Unboxing the Paradox: Understanding How Viewing Motivations Drive User Fatigue and Attrition on Short-Form Video Platforms

Unboxing the Paradox: Understanding How Viewing Motivations Drive User Fatigue and Attrition on Short-Form Video Platforms | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Unboxing the Paradox: Understanding How Viewing Motivations Drive User Fatigue and Attrition on Short-Form Video Platforms Qian Zhang, Zhaoqi Li, Jiangmin Ding, Hong Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8067328/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Understanding how unboxing video viewing motives influence users’ cognitive and behavioral outcomes is essential for managing engagement and fatigue in short-form video environments. This study examines how different viewing motives in unboxing short-form videos - entertainment and boredom/habitual pass time - affect perceived information overload and subsequent discontinuance intention to use. Using structural equation modeling, the results reveal that boredom/habitual pass time motives lead to repetitive and passive viewing patterns, thereby intensifying information overload, whereas entertainment motives exert no significant effect, reflecting their restorative nature. Consistent with Cognitive Overload Theory, when users perceive an overload of information, the resulting fatigue and cognitive confusion collectively drive their intention to withdraw from short-form video use. Moreover, customer engagement moderates these effects: highly engaged users process content via the central route and experience greater strain, while low-engagement users rely on peripheral cues that alleviate overload. These findings deepen the understanding of cognitive and affective mechanisms underlying short-form video fatigue while offering practical guidance for optimizing content rhythm, recommendation algorithms, and user experience design on digital platforms. Collectively, they also extend the Elaboration Likelihood Model by revealing how cognitive overload operates within interactive media contexts. Biological sciences/Neuroscience Biological sciences/Psychology Social science/Psychology Unboxing videos Viewing motives Short-form video fatigue Customer engagement Information overload Cognitive Overload Theory Discontinuance intention Figures Figure 1 Figure 2 1. Introduction Aradius Media Network’s 2006 release was a 90-second clip that captures the process of unboxing the Nokia E61. This video is widely regarded as the starting point of the global “unboxing video” phenomenon (Mowlabocus, 2020 ). By November 2016, searches for “unboxing video” had generated more than 57 million results, highlighting the rapid expansion and influence of this format (Mowlabocus, 2020 ; Agrawal & Mittal, 2022). In parallel, the evolution of social media platforms has accelerated this trend. Among them, TikTok has emerged as a leading force, reshaping how users create and consume short-form content. Centered on quick, visually engaging videos, TikTok has gained immense global traction and, since 2018, consistently ranked among the most downloaded apps worldwide, with over 1.5 billion monthly active users by 2023 (Yang et al., 2024 ). Against this backdrop, unboxing videos have evolved from simple product demonstrations into a form of social entertainment that spans multiple categories, including gaming, beauty, and digital products (Mowlabocus, 2020 ; ). Beyond satisfying users’ curiosity and sense of participation, Brands increasingly leverage unboxing videos as a strategic means to strengthen customer involvement and promote their products (Özer & Uğurhan, 2025 ). Nevertheless, what exactly accounts for the appeal of unboxing videos? The unboxing process is not merely a practical act of acquiring goods, but rather a “consumption ritual” filled with anticipation and gratification (Vaudrey, 2022 ). This immediate and tangible experience not only encourages consumers to enjoy unboxing products themselves but also motivates them to watch others’ unboxing performances on platforms such as YouTube, deriving emotional pleasure and a sense of identification in the process (Kim et al., 2018 ; Vaudrey, 2022 ). In recent years, unboxing videos have gradually evolved into an important marketing tool within social media, serving not only to showcase product attributes but also to shape consumer interest and purchase decisions (Kim, 2020 ). Moreover, the popularity of blind-box products such as Pop Mart further demonstrates the powerful allure of “revealing the unknown” to consumers (Zhang et al., 2025 ). Whether it involves physically unsealing blind boxes or virtually watching unboxing content on short video platforms, consumers consistently display enduring and widespread enthusiasm for the moment of “opening,” which delivers both surprise and emotional satisfaction (Van Droogenbroeck & Willems, 2025 ). Yet, with the exponential growth and accelerating pace of unboxing content, users are increasingly confronted with information redundancy and psychological strain. When such content no longer provides a sense of novelty or fails to align with users’ viewing motivations, experiences of information overload and usage fatigue are likely to arise. Against this backdrop, the present study investigates how different viewing motivations shape users’ perceptions of unboxing videos and their subsequent psychological reactions, thereby clarifying the underlying processes through which these motivations give rise to short-form video fatigue and users’ intentions to disengage from such platforms. Prior research has predominantly focused on examining the influence of unboxing video content on consumers’ purchase behaviors and decision-making processes. For instance, Kim ( 2020 ) found that the source characteristics of unboxing videos, together with purposeful and non-purposeful motivations, shape consumers’ purchase intentions through parasocial interaction. Similarly, Chen and Jiang ( 2025 ) showed that information seeking, entertainment, interpersonal utility, and pastime act as antecedents of perceived coolness, which positively affects customers’ psychological well-being and mediates the effects of these antecedents. In addition, Özer and Uğurhan ( 2025 ) demonstrated that consumers driven by information-seeking, entertainment, and interpersonal motives are more likely to exhibit stronger purchase and eWOM intentions, while pass-time motives show no significant influence. Extending this line of inquiry, Evans et al. ( 2018 ) found that the inclusion of sponsor bumpers in children’s unboxing videos can enhance parents’ perceptions of sponsorship transparency. This increased sense of transparency subsequently influences their attitudes and evaluations indirectly, and the strength of this indirect effect depends on the degree of parental mediation. Taken together, these studies suggest that unboxing videos function not only as an important channel for product information but also as a medium that shapes purchase decisions through diverse psychological and sensory mechanisms. While prior research has primarily examined how unboxing videos stimulate consumers’ purchase intentions and behaviors, less attention has been paid to their potential negative psychological consequences. On short video platforms, the dense stream of content and algorithmically generated repetition can increase users’ cognitive load and emotional exhaustion. When content becomes repetitive or fails to meet expectations, viewing motivations may remain unsatisfied and even result in negative experiences. In such contexts, unboxing videos may shift from being a source of enjoyment to a source of psychological strain, influencing users’ attitudes toward platforms and their discontinuance intentions. However, research has yet to systematically explore how viewing motivations, through information perception mechanisms, shape usage fatigue and behavioral outcomes. Building on this reasoning, we propose the following research questions: RQ1: Do different viewing motivations (e.g., entertainment and boredom/habitual passing time) lead to varying levels of perceived information overload? RQ2: Does perceived information overload indirectly influence users’ discontinuance intentions by triggering short video fatigue, psychological risks, and feelings of uncertainty? RQ3: Does customer engagement (high vs. low) moderate the relationship between viewing motivations and perceived overload of information? To explore the proposed research questions, this research focused on the primary user group of short-form video platforms and adopted unboxing videos as the research context. Drawing on Uses and Gratifications Theory, it examined how viewing motivations (entertainment and boredom/habitual motivations) influence perceived information overload, which subsequently affects user fatigue and discontinuance intentions. In addition, based on Cognitive Overload Theory, the study explored how excessive information processing contributes to users’ psychological strain. Furthermore, integrating the Elaboration Likelihood Model, this study developed a multi-level psychological mechanism framework to explain how user engagement moderates the information processing pathway from viewing motivation to behavioral outcomes. This study enhances understanding of how short-form video use can lead from user fascination to mental fatigue, offering a refined view of its underlying psychological mechanisms. Building on these insights, the findings offer practical implications for short video platforms, particularly in optimizing content recommendation rhythms, reducing information redundancy, and enhancing user experience design. 2. Research background 2.1. Uses and gratifications theory Originating from efforts to understand audience behavior, the uses and gratifications perspective seeks to explain why people select and consume specific media types—such as radio broadcasts or television programs—to fulfill particular needs (Ibáñez-Sánchez et al., 2022 ; Ruggiero, 2000 ). The accelerating growth of the Internet and social media has led scholars to employ the U&G perspective to better understand the psychological and behavioral mechanisms driving online consumer engagement (Ibáñez-Sánchez et al., 2022 ; Nguyen & Nguyen, 2024 ; Pillai et al., 2025 ; Yu, 2024 ). According to the U&G, media audiences actively seek out channels that align with their personal motives and desires, engaging with media content purposefully instead of consuming it passively (Pillai et al., 2025 ). These underlying motivations can include information seeking, experiencing enjoyment, social interaction, escapism or simply passing time. Users on short-video platforms often watch videos for enjoyment, stress relief when they feel bored (Croes & Bartels, 2021 ), which leads them to repeatedly encounter large amounts of homogeneous content. However, such repetitive and excessive exposure does not always yield positive experiences. On the one hand, when users’ needs are not genuinely fulfilled (e.g., seeking novelty but receiving repetitive content), they may experience disappointment and dissatisfaction. On the other hand, motivations can also drive overuse, resulting in a paradoxical effect in which gratification produces unintended negative consequences (Park & Jung, 2024 ). Rather than fostering relaxation or enjoyment, over-gratification may trigger perceived information overload, reduced attention, psychological fatigue, and uncertainty. Thus, U&G provides a critical lens for this study, as it explains both why users continuously engage with short video content (motivation-driven behavior) and how such engagement - when combined with mechanisms emphasized in cognitive overload theory - can ultimately lead to short video fatigue and discontinuance intention. 2.2. Cognitive overload theory Gross originally introduced the term information overload to describe a situation where the amount of information available within a limited period overwhelms an individual’s cognitive capacity to manage or make sense of it (Zhang et al., 2023 ; Zhang et al., 2024 ). The accelerating growth of social media platforms has made information overload a prevalent aspect of modern digital life (Cao & Sun, 2018 ). When users are exposed to large volumes of homogeneous, rapidly updated, structurally complex, or ambiguous information during browsing, they are likely to experience cognitive strain (Cao et al., 2021 ). This process is not only influenced by the external density of information but is also closely related to users’ knowledge background, experience, and cognitive resources. Prior research has demonstrated that experiencing information overload can lead to several detrimental emotional and cognitive consequences, such as feelings of distraction, heightened anxiety, mental fatigue, and the fear of missing out (Cao & Sun, 2018 ; Farooq et al., 2021 ), and may further undermine trust in online environments (Fan et al., 2021 ). Although some studies suggest that a moderate level of information intensity can enhance content attractiveness and platform stickiness, excessive overload beyond users’ cognitive threshold often leads to fatigue and resistance to continued use (Wang & Chi, 2025 ). Accordingly, this research investigates the experience of perceived content pressure within the setting of unboxing short videos. It particularly examines whether individuals who frequently watch such short-form videos—whether for amusement or simply to fill idle time—tend to experience psychological fatigue driven by information overload, which in turn heightens their intention to withdraw from or reduce engagement with these platforms. 2.3. Elaboration likelihood model The Elaboration Likelihood Model is a dual-process framework for explaining information processing and attitude change (Cacioppo et al., 1986 ; Wang et al., 2025 ). The model posits that people engage with information through one of two routes—central or peripheral—based on their degree of motivation and their capacity to process the message. In the central route, individuals engage in thoughtful evaluation of message arguments that require considerable mental effort. In contrast, the peripheral route relies on surface-level signals like source credibility, the number of endorsements, or social validation (Shi et al., 2018 ). In social media contexts, users’ engagement intensity significantly influences their mode of information processing, guiding whether messages are assessed through central or peripheral routes. Highly engaged users are more likely to be motivated to engage in deep processing via the central route, devoting greater attention and cognitive resources (Park et al., 2024 ). However, this heightened engagement may also increase their susceptibility to perceived information overload during prolonged use of short video platforms. By contrast, low-engagement users often rely on peripheral cues and thus experience lower levels of cognitive burden (Park et al., 2024 ). Therefore, user engagement moderates the relationship between viewing motives and perceived information overload, such that highly engaged users are more prone to enter states of high cognitive load when motivated. 