathological "craving" for digital stimuli weakens the individual’s inhibitory control mediated by the prefrontal cortex. Consequently, this reinforces a clinical picture characterized by the inability to cease the behavior despite its detrimental outcomes [ 5 , 25 ]. From a neurobiological perspective, PMU shares common neural pathways and cognitive impairment patterns with substance use disorders. Chronic screen exposure triggers profound synaptic alterations, including long-term depression at the NAc level and dendritic remodeling, leading to a significant down-regulation of the NPY system [ 26 ]. The "variable-ratio reinforcement" mechanisms inherent to digital platforms induce persistent stimulation of the NAc, resulting in reward system sensitization and a concomitant reduction in dopamine receptor density within the ventral striatum [ 23 , 24 ]. This decline in NPY levels not only weakens prefrontal cortical control mechanisms but is also directly associated with circadian rhythm disruptions, diminished sleep quality, and heightened stress sensitivity phenomena frequently observed in digital addicts [ 18 , 27 ]. Such structural degeneration renders the individual anhedonic toward non-digital rewards, facilitates the development of pathological "craving" for digital stimuli, and erodes the inhibitory control of the prefrontal cortex [ 25 ]. Within this cascade, NPY plays a critical role in modulating synaptic plasticity by mediating the interaction between the NAc and the Ventral Tegmental Area [ 27 ]. Currently, the clinical utility of diagnostic modalities such as fMRI, CT, or cerebrospinal fluid sampling is limited by high costs and procedural complexities. This underscores the increasing importance of accessible, objective biochemical screening methods that can be implemented across diverse clinical settings. Recent data confirmed that diminished levels of NPY and Brain Derived Neurotrophic Factor (BDNF) significantly correlate with emotion regulation difficulties and impaired behavioral inhibition in individuals with technology addiction [ 26 ]. Previous research investigating excessive technology exposure in pediatric populations has predominantly focused on IGD, examining various biochemical markers such as orexin, BDNF, nitric oxide, cortisol, leptin, and adiponectin. However, to the best of our knowledge, the literature lacks studies specifically investigating the role of NPY in the broader context of PMU. In contrast, NPY has been extensively studied in the field of alcohol dependence, where a significant inverse relationship between alcohol preference and NPY levels has been established [ 17 ]. Similarly, repeated administration of methamphetamine and cocaine has been shown to reversibly diminish NPY expression within the NAc, the primary reward center of the brain [ 16 ]. A critical component of the addiction cycle involves CRF, which activates stress pathways and mediates the negative emotional states such as dysphoria and anxiety observed during withdrawal and relapse. NPY has been demonstrated to act as a "buffer" against these detrimental effects of CRF within the neurobiological circuitry of addiction [ 28 ]. Furthermore, evidence suggests that chronic morphine exposure triggers an initial rapid decline in NAc NPY levels, followed by a subsequent elevation that plays a role in reward memory and the maintenance of addictive behaviors [ 29 ]. NPY receptors, particularly the Y2 and Y5 subtypes, have also been implicated in modulating reward pathways and withdrawal symptoms in nicotine and cannabis dependence [ 30 ]. Paralleling these psychogenic and substance-based addictions, PMU is characterized by dopaminergic dysfunction within the NAc and mesolimbic regions. This neurobiological overlap serves as the foundational hypothesis of our study. Consistent with findings in other addictive disorders, our results demonstrate a progressive decline in NPY levels as the severity of PMU increases. As illustrated in Table 3 , the total PMUS score emerged as the most potent independent predictor among all analyzed parameters. Excessive exposure and addiction to digital media lead to a spectrum of physical ailments in addition to psychological distress in children. Although this specific clinical presentation has not been extensively documented in cohorts exclusively defined by Problematic Media Use (PMU), it has been thoroughly investigated in related behavioral disorders. Affected patients frequently manifest a cluster of symptoms, including reduced sleep duration, poor sleep quality, obesity, hypertension, insulin resistance, and diminished HDL cholesterol levels, collectively increasing cardiovascular risk factors. Beyond depressive and anxious symptomatology, behaviors mimicking Attention-Deficit/Hyperactivity Disorder (ADHD), such as impulsivity, loss of control, and impaired social skills, are commonly observed [ 3 – 5 , 8 – 10 , 25 ]. Numerous studies have explored the association of NPY with patients presenting these symptoms. Low NPY levels or disruptions in its circadian oscillation lead to significant sleep disturbances. Conversely, exogenous NPY administration has been shown to shorten sleep latency and enhance sleep depth [ 31 ]. Melatonin deficiency or nocturnal exposure to blue light (circadian disruption) interferes with the physiological nocturnal rhythm of NPY. This dysregulation increases the risk of night-eating syndrome and metabolic syndrome [ 32 ]. Within the hypothalamus, NPY functions as a fundamental orexigenic (hunger-inducing) signal. In conditions such as chronic stress and technology addiction, impairment of the NPY system contributes to reduced energy expenditure and increased visceral adiposity, thereby triggering obesity. The re-establishment of NPY signaling has been suggested to ameliorate metabolic disorders such as lipodystrophy [ 33 ]. Furthermore, NPY deficiency, particularly during hormonal transition periods, may disrupt estrogen-mediated lipid balance, leading to excessive adiposity. Conversely, regular physical exercise, specifically voluntary aerobic activity, has been shown to enhance cerebral NPY levels, thereby strengthening stress resilience and exerting antidepressant-like effects [ 34 ]. In conclusion, Problematic Media Use is not merely a behavioral habit but a systemic neurobiological process affecting both the brain and the body. Our findings demonstrate that the uncontrolled use of digital media at a level that impairs functional integrity leads to a significant down-regulation of the NPY system, which plays a critical role in stress regulation. Notably, the total PMUS score was identified as the most potent negative predictor of serum NPY levels, independent of sociodemographic factors. The observed decline in serum NPY levels possesses the potential to elucidate the pathophysiological basis of clinical manifestations frequently seen in children with digital addiction, such as sleep disturbances, loss of appetite control, and increased metabolic risk. In this regard, our study represents one of the pioneering investigations in the literature to explore the association between PMU and serum NPY levels in school-aged children. These results underscore the necessity of integrating objective biochemical markers into the diagnostic and monitoring protocols of digital-era behavioral pathologies. Limitations The present study has several limitations that warrant consideration. First, participants' obesity profiles, physical activity levels, detailed dietary histories, and specific psychogenic symptoms were not analyzed. Furthermore, digital media usage patterns were determined solely through parent-proxy reports, which may be susceptible to recall bias or social desirability bias. Second, serum NPY levels were quantified at a single time point, which may fail to capture the physiological fluctuations inherent to the neuropeptide’s circadian rhythm. Third, although the study population consisted of healthy children presenting to the outpatient clinic for routine follow-up, it may not fully represent community-based healthy volunteers. Finally, due to the cross-sectional design of our study, the observed association between PMU and diminished NPY levels should not be interpreted as a direct causal relationship. Longitudinal studies are necessitated to further elucidate the temporal dynamics and causality between digital addiction and NPY down-regulation. Future Perspectives The multisystemic effects of excessive digital exposure on pediatric health including sleep and appetite dysregulation, melatonin suppression, and chronic activation of the stress axis have been extensively documented through numerous epidemiological studies. Strong evidence in current literature correlates each of these physiological alterations