TikTok Addiction and Attention Control in Gen Y and Gen Z: Parallel Mediating Role of Boredom Intolerance and Cognitive Fatigue

TikTok Addiction and Attention Control in Gen Y and Gen Z: Parallel Mediating Role of Boredom Intolerance and Cognitive Fatigue | 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 Research Article TikTok Addiction and Attention Control in Gen Y and Gen Z: Parallel Mediating Role of Boredom Intolerance and Cognitive Fatigue Aymen Iqbal, Najia Zulfiqar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9393045/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract TikTok has become a dominant component of contemporary digital life; however, its implications for cognitive functioning, particularly attention control, remain underexplored. The present study investigated the relationship between TikTok addiction and attention control among Generation Y and Generation Z, with a specific focus on the parallel mediating roles of boredom intolerance and cognitive fatigue. A comparative cross-sectional design was employed, comprising 300 participants (150 Gen Y, 150 Gen Z) recruited from Haripur District, Pakistan, using stratified sampling. Data were collected from individuals who reported at least 1 hour of daily TikTok use over the past 12 months. The findings revealed that TikTok addiction had a significant negative direct effect on attention control among Gen Z. In contrast, no such effect was observed for Gen Y. Parallel mediation analyses indicated that cognitive fatigue significantly mediated the relationship between TikTok addiction and attention control in both generations. In contrast, boredom intolerance emerged as a significant mediator only among Gen Z, but not among Gen Y. Gender-based analyses further demonstrated that males in both generations exhibited higher attention control. In contrast, females in Gen Y reported higher levels of TikTok addiction. Additionally, females in Gen Z showed elevated levels of boredom intolerance and cognitive fatigue. These findings highlight important generational and gender differences in the cognitive consequences of social media use. The study underscores cognitive fatigue as a key mechanism linking TikTok addiction to attentional deficits and offers important theoretical contributions to models of digital media engagement and cognitive load. Practical implications for digital well-being and targeted interventions are discussed. Attention control boredom intolerance cognitive fatigue Gen Y Gen Z TikTok addiction Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The rapid rise of TikTok and other short-form video platforms has significantly transformed social media engagement patterns across generations, raising concerns about declining attentional capacities among Gen Z and Millennials (Head, 2025 ). TikTok use is increasingly conceptualized as a form of social media dependency, characterized by addiction-like symptoms, compulsive engagement, and reduced self-regulatory control (Qin et al., 2022 ). A key feature driving this phenomenon is algorithm-based content delivery, which continuously personalizes and optimizes short-form videos to maximize user engagement, thereby reinforcing prolonged use and potentially contributing to addictive behavioral patterns (Ye et al., 2025 ). From a developmental perspective, differences between generations further contextualize these effects. Gen Y (1981–1996), who experienced the gradual emergence of digital technologies, differ markedly from Gen Z (1997–2012), who have grown up in a fully digitized environment with constant access to smartphones, social media, and algorithm-driven content (Dimock, 2019 ). Empirical evidence suggests that Gen Z demonstrates higher levels of social media dependence and more intensive platform engagement than older cohorts, spending more time in fast-paced digital content environments (Maguire & Pellosmaa, 2022 ; Mude & Undale, 2023 ). These generational differences imply that age cohort may moderate the relationship between TikTok addiction and attentional control. Several theoretical frameworks help explain the psychological mechanisms underlying these associations. The Uses and Gratifications Theory (UGT) posits that individuals engage with media to fulfill needs such as entertainment, social connection, and escapism (Katz et al., 1974). TikTok effectively satisfies these needs through highly personalized content; however, repeated gratification may reinforce habitual use patterns that evolve into compulsive or addictive behavior. In parallel, Cognitive Load Theory (CLT) suggests that continuous exposure to rapidly changing and emotionally stimulating information can overload working memory, thereby reducing the efficiency of information processing and weakening attentional capacity (Sweller, 1988 ). Within the context of short-form video consumption, such cognitive overload may impair sustained attention and executive functioning. Further insight is provided by the Stimulus–Organism–Response (SOR) framework by Mehrabian and Russell ( 1974 ), which conceptualizes algorithm-driven content as an external stimulus that influences internal psychological states, including boredom intolerance and cognitive fatigue, which in turn, shape behavioral responses such as addictive use patterns and diminished attentional control. Similarly, Attentional Control Theory (Eysenck et al., 2007 ) explains how cognitive overload and emotionally arousing stimuli interfere with executive control systems, reducing the ability to maintain goal-directed attention in the presence of distraction. In digital environments such as TikTok, the rapid and unpredictable stream of content may therefore weaken inhibitory control and increase cognitive strain. Attention control refers to the cognitive ability to selectively focus, resist distractions, and regulate the intensity and allocation of attentional resources (Unsworth et al., 2024 ). Empirical evidence supports a strong association between TikTok addiction and attentional impairments. For instance, excessive engagement with TikTok is associated with reduced attention, increased procrastination, and impaired self-regulation, with some studies also reporting higher vulnerability among female users (Caponnetto et al., 2025 ). Neurocognitive evidence further strengthens this link; EEG-based studies demonstrate that higher short-video addiction is associated with poorer performance on attentional network tasks, suggesting that excessive exposure to algorithm-driven content may overstimulate reward pathways while weakening cognitive control systems (Yan et al., 2024 ). Boredom intolerance has also been identified as a key psychological mechanism in the development of digital media addiction. It refers to an individual's reduced tolerance for low stimulation or disengagement (Pellegrini et al., 2025 ). Empirical studies suggest that boredom-related traits contribute indirectly to short-video addiction through mediating variables such as depression and sensation seeking. Individuals experiencing boredom are more likely to seek out novel and stimulating digital content, thereby increasing their risk of addiction (Baltacı & Açar, 2025 ). Moreover, excessive social media use has been linked to increased boredom proneness and reduced subjective well-being, suggesting a reciprocal relationship between boredom and maladaptive digital engagement (Bai et al., 2021 ). Importantly, boredom intolerance is also negatively associated with attentional functioning. Boredom has additionally been linked to reduced sustained attention performance, even after controlling for other psychological factors, indicating its independent role in attentional decline (Hunter & Eastwood, 2018 ). Overall, boredom intolerance appears to function as both a precursor and consequence of excessive digital media use, thereby linking TikTok addiction to impaired attentional control. Cognitive fatigue provides an additional explanatory mechanism in this relationship. It is defined as the depletion of cognitive resources resulting from prolonged mental effort, leading to reduced executive functioning, slower decision-making, and impaired attentional control (Borragan et al., 2017). Continuous engagement with short-form video platforms may contribute to sustained cognitive overload, thereby increasing fatigue and reducing the capacity for focused attention. A recent review suggests that TikTok use is associated with increased cognitive load, attention deficits, and broader negative cognitive and psychological outcomes in young adults, reinforcing concerns about its long-term impact on mental efficiency and attentional stability (Haque, 2026 ). In summary, existing literature suggests that TikTok addiction is associated with reduced attentional control and that this relationship may be explained through underlying psychological mechanisms, particularly boredom intolerance and cognitive fatigue. Together, these processes provide a comprehensive framework for understanding how algorithm-driven short-form video consumption may contribute to declining cognitive control in younger populations. The Current Study To comprehend the cognitive and psychological effects of excessive social media use, particularly TikTok addiction among Generations Y and Z, the current study is important from both theoretical and practical standpoints. Theoretically, current models are designed for general social media use and tend to analyze cognitive and affective processes separately, lacking a comprehensive framework for TikTok. Empirically, there are gaps in previous studies that have focused little on TikTok addiction, yielded inconsistent results on attention control, and seldom considered mediating variables or generational differences between Gen Y and Gen Z. TikTok's short-form, high-reward content has sparked concerns about its effects on attention control and general cognitive functioning as it has become one of the most popular social networking sites in the world. In light of these gaps, the present study investigates how boredom intolerance and cognitive fatigue function as parallel mediators in the link between TikTok addiction and attention management. Because they represent different motivational and cognitive processes, boredom intolerance and cognitive exhaustion are modeled as parallel mediators. The present study has three objectives. First, to examine the relationship between TikTok addiction, attention control, boredom intolerance, and cognitive fatigue among Gen Y and Gen Z. Second, to assess the parallel mediating role of boredom intolerance and cognitive fatigue between TikTok addiction and attention control between Gen Y and Gen Z. Third, to compare gender differences in the levels of study variables between Gen Y and Gen Z. Two separate models are be tested and findings inform whether the proposed mediation model differs between Generation Y and Generation Z. The following hypotheses were formulated to meet these research objectives. TikTok addiction negatively predicts attention control and positively predicts boredom intolerance and cognitive fatigue among Gen Y and Gen Z. Boredom, intolerance, and cognitive fatigue negatively predict attention control among Gen Y and Gen Z. Boredom intolerance and cognitive fatigue mediate the relationship between TikTok addiction and attention control in a parallel manner among Gen Y and Gen Z. There will be significant gender differences in the levels of TikTok addiction, boredom intolerance, cognitive fatigue, and attention control between Gen Y and Gen Z. Method The present study employed a comparative cross-sectional design to examine the predictive role of TikTok addiction and the parallel mediating roles of boredom intolerance and cognitive fatigue among Gen Y and Gen Z. Data were collected at a single point in time using standardized scales. Participants A stratified purposive sampling technique was used to select 300 participants from district Haripur (Gen Y = 150; Gen Z = 150). Each generation was further divided by gender (Male = 75; Female = 75). The inclusion criteria were that participants had to be regular TikTok users with a minimum daily usage of 60 minutes for the past twelve months. Individuals with a clinical diagnosis of attention-related disorders (e.g., ADHD) or those currently taking psychostimulant medications were excluded from participation. Participants completed a demographic form that collected information on their gender, age, and year of birth. Measures Data were collected on four objective measures and