3. Literature review and hypothesis development 3.1. Effect of viewing motivations (entertainment and boredom) on perceived information overload According to Uses and Gratifications Theory, individuals are not passive recipients of media but actively engage with it to satisfy various personal needs - such as seeking entertainment, maintaining social connections, or alleviating boredom (Ibáñez-Sánchez et al., 2022 ; Pillai et al., 2025 ). In short-form video contexts, entertainment motivation often reflects users’ desire for enjoyment, relaxation, and hedonic gratification (Zeng et al., 2024 ). In contrast, boredom or habitual motives are primarily driven by the avoidance of idleness or the maintenance of routine behaviors (Croes & Bartels, 2021 ). Although, entertainment and boredom motives initially stimulate short-form video use, they can also lead to unintended cognitive consequences. According to research on information overload, frequent encounters with monotonous and swiftly refreshed content can overload users’ cognitive systems, causing attentional lapses, tiredness, and a pronounced sense of mental strain (Cao & Sun, 2018 ; Farooq et al., 2021 ). Users driven by boredom or habitual motives are particularly prone to repetitive and prolonged viewing, which heightens their vulnerability to information overload. Prior research has further shown that excessive exposure to information can lead to various adverse psychological reactions, including distraction, anxiety, fatigue, and even a fear of missing out (Cao & Sun, 2018 ; Farooq et al., 2021 ), and can undermine trust in online environments (Fan et al., 2021 ). While moderate levels of information intensity may enhance content attractiveness and platform stickiness, overload beyond users’ cognitive threshold typically results in fatigue and resistance to continued use (Fu et al., 2020 ; Wang & Chi, 2025 ). Building on uses and gratifications and cognitive overload theory, this study argues that user motivations represent a critical antecedent of perceived information overload. Therefore, we develop our hypothesis as follows: H1: Entertainment motivation positively influences perceived information overload. H2: Boredom/habitual motivation positively influences perceived information overload. 3.2. Effect of perceived information overload on user negative responses When people are exposed to more information than their minds can effectively process and understand, information overload emerges, causing cognitive fatigue and hindering sound decision-making (Zhang et al., 2023 ). Previous research indicates that cognitive overload can significantly reduce individuals’ capacity to sustain attention, depletes cognitive resources, and produces negative psychological reactions such as anxiety and emotional exhaustion (Farooq et al., 2021 ). Prior studies have highlighted that in digital media environments, excessive exposure to information can trigger fatigue (Fu et al., 2020 ), undermine users’ trust (Furner & Zinko, 2017 ), and lower subjective well-being (Chai et al., 2019 ). In the short-form video environment, where users are frequently exposed to highly repetitive, homogeneous, and rapidly updated content, perceived overload is particularly salient. Such overload not only heightens psychological strain but also triggers a range of negative user responses. Specifically, information overload can manifest as short-form video fatigue, reflecting users’ exhaustion from constant exposure to dense content streams (Chung et al., 2023 ; Huang et al., 2023 ). It can also increase perceived psychological risk, as users become more uncertain about the reliability or consequences of prolonged usage (Soto-Acosta et al., 2014 ). Prior research indicate that uncertainty can amplify users’ perception of information overload during information processing (Zhang et al., 2022 ). Building on this, we argue that information overload, in turn, contributes to heightened perceived uncertainty by making it difficult for users to judge the value and credibility of rapidly flowing content. Drawing on cognitive overload theory, this study argues that perceived information overload represents a central mechanism through which users develop negative psychological and behavioral reactions. Thus, we develop our hypothesis as follows: H3: Perceived information overload positively influences short-form video fatigue. H4: Perceived information overload positively influences perceived psychological risk. H5: Perceived information overload positively influences perceived uncertainty. 3.3. Effect of user negative responses on discontinuance intention of short-form video use When users experience negative psychological responses during media consumption, they are more likely to disengage from the platform or discontinue its use. Prior research has shown that media fatigue leads to lower continued usage (Huang et al., 2023 ), discontinuance intention (Chung et al., 2023 ) and users' disengagement (Fernandes & Oliveira, 2024 ). Similarly, perceived psychological risk has been shown to undermine consumer trust in a product, which in turn decreases their behavior intention (Pappas, 2016 ). Moreover, perceived uncertainty, characterized by doubts about the reliability, usefulness, or credibility of media content (Shin et al., 2017 ), discourages users from prolonged usage, as uncertainty is often linked to avoidance behavior and disengagement, which occurs because consumers inherently exhibit uncertainty avoidance (Reimann et al., 2008 ). In the setting of short-form video engagement, these negative responses—fatigue, psychological risk, and uncertainty—represent critical mechanisms driving discontinuance intention. Frequent exposure to information overload can generate adverse psychological experiences, prompting users to reduce or cease short-form video consumption in an effort to reestablish mental balance and emotional stability. Therefore, we propose the following hypothesis: H6: Short-form video fatigue positively influences discontinuance intention of short-form video use. H7: Perceived psychological risk positively influences discontinuance intention of short-form video use. H8: Perceived uncertainty positively influences discontinuance intention of short-form video use. 3.4. The moderating effects of customer engagement As interactive media continue to evolve, the notion of customer engagement has increasingly taken center stage in academic research and industry practice (Oh et al., 2018 ). Specifically, customer engagement reflects the degree of users’ cognitive, emotional, and behavioral involvement with media content (Abbasi et al., 2024 ). According to ELM (Cacioppo et al., 1986 ), individuals with a high level of involvement tend to process persuasive information through a central route—carefully evaluating arguments and devoting substantial cognitive resources to message scrutiny. In contrast, those with lower engagement are inclined to rely on the peripheral route, forming judgments based on surface cues such as social endorsement, attractiveness, or perceived popularity rather than message substance. This distinction implies that customer engagement may moderate the strength of relationships between viewing motives, perceived information overload, and downstream negative responses. Viewers often watch user-generated videos not only for entertainment but also to enjoy co-viewing experiences and to share the content within their social circles (Kim, 2020 ). As De Veirman et al. ( 2017 ) suggest that the entertainment aspect of advertising plays a pivotal role in shaping brand perception, with entertaining messages eliciting more favorable evaluations. Although both high- and low-engagement viewers can derive entertainment from short, episodic consumption, highly engaged viewers tend to engage in more sustained and repetitive viewing behaviors, thereby amplifying potential cognitive load. Previous research also indicates that while entertainment-oriented consumption creates a relaxed and enjoyable state, it is typically marked by positive emotions and a moderate level of arousal (Bartsch & Hartmann, 2017 ), it may also increase the likelihood of attentional fatigue when pursued intensively. Therefore, we propose: H9: The effect of entertainment motivation on perceived information overload is stronger under high engagement than under low engagement. Boredom and habitual media use—often linked to stress relief—represent important motivations behind entertainment consumption. Prior studies indicate that individuals turn to online media to counter boredom (Papacharissi & Rubin, 2000 ) and engage with television as a means of psychological escape (Kim, 2020 ). Extending this logic, user-generated videos such as unboxing content can serve similar purposes, offering viewers a casual, time-filling activity that provides relaxation and temporary distraction from daily routines. Boredom and habitual pass time motives often drive repetitive and prolonged exposure, leading users to scroll automatically without purposeful selection (Arness & Ollis, 2023 ). Under high engagement, these motives are enacted more intensively, resulting in longer sessions and greater exposure to redundant content, which exacerbates information overload. Conversely, low-engagement customers may disengage earlier, weakening this relationship. Thus, we propose: H10: The effect of boredom/habitual motivation on perceived information overload is stronger under high engagement than under low engagement. When people are exposed to too much information, their limited cognitive resources are drained, weakening attentional control and giving rise to fatigue and burnout (Zhang et al., 2023 ). Highly engaged users, who devote more effort to processing and hold higher expectations for content quality, are more sensitive to overload conditions. Research on social media indicates that engaged users report greater fatigue when exposed to excessive information (Farooq et al., 2021 ). Thus, we propose: H11: The effect of perceived information overload on short-form video fatigue is stronger under high engagement than under low engagement. Fatigue reflects a loss of control and mounting costs, such as wasted time, negative emotions, or concerns about harmful consequences (Zhang et al., 2023 ). In addition, Chung et al. ( 2023 ) examined customers’ excessive engagement with social media and found that information overload contributes to greater life dissatisfaction, manifested in outcomes such as distress, negative emotions from social comparison, and reduced well-being. For higher customer engagement, fatigue represents a more salient violation of usage goals, intensifying concerns about risks associated with continued platform use (Cao & Sun, 2018 ; Farooq et al., 2021 ). Thus, customer engagement heightens the extent to which perceived information overload translates into perceived psychological risk. Thus: H12: The effect of perceived information overload on perceived psychological risk is stronger under high engagement than under low engagement. Information overload hampers users’ ability to evaluate the credibility and value of content, creating doubts and confusion (Zhong et al., 2025 ). In fast-paced content streams, highly engaged users—despite their deeper involvement—face stronger expectation–reality discrepancies, as redundant or conflicting content undermines their confidence in information reliability. Prior studies confirm that overload fosters uncertainty and avoidance behaviors (Reimann et al., 2008 ). H13: The effect of perceived information overload on perceived uncertainty is stronger under high engagement than under low engagement. Figure 1 presents the conceptual framework that depicts the hypothesized relationships among the study variables. ==================== Insert Fig. 1 about here ==================== 3. Method 3.1. Measurement development All measurement items were adapted from prior validated scales and refined to align with the specific context of this study. Specifically, entertainment motivation (four items) was adapted from Hur et al. ( 2017 ), Lee and Ma ( 2012 ), and Park et al. ( 2009 ), while boredom/habitual pass time motivation (three items) was adapted from Croes and Bartels ( 2021 ). Perceived information overload (four items) was adopted from Chung et al. ( 2023 ) and Misra and Stokols ( 2012 ). Short-form video fatigue (four items) was adopted from Bright et al. ( 2015 ) and Chung et al. ( 2023 ). Perceived psychological risk (three items) was measured from Mvondo et al. ( 2023 ). Perceived uncertainty (three items) was adapted from Zhang et al. ( 2022 ). Discontinuance intention (four items) was adapted from Chung et al. ( 2023 ) and Maier et al. ( 2015 ). Finally, customer engagement (seven items) was adapted from He et al. ( 2024 ) and Wongkitrungrueng and Assarut ( 2020 ). In summary, all items from the eight constructs were retained in the final questionnaire. Each response was assessed using a 7-point Likert scale ranging from 1 (“strongly disagree”) to 7 (“strongly agree”) (see Appendix A). 3.2. Data collection This study was approved by the University Institutional Review Board (IRB) for Bioethics (Approval Code: 1044396-202505-HR-082-01). Before commencing the survey, respondents were informed of the research objectives, procedures, and their right to withdraw at any time. They were assured that their data would remain anonymous and confidential, after which they provided their informed consent to participate in the study. Data were collected only from those who consented, and all responses were anonymized. The data collection was conducted via the Credamo online research platform ( https://www.credamo.com ). Credamo is an intelligent crowdsourcing survey platform widely used in academic research, similar to Amazon’s Mechanical Turk, and provides access to a broad and demographically diverse respondent pool across China (Tian & Frank, 2024 ). To ensure representativeness, the survey specifically targeted the main user group of short-form video platforms. Prior to the main questionnaire, a screening question was included to identify respondents who had watched unboxing videos within the past six months. Only those who answered affirmatively were allowed to proceed to the formal survey. This ensured that the respondents accurately represented the target population relevant to the research context. A total of 400 qualified Chinese respondents were randomly recruited through Credamo’s automated sampling system, which allocates participants based on region, age, and gender distributions similar to national online user demographics. Each participant received a small monetary reward (USD 0.30) upon completion. After excluding incomplete or invalid responses (e.g., completion time under one minute or identical answers across all items), 387 valid samples were retained for analysis. Overall, the use of a verified national online panel and a screening mechanism targeting actual viewers of unboxing videos ensures that the sample adequately represents the population of short-form video users in China, thereby supporting the generalizability of the study findings. 