directly with serum NPY levels. Our study possesses the potential to model the "missing link" that integrates these disparate pathophysiological components. Given the inherent limitations of current survey-based diagnostic modalities, our findings provide neuroendocrine evidence for the potential clinical utility of NPY as an objective biomarker. Future research should focus on validating the efficacy of NPY across three core clinical domains: Early Screening: Utilizing diminished NPY levels as an "early warning signal" in at-risk pediatric populations before PMU symptoms become clinically manifest. Diagnosis and Severity Assessment: Establishing a biochemical "gold standard" protocol to accompany psychometric testing for quantifying the neurobiological burden of PMU. Therapeutic Monitoring: Validating the re-establishment (up-regulation) of NPY levels following digital detoxification, cognitive-behavioral therapies, or pharmacological interventions as a robust parameter for therapeutic success and neuronal recovery. To fully realize this potential, it is essential to biochemically elucidate the cellular mechanisms and molecular pathwa, specifically the interaction between the leptin/melatonin axis and the mesolimbic reward system involved in NPY modulation within larger, longitudinal cohorts. Declarations Ethics approval and consent to participate Ethical approval was obtained from the Recep Tayyip Erdoğan University Non-Interventional Clinical Research Ethics Committee (Decision No: 2022/118, Date: 15.06.2022). The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. Informed written consent was obtained from the parents or legal guardians of all participating children after they were fully briefed on the study objectives, the voluntary nature of participation, and their right to withdraw at any time without any penalty. Additionally, verbal and/or written assent was obtained from the children themselves prior to their inclusion in the study. Confidentiality was maintained using serial identification numbers in place of personal identifiers, and all data were securely stored with restricted access to ensure participant privacy and data protection. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding This study was funded by the Scientific and Technological Research Council of Türkiye (TÜBİTAK) within the scope of the "2209-A University Students Research Projects Support Program" (Project No: 1919B012402780). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. YY: the conception and design of the study, acquisition of data, analysis and interpretation of data, final approval of the version to be submitted HB: biochemical analysis TC: the conception and design of the study, acquisition of data, EGK: analysis and interpretation of data SÇ: the conception and design of the study MB:: drafting the article or revising it critically for important intellectual content, BU: acquisition of data Author Contribution YY: the conception and design of the study, acquisition of data, analysis and interpretation of data, final approval of the version to be submittedHB: biochemical analysisTC: the conception and design of the study, acquisition of data,EGK: analysis and interpretation of dataSÇ: the conception and design of the studyMB:: drafting the article or revising it critically for important intellectual content, BU: acquisition of data Data Availability The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. 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Development and validation of the problematic media use measure: A parent report measure of screen media ‘addiction’ in children. Psychol. Pop Media Cult. 8 (1), 2–11. 10.1037/PPM0000163 (Jan. 2019). Fujii, K., Suzuki, T., Mimura, M. & Uchida, H. Psychological dependence on antidepressants in patients with panic disorder: a cross-sectional study. Int. Clin. Psychopharmacol. 32 (1), 36–40. 10.1097/YIC.0000000000000143 (Jan. 2017). Fujii, K., Uchida, H., Suzuki, T. & Mimura, M. Dependence on benzodiazepines in patients with panic disorder: a cross-sectional study, Psychiatry Clin. Neurosci. , vol. 69, no. 2, pp. 93–99, Feb. (2015). 10.1111/PCN.12203 Davidson, M. et al. Tryptophan and Substance Abuse: Mechanisms and Impact. Int. J. Mol. Sci. 24 (3). 10.3390/IJMS24032737 (Feb. 2023). Volkow, N. D., Koob, G. F. & McLellan, A. T. Neurobiologic Advances from the Brain Disease Model of Addiction. N Engl. J. Med. 374 (4), 363–371. 10.1056/nejmra1511480 (Jan. 2016). Montag, C. et al. Facebook usage on smartphones and gray matter volume of the nucleus accumbens. Behav. Brain. Res. 329 , 221–228. 10.1016/j.bbr.2017.04.035 (Jun. 2017). Volkow, N. D., Wise, R. A. & Baler, R. The dopamine motive system: implications for drug and food addiction, Nat. Rev. Neurosci. , vol. 18, no. 12, pp. 741–752, Dec. (2017). 10.1038/nrn.2017.130 Weng, C. B. et al. Aug., Gray matter and white matter abnormalities in online game addiction, Eur. J. Radiol. , vol. 82, no. 8, pp. 1308–1312, (2013). 10.1016/j.ejrad.2013.01.031 Demirci, E., Tastepe, N., Ozmen, S. & Kilic, E. The Role of BDNF and NPY Levels, Effects of Behavioral Systems and Emotion Regulation on Internet Addiction in Adolescents, Psychiatr. Q. , vol. 94, no. 4, pp. 605–616, Dec. (2023). 10.1007/s11126-023-10046-7 Szentirmai, E. & Krueger, J. M. Central administration of neuropeptide Y induces wakefulness in rats. Am. J. Physiol. Regul. Integr. Comp. Physiol. 291 (2), 473–480. 10.1152/ajpregu.00919.2005 (2006). Sarmiento, L. F. et al. Do stress hormones influence choice? A systematic review of pharmacological interventions on the HPA axis and/or SAM system. Soc. Cogn. Affect. Neurosci. 19 (1). 10.1093/scan/nsae069 (2024). Wang, X. et al. NPY alterations induced by chronic morphine exposure affect the maintenance and reinstatement of morphine conditioned place preference. Neuropharmacology 181 10.1016/j.neuropharm.2020.108350 (Dec. 2020). Aydin, C., Oztan, O. & Isgor, C. Effects of a selective Y2R antagonist, JNJ-31020028, on nicotine abstinence-related social anxiety-like behavior, neuropeptide Y and corticotropin releasing factor mRNA levels in the novelty-seeking phenotype, Behavioural Brain Research , vol. 222, no. 2, pp. 332–341, Sep. (2011). 10.1016/j.bbr.2011.03.067 Szentirmai, E. & Krueger, J. M. Central administration of neuropeptide Y induces wakefulness in rats. Am. J. Physiol. Regul. Integr. Comp. Physiol. 291 (2). 10.1152/ajpregu.00919.2005 (2006). Bright Futures Guidelines and Pocket Guide. Accessed: Mar. 17, 2026. [Online]. Available: https://www.aap.org/en/practice-management/bright-futures/bright-futures-materials-and-tools/bright-futures-guidelines-and-pocket-guide/?srsltid=AfmBOooWWuiEbsL-VsenbsIGFI0uLVcjK5Lk3JsuUbN90ud7cqLu-eQf Kuo, L. E. et al. Jul., Neuropeptide Y acts directly in the periphery on fat tissue and mediates stress-induced obesity and metabolic syndrome, Nat. Med. , vol. 13, no. 7, pp. 803–811, (2007). 10.1038/nm1611 Brown, L. M. & Clegg, D. J. Central Effects of Estradiol in the Regulation of Adiposity. J. Steroid Biochem. Mol. Biol. 122 , 1–3. 10.1016/j.jsbmb.2009.12.005 (Oct. 2009). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 14 May, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviewers agreed at journal 22 Apr, 2026 Reviewers invited by journal 19 Apr, 2026 Editor invited by journal 06 Apr, 2026 Editor assigned by journal 01 Apr, 2026 Submission checks completed at journal 01 Apr, 2026 First submitted to journal 30 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9270342","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":629112601,"identity":"7159fd33-2053-4154-a369-2464f54548dc","order_by":0,"name":"Yasin Yıldız","email":"data:image/png;base64,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","orcid":"","institution":"Recep Tayyip Erdoğan University","correspondingAuthor":true,"prefix":"","firstName":"Yasin","middleName":"","lastName":"Yıldız","suffix":""},{"id":629112602,"identity":"59967864-bd63-468a-b2a3-211dabce7693","order_by":1,"name":"Medeni Arpa","email":"","orcid":"","institution":"Recep Tayyip Erdoğan University","correspondingAuthor":false,"prefix":"","firstName":"Medeni","middleName":"","lastName":"Arpa","suffix":""},{"id":629112604,"identity":"6c384e21-9b18-42bf-af7c-6443126e5459","order_by":2,"name":"Tuğba Calaboğlu","email":"","orcid":"","institution":"Recep Tayyip Erdoğan University","correspondingAuthor":false,"prefix":"","firstName":"Tuğba","middleName":"","lastName":"Calaboğlu","suffix":""},{"id":629112606,"identity":"1492346e-7ef6-4c02-9482-1f7666a3ffa6","order_by":3,"name":"Elif Göz Karadeniz","email":"","orcid":"","institution":"Recep Tayyip Erdoğan University","correspondingAuthor":false,"prefix":"","firstName":"Elif","middleName":"Göz","lastName":"Karadeniz","suffix":""},{"id":629112607,"identity":"7a230c11-65a4-4de9-a3f1-06a9678ef939","order_by":4,"name":"Semiha