a demographic sheet. TikTok Addiction Scale (TTAS) TikTok addiction was measured using the TikTok Addiction Scale, which was developed by Galanis et al. ( 2024 ). This is a six-factor 15-item scale that measures the level of addiction to TikTok based on symptoms such as salience, tolerance, withdrawal, mood modification, conflict, and relapse. Answers are recorded on a five-point Likert scale ranging from 1 ( Strongly Disagree ) to 5 ( Strongly Agree ). All 15 responses are added to obtain the total score. The score ranges between 15 and 75. Higher scores indicate higher addiction levels. Cronbach's alpha reliability of the original scale ranged from .85 to .91 (Galanis et al., 2024 ). It was .94 in the present study. Boredom Intolerance Scale (BIS) Valerio Pellegrini and Estelle Leombruni (2025) developed the Boredom Intolerance Scale to measure an individual's tolerance for boredom. It is a unidimensional 6-item instrument that employs a five-point Likert scale from 1 ( Strongly Disagree ) to 5 ( Strongly Agree ). Its score ranges from 6 to 36. Higher scores indicate greater intolerance to boredom. Its reliability is .82 in the original study, and .89 in the present study. Multidimensional Fatigue Inventory (MFI) The Multidimensional Fatigue Inventory, developed by Smets et al. ( 1995 ), is a self-report measure designed to assess multiple facets of fatigue. It comprises 20 items, assessed on a five-point Likert scale, with 1 meaning 'Yes, that is true ' and 5 meaning 'No, that is not true' . The scale has five dimensions of fatigue, namely General Fatigue, Physical Fatigue, Mental Fatigue, Reduced Motivation, and Reduced Activity, each with four items of the scale. Only the mental fatigue subscale, with 4 items, was analyzed in this study. Its total score ranges from 20 to 100, and its subscale scores range from 4 to 20. High scores represent increased fatigue. The internal consistency reliability coefficients of mental fatigue were .73 and .81 for Gen Y and Gen Z, respectively. Attentional Control Scale (ACS) Derryberry and Reed ( 2002 ) developed this scale to assess the individual's capacity to focus and shift attention effectively. It comprises 20 items, divided into two subscales: Focusing and Shifting. It uses a four-point Likert scale from 1 ( Almost Never ) to 4 ( Always ). The scores on each scale are summed to obtain the final score, after reverse-scoring specific items, as indicated in the scoring key. Its score ranges between 20 and 80. Higher scores denote a stronger attentional control. The original scale has good internal consistency ( α = .88 ) , as confirmed in the present study ( α = .72). Demographic Information Sheet Participants were asked to complete a demographic information sheet indicating their gender, age, and year of birth. Procedure and Ethical Considerations Ethical approval for the study was obtained from the University of XYZ's Ethical Review Committee, under protocol number UOH/DASR/2026/3322 on January 12, 2025. It adheres to APA ethical principles and the Helsinki Code of Conduct. The researchers personally approached participants in Haripur District, Pakistan. Informed consent was obtained before participation, and data were collected via Google Forms and in person via printed questionnaires. Participants were assured of data confidentiality, voluntary participation, and their right to withdraw at any time. They were encouraged to respond honestly, ask questions freely, and take as much time as they needed to complete the scales. All data were securely stored and used solely for research. Statistical Analysis Before conducting the mediation analysis, key statistical assumptions were evaluated, including data normality, linearity of relationships, absence of multicollinearity, Homoscedasticity, and independence of errors, to ensure the validity and reliability of the results. The analysis was conducted using IBM SPSS Statistics version 25 and the PROCESS Macro (Model 4) to test the parallel mediation model. Descriptive statistics, including mean, standard deviation, range, skewness, and kurtosis, were calculated. Correlation analysis was performed to assess the strength and direction of associations among the study variables. Parallel mediation jointly analyzed the indirect effect of each mediator. To investigate generational differences, the mediation models were examined separately for Generations Y and Z. Lastly, independent-samples t-tests were used to assess gender differences in levels of the study variables. Results First, the data assumptions of normality, linearity, multicollinearity, and Homoscedasticity were assessed in SPSS. The Shapiro–Wilk and Kolmogorov–Smirnov tests for normality had p -values greater than 0.05, indicating that the data were normally distributed. Linearity was checked using scatterplots, which demonstrated linear associations among TikTok addiction, boredom intolerance, cognitive fatigue, and attention control. The Tolerance and Variance Inflation Factor ( VIF ) was used to assess multicollinearity. Table 1 Alpha Reliability and Descriptive Statistics of Study Scales (n = 300) Gen Y ( n = 150) Scales α M SD Min Max Skew Kurt TikTok Addiction .71 39.43 7.91 24 60 .41 − .07 Boredom Intolerance .69 16.90 3.51 6 29 .41 .81 Cognitive Fatigue .46 9.64 8.88 5 15 .20 .67 Attention Control .72 55.61 6.76 37 69 − .65 1.00 Gen Z ( n = 150) TikTok Addiction .94 45.65 14.82 16 72 .10 − .70 Boredom Intolerance .89 19.39 5.16 6 30 − .49 .35 Cognitive Fatigue .27 11.93 9.88 6 20 .49 .41 Attention Control .62 48.26 5.92 35 63 − .05 − .44 Note . n = sample size; M = mean; SD = standard deviation; Min = minimum; Max = maximum; Skew = skewness; Kurt = kurtosis. Multicollinearity was assessed using Tolerance and Variance Inflation Factor ( VIF ). Satisfying the assumption, Tolerance scores for TikTok addiction (.82), boredom intolerance (.82), and cognitive fatigue (.81) were > .20. The VIF values for TikTok addiction (1.23), boredom intolerance (1.21), and cognitive fatigue (1.24) were < 5. The scatterplots of standardized residuals against predicted values were inspected to assess Homoscedasticity, which showed a random distribution of points. Overall, satisfying these assumptions sets the ground for model testing. Table 1 presents the alpha reliability and descriptive statistics for study scales among Gen Y and Gen Z. Cronbach’s alpha indicated that, among Gen Y, TikTok addiction (α = .71) and attention control (α = .72) showed acceptable reliability, boredom intolerance was marginal ( α = .69). Cognitive fatigue was low ( α = .46). Among Gen Z, TikTok addiction ( α = .94) and boredom intolerance ( α = .89) demonstrated excellent reliability. In contrast, cognitive fatigue showed very poor internal consistency ( α = .27). The mean scores indicate moderate to high levels of these constructs among both Gen Y and Gen Z participants. Gen Z had a higher TikTok addiction, boredom intolerance, and cognitive fatigue, and a lower attention control than Gen Y. The scale standard deviations were medium, indicating tolerable variation and suggesting that respondents were consistent in their perceptions and experiences of the measured variables. The observed minimum and maximum values closely aligned with the possible scale ranges, indicating that respondents' scores spanned a wide range of the available response options. Moreover, skewness and kurtosis values for all scales were within acceptable limits (± 3 for skewness and ± 10 for kurtosis), indicating that the data were approximately normally distributed. Table 2 Correlation Analysis of TikTok Addiction, Boredom Intolerance, Cognitive Fatigue, and Attention Control among Gen Y (n = 150) and Gen Z (n = 150) S.N Variables 1 2 3 4 1 TikTok Addiction - .14** .23** − .08 2 Boredom Intolerance .35** - .07 − .14 3 Cognitive Fatigue .38** .46** - − .32** 4 Attention Control − .33** − .39** − .62** - Note . ** p < .01. The upper half-diagonal shows the correlation coefficients for Gen Y, and the lower half-diagonal shows the correlation coefficients for Gen Z. Table 2 presents the Pearson’s correlation analysis to examine interrelationships among study variables separately for Gen Y and Gen Z. For Gen Y, TikTok addiction showed a non-significant and weak positive correlation with boredom intolerance ( r = .14, p = .07). TikTok addiction had a significant and moderate positive correlation with cognitive fatigue ( r = .23, p = .00). At the same time, the correlation coefficients between attention control and TikTok addiction and boredom intolerance were non-significant. Only cognitive fatigue demonstrated a significant negative correlation with attention control ( r = − .32, p = .00). For Gen Z, TikTok addiction was positively associated with boredom intolerance ( r = .35, p = .00) and cognitive fatigue ( r = .38, p = .00) to a moderate degree. Attention control was significantly negatively associated with all variables. Notably, these interrelationships were stronger and more consistent in Gen Z than in Gen Y, and higher levels of TikTok addiction are associated with increased boredom intolerance, cognitive fatigue, and lower attention control. Table 3 Direct, Indirect, and Total Effects of TikTok Addiction, Boredom Intolerance, and Cognitive Fatigue on Attention Control for Gen Y (n = 150) Direct Effect B SE 95% CI p R 2 LL UL TikTok Addiction → Attention Control .007 .09 − .17 .19 .94 .12* TikTok Addiction →Boredom Intolerance .06 .03 − .01 .13 .05 .02* TikTok Addiction →Cognitive Fatigue .06 .02 .02 .11 .00 .05* Boredom Intolerance→ Attention Control − .23 .13 − .50 .03 .09 Cognitive Fatigue →Attention Control -1.03 .27 -1.56 − .49 .00 Indirect Effect (Bootstrapped) TikTok Addiction → Boredom Intolerance → Attention Control − .02 .01 − .05 .00 TikTok Addiction → Cognitive Fatigue → Attention Control − .06 .02 − .13 − .02 Total Effect TikTok Addiction → Attention Control − .07 .09 − .25 .10 .42 .01 Note . CI = confidence interval; SE = standard error; LL = lower limit; UL = upper limit After satisfying data assumptions for the mediation model, hypotheses were tested for both generations separately using Model 4 in the SPSS Hayes Process Macro, with 5,000 bootstrap resamples and 95% significance level. The findings for Gen Y are presented in Table 3 and in Figs. 1 and 2 . The findings for Gen Z are presented in Table 4 , Fig. 3 , and Fig. 4 . The baseline models were tested to examine the direct effect of TikTok addiction on attention control for Gen Y. As shown in Table 3 for Gen Y, TikTok addiction was a non-significant predictor of attention control but a significant predictor of boredom intolerance and cognitive fatigue. These pathways in Fig. 2 also show that TikTok addiction had a significant positive relationship with boredom intolerance ( β = .14, p = .05). However, boredom intolerance did not significantly predict attention control ( β = −.12, p = .09). These findings partially support hypothesis 1. Two indirect effects were bootstrapped, and the indirect effect of TikTok addiction on attention control through boredom intolerance was not significant, indicating that boredom intolerance did not function as a mediator in this relationship. In contrast, TikTok addiction positively predicted cognitive fatigue ( β = .23, p = .00), which in turn, negatively predicted attention control ( β = −.32, p = .00). This finding indicates that individuals experiencing higher levels of cognitive fatigue tend to exhibit poorer attention control. The bootstrap results confirmed that cognitive fatigue significantly mediated the relationship between TikTok addiction and attention control, supporting the proposed mediation hypothesis. Furthermore, the total indirect effect of TikTok addiction on attention control was significant ( β = −.09, 95% CI [− .17, − .03]), despite the absence of a significant direct effect ( β = .008, p = .94) and total effect ( β = −.08, p = .42) for Gen Y. This pattern suggests indirect-only mediation, where TikTok addiction influences attention control primarily through cognitive fatigue rather than through a direct pathway. Overall, these findings indicate that TikTok addiction contributes to diminished attention control by increasing cognitive fatigue, highlighting cognitive fatigue as a key underlying psychological mechanism. In contrast, boredom intolerance does not play a significant mediating role in this relationship among Gen Y. Table 4 Direct, Indirect, and Total Effects for TikTok Addiction, Boredom Intolerance, Cognitive Fatigue, and Attention Control for Gen Z (n = 150) Direct