3.3. Sample characteristics Table 1 outlines the demographic profile of the respondents. A total of 387 participants took part in the study, encompassing a wide range of demographic backgrounds. Of these, 53.2% were female, with a mean age of 29.07 years (SD = 7.48). Table 1 The sample's demographic description (n = 387). Dimensions Items Frequency Percentage Gender Female 206 53.2 Male 181 46.8 Age 18–24 years old 122 31.5 25–35 years old 187 48.3 36–45 years old 68 17.6 46–55 years old 7 1.8 Over 55 years old 3 0.8 Annual Household Income Less than RMB 3,000 66 17.1 RMB 3,001 to RMB 5,000 57 14.7 RMB 5,001 to RMB 8,000 87 22.5 RMB 8,001 to RMB 10,000 87 22.5 Over RMB 10,000 90 23.3 Education Less than high school 5 1.3 High school diploma 62 16 College/University degree 228 58.9 Post graduate degree 92 23.8 Unboxing video viewing frequency 1–3 times/week 167 43.2 4–6 times/week 146 37.7 7–9 times/week 42 10.9 10–12 times/week 14 3.6 More than 12 times/week 18 4.7 ==================== Insert Table 1 about here ==================== 4. Result 4.1. Measurement assessment The measurement structure was examined through confirmatory factor analysis conducted with AMOS 29.0 to ensure construct validity and reliability. Items with factor loadings below 0.50 (EN4, EN5, CE1, DI3) indices were removed (Hu & Bentler, 1991). Thus, the model fix is good: CMIN = 499.856, DF = 377, CMIN/DF = 1.326 0.9, IFI = 0.983 > 0.9, NFI = 0.934 > 0.9, RMSEA = 0.029 < 0.08 (Hoyle, 1995 ). As shown in Table 2 , all retained measurement items exhibited acceptable reliability and validity. The composite reliability (CR) of each construct surpassed 0.70 (0.752 ~ 0.931), while the average variance extracted (AVE) values were above 0.50 (0.508 ~ 0.817), supporting convergent validity. Furthermore, a reliability analysis conducted in SPSS 29.0 indicated high internal consistency, with Cronbach’s alpha values consistently exceeding 0.70. Table 2 Variables, estimate, average variance extracted (AVE), composite reliability (CR), and Cronbach’s alphas. Construct Items Factor Loading AVE CR Cronbach's α Entertainment EN1 0.933 0.817 0.931 0.930 EN2 0.910 EN3 0.868 Boredom/habitual pass time BH1 0.598 0.677 0.859 0.842 BH2 0.903 BH3 0.927 Perceived information overload PIO1 0.765 0.630 0.872 0.871 PIO2 0.769 PIO3 0.847 PIO4 0.790 Short-form video fatigue SVF1 0.842 0.634 0.874 0.873 SVF2 0.797 SVF3 0.790 SVF4 0.752 Perceived psychological risk PPR1 0.589 0.508 0.752 0.741 PPR2 0.841 PPR3 0.685 Perceived uncertainty PU1 0.882 0.760 0.905 0.904 PU2 0.883 PU3 0.850 Customer engagement CE2 0.793 0.602 0.913 0.911 CE3 0.760 CE4 0.635 CE5 0.752 CE6 0.884 CE7 0.792 CE8 0.795 Discontinuance Intention of Short-form Video Use DI1 0.871 0.606 0.821 0.812 DI2 0.742 DI4 0.713 Note: The diagonal values are the square roots of the constructs’ AVE values. The remaining items (see Table 2 ) showed satisfactory construct reliability, with composite reliability values ranging from 0.752 to 0.931 (Peterson & Kim, 2013 ). Convergent validity was supported as all Average Variance Extracted values exceeded 0.50, ranging from 0.508 to 0.817 (Sarstedt et al., 2016 ). Additionally, a reliability analysis in SPSS 29.0 confirmed high internal consistency, with all Cronbach’s alpha values above 0.70. ==================== Insert Table 2 about here ==================== 4.2. Discriminant validity and correlations All constructs demonstrated satisfactory discriminant validity, as the square roots of AVEs exceeded the inter-construct correlations (Fornell & Larcker, 1981 ), providing preliminary support for the proposed hypotheses. ==================== Insert Table 3 about here Table 3 Discriminant validity. Mean SD EN BH PIO SVF PPR PU ITD CE EN 5.041 1.190 0.904 BH 3.910 1.519 0.464 ** 0.823 PIO 2.951 1.208 0.305 ** 0.561 ** 0.794 SVF 2.684 1.186 0.270 ** 0.435 ** 0.562 ** 0.796 PPR 2.309 0.928 0.189 ** 0.324 ** 0.444 ** 0.421 ** 0.713 PU 4.023 1.643 0.280 ** 0.437 ** 0.539 ** 0.378 ** 0.332 ** 0.872 ITD 3.069 1.103 0.267 ** 0.359 ** 0.433 ** 0.471 ** 0.297 ** 0.441 ** 0.778 CE 4.768 1.230 0.443 ** 0.431 ** 0.306 ** 0.307 ** 0.181 ** 0.308 ** 0.365 ** 0.776 Note: The diagonal values are the square roots of the constructs’ AVE values. *** p < 0.001; ** p < 0.01; * p < 0.05. ==================== 4.3. Structural model The SEM model fit is good: CMIN = 250.451, DF = 221; \(\:{x}^{2}\) /df = 1.133 < 3; p 0.9; NFI = 0.955 > 0.9; IFI = 0.994 > 0.9; RMSEA = 0.019 0.05), and thus H1 was not supported. For H2, boredom/habitual pass time had a significant positive effect on perceived information overload (β = 0.374, t = 9.318, p < 0.001), supporting H2. For H3, perceived information overload significantly influenced short-form video fatigue (β = 0.740, t = 11.583, p < 0.001), supporting H3. For H4, perceived information overload also had a significant positive influence perceived psychological risk (β = 0.298, t = 7.756, p < 0.001), supporting H4. In addition, perceived information overload had a strong positive effect on perceived uncertainty (β = 0.845, t = 11.081, p < 0.001), supporting H5. Perceived uncertainty consequently diminished users’ intention to maintain their use of short-form video apps (β = 0.272, t = 5.406, p 0.05), and thus H7 was not supported. Finally, short-form video fatigue exerted a significant positive effect on intention to discontinue the use of short-form video apps (β = 0.422, t = 6.473, p PIO 0.050 0.035 1.433 Not Supported H2 BH ---> PIO 0.374*** 0.040 9.318 Supported H3 PIO ---> SVF 0.740*** 0.064 11.583 Supported H4 PIO ---> PPR 0.298*** 0.038 7.756 Supported H5 PIO ---> PUI 0.845*** 0.076 11.081 Supported H6 PUI ---> DI 0.272*** 0.050 5.406 Supported H7 PPR ---> DI 0.096 0.135 0.711 Not Supported H8 SVF ---> DI 0.422*** 0.065 6.473 Supported Notes: *** p < 0.001; ** p < 0.01; * p < 0.05; B: unstandardized coefficients, S.E.: standard errors. ==================== Insert Table 4 about here ==================== ==================== Insert Fig. 2 about here ==================== 4.4. The moderating effect testing Using AMOS 29.0, we conducted a multi-group analysis (MGA) to examine the moderating effect of customer engagement (high vs. low) on the relationships between entertainment, boredom / habitual pass time, perceived information overload, short-from video fatigue, perceived psychological risk and perceived uncertainty. Participants were divided into two groups based on their customer engagement: low group (n = 177) and high group (n = 210). An independent samples t-test was conducted to assess whether the grouping manipulation successfully distinguished between participants. Results indicated a significant difference in mean scores between the low-level group (M = 3.62, SD = 0.79) and the high-level group (M = 5.74, SD = 0.46), t(385) = − 32.78, p < 0.001, confirming the validity of the classification. Table 5 summarizes the results of the multi-group comparison between participants with low and high levels of customer engagement. First, the effect of entertainment on perceived information overload was not significantly different across groups (Low group: B = 0.032, p = 0.442; High group: B = 0.048, p = 0.354), with a non-significant z-value of 0.238. Second, the path from boredom/habitual pass time to perceived information overload was significantly stronger in the high group (B = 0.440, p < 0.001) than in the low group (B = 0.245, p < 0.001), with a significant z-value of 2.451 ( p < 0.001). Third, the relationship between perceived information overload and short-form video fatigue was also significantly stronger in the high group (B = 0.856, p < 0.001) compared to the low group (B = 0.294, p = 0.007), with a z-value of 4.14 ( p < 0.001). Fourth, the effect of short-form video fatigue on perceived psychological risk was greater under the high group (B = 0.380, p < 0.001) than under the low group (B = 0.122, p = 0.016), with a significant z-value of 3.495 ( p < 0.001). Finally, the effect of perceived information overload on perceived uncertainty was significantly stronger in the high group (B = 0.938, p < 0.001) than in the low group (B = 0.522, p = 0.003), with a z-value of 2.138 ( p PIO 0.032 0.768 0.048 0.927 0.238 H10 BH ---> PIO 0.245*** 4.698 0.440*** 7.291 2.451*** H11 PIO ---> SVF 0.294** 2.698 0.856*** 10.507 4.140*** H12 PIO ---> PPR 0.122* 2.418 0.380*** 7.086 3.495*** H13 PIO ---> PU 0.522** 2.010 0.938*** 0.685 2.138** Notes: *** p < 0.001; ** p < 0.01; * p < 0.05 Taken together, these results suggest that customer engagement type moderates several structural relationships, with consistently stronger effects observed in the high customer engagement group. ==================== Insert Table 5 about here ==================== 5. General discussion This study set out to examine how different viewing motives in the context of unboxing short-form videos influence users’ cognitive and behavioral outcomes. Using structural equation modeling, three key findings emerged. First, the results indicate that when users watch unboxing videos out of boredom or habitual motives, they are more likely to develop repetitive and passive viewing patterns, which increase exposure to redundant content and consume cognitive resources, thereby intensifying perceptions of information overload (Schmitt et al., 2018 ). In contrast, entertainment motivation does not have a significant effect on perceived information overload. This suggests that viewing for entertainment purposes is more restorative than depleting in nature. Users engaging in hedonic use often enter a state of immersion that buffers the sense of informational burden, which aligns with previous findings that hedonic media consumption can help restore cognitive and emotional resources (Bartsch & Hartmann, 2017 ). Second, consistent with Cognitive Overload Theory, this study identifies perceived information overload as a core antecedent of negative user experiences. When the amount of information exceeds individuals’ cognitive capacity, users experience emotional fatigue due to cognitive resource depletion (Sheng et al., 2023 ), and cognitive uncertainty due to judgmental imbalance. These two psychological reactions represent affective and cognitive stress mechanisms that operate through the “emotional exhaustion path” and the “cognitive uncertainty path,” jointly exacerbating short-form video fatigue and strengthening users’ discontinuance intentions. However, psychological risk typically manifests as anticipatory worry rather than directly leading to actual behavioral intention. It is specifically reflected in consumer anticipation - a psychological process in which consumers mentally simulate and evaluate potential material, experiential, social, emotional, or behavioral outcomes before making or engaging in a consumption decision (Vichiengior et al., 2019 ). Therefore, compared with fatigue or uncertainty, its direct effect on discontinuance intention is not significant, though it may influence users’ continued usage intention indirectly or through long-term cumulative effects. Third, the study confirms the moderating role of customer engagement, as proposed by the Elaboration Likelihood Model. Highly engaged customers tend to process content via the central route and thus experience greater strain and fatigue when exposed to repetitive video streams. In contrast, low-engagement customers rely more on peripheral processing and are therefore less susceptible to such negative outcomes. This finding provides nuanced insights into why identical viewing environments may lead to divergent impacts across different customer groups. 5.1. Theoretical contribution This study advances theoretical knowledge and broadens current perspectives on consumer behavior in the field of tourism marketing. First, by integrating Uses and Gratifications Theory with Cognitive Overload Theory, this study reveals the “double-edged sword” effect of user viewing motives. The findings indicate that while users watch short-form videos driven by motives such as boredom/ habitual pass time with the initial purpose of satisfying their needs (Ibáñez-Sánchez et al., 2022 ; Pillai et al., 2025 ), in highly repetitive and homogeneous information environments these motives may instead trigger cognitive strain and negative experiences. This extends prior U&G research, which has largely emphasized positive gratifications, by highlighting its “dark side” perspective and demonstrating that motivation-driven overuse can shift user experiences from satisfaction to fatigue. Second, by introducing the Elaboration Likelihood Model (Cacioppo et al., 1986 ) into the short-form video context, this study highlights the pivotal role of customer engagement in the formation of cognitive overload. Empirical results indicate that highly engaged customers are more likely to process information via the central route, which—under conditions of excessive repetition—renders them more susceptible to overload and fatigue. In contrast, low-engagement customers rely more on peripheral cues, which, to some extent, mitigates overload. Hence, customer engagement serves not only as a predictor of information processing depth but also as a boundary condition for the emergence of cognitive overload. This finding extends the applicability of the ELM beyond attitude change to explaining variations in cognitive strain within digital media environments. Third, this study proposes and validates a comprehensive path model linking viewing motives, cognitive mechanisms, and behavioral outcomes, thereby enriching theoretical explanations of the negative effects of short-form video use. The model demonstrates how viewing motives can lead to perceived information overload, which subsequently induces short-form video fatigue, psychological risk, and uncertainty, ultimately shaping users’ discontinuance intentions. By integrating multiple theoretical perspectives and conducting empirical testing, this study provides a new framework for understanding the shift from motivation-driven engagement to psychological exhaustion, while also offering important implications for future research on overload effects and behavioral consequences in digital media contexts. 5.2. Managerial implications First, the findings offer practical implications for enhancing content recommendation strategies on short-form video platforms. The results indicate that algorithms which repeatedly deliver highly homogeneous unboxing videos may heighten users’ perceived information overload, consequently leading to viewing fatigue and discontinuance intention. Therefore, platforms should strive to balance personalization with content diversity when optimizing their recommendation systems, avoiding excessive reinforcement of a single content type. By incorporating greater novelty and differentiation in content delivery, platforms can better satisfy users’ viewing motives while mitigating the adverse effects of cognitive overload. Second, the results underscore the moderating role of user engagement in the development of cognitive overload, providing practical insights for effective user segmentation and management. While highly engaged users constitute the core audience of platforms, they are also the most vulnerable to information overload. For this group, platforms could implement features such as “usage reminders” or “content pacing controls” to help maintain psychological well-being during prolonged use. Conversely, for low-engagement users, increasing interactivity and entertainment value in the content may help enhance their stickiness and sustained engagement. Third, the study underscores the need to balance motivational gratifications and psychological burdens in optimizing user experience. Although entertainment and habitual motives drive short-term engagement, prolonged reliance on these motives may trigger negative emotions and user attrition risks. Therefore, platforms should focus on fostering “positive experience extension” in content ecosystem design, such as offering diverse usage scenarios, healthier usage rhythms, and more valuable informational elements, to ensure that user needs are fulfilled without leading to fatigue or resistance caused by overuse. 5.3 Limitation and future research Although this study yields meaningful insights, certain limitations remain and open new directions for future research. First, the reliance on a cross-sectional survey design limits the ability to observe changes in users’ psychological states over time. Employing longitudinal or experimental approaches in future work could enable a more robust examination of causal linkages among viewing motives, perceived information overload, and usage fatigue. Second, the present study included a relatively narrow set of variables; for instance, platform-related characteristics (e.g., algorithmic transparency, interactivity) and individual attributes (e.g., self-regulation, personality traits) were not explored. Future research that integrates these factors could offer a more comprehensive understanding of the adverse psychological consequences of short-form video consumption. Declarations Ethical approval Ethical approval for this study was granted by the Institutional Review Board (IRB) of Gachon University, Republic of Korea, on July 11, 2025 (Approval No.: 1044396-202505-HR-082-01). Informed consent This study involved a non-interventional social science survey and did not include any medical procedures, collection of biological samples, or personally identifiable sensitive information. Prior to participation, all respondents were provided with an online informed consent form explaining the purpose of the study, the voluntary nature of participation, confidentiality assurances, and their right to withdraw at any time without penalty. Informed consent was obtained electronically on August 20, 2025, and data collection was conducted between August 25 and September 8, 2025. Only participants who provided explicit consent were allowed to proceed with the survey. Consent for publication Not applicable. Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding This research received no external funding. Author Contribution Qian Zhang: Writing – original draft, Writing – review & editing, Methodology, Investigation, Data analysis, Formal analysis and Visualization. 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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-8067328","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":596702815,"identity":"36ddd0d5-8ff9-43cd-9bad-0fbd08aa417b","order_by":0,"name":"Qian Zhang","email":"","orcid":"","institution":"Gachon University","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Zhang","suffix":""},{"id":596702819,"identity":"e02bc8c5-c326-41ea-b007-a18d725dd97d","order_by":1,"name":"Zhaoqi Li","email":"","orcid":"","institution":"Gachon University","correspondingAuthor":false,"prefix":"","firstName":"Zhaoqi","middleName":"","lastName":"Li","suffix":""},{"id":596702820,"identity":"cdb5fafd-0b35-4b10-bbb0-d3d66a0ffae5","order_by":2,"name":"Jiangmin Ding","email":"","orcid":"","institution":"Pusan National University","correspondingAuthor":false,"prefix":"","firstName":"Jiangmin","middleName":"","lastName":"Ding","suffix":""},{"id":596702821,"identity":"3659a6d9-9a7e-455c-b522-dc19285ab3f2","order_by":3,"name":"Hong Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIie3OMQrCMBSA4SeBukSyRgL1CimFLopexVKoS8GOHYWCjq4FjyE4K4G4BFwLdhN6BCcHU0XHWDfB/EMSHvlIAGy2X4wCoGYn4OiVP2aoHekvviZ877xnZkI2ubykWTXenmTM0lQAWe2Rn5keqeTML1Qd7cpYsoILoGqKQmUgnCYB6y1FFJTdJcM8BigBHRZGMr8+iL8+PsngM0mchow56I9hPgKuSWgitIwDhpWY6kM01AR7Ksw9EyFFVDOciQlZS++Mb9R1j0L0TeTV+ysYoNMGAExa3bLZbLb/7A4hiEQcSnFQEAAAAABJRU5ErkJggg==","orcid":"","institution":"Seokyeong University","correspondingAuthor":true,"prefix":"","firstName":"Hong","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2025-11-09 06:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8067328/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8067328/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103417710,"identity":"999e02da-4f9d-44b2-89ad-a64beff16420","added_by":"auto","created_at":"2026-02-25 12:33:03","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":45219,"visible":true,"origin":"","legend":"\u003cp\u003eThe conceptual model of the study.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8067328/v1/32bc74af43c9aaeb51721153.jpeg"},{"id":103417711,"identity":"1960b86a-e719-4f36-9f21-a74cb32bac5a","added_by":"auto","created_at":"2026-02-25 12:33:03","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":368562,"visible":true,"origin":"","legend":"\u003cp\u003eThe SEM result of the conceptual model.\u003c/p\u003e\n\u003cp\u003eNotes: ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001; **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05;\u003cstrong\u003e⟶\u003c/strong\u003e : significant path;\u003cstrong\u003e⟶\u003c/strong\u003e: insignificant path.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8067328/v1/84c1ebfca7e1a89c675ce964.jpeg"},{"id":103507761,"identity":"ea12f435-9efb-49d4-9937-eb77a8b36b63","added_by":"auto","created_at":"2026-02-26 13:44:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1808618,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8067328/v1/db542a6e-ffda-4a65-885f-a0155634f049.pdf"},{"id":103417712,"identity":"81e8040c-06d3-4057-a8c1-f65acc7d1fd4","added_by":"auto","created_at":"2026-02-25 12:33:03","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":30840,"visible":true,"origin":"","legend":"","description":"","filename":"Questionnaire.docx","url":"https://assets-eu.researchsquare.com/files/rs-8067328/v1/53ff6653b15604612a0503a0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unboxing the Paradox: Understanding How Viewing Motivations Drive User Fatigue and Attrition on Short-Form Video Platforms","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAradius Media Network\u0026rsquo;s 2006 release was a 90-second clip that captures the process of unboxing the Nokia E61. This video is widely regarded as the starting point of the global \u0026ldquo;unboxing video\u0026rdquo; phenomenon (Mowlabocus, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). By November 2016, searches for \u0026ldquo;unboxing video\u0026rdquo; had generated more than 57\u0026nbsp;million results, highlighting the rapid expansion and influence of this format (Mowlabocus, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Agrawal \u0026amp; Mittal, 2022). In parallel, the evolution of social media platforms has accelerated this trend. Among them, TikTok has emerged as a leading force, reshaping how users create and consume short-form content. Centered on quick, visually engaging videos, TikTok has gained immense global traction and, since 2018, consistently ranked among the most downloaded apps worldwide, with over 1.5\u0026nbsp;billion monthly active users by 2023 (Yang et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Against this backdrop, unboxing videos have evolved from simple product demonstrations into a form of social entertainment that spans multiple categories, including gaming, beauty, and digital products (Mowlabocus, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; ). Beyond satisfying users\u0026rsquo; curiosity and sense of participation, Brands increasingly leverage unboxing videos as a strategic means to strengthen customer involvement and promote their products (\u0026Ouml;zer \u0026amp; Uğurhan, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNevertheless, what exactly accounts for the appeal of unboxing videos? The unboxing process is not merely a practical act of acquiring goods, but rather a \u0026ldquo;consumption ritual\u0026rdquo; filled with anticipation and gratification (Vaudrey, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This immediate and tangible experience not only encourages consumers to enjoy unboxing products themselves but also motivates them to watch others\u0026rsquo; unboxing performances on platforms such as YouTube, deriving emotional pleasure and a sense of identification in the process (Kim et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Vaudrey, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In recent years, unboxing videos have gradually evolved into an important marketing tool within social media, serving not only to showcase product attributes but also to shape consumer interest and purchase decisions (Kim, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Moreover, the popularity of blind-box products such as Pop Mart further demonstrates the powerful allure of \u0026ldquo;revealing the unknown\u0026rdquo; to consumers (Zhang et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Whether it involves physically unsealing blind boxes or virtually watching unboxing content on short video platforms, consumers consistently display enduring and widespread enthusiasm for the moment of \u0026ldquo;opening,\u0026rdquo; which delivers both surprise and emotional satisfaction (Van Droogenbroeck \u0026amp; Willems, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eYet, with the exponential growth and accelerating pace of unboxing content, users are increasingly confronted with information redundancy and psychological strain. When such content no longer provides a sense of novelty or fails to align with users\u0026rsquo; viewing motivations, experiences of information overload and usage fatigue are likely to arise. Against this backdrop, the present study investigates how different viewing motivations shape users\u0026rsquo; perceptions of unboxing videos and their subsequent psychological reactions, thereby clarifying the underlying processes through which these motivations give rise to short-form video fatigue and users\u0026rsquo; intentions to disengage from such platforms.\u003c/p\u003e \u003cp\u003ePrior research has predominantly focused on examining the influence of unboxing video content on consumers\u0026rsquo; purchase behaviors and decision-making processes. For instance, Kim (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) found that the source characteristics of unboxing videos, together with purposeful and non-purposeful motivations, shape consumers\u0026rsquo; purchase intentions through parasocial interaction. Similarly, Chen and Jiang (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) showed that information seeking, entertainment, interpersonal utility, and pastime act as antecedents of perceived coolness, which positively affects customers\u0026rsquo; psychological well-being and mediates the effects of these antecedents. In addition, \u0026Ouml;zer and Uğurhan (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) demonstrated that consumers driven by information-seeking, entertainment, and interpersonal motives are more likely to exhibit stronger purchase and eWOM intentions, while pass-time motives show no significant influence. Extending this line of inquiry, Evans et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) found that the inclusion of sponsor bumpers in children\u0026rsquo;s unboxing videos can enhance parents\u0026rsquo; perceptions of sponsorship transparency. This increased sense of transparency subsequently influences their attitudes and evaluations indirectly, and the strength of this indirect effect depends on the degree of parental mediation. Taken together, these studies suggest that unboxing videos function not only as an important channel for product information but also as a medium that shapes purchase decisions through diverse psychological and sensory mechanisms.\u003c/p\u003e \u003cp\u003eWhile prior research has primarily examined how unboxing videos stimulate consumers\u0026rsquo; purchase intentions and behaviors, less attention has been paid to their potential negative psychological consequences. On short video platforms, the dense stream of content and algorithmically generated repetition can increase users\u0026rsquo; cognitive load and emotional exhaustion. When content becomes repetitive or fails to meet expectations, viewing motivations may remain unsatisfied and even result in negative experiences. In such contexts, unboxing videos may shift from being a source of enjoyment to a source of psychological strain, influencing users\u0026rsquo; attitudes toward platforms and their discontinuance intentions. However, research has yet to systematically explore how viewing motivations, through information perception mechanisms, shape usage fatigue and behavioral outcomes.\u003c/p\u003e \u003cp\u003eBuilding on this reasoning, we propose the following research questions:\u003c/p\u003e \u003cp\u003eRQ1: Do different viewing motivations (e.g., entertainment and boredom/habitual passing time) lead to varying levels of perceived information overload?\u003c/p\u003e \u003cp\u003eRQ2: Does perceived information overload indirectly influence users\u0026rsquo; discontinuance intentions by triggering short video fatigue, psychological risks, and feelings of uncertainty?\u003c/p\u003e \u003cp\u003eRQ3: Does customer engagement (high vs. low) moderate the relationship between viewing motivations and perceived overload of information?\u003c/p\u003e \u003cp\u003eTo explore the proposed research questions, this research focused on the primary user group of short-form video platforms and adopted unboxing videos as the research context. Drawing on Uses and Gratifications Theory, it examined how viewing motivations (entertainment and boredom/habitual motivations) influence perceived information overload, which subsequently affects user fatigue and discontinuance intentions. In addition, based on Cognitive Overload Theory, the study explored how excessive information processing contributes to users\u0026rsquo; psychological strain. Furthermore, integrating the Elaboration Likelihood Model, this study developed a multi-level psychological mechanism framework to explain how user engagement moderates the information processing pathway from viewing motivation to behavioral outcomes.\u003c/p\u003e \u003cp\u003eThis study enhances understanding of how short-form video use can lead from user fascination to mental fatigue, offering a refined view of its underlying psychological mechanisms. Building on these insights, the findings offer practical implications for short video platforms, particularly in optimizing content recommendation rhythms, reducing information redundancy, and enhancing user experience design.\u003c/p\u003e"},{"header":"2. Research background","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Uses and gratifications theory\u003c/h2\u003e \u003cp\u003eOriginating from efforts to understand audience behavior, the uses and gratifications perspective seeks to explain why people select and consume specific media types\u0026mdash;such as radio broadcasts or television programs\u0026mdash;to fulfill particular needs (Ib\u0026aacute;\u0026ntilde;ez-S\u0026aacute;nchez et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ruggiero, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). The accelerating growth of the Internet and social media has led scholars to employ the U\u0026amp;G perspective to better understand the psychological and behavioral mechanisms driving online consumer engagement (Ib\u0026aacute;\u0026ntilde;ez-S\u0026aacute;nchez et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Nguyen \u0026amp; Nguyen, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Pillai et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Yu, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to the U\u0026amp;G, media audiences actively seek out channels that align with their personal motives and desires, engaging with media content purposefully instead of consuming it passively (Pillai et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These underlying motivations can include information seeking, experiencing enjoyment, social interaction, escapism or simply passing time.\u003c/p\u003e \u003cp\u003eUsers on short-video platforms often watch videos for enjoyment, stress relief when they feel bored (Croes \u0026amp; Bartels, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which leads them to repeatedly encounter large amounts of homogeneous content. However, such repetitive and excessive exposure does not always yield positive experiences. On the one hand, when users\u0026rsquo; needs are not genuinely fulfilled (e.g., seeking novelty but receiving repetitive content), they may experience disappointment and dissatisfaction. On the other hand, motivations can also drive overuse, resulting in a paradoxical effect in which gratification produces unintended negative consequences (Park \u0026amp; Jung, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Rather than fostering relaxation or enjoyment, over-gratification may trigger perceived information overload, reduced attention, psychological fatigue, and uncertainty. Thus, U\u0026amp;G provides a critical lens for this study, as it explains both why users continuously engage with short video content (motivation-driven behavior) and how such engagement - when combined with mechanisms emphasized in cognitive overload theory - can ultimately lead to short video fatigue and discontinuance intention.