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22 SES 15 D: Challenging Students Learning
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22. Research in Higher Education
Paper Knowledge Governance and Dynamic Capabilities for Meaningful Adoption of Artificial Intelligence in Universities of Emerging Economies 1: Universidad Juárez Autónoma de Tabasco, México.; 2: Universidad Juárez Autónoma de Tabasco, México.; 3: Universidad Juárez Autónoma de Tabasco, México.; 4: Universidad Juárez Autónoma de Tabasco, México.; 5: Universidad Juárez Autónoma de Tabasco, México.; 6: Universidad Juárez Autónoma de Tabasco, México. Presenting Author:Knowledge, in its deepest sense, is not an immediate act nor a simple accumulation of information but a historical, progressive, and dialectical process through which the human spirit recognizes itself in its relationship with the world. Through this leadership movement in organizations, decision-makers not only learn about their reality but also seek to influence and transform it, understanding the practices of organizational knowledge management (creation, exchange, and transfer) in the public university (Mohammad-AlQhtani, 2025; Tarko-Kassa and Jing, 2025; Vyas, 2024), starting from the orchestration of a conservatory for the development of an artificial intelligence laboratory. This is achieved through a descriptive-interpretive and critical phenomenological analysis (Hegel, 1971: 1807) of secondary documents and narratives of institutional practices, using grounded theory as the analytical method and axial coding to identify the institutional, human, leadership, resource, and infrastructure factors that influence their effectiveness. This is done from the perspective of knowledge-based theory (Miller, 1995), institutional theory (Meyer and Rowan, 1977; Scott, 2008), and theories of organizations and social change (dependency theory, modernization theory, conflict theory, dynamic capabilities theory, life cycle theory, and teleological theory). The following question is addressed: How does the structural flexibility of organizations in emerging economies facilitate or hinder technological leaps relative to legacy innovation models? How do institutional resistance and new dynamic capabilities interact during the transition to an AI-based management model? To what extent does the transfer of tacit knowledge, mediated by international collaboration networks, determine the capacity of organizations in developing countries to absorb explicit knowledge? This allows us to identify categories, relationships, and patterns linked to institutional governance rules, the reach of university services, the use of models, algorithms, and frameworks, as well as the university's core values and social purpose, in relation to the impact of research funded by public sources. We describe three isomorphic processes coercive, mimetic, and normative based on pressure for legitimacy and mandate exerted by national organizations upon which the creation of new knowledge and the formation of expectations for social employability depend. This also addresses global uncertainty, improves the efficiency of the teaching profession, fosters the development of 21st-century skills, and optimizes educational management. The use of procedural manuals, workflows, and collaboration agreements is considered a form of knowledge transfer that universities replicate by adopting similar methods. In line with the European-international dimension, the study aligns with Sustainable Development Goals 4, 9, 16, and 17 by analyzing how knowledge governance and the management of AI laboratories in public universities contribute to responsible innovation, international academic cooperation, and institutional strengthening in emerging economies through Open Science and Responsible Research and Innovation (RRI) approaches. The European public university is conceived as a key player in the social innovation ecosystem, capable of articulating institutional leadership, ethical values, and digital transformation in service of the common good. Beyond the professionalization of their members (researchers, administrators), they share a common educational foundation and behavioral models. This means that European and Latin American actors are assuming increasingly similar roles in their efforts to transform the university context and consolidate dynamic capacities through international academic networks. Methodology, Methods, Research Instruments or Sources Used Using a qualitative (Denzin et al., 2023), interpretive, phenomenological, and emergent design (Creswell, 2013), faculty narratives were analyzed to understand the complexity of artificial intelligence in the university setting, without recourse to predefined theoretical frameworks. The analysis was conducted using the constant comparative method of grounded theory (Strauss & Corbin, 1990), supported by MAXQDA, a software tool for organizing, tracking, and systematizing the data. The corpus consisted of the complete transcript of the Institutional Program on Artificial Intelligence in the University Setting (UJAT, 2026), totaling 3 hours, 27 