Effect B SE 95% CI p R 2 LL UL TikTok Addiction → Attention Control − .06 .03 − .12 − .00 .04 .38* TikTok Addiction →Boredom Intolerance .12 .03 .06 .18 .00 .13* TikTok Addiction →Cognitive Fatigue .05 .01 .02 .08 .00 .10* Boredom Intolerance→ Attention Control − .31 .08 − .49 − .14 .00 Cognitive Fatigue →Attention Control − .87 .19 -1.26 − .49 .00 Indirect Effect (Bootstrapped) TikTok Addiction →Boredom Intolerance→ Attention Control − .04 .02 − .07 − .01 TikTok Addiction →Cognitive Fatigue →Attention Control − .05 .02 − .09 − .02 Total Effect TikTok Addiction →Attention Control − .16 .03 − .21 − .08 .00 .14 Note . CI = confidence interval; SE = standard error; LL = lower limit; UL = upper limit. Table 4 shows the direct, indirect, and total effects of predictors on attention control among Gen Z. TikTok addiction was a significant negative predictor of attention control and a positive predictor of boredom intolerance and cognitive fatigue. As shown in Fig. 4 , TikTok addiction had a significant positive relationship with boredom intolerance ( β = .35, p = .05). Boredom intolerance had a significant negative relationship with attention control ( β = −.28, p = .09). These findings support hypothesis 1. The amount of variance explained ranged from small to moderately high. The bootstrapped results for indirect paths showed that TikTok addiction positively predicted boredom intolerance ( β = .35, p = .00), which in turn, negatively predicted attention control ( β = −.28, p = .00). This finding indicates that individuals with higher TikTok addiction are more likely to experience boredom intolerance, which further contributes to diminished attention control. Thus, boredom intolerance was a significant mediator of the relationship between TikTok addiction and attention control. Similarly, TikTok addiction positively predicted cognitive fatigue ( β = .32, p = .00), which in turn, negatively predicted attention control ( β = −.36, p = .00). This finding suggests that higher levels of TikTok addiction are associated with increased cognitive fatigue, which subsequently leads to reduced attention control. It implies that cognitive fatigue significantly mediated the relationship between TikTok addiction and attention control. Furthermore, the total indirect effect of TikTok addiction on attention control was significant ( β = −.21, 95% CI [− .32, − .12]). In addition, both the direct effect ( β = −.16, p = .04) and total effect ( β = −.37, p = .00) were significant. These findings highlight that TikTok addiction influences attention control both directly and indirectly through boredom intolerance and cognitive fatigue among Gen Z. The results suggest a stronger, more comprehensive mediation pattern than indirect-only models, underscoring the combined role of cognitive and affective processes in explaining attentional deficits. Supporting the hypothesis, these findings imply that both boredom intolerance and cognitive fatigue serve as important psychological mechanisms through which TikTok addiction impairs attention control among Gen Z individuals. Table 5 Gender Differences in Study Variables between Gen Y and Gen Z Gen Y ( n = 150) Scales Male ( n = 150) Female ( n = 150) t P 95% CI Cohen’s d M SD M SD LL UL TikTok Addiction 38.13 8.30 40.72 7.31 -2.02 .05 -5.11 − .06 .33 Boredom Intolerance 16.05 3.34 17.75 3.48 -3.04 .00 -2.80 − .59 .50 Cognitive Fatigue 9.25 2.20 10.03 1.93 -2.42 .02 -1.44 − .11 .38 Attention Control 56.68 7.96 54.55 5.13 1.95 .05 − .03 4.30 .32 Gen Z ( n = 150) TikTok Addiction 45.33 15.39 45.97 13.72 − .26 .79 -5.44 4.16 .04 Boredom Intolerance 17.39 4.91 21.39 4.62 -5.14 .00 -5.54 -2.46 .84 Cognitive Fatigue 11.72 1.92 12.15 2.82 -1.08 .28 -1.20 .35 .18 Attention Control 49.40 5.57 47.12 6.06 2.40 .02 0.40 4.16 .39 Note . M = mean, SD = standard deviation, CI = confidence interval An independent-samples t-test was used to compare differences in TikTok addiction, boredom intolerance, cognitive fatigue, and attention control among Gen Y and Gen Z participants. For Gen Y, the gender difference was statistically significant, as indicated in Table 5 . Women reported higher levels of TikTok addiction, boredom intolerance, and cognitive fatigue compared to men. However, males showed higher scores on attention control. These findings support the assumption about gender differences in TikTok addiction and related psychological outcomes among Generation Y. Among Gen Z, females demonstrated greater boredom intolerance than males, whereas males reported significantly greater attention control than females. No statistically significant gender differences were found in TikTok addiction and cognitive fatigue. Overall, these results partially support the hypothesis about gender differences in TikTok addiction and related psychological outcomes. Discussion The present study examined the effect of TikTok addiction on attention control among Generation Y and Generation Z, with boredom intolerance and cognitive fatigue as parallel mediators. Overall, the findings provide partial to full support for the proposed hypotheses and offer important insights into the cognitive and psychological consequences of problematic social media use across generations. Consistent with the first hypothesis, TikTok addiction positively predicted boredom intolerance and cognitive fatigue in Gen Y and Gen Z groups. However, its negative effect on attention control was significant only among Gen Z, indicating a stronger direct impact on younger users, possibly due to greater exposure to highly stimulating content and less stable attentional regulation. At the same time, no such relationship was observed among Gen Y. This suggests that although TikTok addiction contributes to increased cognitive and affective strain across both generations, its direct detrimental impact on attentional control is more pronounced among younger users. This may be explained by Gen Z's heightened exposure to fast-paced, highly stimulating short-form content, along with relatively less stable attentional regulation compared to Gen Y. This finding supports Yan et al.’s ( 2024 ) study. In line with the second hypothesis, boredom intolerance and cognitive fatigue negatively predicted attention control. This was fully supported in Gen Z, where both variables were significant predictors of reduced attentional control. In Gen Y, only cognitive fatigue was significant, suggesting it is a consistent predictor across generations. At the same time, boredom intolerance is more influential among Gen Z. These findings indicate that cognitive fatigue is a consistent and robust determinant of attentional impairment across generations. In contrast, boredom intolerance appears to play a more prominent role among younger Gen Z individuals. This generational variation suggests differences in how affective and cognitive processes contribute to attentional functioning. These findings align with studies by Baltacı and Açar ( 2025 ) and Haque ( 2026 ). Regarding the third hypothesis, partial support was found for parallel mediation. In Gen Z, both boredom intolerance and cognitive fatigue significantly mediated the relationship between TikTok addiction and attention control. In Gen Y, only cognitive fatigue acted as a mediator. Additionally, Gen Y showed indirect-only mediation, whereas Gen Z demonstrated partial mediation, indicating more complex underlying mechanisms in younger users. These findings suggest that the mechanisms underlying the relationship between TikTok addiction and attention control are more complex and multifaceted among younger users, involving both cognitive exhaustion and intolerance of low stimulation. The fourth hypothesis on gender differences was partially supported. Among Gen Y, females reported higher TikTok addiction, boredom intolerance, and cognitive fatigue than males, while males showed better attention control. Among Gen Z, females reported higher boredom intolerance and males higher attention control, with no significant gender differences in TikTok addiction and cognitive fatigue. These findings suggest that gender differences in digital behavior and its psychological outcomes vary across generations and reflect differing behavioral and coping patterns. Gender-sensitive approaches may further enhance the effectiveness of interventions. The magnitude and pattern of direct and indirect effects clearly demonstrated generational differences. Specifically, the direct negative effect of TikTok addiction on attention control was significant only among Gen Z, and boredom intolerance acted as a significant mediator only within this group. In contrast, cognitive fatigue emerged as a consistent mediator across both generations. These findings highlight that Gen Z individuals are more vulnerable to both direct and indirect effects of TikTok addiction, reflecting a stronger and more complex interplay of cognitive and affective mechanisms. Overall, this study contributes to the literature by identifying key generational and gender-specific mechanisms linking TikTok addiction to attention control within a Pakistani context. Limitations and Recommendations Despite its contributions, the present study has several limitations. The use of mediation analysis in a cross-sectional design restricts causal inferences. The reliance on self-report measures may introduce response bias and common method variance. Additionally, the sample was drawn from a single geographic region, limiting generalizability. The study focused only on boredom intolerance and cognitive fatigue, excluding other relevant variables such as sleep quality and impulsivity, and did not differentiate between TikTok addiction types or contexts, which may influence cognitive outcomes. Future research should employ longitudinal designs to establish causal relationships between TikTok addiction and attentional control and to investigate the over-time effects of other short-form video platforms, such as Instagram Reels, YouTube Shorts, and Snapchat. The issues of response bias and common method variance can be addressed by comparing self-reports with other-reports and using multiple informants. Another ignored area of research is the investigation of the role of cultural and contextual factors in predicting social media–related cognitive outcomes. Future researchers can expand the external validity of the research by collecting data from cultural contexts and diverse populations at multiple sites with additional mediators such as sleep quality and impulsivity. Theoretical and Practical Implications This research has serious theoretical and practical implications. This study adds empirical literature to expand the understanding of Eysenck's Attentional Control theory, Katz’s Uses and Gratifications theory, and Sweller’s Cognitive Load theory. The findings improve our understanding of how social media usage, specifically TikTok addiction, influences cognitive skills among younger populations. In line with Attentional Control theory, TikTok impairs inhibitory control, and users find it hard to sustain goal-directed attention in the presence of distracting stimuli. Repeated exposure to a constant flow of content diminishes attention control in such digital environments. Aligned with the Uses and Gratifications theory, participants seek gratification from repeated use of TikTok, but the rapidly changing content emotionally stimulates them and impairs their executive functioning. According to the Cognitive Load theory, cognitive overload decreases the capacity for attention, working memory, and efficient information processing. The study also highlights boredom intolerance and cognitive fatigue as major mediators, depicting the interplay between cognitive and psychological processes in the determination of attention control. It means that the influence of social media cannot be reduced to a direct one, but rather to more profound individual differences in tolerance for cognitive and emotional difficulties, leading to a more sophisticated view of the relationship between digital media involvement and cognitive performance. Practically, this study offers guidance on advancing evidence-based interventions to promote healthy social media use and improve cognitive performance among younger generations. The results indicate that certain actions are necessary to reduce the negative cognitive consequences of extended TikTok addiction. Therefore, interventions should focus on reducing excessive TikTok use and managing cognitive fatigue across both generations, with additional emphasis on improving boredom