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Cognitive overload theory\u003c/h2\u003e \u003cp\u003eGross originally introduced the term information overload to describe a situation where the amount of information available within a limited period overwhelms an individual\u0026rsquo;s cognitive capacity to manage or make sense of it (Zhang et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The accelerating growth of social media platforms has made information overload a prevalent aspect of modern digital life (Cao \u0026amp; Sun, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). When users are exposed to large volumes of homogeneous, rapidly updated, structurally complex, or ambiguous information during browsing, they are likely to experience cognitive strain (Cao et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This process is not only influenced by the external density of information but is also closely related to users\u0026rsquo; knowledge background, experience, and cognitive resources.\u003c/p\u003e \u003cp\u003ePrior research has demonstrated that experiencing information overload can lead to several detrimental emotional and cognitive consequences, such as feelings of distraction, heightened anxiety, mental fatigue, and the fear of missing out (Cao \u0026amp; Sun, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Farooq et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and may further undermine trust in online environments (Fan et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although some studies suggest that a moderate level of information intensity can enhance content attractiveness and platform stickiness, excessive overload beyond users\u0026rsquo; cognitive threshold often leads to fatigue and resistance to continued use (Wang \u0026amp; Chi, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccordingly, this research investigates the experience of perceived content pressure within the setting of unboxing short videos. It particularly examines whether individuals who frequently watch such short-form videos\u0026mdash;whether for amusement or simply to fill idle time\u0026mdash;tend to experience psychological fatigue driven by information overload, which in turn heightens their intention to withdraw from or reduce engagement with these platforms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Elaboration likelihood model\u003c/h2\u003e \u003cp\u003eThe Elaboration Likelihood Model is a dual-process framework for explaining information processing and attitude change (Cacioppo et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The model posits that people engage with information through one of two routes\u0026mdash;central or peripheral\u0026mdash;based on their degree of motivation and their capacity to process the message. In the central route, individuals engage in thoughtful evaluation of message arguments that require considerable mental effort. In contrast, the peripheral route relies on surface-level signals like source credibility, the number of endorsements, or social validation (Shi et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn social media contexts, users\u0026rsquo; engagement intensity significantly influences their mode of information processing, guiding whether messages are assessed through central or peripheral routes. Highly engaged users are more likely to be motivated to engage in deep processing via the central route, devoting greater attention and cognitive resources (Park et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, this heightened engagement may also increase their susceptibility to perceived information overload during prolonged use of short video platforms. By contrast, low-engagement users often rely on peripheral cues and thus experience lower levels of cognitive burden (Park et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Therefore, user engagement moderates the relationship between viewing motives and perceived information overload, such that highly engaged users are more prone to enter states of high cognitive load when motivated.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Literature review and hypothesis development","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Effect of viewing motivations (entertainment and boredom) on perceived information overload\u003c/h2\u003e \u003cp\u003eAccording to Uses and Gratifications Theory, individuals are not passive recipients of media but actively engage with it to satisfy various personal needs - such as seeking entertainment, maintaining social connections, or alleviating boredom (Ib\u0026aacute;\u0026ntilde;ez-S\u0026aacute;nchez et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Pillai et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In short-form video contexts, entertainment motivation often reflects users\u0026rsquo; desire for enjoyment, relaxation, and hedonic gratification (Zeng et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In contrast, boredom or habitual motives are primarily driven by the avoidance of idleness or the maintenance of routine behaviors (Croes \u0026amp; Bartels, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough, entertainment and boredom motives initially stimulate short-form video use, they can also lead to unintended cognitive consequences. According to research on information overload, frequent encounters with monotonous and swiftly refreshed content can overload users\u0026rsquo; cognitive systems, causing attentional lapses, tiredness, and a pronounced sense of mental strain (Cao \u0026amp; Sun, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Farooq et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Users driven by boredom or habitual motives are particularly prone to repetitive and prolonged viewing, which heightens their vulnerability to information overload.\u003c/p\u003e \u003cp\u003ePrior research has further shown that excessive exposure to information can lead to various adverse psychological reactions, including distraction, anxiety, fatigue, and even a fear of missing out (Cao \u0026amp; Sun, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Farooq et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and can undermine trust in online environments (Fan et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). While moderate levels of information intensity may enhance content attractiveness and platform stickiness, overload beyond users\u0026rsquo; cognitive threshold typically results in fatigue and resistance to continued use (Fu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wang \u0026amp; Chi, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Building on uses and gratifications and cognitive overload theory, this study argues that user motivations represent a critical antecedent of perceived information overload.\u003c/p\u003e \u003cp\u003eTherefore, we develop our hypothesis as follows:\u003c/p\u003e \u003cp\u003e \u003cem\u003eH1: Entertainment motivation positively influences perceived information overload.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eH2: Boredom/habitual motivation positively influences perceived information overload.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Effect of perceived information overload on user negative responses\u003c/h2\u003e \u003cp\u003eWhen people are exposed to more information than their minds can effectively process and understand, information overload emerges, causing cognitive fatigue and hindering sound decision-making (Zhang et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Previous research indicates that cognitive overload can significantly reduce individuals\u0026rsquo; capacity to sustain attention, depletes cognitive resources, and produces negative psychological reactions such as anxiety and emotional exhaustion (Farooq et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Prior studies have highlighted that in digital media environments, excessive exposure to information can trigger fatigue (Fu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), undermine users\u0026rsquo; trust (Furner \u0026amp; Zinko, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and lower subjective well-being (Chai et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the short-form video environment, where users are frequently exposed to highly repetitive, homogeneous, and rapidly updated content, perceived overload is particularly salient. Such overload not only heightens psychological strain but also triggers a range of negative user responses. Specifically, information overload can manifest as short-form video fatigue, reflecting users\u0026rsquo; exhaustion from constant exposure to dense content streams (Chung et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Huang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It can also increase perceived psychological risk, as users become more uncertain about the reliability or consequences of prolonged usage (Soto-Acosta et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Prior research indicate that uncertainty can amplify users\u0026rsquo; perception of information overload during information processing (Zhang et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Building on this, we argue that information overload, in turn, contributes to heightened perceived uncertainty by making it difficult for users to judge the value and credibility of rapidly flowing content. Drawing on cognitive overload theory, this study argues that perceived information overload represents a central mechanism through which users develop negative psychological and behavioral reactions.\u003c/p\u003e \u003cp\u003eThus, we develop our hypothesis as follows:\u003c/p\u003e \u003cp\u003e \u003cem\u003eH3: Perceived information overload positively influences short-form video fatigue.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eH4: Perceived information overload positively influences perceived psychological risk.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eH5: Perceived information overload positively influences perceived uncertainty.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Effect of user negative responses on discontinuance intention of short-form video use\u003c/h2\u003e \u003cp\u003eWhen users experience negative psychological responses during media consumption, they are more likely to disengage from the platform or discontinue its use. Prior research has shown that media fatigue leads to lower continued usage (Huang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), discontinuance intention (Chung et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and users' disengagement (Fernandes \u0026amp; Oliveira, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Similarly, perceived psychological risk has been shown to undermine consumer trust in a product, which in turn decreases their behavior intention (Pappas, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Moreover, perceived uncertainty, characterized by doubts about the reliability, usefulness, or credibility of media content (Shin et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), discourages users from prolonged usage, as uncertainty is often linked to avoidance behavior and disengagement, which occurs because consumers inherently exhibit uncertainty avoidance (Reimann et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the setting of short-form video engagement, these negative responses\u0026mdash;fatigue, psychological risk, and uncertainty\u0026mdash;represent critical mechanisms driving discontinuance intention. Frequent exposure to information overload can generate adverse psychological experiences, prompting users to reduce or cease short-form video consumption in an effort to reestablish mental balance and emotional stability.\u003c/p\u003e \u003cp\u003eTherefore, we propose the following hypothesis:\u003c/p\u003e \u003cp\u003e \u003cem\u003eH6: Short-form video fatigue positively influences discontinuance intention of short-form video use.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eH7: Perceived psychological risk positively influences discontinuance intention of short-form video use.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eH8: Perceived uncertainty positively influences discontinuance intention of short-form video use.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4. The moderating effects of customer engagement\u003c/h2\u003e \u003cp\u003eAs interactive media continue to evolve, the notion of customer engagement has increasingly taken center stage in academic research and industry practice (Oh et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Specifically, customer engagement reflects the degree of users\u0026rsquo; cognitive, emotional, and behavioral involvement with media content (Abbasi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). According to ELM (Cacioppo et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1986\u003c/span\u003e), individuals with a high level of involvement tend to process persuasive information through a central route\u0026mdash;carefully evaluating arguments and devoting substantial cognitive resources to message scrutiny. In contrast, those with lower engagement are inclined to rely on the peripheral route, forming judgments based on surface cues such as social endorsement, attractiveness, or perceived popularity rather than message substance. This distinction implies that customer engagement may moderate the strength of relationships between viewing motives, perceived information overload, and downstream negative responses.\u003c/p\u003e \u003cp\u003eViewers often watch user-generated videos not only for entertainment but also to enjoy co-viewing experiences and to share the content within their social circles (Kim, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). As De Veirman et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) suggest that the entertainment aspect of advertising plays a pivotal role in shaping brand perception, with entertaining messages eliciting more favorable evaluations. Although both high- and low-engagement viewers can derive entertainment from short, episodic consumption, highly engaged viewers tend to engage in more sustained and repetitive viewing behaviors, thereby amplifying potential cognitive load. Previous research also indicates that while entertainment-oriented consumption creates a relaxed and enjoyable state, it is typically marked by positive emotions and a moderate level of arousal (Bartsch \u0026amp; Hartmann, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), it may also increase the likelihood of attentional fatigue when pursued intensively. Therefore, we propose:\u003c/p\u003e \u003cp\u003e \u003cem\u003eH9: The effect of entertainment motivation on perceived information overload is stronger under high engagement than under low engagement.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eBoredom and habitual media use\u0026mdash;often linked to stress relief\u0026mdash;represent important motivations behind entertainment consumption. Prior studies indicate that individuals turn to online media to counter boredom (Papacharissi \u0026amp; Rubin, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) and engage with television as a means of psychological escape (Kim, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Extending this logic, user-generated videos such as unboxing content can serve similar purposes, offering viewers a casual, time-filling activity that provides relaxation and temporary distraction from daily routines.