Çakmak","email":"","orcid":"","institution":"Recep Tayyip Erdoğan University","correspondingAuthor":false,"prefix":"","firstName":"Semiha","middleName":"","lastName":"Çakmak","suffix":""},{"id":629112608,"identity":"35405407-3e99-432a-979d-1060e1275973","order_by":5,"name":"Müge Baykan","email":"","orcid":"","institution":"Rize Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Müge","middleName":"","lastName":"Baykan","suffix":""},{"id":629112609,"identity":"697c7352-c176-4257-b03f-7273255541f9","order_by":6,"name":"Hacer Bilgin","email":"","orcid":"","institution":"Rize State Hospital, Biochemistry Clinic","correspondingAuthor":false,"prefix":"","firstName":"Hacer","middleName":"","lastName":"Bilgin","suffix":""},{"id":629112610,"identity":"b5dfc226-01e0-4b97-bce4-96b487492465","order_by":7,"name":"Burak Uçan","email":"","orcid":"","institution":"Recep Tayyip Erdoğan University","correspondingAuthor":false,"prefix":"","firstName":"Burak","middleName":"","lastName":"Uçan","suffix":""}],"badges":[],"createdAt":"2026-03-30 17:23:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9270342/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9270342/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107916438,"identity":"6c5557c5-1baf-4919-ad23-d3ed6218a8f4","added_by":"auto","created_at":"2026-04-27 14:14:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":9156,"visible":true,"origin":"","legend":"\u003cp\u003eNPY levels according to PMUS Tertile Groups (ng/mL)\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9270342/v1/3c7c419b27e37176ea7b3c9a.png"},{"id":107916465,"identity":"7bfb5650-69dd-4eb3-816c-ecf239cc26be","added_by":"auto","created_at":"2026-04-27 14:14:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":867067,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 1. Graphical Abstract:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis illustration summarizes the study's central neurobiological finding: a significant inverse relationship between Problematic Media Use (PMU) severity and serum Neuropeptide Y (NPY) levels in school-aged children. The schematic depicts how increasing digital addiction scores correlate with a decline in NPY—a key neurobiological mediator of stress and reward systems—positioning it as a potential objective biomarker for diagnosing and monitoring PMU.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9270342/v1/1c980ce33e221177ab0f0c29.png"},{"id":107916470,"identity":"7a0229cb-ba1c-400e-a9f0-d1f82e7317d7","added_by":"auto","created_at":"2026-04-27 14:14:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1311136,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9270342/v1/2bf695e2-1c36-4ba9-b085-4e5f14ba5e93.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Reduced Serum Neuropeptide Y Levels as a Potential Neurobiological Marker for Problematic Media Use in School-Aged Children","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe global integration of digital technologies has fundamentally transformed human interaction, learning, and entertainment. Within this emerging ecosystem, children and adolescents defined as \"digital natives\" engage in intensive interactions with internet-based platforms from the earliest stages of their developmental processes. The excessive and unregulated use of these platforms, particularly online gaming, has emerged as a significant public health concern [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Consequently, distinguishing between the \"normative use\" and \"problematic use\" of digital media products is of paramount importance. In clinical evaluation, defining problematic media use in a child should transcend mere \"screen time duration\" and focus on \"excessive use impairing the child\u0026rsquo;s functionality.\" Prioritizing functional impairment is essential when assessing pediatric behavioral or developmental disorders, as it serves as the definitive boundary separating normal variations of behavior from pathological levels [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Similarly, updated guidelines by the American Academy of Pediatrics emphasize that digital media interactions should be evaluated not only by quantity or time spent but also by the quality of engagement. Thus, the concept of \"Effective Use of Technology\" has become a focal point in contemporary pediatric discourse.\u003c/p\u003e \u003cp\u003eThe transformation of digital technologies and the internet ecosystem into indispensable components of daily life has fundamentally altered information consumption and social interaction patterns, introducing a novel behavioral pathology categorized as \"Problematic Media Use\" (PMU). PMU is conceptualized as the uncontrolled and compulsive use of social media, video platforms, and smartphones to an extent that impairs an individual\u0026rsquo;s socio-psychological functionality [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Various methodologies are employed to delineate the spectrum ranging from functional/normative use to problematic engagement and full-scale addiction. Within the framework of digital-era pathologies, Internet Gaming Disorder (IGD) remains the only condition formally recognized by international health organizations. In the DSM-5-TR, IGD is categorized under \u003cem\u003eSection III\u003c/em\u003e: Emerging Measures and Models, rather than as a formal diagnosis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Conversely, the World Health Organization\u0026rsquo;s ICD-11 (International Classification of Diseases, 2022) has officially recognized \"Gaming Disorder\" (6C.51) as a distinct clinical entity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Diagnosis is established by the presence of at least five out of nine criteria over a 12-month period (preoccupation, withdrawal, tolerance, unsuccessful attempts to control, loss of interest, continued use despite problems, deception, escape, and jeopardy or loss) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Furthermore, various psychometric instruments have been developed for conditions such as Problematic Smartphone Use, Problematic Social Media Use, Online Buying, and Online Gambling [\u003cspan additionalcitationids=\"CR8 CR9 CR10\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, these scales rely heavily on self-reported data and subjective scoring systems. Consequently, the diagnosis of digital technology-related disorders is currently predicated on subjective data derived from survey responses and individual observations. The potential for social desirability bias or inaccurate self-reporting remains a significant limitation. Therefore, there is an exigent need for objective biomarkers to enhance diagnostic accuracy and clinical monitoring in digital-related pathologies.\u003c/p\u003e \u003cp\u003eNeuropeptide Y (NPY) is highly expressed within the central nervous system, particularly in the hippocampus, cortex, and hypothalamus. It is co-released with classical neurotransmitters, such as GABA and other inhibitory mediators. The expression of its two primary receptor subtypes, Y1 and Y2, has been documented in the frontal cortex, lateral septum, paraventricular nucleus (PVN), lateral hypothalamus, amygdala, hippocampus, and the nucleus tractus solitarius [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. NPY modulates diverse physiological and pathophysiological processes, including food intake, fear and anxiety, learning and memory, depression, post-traumatic stress, and the processing of pain and pruritus [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Furthermore, NPY may support neuronal health and function by stimulating the release of nerve growth factors, mitigating neuroinflammation, and inducing both autophagy and neurogenesis [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Extensive research suggests a robust association between various forms of addiction and NPY signaling. The Nucleus Accumbens (NAc) regulates reward-related behaviors, and the mesolimbic dopamine system plays a pivotal role in the reinforcing effects of addictive substances [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Repeated administration of psychotomimetic agents, such as methamphetamine and cocaine, reversibly reduces NPY expression at both peptide and mRNA levels within the NAc [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Notably, alcohol-preferring rats exhibit lower NPY levels across several brain regions compared to non-preferring counterparts [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsequently, significant alterations in NPY levels have been demonstrated in various forms of psychogenic addiction. Similar to classical substance use disorders, Problematic Media Use should be conceptualized within the spectrum of behavioral addictions, characterized by the chronic and excessive stimulation of dopaminergic neurons in the mesolimbic reward system [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In the context of excessive exposure to digital technologies, diagnostic criteria for disorders other than Internet Gaming Disorder remain inadequately defined, and psychometric assessments may lack sufficient reliability. Building upon this evidence, the objective of our study is to evaluate excessive digital media exposure through an objective laboratory parameter. To this end, we quantified serum NPY levels in children with Problematic Media Use.