tolerance among younger users. Furthermore, improving cognitive resilience, sharpening attention-control skills, and providing adolescents and young adults with effective coping strategies to manage digital interactions are also necessary. For example, systematic activities that increase concentration and scheduled screen-free time could help reduce mental burnout. Age- and gender-based strategies might be particularly beneficial, as females and Gen Zs appear to be more susceptible to the combined effects of boredom intolerance and cognitive fatigue. Gender-based strategies can also be helpful, such as focusing on female fatigue and emotional regulation, and reinforcing the male focus on attention control. Among younger users, attentional control can be alleviated by strategies that increase boredom tolerance, limit screen time, and offer alternative attention-engaging activities. Time management, mindfulness, and attentional exercises can be more effective for those who experience cognitive fatigue. Understanding the augmenting role of boredom intolerance is a useful guide to teachers, caregivers, and mental health practitioners. Programs that encourage adaptive coping strategies, engagement in meaningful offline activities, and resilience during periods of low stimulation may reduce the mental health risks associated with TikTok addiction. It recommends that parents, teachers, and policymakers promote balanced online practices, address extended screen time on social media, and create conditions that support cognitive well-being and adaptive attentional control across generations. Conclusion The findings of this study emphasize that the impact of TikTok addiction extends beyond simple screen use, shaping how individuals manage attention through both cognitive and affective pathways. The stronger vulnerability observed in Gen Z suggests that growing up in highly stimulating digital environments may alter attentional regulation, increasing vulnerability to fatigue and boredom. The role of cognitive fatigue as a consistent mechanism highlights the importance of mental exhaustion in understanding attentional decline. At the same time, the additional influence of boredom intolerance among younger users reflects a reduced capacity to engage with low-stimulation tasks. Moreover, the observed gender differences point toward distinct patterns in how individuals experience and cope with digital engagement, indicating that attentional outcomes are influenced not only by usage intensity but also by underlying psychological and social factors. Overall, the study underscores the need to view attention control in the context of modern digital habits, where excessive consumption of short-form content may gradually reshape cognitive functioning, particularly among younger generations. Declarations Author Contribution AI: Conceptualization, data collection, data entry, literature review search, writing the original draft. NZ: Conceptualization, literature review search, research plan, supervision, data analysis and interpretation, editing, formatting, and submission. Data Availability The dataset utilized in this research can be made available to interested researchers. Requests for access to data, material, and codebook should be directed to the first author A.I., ensuring alignment with ethical guidelines and data-sharing protocols. References Bai, J., Mo, K., Peng, Y., Hao, W., Qu, Y., Lei, X., & Yang, Y. (2021). The relationship between the use of mobile social media and subjective well-being: The mediating effect of boredom proneness. Frontiers in Psychology , 11 , 568492. https://doi.org/10.3389/fpsyg.2020.568492 Baltacı, Ö., & Açar, I. (2025). Does leisure boredom predict short video addiction in adolescents? Psychiatric Quarterly , 1–15. https://doi.org/10.1007/s11126-025-10172-4 Borragán, G., Slama, H., Bartolomei, M., & Peigneux, P. (2017). Cognitive fatigue: A time- based resource-sharing account. Cortex; A Journal Devoted To The Study Of The Nervous System And Behavior , 89 , 71–84. https://doi.org/10.1016/j.cortex.2017.01.023 Caponnetto, P., Lanzafame, I., Prezzavento, G. C., Fakhrou, A., Lenzo, V., Sardella, A., & Quattropani, M. C. (2025). Does TikTok Addiction exist? A qualitative study. Health Psychology Research , 13 , 127796. https://doi.org/10.52965/001c.127796 Derryberry, D., & Reed, M. A. (2002). Anxiety-related attentional biases and their regulation by attentional control. Journal of Abnormal Psychology , 111 (2), 225. https://doi.org/10.1037/0021-843X.111.2.225 Dimock, M. (2019). Defining generations: Where Millennials end, and Generation Z begins. Pew Research Center , 17 (1), 1–7. https://www.pewresearch.org/fact-tank/2019/01/17/where-millennials-end-and-generation-z-begins Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7(2) , 336. http://doi.org/10.1037/1528-3542.7.2.336 Galanis, P., Katsiroumpa, A., Moisoglou, I., & Konstantakopoulou, O. (2024). The TikTok Addiction Scale: Development and validation. AIMS Public Health , 11 (4), 1172. https://doi.org/10.3934/publichealth.2024061 Haque, S. (2026). TikTok and young adults: A decade of research on mental health, cognition, sleep, and social outcomes (2016–2025). Acta Psychologica , 263 , 106216. https://doi.org/10.1016/j.actpsy.2026.106216 Head, K. R. (2025). Short-form video use and sustained attention: A narrative. International Journal of Community Empowerment and Society Administration , 2 (4), 60–67. https://doi.org/10.6084/m9.figshare.30648764 Hunter, A., & Eastwood, J. D. (2018). Does state boredom cause failures of attention? Examining the relations between trait boredom, state boredom, and sustained attention. Experimental Brain Research , 236 (9), 2483–2492. https://doi.org/10.1007/s00221-016-4749-7 Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and gratifications research. The Public Opinion Quarterly, 37 (4), 509–523. https://www.jstor.org/stable/2747854 Maguire, S. L., & Pellosmaa, H. (2022). Depression, anxiety, and stress severity impact social media use and TikTok addiction. Chancellor's Honors Program Projects https://trace.tennessee.edu/utk_chanhonoproj/2511 Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology . Psycnet apa org https://psycnet.apa.org/record/1974-22049-000 Mude, G., & Undale, S. (2023). Social media usage: A comparison between Generation Y and Generation Z in India. International Journal of E-Business Research , 19 (1), 1–20. https://doi.org/10.4018/ijebr.317889 Pellegrini, V., Leombruni, E., Iazzetta, S., Saettoni, M., & Gragnani, A. (2025). Development, validation, and psychometric properties of the Italian and English versions of the Boredom Intolerance Scale (BIS). Personality and Individual Differences , 240 , 113151. https://doi.org/10.1016/j.paid.2025.113151 Qin, Y., Omar, B., & Musetti, A. (2022). The addictive behavior of the short-form video app TikTok: An information quality and system quality perspective. Frontiers in Psychology , 13 , 932805. https://doi.org/10.3389/fpsyg.2022.932805 Smets, E. M. A., Garssen, B., Bonke, B. D., & De Haes, J. C. J. M. (1995). The Multidimensional Fatigue Inventory (MFI) psychometric qualities of an instrument to assess fatigue. Journal of Psychosomatic Research , 39 (3), 315–325. https://doi.org/10.1016/0022-3999(94)00125-O Sweller, J. (1988). Cognitive load during problem-solving: effects on learning. Cognitive Science , 12 (2), 257–285. https://doi.org/10.1207/s15516709cog1202_4 Unsworth, N., Miller, A. L., & Strayer, D. L. (2024). Individual differences in attention control: A meta-analysis and re-analysis of latent variable studies. Psychonomic Bulletin & Review , 31 (6), 2487–2533. https://doi.org/10.3758/s13423-024-02516-1 Yan, T., Su, C., Xue, W., Hu, Y., & Zhou, H. (2024). Mobile phone short video use negatively impacts attention functions: An EEG study. Frontiers in Human Neuroscience , 18 (18), 1383913. https://doi.org/10.3389/fnhum.2024.1383913 Ye, J. H., Zheng, J., Nong, W., & Yang, X. (2025). Potential effect of short video usage intensity on short video addiction, perceived mood enhancement ('TikTok brain'), and attention control among Chinese adolescents. International Journal of Mental Health Promotion , 27 (3). https://doi.org/10.32604/ijmhp.2025.059929 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-9393045","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623042345,"identity":"e41807a6-f7ee-4b43-904d-6512459d016f","order_by":0,"name":"Aymen Iqbal","email":"","orcid":"","institution":"University of Haripur","correspondingAuthor":false,"prefix":"","firstName":"Aymen","middleName":"","lastName":"Iqbal","suffix":""},{"id":623042346,"identity":"b8de5663-698b-4a5c-9ec8-249384e42253","order_by":1,"name":"Najia 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Z\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9393045/v1/b284834a7d4b16d599473353.png"},{"id":106965207,"identity":"43075fdf-741b-4862-b208-eafe829ea253","added_by":"auto","created_at":"2026-04-15 09:53:29","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":39460,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eThe Mediating Role of Boredom Intolerance and Cognitive Fatigue between TikTok Addiction and Attention Control in Gen Z\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9393045/v1/6fad981e8a6b3d9abde5107c.png"},{"id":108803470,"identity":"b39350e9-fc80-42fa-aa6f-b1260ab0db80","added_by":"auto","created_at":"2026-05-08 14:55:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":578980,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9393045/v1/2dcac89c-38f0-4315-840f-848468d95189.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"TikTok Addiction and Attention Control in Gen Y and Gen Z: Parallel Mediating Role of Boredom Intolerance and Cognitive Fatigue","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe rapid rise of TikTok and other short-form video platforms has significantly transformed social media engagement patterns across generations, raising concerns about declining attentional capacities among Gen Z and Millennials (Head, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). TikTok use is increasingly conceptualized as a form of social media dependency, characterized by addiction-like symptoms, compulsive engagement, and reduced self-regulatory control (Qin et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). A key feature driving this phenomenon is algorithm-based content delivery, which continuously personalizes and optimizes short-form videos to maximize user engagement, thereby reinforcing prolonged use and potentially contributing to addictive behavioral patterns (Ye et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFrom a developmental perspective, differences between generations further contextualize these effects. Gen Y (1981–1996), who experienced the gradual emergence of digital technologies, differ markedly from Gen Z (1997–2012), who have grown up in a fully digitized environment with constant access to smartphones, social media, and algorithm-driven content (Dimock, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Empirical evidence suggests that Gen Z demonstrates higher levels of social media dependence and more intensive platform engagement than older cohorts, spending more time in fast-paced digital content environments (Maguire \u0026amp; Pellosmaa, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mude \u0026amp; Undale, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). These generational differences imply that age cohort may moderate the relationship between TikTok addiction and attentional control.\u003c/p\u003e \u003cp\u003eSeveral theoretical frameworks help explain the psychological mechanisms underlying these associations. The Uses and Gratifications Theory (UGT) posits that individuals engage with media to fulfill needs such as entertainment, social connection, and escapism (Katz et al., 1974). TikTok effectively satisfies these needs through highly personalized content; however, repeated gratification may reinforce habitual use patterns that evolve into compulsive or addictive behavior. In parallel, Cognitive Load Theory (CLT) suggests that continuous exposure to rapidly changing and emotionally stimulating information can overload working memory, thereby reducing the efficiency of information processing and weakening attentional capacity (Sweller, \u003cspan class=\"CitationRef\"\u003e1988\u003c/span\u003e). Within the context of short-form video consumption, such cognitive overload may impair sustained attention and executive functioning.