\u003c/p\u003e \u003cp\u003eBoredom and habitual pass time motives often drive repetitive and prolonged exposure, leading users to scroll automatically without purposeful selection (Arness \u0026amp; Ollis, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Under high engagement, these motives are enacted more intensively, resulting in longer sessions and greater exposure to redundant content, which exacerbates information overload. Conversely, low-engagement customers may disengage earlier, weakening this relationship. Thus, we propose:\u003c/p\u003e \u003cp\u003e \u003cem\u003eH10: The effect of boredom/habitual motivation on perceived information overload is stronger under high engagement than under low engagement.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eWhen people are exposed to too much information, their limited cognitive resources are drained, weakening attentional control and giving rise to fatigue and burnout (Zhang et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Highly engaged users, who devote more effort to processing and hold higher expectations for content quality, are more sensitive to overload conditions. Research on social media indicates that engaged users report greater fatigue when exposed to excessive information (Farooq et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Thus, we propose:\u003c/p\u003e \u003cp\u003e \u003cem\u003eH11: The effect of perceived information overload on short-form video fatigue is stronger under high engagement than under low engagement.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eFatigue reflects a loss of control and mounting costs, such as wasted time, negative emotions, or concerns about harmful consequences (Zhang et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In addition, Chung et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) examined customers\u0026rsquo; excessive engagement with social media and found that information overload contributes to greater life dissatisfaction, manifested in outcomes such as distress, negative emotions from social comparison, and reduced well-being.\u003c/p\u003e \u003cp\u003eFor higher customer engagement, fatigue represents a more salient violation of usage goals, intensifying concerns about risks associated with continued platform use (Cao \u0026amp; Sun, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Farooq et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Thus, customer engagement heightens the extent to which perceived information overload translates into perceived psychological risk. Thus:\u003c/p\u003e \u003cp\u003e \u003cem\u003eH12: The effect of perceived information overload on perceived psychological risk is stronger under high engagement than under low engagement.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eInformation overload hampers users\u0026rsquo; ability to evaluate the credibility and value of content, creating doubts and confusion (Zhong et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In fast-paced content streams, highly engaged users\u0026mdash;despite their deeper involvement\u0026mdash;face stronger expectation\u0026ndash;reality discrepancies, as redundant or conflicting content undermines their confidence in information reliability. Prior studies confirm that overload fosters uncertainty and avoidance behaviors (Reimann et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eH13: The effect of perceived information overload on perceived uncertainty is stronger under high engagement than under low engagement.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the conceptual framework that depicts the hypothesized relationships among the study variables.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eInsert\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eabout here\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Method","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Measurement development\u003c/h2\u003e \u003cp\u003eAll measurement items were adapted from prior validated scales and refined to align with the specific context of this study. Specifically, entertainment motivation (four items) was adapted from Hur et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), Lee and Ma (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and Park et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), while boredom/habitual pass time motivation (three items) was adapted from Croes and Bartels (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Perceived information overload (four items) was adopted from Chung et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and Misra and Stokols (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Short-form video fatigue (four items) was adopted from Bright et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and Chung et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Perceived psychological risk (three items) was measured from Mvondo et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Perceived uncertainty (three items) was adapted from Zhang et al. (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Discontinuance intention (four items) was adapted from Chung et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and Maier et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Finally, customer engagement (seven items) was adapted from He et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and Wongkitrungrueng and Assarut (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn summary, all items from the eight constructs were retained in the final questionnaire. Each response was assessed using a 7-point Likert scale ranging from 1 (\u0026ldquo;strongly disagree\u0026rdquo;) to 7 (\u0026ldquo;strongly agree\u0026rdquo;) (see Appendix A).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Data collection\u003c/h2\u003e \u003cp\u003e This study was approved by the University Institutional Review Board (IRB) for Bioethics (Approval Code: 1044396-202505-HR-082-01). Before commencing the survey, respondents were informed of the research objectives, procedures, and their right to withdraw at any time. They were assured that their data would remain anonymous and confidential, after which they provided their informed consent to participate in the study. Data were collected only from those who consented, and all responses were anonymized.\u003c/p\u003e \u003cp\u003eThe data collection was conducted via the Credamo online research platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.credamo.com\u003c/span\u003e\u003cspan address=\"https://www.credamo.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Credamo is an intelligent crowdsourcing survey platform widely used in academic research, similar to Amazon\u0026rsquo;s Mechanical Turk, and provides access to a broad and demographically diverse respondent pool across China (Tian \u0026amp; Frank, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo ensure representativeness, the survey specifically targeted the main user group of short-form video platforms. Prior to the main questionnaire, a screening question was included to identify respondents who had watched unboxing videos within the past six months. Only those who answered affirmatively were allowed to proceed to the formal survey. This ensured that the respondents accurately represented the target population relevant to the research context.\u003c/p\u003e \u003cp\u003eA total of 400 qualified Chinese respondents were randomly recruited through Credamo\u0026rsquo;s automated sampling system, which allocates participants based on region, age, and gender distributions similar to national online user demographics. Each participant received a small monetary reward (USD 0.30) upon completion. After excluding incomplete or invalid responses (e.g., completion time under one minute or identical answers across all items), 387 valid samples were retained for analysis.\u003c/p\u003e \u003cp\u003eOverall, the use of a verified national online panel and a screening mechanism targeting actual viewers of unboxing videos ensures that the sample adequately represents the population of short-form video users in China, thereby supporting the generalizability of the study findings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Sample characteristics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e outlines the demographic profile of the respondents. A total of 387 participants took part in the study, encompassing a wide range of demographic backgrounds. Of these, 53.2% were female, with a mean age of 29.07 years (SD\u0026thinsp;=\u0026thinsp;7.48).\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\u003eThe sample's demographic description (n\u0026thinsp;=\u0026thinsp;387).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDimensions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;24 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u0026ndash;35 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u0026ndash;45 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46\u0026ndash;55 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOver 55 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAnnual Household Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than RMB 3,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRMB 3,001 to RMB 5,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRMB 5,001 to RMB 8,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRMB 8,001 to RMB 10,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOver RMB 10,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh school diploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCollege/University degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost graduate degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eUnboxing video viewing frequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;3 times/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u0026ndash;6 times/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;9 times/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u0026ndash;12 times/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMore than 12 times/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eInsert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eabout here\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Result","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Measurement assessment\u003c/h2\u003e \u003cp\u003eThe measurement structure was examined through confirmatory factor analysis conducted with AMOS 29.0 to ensure construct validity and reliability. Items with factor loadings below 0.50 (EN4, EN5, CE1, DI3) indices were removed (Hu \u0026amp; Bentler, 1991). Thus, the model fix is good: CMIN\u0026thinsp;=\u0026thinsp;499.856, DF\u0026thinsp;=\u0026thinsp;377, CMIN/DF\u0026thinsp;=\u0026thinsp;1.326\u0026thinsp;\u0026lt;\u0026thinsp;3, CFI\u0026thinsp;=\u0026thinsp;0.983\u0026thinsp;\u0026gt;\u0026thinsp;0.9, IFI\u0026thinsp;=\u0026thinsp;0.983\u0026thinsp;\u0026gt;\u0026thinsp;0.9, NFI\u0026thinsp;=\u0026thinsp;0.934\u0026thinsp;\u0026gt;\u0026thinsp;0.9, RMSEA\u0026thinsp;=\u0026thinsp;0.029\u0026thinsp;\u0026lt;\u0026thinsp;0.08 (Hoyle, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1995\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, all retained measurement items exhibited acceptable reliability and validity. The composite reliability (CR) of each construct surpassed 0.70 (0.752\u0026thinsp;~\u0026thinsp;0.931), while the average variance extracted (AVE) values were above 0.50 (0.508\u0026thinsp;~\u0026thinsp;0.817), supporting convergent validity. Furthermore, a reliability analysis conducted in SPSS 29.0 indicated high internal consistency, with Cronbach\u0026rsquo;s alpha values consistently exceeding 0.70.\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\u003eVariables, estimate, average variance extracted (AVE), composite reliability (CR), and Cronbach\u0026rsquo;s alphas.\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eConstruct Items\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFactor Loading\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAVE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCronbach's α\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEntertainment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEN2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEN3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBoredom/habitual\u003c/p\u003e \u003cp\u003epass time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBH1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.842\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBH2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.903\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBH3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ePerceived information overload\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePIO1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.871\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePIO2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.769\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePIO3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.847\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePIO4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.790\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eShort-form video fatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSVF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.873\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSVF2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSVF3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.790\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSVF4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePerceived psychological risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePPR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.741\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePPR2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.841\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePPR3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePerceived uncertainty\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePU1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePU2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePU3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.850\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eCustomer engagement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCE2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCE3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.760\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCE4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCE5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCE6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.884\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCE7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.792\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCE8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.795\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDiscontinuance Intention of Short-form Video Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDI1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDI2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDI4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.713\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: The diagonal values are the square roots of the constructs\u0026rsquo; AVE values.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe remaining items (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) showed satisfactory construct reliability, with composite reliability values ranging from 0.752 to 0.931 (Peterson \u0026amp; Kim, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Convergent validity was supported as all Average Variance Extracted values exceeded 0.50, ranging from 0.508 to 0.817 (Sarstedt et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Additionally, a reliability analysis in SPSS 29.0 confirmed high internal consistency, with all Cronbach\u0026rsquo;s alpha values above 0.70.