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eThis study was designed as a descriptive, quantitative research to investigate the correlation between Problematic Media Use and serum Neuropeptide Y levels. The research was conducted at the Department of Pediatrics, Faculty of Medicine, Recep Tayyip Erdogan University. The study population consisted of healthy children of both genders, aged 5\u0026ndash;11 years, who presented to the outpatient clinic for routine follow-up or screening and required blood sampling for clinical indications. The study was carried out between May and October 2025. Inclusion criteria were defined as being between the ages of 5 and 11 years and providing informed consent for participation. Exclusion criteria were strictly established to eliminate potential confounding factors affecting the central nervous system or NPY levels:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePresence of chronic neurological disorders or developmental delays.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDiagnosed neurodevelopmental conditions, including Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eKnown genetic syndromes.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eChronic medication use, particularly agents with potential CNS activity (e.g., antiepileptics, antihistamines, atomoxetine, and methylphenidate).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e The study was conducted in accordance with the Helsinki Declaration, and written informed consent was obtained from all participants and/or their legal guardians. After obtaining consent from participants who met the eligibility criteria, they were asked to complete an epidemiological data form (demographic information form) and the \u0026ldquo;Problem Media Use Scale\u0026rdquo; (PMUS).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample Size Determination\u003c/h3\u003e\n\u003cp\u003eThe sample size for this study was calculated using G*Power software (version 3.1.9.4), based on Cohen\u0026rsquo;s standardized effect size conventions. According to Cohen (1992), effect sizes are categorized as small (0.10), medium (0.25), and large (0.40). To achieve a statistical power of 95% (1-beta\u0026thinsp;=\u0026thinsp;0.95) with a medium effect size of 0.25 and a Type I error rate (alpha) of 0.05, the minimum required sample size was determined to be 78 participants.\u003c/p\u003e\n\u003ch3\u003eData Collection Instruments\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e*Sociodemographic Data Form\u003c/h2\u003e \u003cp\u003eA descriptive form was developed by the researchers based on current literature [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] to collect participants' characteristics. This form included items regarding chronological age, parental educational attainment, household income levels, and residential location.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e*Problematic Media Use Scale (PMUS)\u003c/h3\u003e\n\u003cp\u003eThe Problematic Media Use Scale (PMUS) was originally developed by Domoff et al. in 2017 to assess screen dependency across all visual media modalities in children aged 4\u0026ndash;11 years. The scale items were constructed based on the diagnostic criteria for Internet Gaming Disorder as outlined in the DSM-5. Items are scored on a 5-point Likert-type scale ranging from 1 (never) to 5 (always), with a maximum attainable score of 105. The instrument exists in both short (9-item) and long (27-item) versions; higher total scores indicate increased severity of problematic use. The scale is proxy-reported by parents based on their observations of the child's behaviors. Rather than focusing on a specific digital device, the PMUS aims to detect problematic use or \"screen dependency\" encompassing various visual media platforms, including television, computers, tablets, and smartphones.\u003c/p\u003e \u003cp\u003eThe internal consistency (Cronbach\u0026rsquo;s alpha) of the original scale was reported as 0.97 for the long form and 0.93 for the short form [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The Turkish adaptation and validation study was conducted and published by Furuncu and \u0026Ouml;zt\u0026uuml;rk in 2020 [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In the present study, the 27-item long form was utilized. Following data collection, participants were stratified into three risk groups (low, moderate, and high risk) based on their total PMUS scores.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBiochemical analysis\u003c/h2\u003e \u003cp\u003eSerum samples remaining after routine biochemical analyses were used in the study. The collected serum samples were stored at \u0026minus;\u0026thinsp;20\u0026deg;C until the time of analysis. During the study period, all samples were thawed at once and analyzed in batches. Serum Neuropeptide Y levels were measured using the enzyme-linked immunosorbent assay (ELISA) method in accordance with the manufacturer\u0026rsquo;s instructions (Cat. No.: E-EL-H1893, Elabscience, Houston, USA). The kit manufacturer specifies the analytical sensitivity of the kit as 18.75 pg/mL and the measurement range as 31.25\u0026ndash;2000 pg/mL.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using IBM SPSS Statistics for Windows, Version 29.0 (IBM Corp., Armonk, NY, USA). The normality of continuous variables was verified with the Shapiro\u0026ndash;Wilk test and confirmed by visual inspection of histograms and Q‑Q plots. Since our data distributed normally, the continuous variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Categorical variables were reported as n (%). Comparisons between two independent groups were evaluated using the Independent‑Samples t test, and the corresponding effect size was expressed as Cohen\u0026rsquo;s d. Associations between categorical variables were examined using the chi‑square (χ\u0026sup2;) test, and the magnitude of association was expressed as Phi (φ) or Cramer\u0026rsquo;s V, as appropriate effect size. Relationships between variables were assessed using Pearson\u0026rsquo;s correlation analysis. Correlation strength was reported through the correlation coefficient (r). In addition, partial correlation analysis was conducted to control for the potential effects of age and sex. Participants were stratified into tertiles according to PMUS total scores (low, moderate, and high problematic media use). Differences in mean NPY levels among tertile groups were compared using ANOVA following the verification of homogeneity of variances with Levene\u0026rsquo;s test. When overall significance was observed, Tukey\u0026rsquo;s post‑hoc test was applied for pairwise comparisons. A linear trend analysis was also performed within the ANOVA model across the ordered tertiles. Effect sizes for ANOVA and trend analyses were reported as eta‑squared (η\u0026sup2;). To identify independent predictors of serum NPY levels, multiple linear regression analysis using the forced‑entry (enter) method was performed and NPY level was entered as the dependent variable, while PMUS total score, sex, child age, mother\u0026rsquo;s age, residential area (urban/rural), and parental education level were included simultaneously as independent variables based on theoretical and biological relevance. The overall model fit was expressed by the coefficient of determination (R\u0026sup2; and adjusted R\u0026sup2;), while the relative contribution of each covariate was represented by its standardized beta coefficient (β) and the change‑in‑R\u0026sup2; value. Multicollinearity was checked using the variance inflation factor (VIF). All statistical tests were two‑tailed, and a p‑value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthics\u003c/h3\u003e\n\u003cp\u003e Our study was approved by the Non-Interventional Ethics Committee of Recep Tayyip Erdoğan University (Date: June 18, 2025, No. 2025/264) and the Rize Provincial Health Directorate (Date: July 23, 2024, No. E-64960800-799-249332101).