\u003c/p\u003e \u003cp\u003eFurther insight is provided by the Stimulus–Organism–Response (SOR) framework by Mehrabian and Russell (\u003cspan class=\"CitationRef\"\u003e1974\u003c/span\u003e), which conceptualizes algorithm-driven content as an external stimulus that influences internal psychological states, including boredom intolerance and cognitive fatigue, which in turn, shape behavioral responses such as addictive use patterns and diminished attentional control. Similarly, Attentional Control Theory (Eysenck et al., \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e) explains how cognitive overload and emotionally arousing stimuli interfere with executive control systems, reducing the ability to maintain goal-directed attention in the presence of distraction. In digital environments such as TikTok, the rapid and unpredictable stream of content may therefore weaken inhibitory control and increase cognitive strain.\u003c/p\u003e \u003cp\u003eAttention control refers to the cognitive ability to selectively focus, resist distractions, and regulate the intensity and allocation of attentional resources (Unsworth et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Empirical evidence supports a strong association between TikTok addiction and attentional impairments. For instance, excessive engagement with TikTok is associated with reduced attention, increased procrastination, and impaired self-regulation, with some studies also reporting higher vulnerability among female users (Caponnetto et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Neurocognitive evidence further strengthens this link; EEG-based studies demonstrate that higher short-video addiction is associated with poorer performance on attentional network tasks, suggesting that excessive exposure to algorithm-driven content may overstimulate reward pathways while weakening cognitive control systems (Yan et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBoredom intolerance has also been identified as a key psychological mechanism in the development of digital media addiction. It refers to an individual's reduced tolerance for low stimulation or disengagement (Pellegrini et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Empirical studies suggest that boredom-related traits contribute indirectly to short-video addiction through mediating variables such as depression and sensation seeking. Individuals experiencing boredom are more likely to seek out novel and stimulating digital content, thereby increasing their risk of addiction (Baltacı \u0026amp; Açar, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Moreover, excessive social media use has been linked to increased boredom proneness and reduced subjective well-being, suggesting a reciprocal relationship between boredom and maladaptive digital engagement (Bai et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImportantly, boredom intolerance is also negatively associated with attentional functioning. Boredom has additionally been linked to reduced sustained attention performance, even after controlling for other psychological factors, indicating its independent role in attentional decline (Hunter \u0026amp; Eastwood, \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). Overall, boredom intolerance appears to function as both a precursor and consequence of excessive digital media use, thereby linking TikTok addiction to impaired attentional control.\u003c/p\u003e \u003cp\u003eCognitive fatigue provides an additional explanatory mechanism in this relationship. It is defined as the depletion of cognitive resources resulting from prolonged mental effort, leading to reduced executive functioning, slower decision-making, and impaired attentional control (Borragan et al., 2017). Continuous engagement with short-form video platforms may contribute to sustained cognitive overload, thereby increasing fatigue and reducing the capacity for focused attention. A recent review suggests that TikTok use is associated with increased cognitive load, attention deficits, and broader negative cognitive and psychological outcomes in young adults, reinforcing concerns about its long-term impact on mental efficiency and attentional stability (Haque, \u003cspan class=\"CitationRef\"\u003e2026\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn summary, existing literature suggests that TikTok addiction is associated with reduced attentional control and that this relationship may be explained through underlying psychological mechanisms, particularly boredom intolerance and cognitive fatigue. Together, these processes provide a comprehensive framework for understanding how algorithm-driven short-form video consumption may contribute to declining cognitive control in younger populations.\u003c/p\u003e\n\u003ch3\u003eThe Current Study\u003c/h3\u003e\n\u003cp\u003eTo comprehend the cognitive and psychological effects of excessive social media use, particularly TikTok addiction among Generations Y and Z, the current study is important from both theoretical and practical standpoints. Theoretically, current models are designed for general social media use and tend to analyze cognitive and affective processes separately, lacking a comprehensive framework for TikTok. Empirically, there are gaps in previous studies that have focused little on TikTok addiction, yielded inconsistent results on attention control, and seldom considered mediating variables or generational differences between Gen Y and Gen Z.\u003c/p\u003e \u003cp\u003eTikTok's short-form, high-reward content has sparked concerns about its effects on attention control and general cognitive functioning as it has become one of the most popular social networking sites in the world. In light of these gaps, the present study investigates how boredom intolerance and cognitive fatigue function as parallel mediators in the link between TikTok addiction and attention management. Because they represent different motivational and cognitive processes, boredom intolerance and cognitive exhaustion are modeled as parallel mediators. The present study has three objectives. First, to examine the relationship between TikTok addiction, attention control, boredom intolerance, and cognitive fatigue among Gen Y and Gen Z. Second, to assess the parallel mediating role of boredom intolerance and cognitive fatigue between TikTok addiction and attention control between Gen Y and Gen Z. Third, to compare gender differences in the levels of study variables between Gen Y and Gen Z. Two separate models are be tested and findings inform whether the proposed mediation model differs between Generation Y and Generation Z. The following hypotheses were formulated to meet these research objectives.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTikTok addiction negatively predicts attention control and positively predicts boredom intolerance and cognitive fatigue among Gen Y and Gen Z.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBoredom, intolerance, and cognitive fatigue negatively predict attention control among Gen Y and Gen Z.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBoredom intolerance and cognitive fatigue mediate the relationship between TikTok addiction and attention control in a parallel manner among Gen Y and Gen Z.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThere will be significant gender differences in the levels of TikTok addiction, boredom intolerance, cognitive fatigue, and attention control between Gen Y and Gen Z.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003cp\u003e\u003c/p\u003e "},{"header":"Method","content":"\u003cp\u003eThe present study employed a comparative cross-sectional design to examine the predictive role of TikTok addiction and the parallel mediating roles of boredom intolerance and cognitive fatigue among Gen Y and Gen Z. Data were collected at a single point in time using standardized scales.\u003c/p\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eA stratified purposive sampling technique was used to select 300 participants from district Haripur (Gen Y\u0026thinsp;=\u0026thinsp;150; Gen Z\u0026thinsp;=\u0026thinsp;150). Each generation was further divided by gender (Male\u0026thinsp;=\u0026thinsp;75; Female\u0026thinsp;=\u0026thinsp;75). The inclusion criteria were that participants had to be regular TikTok users with a minimum daily usage of 60 minutes for the past twelve months. Individuals with a clinical diagnosis of attention-related disorders (e.g., ADHD) or those currently taking psychostimulant medications were excluded from participation. Participants completed a demographic form that collected information on their gender, age, and year of birth.\u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eData were collected on four objective measures and a demographic sheet.\u003c/p\u003e\n\u003ch3\u003eTikTok Addiction Scale (TTAS)\u003c/h3\u003e\n\u003cp\u003eTikTok addiction was measured using the TikTok Addiction Scale, which was developed by Galanis et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This is a six-factor 15-item scale that measures the level of addiction to TikTok based on symptoms such as salience, tolerance, withdrawal, mood modification, conflict, and relapse. Answers are recorded on a five-point Likert scale ranging from 1 (\u003cem\u003eStrongly Disagree\u003c/em\u003e) to 5 (\u003cem\u003eStrongly Agree\u003c/em\u003e). All 15 responses are added to obtain the total score. The score ranges between 15 and 75. Higher scores indicate higher addiction levels. Cronbach's alpha reliability of the original scale ranged from .85 to .91 (Galanis et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It was .94 in the present study.\u003c/p\u003e\n\u003ch3\u003eBoredom Intolerance Scale (BIS)\u003c/h3\u003e\n\u003cp\u003eValerio Pellegrini and Estelle Leombruni (2025) developed the Boredom Intolerance Scale to measure an individual's tolerance for boredom. It is a unidimensional 6-item instrument that employs a five-point Likert scale from 1 (\u003cem\u003eStrongly Disagree\u003c/em\u003e) to 5 (\u003cem\u003eStrongly Agree\u003c/em\u003e). Its score ranges from 6 to 36. Higher scores indicate greater intolerance to boredom. Its reliability is .82 in the original study, and .89 in the present study.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMultidimensional Fatigue Inventory (MFI)\u003c/h2\u003e \u003cp\u003eThe Multidimensional Fatigue Inventory, developed by Smets et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), is a self-report measure designed to assess multiple facets of fatigue. It comprises 20 items, assessed on a five-point Likert scale, with 1 meaning \u003cem\u003e'Yes, that is true\u003c/em\u003e' and 5 meaning \u003cem\u003e'No, that is not true'\u003c/em\u003e. The scale has five dimensions of fatigue, namely General Fatigue, Physical Fatigue, Mental Fatigue, Reduced Motivation, and Reduced Activity, each with four items of the scale. Only the mental fatigue subscale, with 4 items, was analyzed in this study. Its total score ranges from 20 to 100, and its subscale scores range from 4 to 20. High scores represent increased fatigue. The internal consistency reliability coefficients of mental fatigue were .73 and .81 for Gen Y and Gen Z, respectively.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAttentional Control Scale (ACS)\u003c/h3\u003e\n\u003cp\u003eDerryberry and Reed (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) developed this scale to assess the individual's capacity to focus and shift attention effectively. It comprises 20 items, divided into two subscales: Focusing and Shifting. It uses a four-point Likert scale from 1 (\u003cem\u003eAlmost Never\u003c/em\u003e) to 4 (\u003cem\u003eAlways\u003c/em\u003e). The scores on each scale are summed to obtain the final score, after reverse-scoring specific items, as indicated in the scoring key. Its score ranges between 20 and 80. Higher scores denote a stronger attentional control. The original scale has good internal consistency (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.88\u003cem\u003e)\u003c/em\u003e, as confirmed in the present study (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.72).\u003c/p\u003e\n\u003ch3\u003eDemographic Information Sheet\u003c/h3\u003e\n\u003cp\u003eParticipants were asked to complete a demographic information sheet indicating their gender, age, and year of birth.