\u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eInsert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003eabout here\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Discriminant validity and correlations\u003c/h2\u003e \u003cp\u003eAll constructs demonstrated satisfactory discriminant validity, as the square roots of AVEs exceeded the inter-construct correlations (Fornell \u0026amp; Larcker, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1981\u003c/span\u003e), providing preliminary support for the proposed hypotheses.\u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eInsert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003eabout here\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiscriminant validity.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePIO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSVF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePPR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePU\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eITD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eCE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.904\u003c/b\u003e\u003c/p\u003e \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 \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.464\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.823\u003c/b\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.305\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.561\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.794\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSVF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.270\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.435\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.562\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.796\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.189\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.324\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.444\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.421\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.713\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.280\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.437\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.539\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.378\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.332\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.872\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eITD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.267\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.359\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.433\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.471\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.297\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.441\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.778\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.443\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.431\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.306\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.307\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.181\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.308\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.365\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.776\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote: The diagonal values are the square roots of the constructs\u0026rsquo; AVE values.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Structural model\u003c/h2\u003e \u003cp\u003eThe SEM model fit is good: CMIN\u0026thinsp;=\u0026thinsp;250.451, DF\u0026thinsp;=\u0026thinsp;221; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{x}^{2}\\)\u003c/span\u003e\u003c/span\u003e/df\u0026thinsp;=\u0026thinsp;1.133\u0026thinsp;\u0026lt;\u0026thinsp;3; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; CFI\u0026thinsp;=\u0026thinsp;0.994\u0026thinsp;\u0026gt;\u0026thinsp;0.9; NFI\u0026thinsp;=\u0026thinsp;0.955\u0026thinsp;\u0026gt;\u0026thinsp;0.9; IFI\u0026thinsp;=\u0026thinsp;0.994\u0026thinsp;\u0026gt;\u0026thinsp;0.9; RMSEA\u0026thinsp;=\u0026thinsp;0.019\u0026thinsp;\u0026lt;\u0026thinsp;0.08 (Hoyle, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1995\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;4 shows the structural model testing results. For H1, the effect of entertainment on perceived information overload was not significant (β\u0026thinsp;=\u0026thinsp;0.050, t\u0026thinsp;=\u0026thinsp;1.433, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), and thus H1 was not supported. For H2, boredom/habitual pass time had a significant positive effect on perceived information overload (β\u0026thinsp;=\u0026thinsp;0.374, t\u0026thinsp;=\u0026thinsp;9.318, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), supporting H2. For H3, perceived information overload significantly influenced short-form video fatigue (β\u0026thinsp;=\u0026thinsp;0.740, t\u0026thinsp;=\u0026thinsp;11.583, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), supporting H3. For H4, perceived information overload also had a significant positive influence perceived psychological risk (β\u0026thinsp;=\u0026thinsp;0.298, t\u0026thinsp;=\u0026thinsp;7.756, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), supporting H4. In addition, perceived information overload had a strong positive effect on perceived uncertainty (β\u0026thinsp;=\u0026thinsp;0.845, t\u0026thinsp;=\u0026thinsp;11.081, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), supporting H5. Perceived uncertainty consequently diminished users\u0026rsquo; intention to maintain their use of short-form video apps (β\u0026thinsp;=\u0026thinsp;0.272, t\u0026thinsp;=\u0026thinsp;5.406, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), supporting H6. However, the perceived psychological risk did not exert a significant influence on users\u0026rsquo; intention to discontinue using short-form video apps (β\u0026thinsp;=\u0026thinsp;0.096, t\u0026thinsp;=\u0026thinsp;0.711, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), and thus H7 was not supported. Finally, short-form video fatigue exerted a significant positive effect on intention to discontinue the use of short-form video apps (β\u0026thinsp;=\u0026thinsp;0.422, t\u0026thinsp;=\u0026thinsp;6.473, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), supporting H8.\u003c/p\u003e\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 482px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4. The result of SEM (n=387). \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypotheses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS.E.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResult\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eH1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e---\u0026gt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePIO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.050\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.035\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.433\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eNot Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eH2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eBH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e---\u0026gt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePIO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.374***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.040\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e9.318\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eH3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePIO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e---\u0026gt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eSVF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.740***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.064\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e11.583\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eH4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePIO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e---\u0026gt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePPR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.298***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.038\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e7.756\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eH5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePIO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e---\u0026gt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePUI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.845***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.076\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e11.081\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eH6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePUI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e---\u0026gt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.272***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.050\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5.406\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eH7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePPR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e---\u0026gt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.096\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.135\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.711\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eNot Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eH8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eSVF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e---\u0026gt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.422***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.065\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e6.473\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNotes: ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001; **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; B: unstandardized coefficients, S.E.: standard errors.\u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eInsert Table\u0026nbsp;4 about here\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eInsert\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003eabout here\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.4. The moderating effect testing\u003c/h2\u003e \u003cp\u003eUsing AMOS 29.0, we conducted a multi-group analysis (MGA) to examine the moderating effect of customer engagement (high vs. low) on the relationships between entertainment, boredom / habitual pass time, perceived information overload, short-from video fatigue, perceived psychological risk and perceived uncertainty. Participants were divided into two groups based on their customer engagement: low group (n\u0026thinsp;=\u0026thinsp;177) and high group (n\u0026thinsp;=\u0026thinsp;210).\u003c/p\u003e \u003cp\u003eAn independent samples t-test was conducted to assess whether the grouping manipulation successfully distinguished between participants. Results indicated a significant difference in mean scores between the low-level group (M\u0026thinsp;=\u0026thinsp;3.62, SD\u0026thinsp;=\u0026thinsp;0.79) and the high-level group (M\u0026thinsp;=\u0026thinsp;5.74, SD\u0026thinsp;=\u0026thinsp;0.46), t(385)\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;32.78, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, confirming the validity of the classification.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e summarizes the results of the multi-group comparison between participants with low and high levels of customer engagement. First, the effect of entertainment on perceived information overload was not significantly different across groups (Low group: B\u0026thinsp;=\u0026thinsp;0.032, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.442; High group: B\u0026thinsp;=\u0026thinsp;0.048, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.354), with a non-significant z-value of 0.238. Second, the path from boredom/habitual pass time to perceived information overload was significantly stronger in the high group (B\u0026thinsp;=\u0026thinsp;0.440, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than in the low group (B\u0026thinsp;=\u0026thinsp;0.245, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with a significant z-value of 2.451 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Third, the relationship between perceived information overload and short-form video fatigue was also significantly stronger in the high group (B\u0026thinsp;=\u0026thinsp;0.856, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to the low group (B\u0026thinsp;=\u0026thinsp;0.294, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007), with a z-value of 4.14 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Fourth, the effect of short-form video fatigue on perceived psychological risk was greater under the high group (B\u0026thinsp;=\u0026thinsp;0.380, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than under the low group (B\u0026thinsp;=\u0026thinsp;0.122, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016), with a significant z-value of 3.495 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Finally, the effect of perceived information overload on perceived uncertainty was significantly stronger in the high group (B\u0026thinsp;=\u0026thinsp;0.938, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than in the low group (B\u0026thinsp;=\u0026thinsp;0.522, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), with a z-value of 2.138 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe result testing moderating effects.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" morerows=\"1\" nameend=\"c4\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eHypotheses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eLow consumer engagement group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eHigh consumer engagement group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ez-score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS.E.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eS.E.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e---\u0026gt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePIO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e---\u0026gt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePIO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.245***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.440***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.451***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePIO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e---\u0026gt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSVF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.294**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.856***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e10.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4.140***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePIO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e---\u0026gt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.122*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.380***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e3.495***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePIO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e---\u0026gt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.522**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.938***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.138**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eNotes: ***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTaken together, these results suggest that customer engagement type moderates several structural relationships, with consistently stronger effects observed in the high customer engagement group.