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe mean age of the 80 patients included in the study was 7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19 years (5\u0026ndash;11). The proportion of female patients was 56.3% (n\u0026thinsp;=\u0026thinsp;45). The epidemiological data of the participants are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEpidemiological data of the participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eMean age of participants (mean/sd)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c9\" namest=\"c5\"\u003e \u003cp\u003e7,9\u0026thinsp;\u0026plusmn;\u0026thinsp;0,19 (5\u0026ndash;11) years\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eMean age of mothers (mean/sd)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c9\" namest=\"c5\"\u003e \u003cp\u003e27,2\u0026thinsp;\u0026plusmn;\u0026thinsp;3,1 (25\u0026ndash;41) years\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eMean age of fathers (mean/sd)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c9\" namest=\"c5\"\u003e \u003cp\u003e32,3\u0026thinsp;\u0026plusmn;\u0026thinsp;4,4 (29\u0026ndash;48) years\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGirl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e56,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eFather's education level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eElementary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12,5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e43,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMiddle school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eResidential area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVillage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e10,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e42,5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e20,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCollege\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e70,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMother's education level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eElementary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eParents' employment status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDad works\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e62,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMiddle school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeither of them\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e45,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMom works\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e27,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCollege\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth of them\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e8,8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eFamily Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnder \u003cspan\u003e$\u003c/span\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6,3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eDevice most frequently used\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTablet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e25,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e500\u0026ndash;750\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48,8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMobile phone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e46,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e750\u0026ndash;1000\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e35,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e22,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1000\u0026ndash;1500\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGame console\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e6,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOver \u003cspan\u003e$\u003c/span\u003e1500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eResults from the problem media use survey indicate that participants\u0026rsquo; average scores were 56.1\u0026thinsp;\u0026plusmn;\u0026thinsp;22.9 (27\u0026ndash;107), and participants were divided into three groups based on their scores (participants were ranked from lowest to highest score). The sociodemographic and clinical characteristics of the participants are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e according to the tertiles of the PMUS total scores. Father\u0026rsquo;s age differed significantly between the high‑ and moderate‑PMUS groups after post‑hoc correction (p\u0026thinsp;=\u0026thinsp;0.039), indicating slightly older paternal age in children with severe problematic media use. Mother\u0026rsquo;s age showed a marginal trend but did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.062). No significant group differences were observed for sex distribution, family income, residential area (urban/rural), parental employment status, addiction type, or parental education level (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 for all). Serum NPY levels were quantified across the three risk groups as follows: 91.13\u0026thinsp;\u0026plusmn;\u0026thinsp;27.91 ng/mL in the low-risk group, 73.08\u0026thinsp;\u0026plusmn;\u0026thinsp;29.83 ng/mL in the moderate-risk group, and 72.03\u0026thinsp;\u0026plusmn;\u0026thinsp;17.58 ng/mL in the high-risk group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A one-way analysis of variance (ANOVA) revealed that these differences between groups were statistically significant (F(2,77)\u0026thinsp;=\u0026thinsp;5.055, p\u0026thinsp;=\u0026thinsp;0.009).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe linear trend analysis indicated a significant decreasing trend in NPY concentrations with increasing PMUS scores (F(1,77)\u0026thinsp;=\u0026thinsp;9.772, p\u0026thinsp;=\u0026thinsp;0.002), with no deviation from linearity (p\u0026thinsp;=\u0026thinsp;0.562). The effect size (η\u0026sup2; = 0.116, 95% CI [0.009\u0026ndash;0.243]) indicates a moderate magnitude of effect, suggesting that higher levels of problematic media use are associated with lower circulating NPY, pointing to a possible downregulation of stress-related neuropeptide systems. Effect‑size estimates indicated the strongest difference for NPY (η\u0026sup2; = 0.116), followed by father\u0026rsquo;s age (η\u0026sup2; = 0.086).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Sociodemographic and Clinical Characteristics Across PMUS Tertile Groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow (n\u0026thinsp;=\u0026thinsp;27)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate (n\u0026thinsp;=\u0026thinsp;27)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eeffect size\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD; n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePMUS Total Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eNPY (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174.8\u0026thinsp;\u0026plusmn;\u0026thinsp;71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e156.7\u0026thinsp;\u0026plusmn;\u0026thinsp;62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e121.5\u0026thinsp;\u0026plusmn;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eChid age (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMother's age (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFather's age (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (53.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFamily Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1.000 \u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (40.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (65.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1.000 \u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (40.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (34.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eResidential area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (40.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (74.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 (76.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParental employment status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFather\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 (76.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMother\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (23.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eDevice most\u003c/p\u003e \u003cp\u003efrequently used\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTablet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMobile Phone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (40.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (53.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTelevision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (7.