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eProcedure and Ethical Considerations\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003e for the study was obtained from the University of XYZ's Ethical Review Committee, under protocol number UOH/DASR/2026/3322 on January 12, 2025. It adheres to APA ethical principles and the Helsinki Code of Conduct. The researchers personally approached participants in Haripur District, Pakistan. Informed consent was obtained before participation, and data were collected via Google Forms and in person via printed questionnaires. Participants were assured of data confidentiality, voluntary participation, and their right to withdraw at any time. They were encouraged to respond honestly, ask questions freely, and take as much time as they needed to complete the scales. All data were securely stored and used solely for research.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eBefore conducting the mediation analysis, key statistical assumptions were evaluated, including data normality, linearity of relationships, absence of multicollinearity, Homoscedasticity, and independence of errors, to ensure the validity and reliability of the results. The analysis was conducted using IBM SPSS Statistics version 25 and the PROCESS Macro (Model 4) to test the parallel mediation model. Descriptive statistics, including mean, standard deviation, range, skewness, and kurtosis, were calculated. Correlation analysis was performed to assess the strength and direction of associations among the study variables. Parallel mediation jointly analyzed the indirect effect of each mediator. To investigate generational differences, the mediation models were examined separately for Generations Y and Z. Lastly, independent-samples t-tests were used to assess gender differences in levels of the study variables.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eFirst, the data assumptions of normality, linearity, multicollinearity, and Homoscedasticity were assessed in SPSS. The Shapiro\u0026ndash;Wilk and Kolmogorov\u0026ndash;Smirnov tests for normality had \u003cem\u003ep\u003c/em\u003e-values greater than 0.05, indicating that the data were normally distributed. Linearity was checked using scatterplots, which demonstrated linear associations among TikTok addiction, boredom intolerance, cognitive fatigue, and attention control. The Tolerance and Variance Inflation Factor (\u003cem\u003eVIF\u003c/em\u003e) was used to assess multicollinearity.\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\u003e\u003cem\u003eAlpha Reliability and Descriptive Statistics of Study Scales (n\u0026thinsp;=\u0026thinsp;300)\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eGen Y (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eα\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eMin\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eMax\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eSkew\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eKurt\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoredom Intolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive Fatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eGen Z (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoredom Intolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive Fatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cb\u003eNote\u003c/b\u003e. \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;sample size; \u003cem\u003eM\u0026thinsp;=\u003c/em\u003e\u0026thinsp;mean; \u003cem\u003eSD\u0026thinsp;=\u003c/em\u003e\u0026thinsp;standard deviation; \u003cem\u003eMin\u003c/em\u003e\u0026thinsp;=\u0026thinsp;minimum; \u003cem\u003eMax\u003c/em\u003e\u0026thinsp;=\u0026thinsp;maximum; \u003cem\u003eSkew\u003c/em\u003e\u0026thinsp;=\u0026thinsp;skewness; \u003cem\u003eKurt\u003c/em\u003e\u0026thinsp;=\u0026thinsp;kurtosis.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMulticollinearity was assessed using Tolerance and Variance Inflation Factor (\u003cem\u003eVIF\u003c/em\u003e). Satisfying the assumption, Tolerance scores for TikTok addiction (.82), boredom intolerance (.82), and cognitive fatigue (.81) were \u0026gt;\u0026thinsp;.20. The VIF values for TikTok addiction (1.23), boredom intolerance (1.21), and cognitive fatigue (1.24) were \u0026lt;\u0026thinsp;5. The scatterplots of standardized residuals against predicted values were inspected to assess Homoscedasticity, which showed a random distribution of points. Overall, satisfying these assumptions sets the ground for model testing.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the alpha reliability and descriptive statistics for study scales among Gen Y and Gen Z. Cronbach\u0026rsquo;s alpha indicated that, among Gen Y, TikTok addiction \u003cem\u003e(α\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.71) and attention control \u003cem\u003e(α\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.72) showed acceptable reliability, boredom intolerance was marginal (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.69). Cognitive fatigue was low (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.46). Among Gen Z, TikTok addiction (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.94) and boredom intolerance (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.89) demonstrated excellent reliability. In contrast, cognitive fatigue showed very poor internal consistency (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.27). The mean scores indicate moderate to high levels of these constructs among both Gen Y and Gen Z participants. Gen Z had a higher TikTok addiction, boredom intolerance, and cognitive fatigue, and a lower attention control than Gen Y. The scale standard deviations were medium, indicating tolerable variation and suggesting that respondents were consistent in their perceptions and experiences of the measured variables. The observed minimum and maximum values closely aligned with the possible scale ranges, indicating that respondents' scores spanned a wide range of the available response options. Moreover, skewness and kurtosis values for all scales were within acceptable limits (\u0026plusmn;\u0026thinsp;3 for skewness and \u0026plusmn;\u0026thinsp;10 for kurtosis), indicating that the data were approximately normally distributed.\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\u003e\u003cem\u003eCorrelation Analysis of TikTok Addiction, Boredom Intolerance, Cognitive Fatigue, and Attention Control among Gen Y (n\u0026thinsp;=\u0026thinsp;150) and Gen Z (n\u0026thinsp;=\u0026thinsp;150)\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTikTok Addiction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.14**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.23**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoredom Intolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.35**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCognitive Fatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.38**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.46**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.32**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAttention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.33**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.39**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.62**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eNote\u003c/b\u003e. ** \u003cem\u003ep\u003c/em\u003e \u0026lt; .01. The upper half-diagonal shows the correlation coefficients for Gen Y, and the lower half-diagonal shows the correlation coefficients for Gen Z.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the Pearson\u0026rsquo;s correlation analysis to examine interrelationships among study variables separately for Gen Y and Gen Z. For Gen Y, TikTok addiction showed a non-significant and weak positive correlation with boredom intolerance (\u003cem\u003er\u003c/em\u003e = .14, \u003cem\u003ep\u003c/em\u003e = .07). TikTok addiction had a significant and moderate positive correlation with cognitive fatigue (\u003cem\u003er\u003c/em\u003e = .23, \u003cem\u003ep\u003c/em\u003e = .00). At the same time, the correlation coefficients between attention control and TikTok addiction and boredom intolerance were non-significant. Only cognitive fatigue demonstrated a significant negative correlation with attention control (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.32, \u003cem\u003ep\u003c/em\u003e = .00). For Gen Z, TikTok addiction was positively associated with boredom intolerance (\u003cem\u003er\u003c/em\u003e = .35, \u003cem\u003ep\u003c/em\u003e = .00) and cognitive fatigue (\u003cem\u003er\u003c/em\u003e = .38, \u003cem\u003ep\u003c/em\u003e = .00) to a moderate degree. Attention control was significantly negatively associated with all variables. Notably, these interrelationships were stronger and more consistent in Gen Z than in Gen Y, and higher levels of TikTok addiction are associated with increased boredom intolerance, cognitive fatigue, and lower attention control.\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\u003e\u003cem\u003eDirect, Indirect, and Total Effects of TikTok Addiction, Boredom Intolerance, and Cognitive Fatigue on Attention Control for Gen Y (n\u0026thinsp;=\u0026thinsp;150)\u003c/em\u003e\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\u003eDirect Effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eLL\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eUL\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\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\u003eTikTok Addiction \u0026rarr; Attention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.12*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction \u0026rarr;Boredom Intolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.02*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction \u0026rarr;Cognitive Fatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.05*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoredom Intolerance\u0026rarr; Attention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive Fatigue \u0026rarr;Attention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndirect Effect (Bootstrapped)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction \u0026rarr; Boredom Intolerance \u0026rarr; Attention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.00\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\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction \u0026rarr; Cognitive Fatigue \u0026rarr; Attention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.02\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\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal Effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction \u0026rarr; Attention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eNote\u003c/b\u003e. \u003cem\u003eCI\u003c/em\u003e\u0026thinsp;=\u0026thinsp;confidence interval; \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;standard error; \u003cem\u003eLL\u003c/em\u003e\u0026thinsp;=\u0026thinsp;lower limit; \u003cem\u003eUL\u0026thinsp;=\u003c/em\u003e\u0026thinsp;upper limit\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAfter satisfying data assumptions for the mediation model, hypotheses were tested for both generations separately using Model 4 in the SPSS Hayes Process Macro, with 5,000 bootstrap resamples and 95% significance level. The findings for Gen Y are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and in Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The findings for Gen Z are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The baseline models were tested to examine the direct effect of TikTok addiction on attention control for Gen Y. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e for Gen Y, TikTok addiction was a non-significant predictor of attention control but a significant predictor of boredom intolerance and cognitive fatigue. These pathways in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e also show that TikTok addiction had a significant positive relationship with boredom intolerance (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.14, \u003cem\u003ep\u003c/em\u003e = .05). However, boredom intolerance did not significantly predict attention control (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;.12, \u003cem\u003ep\u003c/em\u003e = .09). These findings partially support hypothesis 1.