\u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eInsert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e \u003cb\u003eabout here\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003e====================\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. General discussion","content":"\u003cp\u003eThis study set out to examine how different viewing motives in the context of unboxing short-form videos influence users\u0026rsquo; cognitive and behavioral outcomes. Using structural equation modeling, three key findings emerged.\u003c/p\u003e \u003cp\u003eFirst, the results indicate that when users watch unboxing videos out of boredom or habitual motives, they are more likely to develop repetitive and passive viewing patterns, which increase exposure to redundant content and consume cognitive resources, thereby intensifying perceptions of information overload (Schmitt et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In contrast, entertainment motivation does not have a significant effect on perceived information overload. This suggests that viewing for entertainment purposes is more restorative than depleting in nature. Users engaging in hedonic use often enter a state of immersion that buffers the sense of informational burden, which aligns with previous findings that hedonic media consumption can help restore cognitive and emotional resources (Bartsch \u0026amp; Hartmann, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSecond, consistent with Cognitive Overload Theory, this study identifies perceived information overload as a core antecedent of negative user experiences. When the amount of information exceeds individuals\u0026rsquo; cognitive capacity, users experience emotional fatigue due to cognitive resource depletion (Sheng et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and cognitive uncertainty due to judgmental imbalance. These two psychological reactions represent affective and cognitive stress mechanisms that operate through the \u0026ldquo;emotional exhaustion path\u0026rdquo; and the \u0026ldquo;cognitive uncertainty path,\u0026rdquo; jointly exacerbating short-form video fatigue and strengthening users\u0026rsquo; discontinuance intentions. However, psychological risk typically manifests as anticipatory worry rather than directly leading to actual behavioral intention. It is specifically reflected in consumer anticipation - a psychological process in which consumers mentally simulate and evaluate potential material, experiential, social, emotional, or behavioral outcomes before making or engaging in a consumption decision (Vichiengior et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Therefore, compared with fatigue or uncertainty, its direct effect on discontinuance intention is not significant, though it may influence users\u0026rsquo; continued usage intention indirectly or through long-term cumulative effects.\u003c/p\u003e \u003cp\u003eThird, the study confirms the moderating role of customer engagement, as proposed by the Elaboration Likelihood Model. Highly engaged customers tend to process content via the central route and thus experience greater strain and fatigue when exposed to repetitive video streams. In contrast, low-engagement customers rely more on peripheral processing and are therefore less susceptible to such negative outcomes. This finding provides nuanced insights into why identical viewing environments may lead to divergent impacts across different customer groups.\u003c/p\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e5.1. Theoretical contribution\u003c/h2\u003e \u003cp\u003eThis study advances theoretical knowledge and broadens current perspectives on consumer behavior in the field of tourism marketing.\u003c/p\u003e \u003cp\u003eFirst, by integrating Uses and Gratifications Theory with Cognitive Overload Theory, this study reveals the \u0026ldquo;double-edged sword\u0026rdquo; effect of user viewing motives. The findings indicate that while users watch short-form videos driven by motives such as boredom/ habitual pass time with the initial purpose of satisfying their needs (Ib\u0026aacute;\u0026ntilde;ez-S\u0026aacute;nchez et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Pillai et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), in highly repetitive and homogeneous information environments these motives may instead trigger cognitive strain and negative experiences. This extends prior U\u0026amp;G research, which has largely emphasized positive gratifications, by highlighting its \u0026ldquo;dark side\u0026rdquo; perspective and demonstrating that motivation-driven overuse can shift user experiences from satisfaction to fatigue.\u003c/p\u003e \u003cp\u003eSecond, by introducing the Elaboration Likelihood Model (Cacioppo et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1986\u003c/span\u003e) into the short-form video context, this study highlights the pivotal role of customer engagement in the formation of cognitive overload. Empirical results indicate that highly engaged customers are more likely to process information via the central route, which\u0026mdash;under conditions of excessive repetition\u0026mdash;renders them more susceptible to overload and fatigue. In contrast, low-engagement customers rely more on peripheral cues, which, to some extent, mitigates overload. Hence, customer engagement serves not only as a predictor of information processing depth but also as a boundary condition for the emergence of cognitive overload. This finding extends the applicability of the ELM beyond attitude change to explaining variations in cognitive strain within digital media environments.\u003c/p\u003e \u003cp\u003eThird, this study proposes and validates a comprehensive path model linking viewing motives, cognitive mechanisms, and behavioral outcomes, thereby enriching theoretical explanations of the negative effects of short-form video use. The model demonstrates how viewing motives can lead to perceived information overload, which subsequently induces short-form video fatigue, psychological risk, and uncertainty, ultimately shaping users\u0026rsquo; discontinuance intentions. By integrating multiple theoretical perspectives and conducting empirical testing, this study provides a new framework for understanding the shift from motivation-driven engagement to psychological exhaustion, while also offering important implications for future research on overload effects and behavioral consequences in digital media contexts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e5.2. Managerial implications\u003c/h2\u003e \u003cp\u003eFirst, the findings offer practical implications for enhancing content recommendation strategies on short-form video platforms. The results indicate that algorithms which repeatedly deliver highly homogeneous unboxing videos may heighten users\u0026rsquo; perceived information overload, consequently leading to viewing fatigue and discontinuance intention. Therefore, platforms should strive to balance personalization with content diversity when optimizing their recommendation systems, avoiding excessive reinforcement of a single content type. By incorporating greater novelty and differentiation in content delivery, platforms can better satisfy users\u0026rsquo; viewing motives while mitigating the adverse effects of cognitive overload.\u003c/p\u003e \u003cp\u003eSecond, the results underscore the moderating role of user engagement in the development of cognitive overload, providing practical insights for effective user segmentation and management. While highly engaged users constitute the core audience of platforms, they are also the most vulnerable to information overload. For this group, platforms could implement features such as \u0026ldquo;usage reminders\u0026rdquo; or \u0026ldquo;content pacing controls\u0026rdquo; to help maintain psychological well-being during prolonged use. Conversely, for low-engagement users, increasing interactivity and entertainment value in the content may help enhance their stickiness and sustained engagement.\u003c/p\u003e \u003cp\u003eThird, the study underscores the need to balance motivational gratifications and psychological burdens in optimizing user experience. Although entertainment and habitual motives drive short-term engagement, prolonged reliance on these motives may trigger negative emotions and user attrition risks. Therefore, platforms should focus on fostering \u0026ldquo;positive experience extension\u0026rdquo; in content ecosystem design, such as offering diverse usage scenarios, healthier usage rhythms, and more valuable informational elements, to ensure that user needs are fulfilled without leading to fatigue or resistance caused by overuse.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Limitation and future research\u003c/h2\u003e \u003cp\u003eAlthough this study yields meaningful insights, certain limitations remain and open new directions for future research. First, the reliance on a cross-sectional survey design limits the ability to observe changes in users\u0026rsquo; psychological states over time. Employing longitudinal or experimental approaches in future work could enable a more robust examination of causal linkages among viewing motives, perceived information overload, and usage fatigue. Second, the present study included a relatively narrow set of variables; for instance, platform-related characteristics (e.g., algorithmic transparency, interactivity) and individual attributes (e.g., self-regulation, personality traits) were not explored. Future research that integrates these factors could offer a more comprehensive understanding of the adverse psychological consequences of short-form video consumption.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthical approval\u003c/h2\u003e \u003cp\u003e Ethical approval for this study was granted by the Institutional Review Board (IRB) of Gachon University, Republic of Korea, on July 11, 2025 (Approval No.: 1044396-202505-HR-082-01).\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eInformed consent\u003c/h2\u003e \u003cp\u003eThis study involved a non-interventional social science survey and did not include any medical procedures, collection of biological samples, or personally identifiable sensitive information. Prior to participation, all respondents were provided with an online informed consent form explaining the purpose of the study, the voluntary nature of participation, confidentiality assurances, and their right to withdraw at any time without penalty. Informed consent was obtained electronically on August 20, 2025, and data collection was conducted between August 25 and September 8, 2025. Only participants who provided explicit consent were allowed to proceed with the survey.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eQian Zhang: Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing, Methodology, Investigation, Data analysis, Formal analysis and Visualization. Zhaoqi Li: Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing, Methodology, Project administration and Resources.Jiangmin Ding: Data curation, Software analysis, Validation, and Visualization. Hong Chen: Writing \u0026ndash; review \u0026amp; editing, Conceptualization, Supervision, and Resources.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the corresponding author, upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbbasi AZ, Qummar H, Bashir S, Aziz S, Ting DH (2024) Customer engagement in Saudi food delivery apps through social media marketing: Examining the antecedents and consequences using PLS-SEM and NCA. 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Inform Dev 02666669251334136. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/02666669251334136\u003c/span\u003e\u003cspan address=\"10.1177/02666669251334136\" 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":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Unboxing videos, Viewing motives, Short-form video fatigue, Customer engagement, Information overload, Cognitive Overload Theory, Discontinuance intention","lastPublishedDoi":"10.21203/rs.3.rs-8067328/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8067328/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUnderstanding how unboxing video viewing motives influence users\u0026rsquo; cognitive and behavioral outcomes is essential for managing engagement and fatigue in short-form video environments. This study examines how different viewing motives in unboxing short-form videos - entertainment and boredom/habitual pass time - affect perceived information overload and subsequent discontinuance intention to use. Using structural equation modeling, the results reveal that boredom/habitual pass time motives lead to repetitive and passive viewing patterns, thereby intensifying information overload, whereas entertainment motives exert no significant effect, reflecting their restorative nature. Consistent with Cognitive Overload Theory, when users perceive an overload of information, the resulting fatigue and cognitive confusion collectively drive their intention to withdraw from short-form video use. Moreover, customer engagement moderates these effects: highly engaged users process content via the central route and experience greater strain, while low-engagement users rely on peripheral cues that alleviate overload. These findings deepen the understanding of cognitive and affective mechanisms underlying short-form video fatigue while offering practical guidance for optimizing content rhythm, recommendation algorithms, and user experience design on digital platforms. Collectively, they also extend the Elaboration Likelihood Model by revealing how cognitive overload operates within interactive media contexts.\u003c/p\u003e","manuscriptTitle":"Unboxing the Paradox: Understanding How Viewing Motivations Drive User Fatigue and Attrition on Short-Form Video Platforms","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-25 12:32:58","doi":"10.21203/rs.3.rs-8067328/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-18T03:02:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-11T10:07:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"77492770207544673495756536473344212705","date":"2026-04-26T23:42:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"24118868982130977633181182082428214345","date":"2026-04-26T13:54:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256491380992783139133264916048778117222","date":"2026-04-14T02:47:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-24T05:06:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-24T05:03:26+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-16T07:44:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-28T05:56:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2025-11-28T05:47:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"45346248-3f70-486a-a9ef-e4d023b295c1","owner":[],"postedDate":"February 25th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-18T03:02:41+00:00","index":125,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-11T10:07:59+00:00","index":124,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":63490209,"name":"Biological sciences/Neuroscience"},{"id":63490210,"name":"Biological sciences/Psychology"},{"id":63490211,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2026-02-25T12:32:58+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-25 12:32:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8067328","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8067328","identity":"rs-8067328","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}