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComputer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (7.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMother\u0026rsquo;s education level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (19.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (40.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (51.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (42.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (11.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eFather\u0026rsquo;s education level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (11.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (61.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (15.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMultiple linear regression analysis was performed to identify independent predictors of NPY levels. The overall model was statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; adjusted R\u0026sup2; = 0.185). Among the variables entered into the model, problematic media use score, family income, and sex emerged as significant independent predictors of NPY concentration.\u003c/p\u003e \u003cp\u003eSpecifically, the PMUS total score demonstrated a significant negative association with NPY levels (β= \u0026minus;\u0026thinsp;0.396, t= \u0026minus;\u0026thinsp;3.596, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that higher problem media use was related to lower circulating NPY values. Conversely, higher family income was positively associated with NPY (β\u0026thinsp;=\u0026thinsp;0.265, t\u0026thinsp;=\u0026thinsp;2.560, p\u0026thinsp;=\u0026thinsp;0.013), and male sex contributed to higher NPY levels (β\u0026thinsp;=\u0026thinsp;0.253, t\u0026thinsp;=\u0026thinsp;2.334, p\u0026thinsp;=\u0026thinsp;0.022). The child age, father\u0026rsquo;s age, and residential setting (urban/rural) did not significantly predict NPY after adjusting them for the other variables (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 for all). No multicollinearity issues were observed (VIF\u0026thinsp;=\u0026thinsp;1.039\u0026ndash;1.177). Collectively, these findings indicate that the increase in problematic media use was independently associated with a decrease in serum NPY levels, even after controlling for demographic and socioeconomic factors (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple Linear Regression for Independent Predictors of NPY Levels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE (B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ (Std)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e149,910\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48,216\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,109\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,003\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePMUS Total Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1,123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0,396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3,596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (Male)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32,984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14,130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily Income (High)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34,378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,560\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild Age (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFather\u0026rsquo;s Age (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,137\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidential Area (Urban)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eModel Statistics: R\u0026sup2; = 0.247; Adjusted R\u0026sup2; = 0.185; F(6, 73)\u0026thinsp;=\u0026thinsp;3.997, p\u0026thinsp;=\u0026thinsp;0.002\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOf the total participants, 45 (56.3%) were girls and 35 (43.8%) were boys. Mean NPY levels were 142.4\u0026thinsp;\u0026plusmn;\u0026thinsp;46.1 pg/mL in girls and 162.5\u0026thinsp;\u0026plusmn;\u0026thinsp;82.7 pg/mL in boys, and this difference was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.179, Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.305), representing a small- to- moderate effect size in favor of males. In contrast, the PMUS total score was significantly higher in boys (61.9\u0026thinsp;\u0026plusmn;\u0026thinsp;25.7) than in girls (51.6\u0026thinsp;\u0026plusmn;\u0026thinsp;19.7) (p\u0026thinsp;=\u0026thinsp;0.046, Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.456), indicating that boys exhibited a greater degree of problematic media use with a medium effect size. While serum NPY concentrations tended to be higher in male participants, the inverse pattern was observed for media‑related behavioral risk, suggesting that increasing problematic media use in boys was not accompanied by corresponding elevations in NPY levels.\u003c/p\u003e \u003cp\u003ePearson\u0026rsquo;s correlation analysis revealed a significant negative relationship between NPY levels and the PMUS (r = \u0026minus;\u0026thinsp;0.346, p\u0026thinsp;=\u0026thinsp;0.002). This indicates that higher levels of problematic media use were associated with lower circulating NPY concentrations. The correlation strength was of moderate magnitude, suggesting a meaningful but not strong inverse link between behavioral media dependence and this neuropeptidergic parameter.\u003c/p\u003e \u003cp\u003eThe combined findings indicate a consistent association between increased problematic media use and decreased serum NPY levels in school-age children. Despite the limited impact of sociodemographic and environmental factors, such as parental education, residential area, and family income, the behavioral burden, as reflected in higher PMUS scores, was identified as the primary factor influencing NPY variation (adjusted R\u0026sup2; = 0.185). The negative association was supported by both tertile-based group comparisons and multiple regression models, and further confirmed by a moderate inverse correlation between NPY and PMUS scores (r= -0.346, p\u0026thinsp;=\u0026thinsp;0.002). Despite the fact that male subjects presented slightly elevated NPY levels, they also demonstrated considerably higher PMUS scores, indicating that neuropeptidergic stress regulation mechanisms do not mitigate behavioral risk within this setting. Overall, these results point towards a potential biochemical mechanism underlying children's problematic media use, with increased engagement in digital media potentially associated with a reduction in stress-related neuropeptide systems.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe diagnosis of disorders arising from excessive exposure to digital technologies currently relies predominantly on psychometric scales and structured surveys. However, there is an exigent clinical need for objective evidence to categorize the severity of these conditions, monitor treatment responses, and facilitate longitudinal patient follow-up. In our study, which aimed to identify a potential biochemical surrogate for screen exposure, we demonstrated a significant inverse relationship between the severity of Problematic Media Use and serum Neuropeptide Y levels.\u003c/p\u003e \u003cp\u003ePsychological addiction is characterized by the persistent need to engage in a substance or behavior due to emotional reinforcement, despite its potential adverse consequences. It often serves as a maladaptive coping mechanism utilized to manage negative affectivity, such as anxiety and stress [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Commonly consumed substances, including alcohol, nicotine, and caffeine, modulate mood and cognition by altering dopaminergic pathways within the brain's reward circuitry [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In the context of PMU, the \"variable-ratio reinforcement\" schedules inherent to digital platforms induce continuous stimulation of the NAc. This process leads to the maladaptive sensitization of the reward system and a subsequent reduction in dopamine receptor density within the ventral striatum [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This neurotransmitter imbalance manifesting as impulsivity, anhedonia, and a pathological \"craving\" for digital stimuli weakens the individual\u0026rsquo;s inhibitory control mediated by the prefrontal cortex. Consequently, this reinforces a clinical picture characterized by the inability to cease the behavior despite its detrimental outcomes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom a neurobiological perspective, PMU shares common neural pathways and cognitive