\u003c/p\u003e \u003cp\u003e Two indirect effects were bootstrapped, and the indirect effect of TikTok addiction on attention control through boredom intolerance was not significant, indicating that boredom intolerance did not function as a mediator in this relationship. In contrast, TikTok addiction positively predicted cognitive fatigue (\u003cem\u003eβ\u003c/em\u003e = .23, \u003cem\u003ep\u003c/em\u003e = .00), which in turn, negatively predicted attention control (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;.32, \u003cem\u003ep\u003c/em\u003e = .00). This finding indicates that individuals experiencing higher levels of cognitive fatigue tend to exhibit poorer attention control. The bootstrap results confirmed that cognitive fatigue significantly mediated the relationship between TikTok addiction and attention control, supporting the proposed mediation hypothesis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurthermore, the total indirect effect of TikTok addiction on attention control was significant (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;.09, 95% CI [\u0026minus;\u0026thinsp;.17, \u0026minus;\u0026thinsp;.03]), despite the absence of a significant direct effect (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.008, \u003cem\u003ep\u003c/em\u003e = .94) and total effect (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;.08, \u003cem\u003ep\u003c/em\u003e = .42) for Gen Y. This pattern suggests indirect-only mediation, where TikTok addiction influences attention control primarily through cognitive fatigue rather than through a direct pathway. Overall, these findings indicate that TikTok addiction contributes to diminished attention control by increasing cognitive fatigue, highlighting cognitive fatigue as a key underlying psychological mechanism. In contrast, boredom intolerance does not play a significant mediating role in this relationship among Gen Y.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eDirect, Indirect, and Total Effects for TikTok Addiction, Boredom Intolerance, Cognitive Fatigue, and Attention Control for Gen Z (n\u0026thinsp;=\u0026thinsp;150)\u003c/em\u003e\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\u003eDirect Effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eLL\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eUL\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\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\u003eTikTok Addiction \u0026rarr; Attention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.38*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction \u0026rarr;Boredom Intolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.13*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction \u0026rarr;Cognitive Fatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.10*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoredom Intolerance\u0026rarr; Attention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive Fatigue \u0026rarr;Attention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndirect Effect (Bootstrapped)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction \u0026rarr;Boredom Intolerance\u0026rarr; Attention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.01\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\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction \u0026rarr;Cognitive Fatigue \u0026rarr;Attention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.02\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\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal Effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction \u0026rarr;Attention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eNote\u003c/b\u003e. \u003cem\u003eCI\u003c/em\u003e\u0026thinsp;=\u0026thinsp;confidence interval; \u003cem\u003eSE\u0026thinsp;=\u003c/em\u003e\u0026thinsp;standard error; \u003cem\u003eLL\u003c/em\u003e\u0026thinsp;=\u0026thinsp;lower limit; \u003cem\u003eUL\u0026thinsp;=\u003c/em\u003e\u0026thinsp;upper limit.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the direct, indirect, and total effects of predictors on attention control among Gen Z. TikTok addiction was a significant negative predictor of attention control and a positive predictor of boredom intolerance and cognitive fatigue. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, TikTok addiction had a significant positive relationship with boredom intolerance (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.35, \u003cem\u003ep\u003c/em\u003e = .05). Boredom intolerance had a significant negative relationship with attention control (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;.28, \u003cem\u003ep\u003c/em\u003e = .09). These findings support hypothesis 1. The amount of variance explained ranged from small to moderately high.\u003c/p\u003e \u003cp\u003eThe bootstrapped results for indirect paths showed that TikTok addiction positively predicted boredom intolerance (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.35, \u003cem\u003ep\u003c/em\u003e = .00), which in turn, negatively predicted attention control (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;.28, \u003cem\u003ep\u003c/em\u003e = .00). This finding indicates that individuals with higher TikTok addiction are more likely to experience boredom intolerance, which further contributes to diminished attention control. Thus, boredom intolerance was a significant mediator of the relationship between TikTok addiction and attention control. Similarly, TikTok addiction positively predicted cognitive fatigue (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.32, \u003cem\u003ep\u003c/em\u003e = .00), which in turn, negatively predicted attention control (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;.36, \u003cem\u003ep\u003c/em\u003e = .00). This finding suggests that higher levels of TikTok addiction are associated with increased cognitive fatigue, which subsequently leads to reduced attention control. It implies that cognitive fatigue significantly mediated the relationship between TikTok addiction and attention control.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurthermore, the total indirect effect of TikTok addiction on attention control was significant (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;.21, 95% \u003cem\u003eCI\u003c/em\u003e [\u0026minus;\u0026thinsp;.32, \u0026minus;\u0026thinsp;.12]). In addition, both the direct effect (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;.16, \u003cem\u003ep\u003c/em\u003e = .04) and total effect (\u003cem\u003eβ\u003c/em\u003e = \u0026minus;.37, \u003cem\u003ep\u003c/em\u003e = .00) were significant. These findings highlight that TikTok addiction influences attention control both directly and indirectly through boredom intolerance and cognitive fatigue among Gen Z. The results suggest a stronger, more comprehensive mediation pattern than indirect-only models, underscoring the combined role of cognitive and affective processes in explaining attentional deficits. Supporting the hypothesis, these findings imply that both boredom intolerance and cognitive fatigue serve as important psychological mechanisms through which TikTok addiction impairs attention control among Gen Z individuals.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eGender Differences in Study Variables between Gen Y and Gen Z\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eGen Y (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eCohen\u0026rsquo;s d\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\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 \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eLL\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eUL\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-5.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoredom Intolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive Fatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eGen Z (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTikTok Addiction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-5.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoredom Intolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-5.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive Fatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttention Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cb\u003eNote\u003c/b\u003e. \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;mean, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;standard deviation, \u003cem\u003eCI\u003c/em\u003e\u0026thinsp;=\u0026thinsp;confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAn independent-samples t-test was used to compare differences in TikTok addiction, boredom intolerance, cognitive fatigue, and attention control among Gen Y and Gen Z participants. For Gen Y, the gender difference was statistically significant, as indicated in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Women reported higher levels of TikTok addiction, boredom intolerance, and cognitive fatigue compared to men. However, males showed higher scores on attention control. These findings support the assumption about gender differences in TikTok addiction and related psychological outcomes among Generation Y. Among Gen Z, females demonstrated greater boredom intolerance than males, whereas males reported significantly greater attention control than females. No statistically significant gender differences were found in TikTok addiction and cognitive fatigue. Overall, these results partially support the hypothesis about gender differences in TikTok addiction and related psychological outcomes.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study examined the effect of TikTok addiction on attention control among Generation Y and Generation Z, with boredom intolerance and cognitive fatigue as parallel mediators. Overall, the findings provide partial to full support for the proposed hypotheses and offer important insights into the cognitive and psychological consequences of problematic social media use across generations. Consistent with the first hypothesis, TikTok addiction positively predicted boredom intolerance and cognitive fatigue in Gen Y and Gen Z groups. However, its negative effect on attention control was significant only among Gen Z, indicating a stronger direct impact on younger users, possibly due to greater exposure to highly stimulating content and less stable attentional regulation. At the same time, no such relationship was observed among Gen Y. This suggests that although TikTok addiction contributes to increased cognitive and affective strain across both generations, its direct detrimental impact on attentional control is more pronounced among younger users. This may be explained by Gen Z's heightened exposure to fast-paced, highly stimulating short-form content, along with relatively less stable attentional regulation compared to Gen Y. This finding supports Yan et al.\u0026rsquo;s (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) study.\u003c/p\u003e \u003cp\u003eIn line with the second hypothesis, boredom intolerance and cognitive fatigue negatively predicted attention control. This was fully supported in Gen Z, where both variables were significant predictors of reduced attentional control. In Gen Y, only cognitive fatigue was significant, suggesting it is a consistent predictor across generations. At the same time, boredom intolerance is more influential among Gen Z. These findings indicate that cognitive fatigue is a consistent and robust determinant of attentional impairment across generations. In contrast, boredom intolerance appears to play a more prominent role among younger Gen Z individuals. This generational variation suggests differences in how affective and cognitive processes contribute to attentional functioning. These findings align with studies by Baltacı and A\u0026ccedil;ar (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and Haque (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2026\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding the third hypothesis, partial support was found for parallel mediation. In Gen Z, both boredom intolerance and cognitive fatigue significantly mediated the relationship between TikTok addiction and attention control. In Gen Y, only cognitive fatigue acted as a mediator. Additionally, Gen Y showed indirect-only mediation, whereas Gen Z demonstrated partial mediation, indicating more complex underlying mechanisms in younger users. These findings suggest that the mechanisms underlying the relationship between TikTok addiction and attention control are more complex and multifaceted among younger users, involving both cognitive exhaustion and intolerance of low stimulation.