impairment patterns with substance use disorders. Chronic screen exposure triggers profound synaptic alterations, including long-term depression at the NAc level and dendritic remodeling, leading to a significant down-regulation of the NPY system [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The \"variable-ratio reinforcement\" mechanisms inherent to digital platforms induce persistent stimulation of the NAc, resulting in reward system sensitization and a concomitant reduction in dopamine receptor density within the ventral striatum [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This decline in NPY levels not only weakens prefrontal cortical control mechanisms but is also directly associated with circadian rhythm disruptions, diminished sleep quality, and heightened stress sensitivity phenomena frequently observed in digital addicts [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Such structural degeneration renders the individual anhedonic toward non-digital rewards, facilitates the development of pathological \"craving\" for digital stimuli, and erodes the inhibitory control of the prefrontal cortex [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Within this cascade, NPY plays a critical role in modulating synaptic plasticity by mediating the interaction between the NAc and the Ventral Tegmental Area [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCurrently, the clinical utility of diagnostic modalities such as fMRI, CT, or cerebrospinal fluid sampling is limited by high costs and procedural complexities. This underscores the increasing importance of accessible, objective biochemical screening methods that can be implemented across diverse clinical settings. Recent data confirmed that diminished levels of NPY and Brain Derived Neurotrophic Factor (BDNF) significantly correlate with emotion regulation difficulties and impaired behavioral inhibition in individuals with technology addiction [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious research investigating excessive technology exposure in pediatric populations has predominantly focused on IGD, examining various biochemical markers such as orexin, BDNF, nitric oxide, cortisol, leptin, and adiponectin. However, to the best of our knowledge, the literature lacks studies specifically investigating the role of NPY in the broader context of PMU. In contrast, NPY has been extensively studied in the field of alcohol dependence, where a significant inverse relationship between alcohol preference and NPY levels has been established [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Similarly, repeated administration of methamphetamine and cocaine has been shown to reversibly diminish NPY expression within the NAc, the primary reward center of the brain [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A critical component of the addiction cycle involves CRF, which activates stress pathways and mediates the negative emotional states such as dysphoria and anxiety observed during withdrawal and relapse. NPY has been demonstrated to act as a \"buffer\" against these detrimental effects of CRF within the neurobiological circuitry of addiction [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Furthermore, evidence suggests that chronic morphine exposure triggers an initial rapid decline in NAc NPY levels, followed by a subsequent elevation that plays a role in reward memory and the maintenance of addictive behaviors [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. NPY receptors, particularly the Y2 and Y5 subtypes, have also been implicated in modulating reward pathways and withdrawal symptoms in nicotine and cannabis dependence [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Paralleling these psychogenic and substance-based addictions, PMU is characterized by dopaminergic dysfunction within the NAc and mesolimbic regions. This neurobiological overlap serves as the foundational hypothesis of our study. Consistent with findings in other addictive disorders, our results demonstrate a progressive decline in NPY levels as the severity of PMU increases. As illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the total PMUS score emerged as the most potent independent predictor among all analyzed parameters.\u003c/p\u003e \u003cp\u003eExcessive exposure and addiction to digital media lead to a spectrum of physical ailments in addition to psychological distress in children. Although this specific clinical presentation has not been extensively documented in cohorts exclusively defined by Problematic Media Use (PMU), it has been thoroughly investigated in related behavioral disorders. Affected patients frequently manifest a cluster of symptoms, including reduced sleep duration, poor sleep quality, obesity, hypertension, insulin resistance, and diminished HDL cholesterol levels, collectively increasing cardiovascular risk factors. Beyond depressive and anxious symptomatology, behaviors mimicking Attention-Deficit/Hyperactivity Disorder (ADHD), such as impulsivity, loss of control, and impaired social skills, are commonly observed [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNumerous studies have explored the association of NPY with patients presenting these symptoms. Low NPY levels or disruptions in its circadian oscillation lead to significant sleep disturbances. Conversely, exogenous NPY administration has been shown to shorten sleep latency and enhance sleep depth [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Melatonin deficiency or nocturnal exposure to blue light (circadian disruption) interferes with the physiological nocturnal rhythm of NPY. This dysregulation increases the risk of night-eating syndrome and metabolic syndrome [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Within the hypothalamus, NPY functions as a fundamental orexigenic (hunger-inducing) signal. In conditions such as chronic stress and technology addiction, impairment of the NPY system contributes to reduced energy expenditure and increased visceral adiposity, thereby triggering obesity. The re-establishment of NPY signaling has been suggested to ameliorate metabolic disorders such as lipodystrophy [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Furthermore, NPY deficiency, particularly during hormonal transition periods, may disrupt estrogen-mediated lipid balance, leading to excessive adiposity. Conversely, regular physical exercise, specifically voluntary aerobic activity, has been shown to enhance cerebral NPY levels, thereby strengthening stress resilience and exerting antidepressant-like effects [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn conclusion, Problematic Media Use is not merely a behavioral habit but a systemic neurobiological process affecting both the brain and the body. Our findings demonstrate that the uncontrolled use of digital media at a level that impairs functional integrity leads to a significant down-regulation of the NPY system, which plays a critical role in stress regulation. Notably, the total PMUS score was identified as the most potent negative predictor of serum NPY levels, independent of sociodemographic factors. The observed decline in serum NPY levels possesses the potential to elucidate the pathophysiological basis of clinical manifestations frequently seen in children with digital addiction, such as sleep disturbances, loss of appetite control, and increased metabolic risk. In this regard, our study represents one of the pioneering investigations in the literature to explore the association between PMU and serum NPY levels in school-aged children. These results underscore the necessity of integrating objective biochemical markers into the diagnostic and monitoring protocols of digital-era behavioral pathologies.