\u003c/p\u003e \u003cp\u003eThe fourth hypothesis on gender differences was partially supported. Among Gen Y, females reported higher TikTok addiction, boredom intolerance, and cognitive fatigue than males, while males showed better attention control. Among Gen Z, females reported higher boredom intolerance and males higher attention control, with no significant gender differences in TikTok addiction and cognitive fatigue. These findings suggest that gender differences in digital behavior and its psychological outcomes vary across generations and reflect differing behavioral and coping patterns.\u003c/p\u003e \u003cp\u003eGender-sensitive approaches may further enhance the effectiveness of interventions. The magnitude and pattern of direct and indirect effects clearly demonstrated generational differences. Specifically, the direct negative effect of TikTok addiction on attention control was significant only among Gen Z, and boredom intolerance acted as a significant mediator only within this group. In contrast, cognitive fatigue emerged as a consistent mediator across both generations. These findings highlight that Gen Z individuals are more vulnerable to both direct and indirect effects of TikTok addiction, reflecting a stronger and more complex interplay of cognitive and affective mechanisms. Overall, this study contributes to the literature by identifying key generational and gender-specific mechanisms linking TikTok addiction to attention control within a Pakistani context.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and Recommendations\u003c/h2\u003e \u003cp\u003eDespite its contributions, the present study has several limitations. The use of mediation analysis in a cross-sectional design restricts causal inferences. The reliance on self-report measures may introduce response bias and common method variance. Additionally, the sample was drawn from a single geographic region, limiting generalizability. The study focused only on boredom intolerance and cognitive fatigue, excluding other relevant variables such as sleep quality and impulsivity, and did not differentiate between TikTok addiction types or contexts, which may influence cognitive outcomes. Future research should employ longitudinal designs to establish causal relationships between TikTok addiction and attentional control and to investigate the over-time effects of other short-form video platforms, such as Instagram Reels, YouTube Shorts, and Snapchat. The issues of response bias and common method variance can be addressed by comparing self-reports with other-reports and using multiple informants. Another ignored area of research is the investigation of the role of cultural and contextual factors in predicting social media\u0026ndash;related cognitive outcomes. Future researchers can expand the external validity of the research by collecting data from cultural contexts and diverse populations at multiple sites with additional mediators such as sleep quality and impulsivity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eTheoretical and Practical Implications\u003c/h2\u003e \u003cp\u003eThis research has serious theoretical and practical implications. This study adds empirical literature to expand the understanding of Eysenck's Attentional Control theory, Katz\u0026rsquo;s Uses and Gratifications theory, and Sweller\u0026rsquo;s Cognitive Load theory. The findings improve our understanding of how social media usage, specifically TikTok addiction, influences cognitive skills among younger populations. In line with Attentional Control theory, TikTok impairs inhibitory control, and users find it hard to sustain goal-directed attention in the presence of distracting stimuli. Repeated exposure to a constant flow of content diminishes attention control in such digital environments. Aligned with the Uses and Gratifications theory, participants seek gratification from repeated use of TikTok, but the rapidly changing content emotionally stimulates them and impairs their executive functioning. According to the Cognitive Load theory, cognitive overload decreases the capacity for attention, working memory, and efficient information processing. The study also highlights boredom intolerance and cognitive fatigue as major mediators, depicting the interplay between cognitive and psychological processes in the determination of attention control. It means that the influence of social media cannot be reduced to a direct one, but rather to more profound individual differences in tolerance for cognitive and emotional difficulties, leading to a more sophisticated view of the relationship between digital media involvement and cognitive performance.\u003c/p\u003e \u003cp\u003ePractically, this study offers guidance on advancing evidence-based interventions to promote healthy social media use and improve cognitive performance among younger generations. The results indicate that certain actions are necessary to reduce the negative cognitive consequences of extended TikTok addiction. Therefore, interventions should focus on reducing excessive TikTok use and managing cognitive fatigue across both generations, with additional emphasis on improving boredom tolerance among younger users. Furthermore, improving cognitive resilience, sharpening attention-control skills, and providing adolescents and young adults with effective coping strategies to manage digital interactions are also necessary. For example, systematic activities that increase concentration and scheduled screen-free time could help reduce mental burnout.\u003c/p\u003e \u003cp\u003eAge- and gender-based strategies might be particularly beneficial, as females and Gen Zs appear to be more susceptible to the combined effects of boredom intolerance and cognitive fatigue. Gender-based strategies can also be helpful, such as focusing on female fatigue and emotional regulation, and reinforcing the male focus on attention control. Among younger users, attentional control can be alleviated by strategies that increase boredom tolerance, limit screen time, and offer alternative attention-engaging activities. Time management, mindfulness, and attentional exercises can be more effective for those who experience cognitive fatigue. Understanding the augmenting role of boredom intolerance is a useful guide to teachers, caregivers, and mental health practitioners. Programs that encourage adaptive coping strategies, engagement in meaningful offline activities, and resilience during periods of low stimulation may reduce the mental health risks associated with TikTok addiction. It recommends that parents, teachers, and policymakers promote balanced online practices, address extended screen time on social media, and create conditions that support cognitive well-being and adaptive attentional control across generations.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings of this study emphasize that the impact of TikTok addiction extends beyond simple screen use, shaping how individuals manage attention through both cognitive and affective pathways. The stronger vulnerability observed in Gen Z suggests that growing up in highly stimulating digital environments may alter attentional regulation, increasing vulnerability to fatigue and boredom. The role of cognitive fatigue as a consistent mechanism highlights the importance of mental exhaustion in understanding attentional decline. At the same time, the additional influence of boredom intolerance among younger users reflects a reduced capacity to engage with low-stimulation tasks. Moreover, the observed gender differences point toward distinct patterns in how individuals experience and cope with digital engagement, indicating that attentional outcomes are influenced not only by usage intensity but also by underlying psychological and social factors. Overall, the study underscores the need to view attention control in the context of modern digital habits, where excessive consumption of short-form content may gradually reshape cognitive functioning, particularly among younger generations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAI: Conceptualization, data collection, data entry, literature review search, writing the original draft. NZ: Conceptualization, literature review search, research plan, supervision, data analysis and interpretation, editing, formatting, and submission.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe dataset utilized in this research can be made available to interested researchers. Requests for access to data, material, and codebook should be directed to the first author A.I., ensuring alignment with ethical guidelines and data-sharing protocols.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBai, J., Mo, K., Peng, Y., Hao, W., Qu, Y., Lei, X., \u0026amp; Yang, Y. (2021). The relationship between the use of mobile social media and subjective well-being: The mediating effect of boredom proneness. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e, 568492. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fpsyg.2020.568492\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2020.568492\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaltacı, \u0026Ouml;., \u0026amp; A\u0026ccedil;ar, I. (2025). 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Potential effect of short video usage intensity on short video addiction, perceived mood enhancement ('TikTok brain'), and attention control among Chinese adolescents. \u003cem\u003eInternational Journal of Mental Health Promotion\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e(3). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.32604/ijmhp.2025.059929\u003c/span\u003e\u003cspan address=\"10.32604/ijmhp.2025.059929\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Attention control, boredom intolerance, cognitive fatigue, Gen Y, Gen Z, TikTok addiction","lastPublishedDoi":"10.21203/rs.3.rs-9393045/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9393045/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTikTok has become a dominant component of contemporary digital life; however, its implications for cognitive functioning, particularly attention control, remain underexplored. The present study investigated the relationship between TikTok addiction and attention control among Generation Y and Generation Z, with a specific focus on the parallel mediating roles of boredom intolerance and cognitive fatigue. A comparative cross-sectional design was employed, comprising 300 participants (150 Gen Y, 150 Gen Z) recruited from Haripur District, Pakistan, using stratified sampling. Data were collected from individuals who reported at least 1 hour of daily TikTok use over the past 12 months. The findings revealed that TikTok addiction had a significant negative direct effect on attention control among Gen Z. In contrast, no such effect was observed for Gen Y. Parallel mediation analyses indicated that cognitive fatigue significantly mediated the relationship between TikTok addiction and attention control in both generations.\u003c/p\u003e \u003cp\u003eIn contrast, boredom intolerance emerged as a significant mediator only among Gen Z, but not among Gen Y. Gender-based analyses further demonstrated that males in both generations exhibited higher attention control. In contrast, females in Gen Y reported higher levels of TikTok addiction. Additionally, females in Gen Z showed elevated levels of boredom intolerance and cognitive fatigue. These findings highlight important generational and gender differences in the cognitive consequences of social media use. The study underscores cognitive fatigue as a key mechanism linking TikTok addiction to attentional deficits and offers important theoretical contributions to models of digital media engagement and cognitive load. Practical implications for digital well-being and targeted interventions are discussed.\u003c/p\u003e","manuscriptTitle":"TikTok Addiction and Attention Control in Gen Y and Gen Z: Parallel Mediating Role of Boredom Intolerance and Cognitive Fatigue","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-15 09:04:41","doi":"10.21203/rs.3.rs-9393045/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ceeb1922-4b2d-4895-9286-73d9df8accc5","owner":[],"postedDate":"April 15th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-21T07:30:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-15 09:04:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9393045","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9393045","identity":"rs-9393045","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}