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThe present study has several limitations that warrant consideration. First, participants' obesity profiles, physical activity levels, detailed dietary histories, and specific psychogenic symptoms were not analyzed. Furthermore, digital media usage patterns were determined solely through parent-proxy reports, which may be susceptible to recall bias or social desirability bias. Second, serum NPY levels were quantified at a single time point, which may fail to capture the physiological fluctuations inherent to the neuropeptide\u0026rsquo;s circadian rhythm. Third, although the study population consisted of healthy children presenting to the outpatient clinic for routine follow-up, it may not fully represent community-based healthy volunteers. Finally, due to the cross-sectional design of our study, the observed association between PMU and diminished NPY levels should not be interpreted as a direct causal relationship. Longitudinal studies are necessitated to further elucidate the temporal dynamics and causality between digital addiction and NPY down-regulation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eFuture Perspectives\u003c/h2\u003e \u003cp\u003eThe multisystemic effects of excessive digital exposure on pediatric health including sleep and appetite dysregulation, melatonin suppression, and chronic activation of the stress axis have been extensively documented through numerous epidemiological studies. Strong evidence in current literature correlates each of these physiological alterations directly with serum NPY levels. Our study possesses the potential to model the \"missing link\" that integrates these disparate pathophysiological components. Given the inherent limitations of current survey-based diagnostic modalities, our findings provide neuroendocrine evidence for the potential clinical utility of NPY as an objective biomarker. Future research should focus on validating the efficacy of NPY across three core clinical domains:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eEarly Screening: Utilizing diminished NPY levels as an \"early warning signal\" in at-risk pediatric populations before PMU symptoms become clinically manifest.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDiagnosis and Severity Assessment: Establishing a biochemical \"gold standard\" protocol to accompany psychometric testing for quantifying the neurobiological burden of PMU.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTherapeutic Monitoring: Validating the re-establishment (up-regulation) of NPY levels following digital detoxification, cognitive-behavioral therapies, or pharmacological interventions as a robust parameter for therapeutic success and neuronal recovery.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eTo fully realize this potential, it is essential to biochemically elucidate the cellular mechanisms and molecular pathwa, specifically the interaction between the leptin/melatonin axis and the mesolimbic reward system involved in NPY modulation within larger, longitudinal cohorts.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e Ethical approval was obtained from the Recep Tayyip Erdoğan University Non-Interventional Clinical Research Ethics Committee (Decision No: 2022/118, Date: 15.06.2022). The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. Informed written consent was obtained from the parents or legal guardians of all participating children after they were fully briefed on the study objectives, the voluntary nature of participation, and their right to withdraw at any time without any penalty. Additionally, verbal and/or written assent was obtained from the children themselves prior to their inclusion in the study. Confidentiality was maintained using serial identification numbers in place of personal identifiers, and all data were securely stored with restricted access to ensure participant privacy and data protection.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was funded by the Scientific and Technological Research Council of T\u0026uuml;rkiye (T\u0026Uuml;BİTAK) within the scope of the \"2209-A University Students Research Projects Support Program\" (Project No: 1919B012402780). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e \u003cp\u003eYY: the conception and design of the study, acquisition of data, analysis and interpretation of data, final approval of the version to be submitted\u003c/p\u003e \u003cp\u003eHB: biochemical analysis\u003c/p\u003e \u003cp\u003eTC: the conception and design of the study, acquisition of data,\u003c/p\u003e \u003cp\u003eEGK: analysis and interpretation of data\u003c/p\u003e \u003cp\u003eS\u0026Ccedil;: the conception and design of the study\u003c/p\u003e \u003cp\u003eMB:: drafting the article or revising it critically for important intellectual content,\u003c/p\u003e \u003cp\u003eBU: acquisition of data\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYY: the conception and design of the study, acquisition of data, analysis and interpretation of data, final approval of the version to be submittedHB: biochemical analysisTC: the conception and design of the study, acquisition of data,EGK: analysis and interpretation of dataS\u0026Ccedil;: the conception and design of the studyMB:: drafting the article or revising it critically for important intellectual content, BU: acquisition of data\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePrensky, M. 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Biol.\u003c/em\u003e \u003cb\u003e122\u003c/b\u003e, 1\u0026ndash;3. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jsbmb.2009.12.005\u003c/span\u003e\u003cspan address=\"10.1016/j.jsbmb.2009.12.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (Oct. 2009).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Problematic Media Use, Neuropeptide Y, Child Health, Biomarker","lastPublishedDoi":"10.21203/rs.3.rs-9270342/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9270342/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eThe intensive integration of digital technologies into children's daily lives has introduced a novel behavioral pathology characterized as Problematic Media Use (PMU). Current diagnostic modalities predominantly rely on subjective psychometric scales. Hence, there is a critical need for objective biomarkers. This study aims to investigate the association between the severity of PMU and serum levels of Neuropeptide Y (NPY), a key mediator in stress regulation and reward circuitry.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 80 children aged 5\u0026ndash;11 years were enrolled in the study. PMU levels were assessed using the Problematic Media Use Scale (PMUS), and participants were stratified into three risk groups (low, moderate, and high risk) based on their scores. Serum NPY concentrations were quantified via ELISA.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mean PMUS score of the participants was 56.1\u0026thinsp;\u0026plusmn;\u0026thinsp;22.9 (27\u0026ndash;107). A significant decline in serum NPY levels was observed as PMU severity increased (p\u0026thinsp;=\u0026thinsp;0.009). Correlation analysis revealed a moderate negative correlation between PMUS scores and NPY concentrations (r= -0.346, p\u0026thinsp;=\u0026thinsp;0.002\u003cspan\u003e$\u003c/span\u003e). In the multiple regression model, PMUS score, family income, and gender were identified as independent predictors of NPY levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.185). Notably, the PMUS score demonstrated the strongest negative impact on NPY levels (β = -0.396).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study provides early evidence demonstrating that problematic media use in children leads to the down-regulation of serum NPY levels. NPY emerges as a promising candidate for an objective biomarker in the diagnosis, screening, and therapeutic monitoring of digital addictions. Elucidating the biochemical pathways of NPY in larger longitudinal cohorts may establish a new standard in the clinical management of digital-era pathologies.\u003c/p\u003e","manuscriptTitle":"Reduced Serum Neuropeptide Y Levels as a Potential Neurobiological Marker for Problematic Media Use in School-Aged Children","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-27 14:14:31","doi":"10.21203/rs.3.rs-9270342/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-14T12:37:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"247114302106658939053820532360751959124","date":"2026-04-28T09:44:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"273588169446408490559018778319804866204","date":"2026-04-23T03:28:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-19T07:32:33+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-06T13:31:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-01T07:38:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-01T07:38:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-03-30T17:11:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1f6743c5-6aec-4bef-8078-47bbcc808a68","owner":[],"postedDate":"April 27th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-14T12:37:48+00:00","index":91,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":66965470,"name":"Health sciences/Biomarkers"},{"id":66965471,"name":"Health sciences/Diseases"},{"id":66965472,"name":"Health sciences/Medical research"},{"id":66965473,"name":"Health sciences/Neurology"},{"id":66965474,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2026-04-27T14:14:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-27 14:14:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9270342","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9270342","identity":"rs-9270342","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}