minutes, and 2 seconds, equivalent to 1,807 paragraphs, 25,578 words, and 159,732 characters. The analytical process continued until theoretical saturation was reached, identifying 64 emergent categories. Through axial coding, 17 core categories related to learning, teacher training, digital culture, digital literacy, artificial intelligence, intellectual property, technology, and the university were integrated. Subsequently, selective coding allowed for the articulation of three thematic axes: (1) teaching perspectives; (2) AI training pathways; (3) a future vision of the university as a base for international academic cooperation and institutional strengthening in emerging economies. For theoretical validation, the Lakatos Scientific Research Program (Jiménez-León, 2026) was followed, structuring an integrative model: (a) core: knowledge as a strategic resource, AI adoption as a multicausal change process, dual cognition in natural thinking (pedagogical judgment, criteria, meaning) and automated thinking (algorithmic assistance, suggestions, optimization); (b) protective belt: empirically adjusted dimensions, resources, institutional pressures, dynamic capabilities, micropolitics, modernization/leapfrogging; (c) layered model architecture. Cognitive Layer A (micro): Teacher's natural thinking, pedagogical judgment, expert intuition, situated ethics, metacognition. Automated thinking: suggestions, templates, generation, automated evaluation. Knowledge Layer B (meso): Creation, sharing, and transfer processes, mechanisms, and communities of practice. Institutional Layer C (macro): rules, legitimacy, authorities, ethics, intellectual property, data governance, accreditation. Social/organizational Change Layer D (expanded macro): technological dependence, inequality of capabilities, resistance, cycles, public purposes. Code grids and diagrams were used for analytical visualization. Methodological rigor was ensured through criteria of credibility, dependability, and confirmability, via peer review, analytical traceability, and comparison with open institutional sources. The study was approved by the University Research Ethics Committee. Generative artificial intelligence was used in the preparation of this manuscript as a support tool for improving writing and linguistic revision with the Grammarly and Transkriptor tools. The intellectual content, analysis, interpretation, and conclusions are the sole responsibility of the authors. Conclusions, Expected Outcomes or Findings This study demonstrates that the integration of Artificial Intelligence (AI) in higher education transcends mere technological acquisition; it is, fundamentally, a challenge of governance and organizational change. Under the principles of Open Science and RRI (Research, Innovation, and Research), an effective transition depends on overcoming mimetic isomorphism, in which institutions replicate external structures for legitimacy while maintaining anachronistic pedagogical practices of control and prohibition. The evidence suggests that structural flexibility is a necessary but insufficient condition for technological leapfrogging. Without a clear governance framework, this flexibility leads to fragmented and "ceremonial" adoptions that fail to scale to the institutional level. Conversely, the consolidation of dynamic capacities enables universities to reconfigure their resources, moving from initial resistance toward critical regulation and meaningful pedagogical appropriation. In the context of developing universities, a critical gap is identified between the availability of explicit knowledge (guidelines and regulations) and its actual implementation. True transformation doesn't happen by decree, but rather through the transfer of tacit knowledge via communities of practice, mentorship, and co-design of instruction. These elements act as the engine of absorption, allowing AI to be "territorialized" in the classroom. As the following excerpt indicates: [...] "I decided to go to the parks under the mango trees with the cell phones, to provide training to help democratize the tool so that others can use it." Participant. Finally, collaboration within international academic networks is vital to reducing uncertainty and increasing institutions' capacity to absorb this knowledge. In short, the meaningful adoption of AI requires a systemic articulation between tiered teacher training, knowledge management, and ethical governance oriented toward the common good. Only in this way will technological innovation translate into a real educational transformation, capable of closing gaps in the Latin American university environment. References Aldrich, H. (1979). Organizations and environments. Prentice-Hall. Aldrich, H., & Ruef, M. (2006). Organizations Evolving. SAGE Publications Ltd. https://share.google/Jz4rDGPMueTlvrlWZ Creswell, J. (2013). Qualitative Inquiry and Research Design: Choosing Among Five Approaches. SAGE Publications. https://share.google/E36EgY8hrotuL2TZh Denzin, N., K., Lincoln, Y., S., Giardina, M., D. & Cannella, G., S. (2023). The SAGE Handbook of Qualitative Research. Sage Publications . https://www.google.com.mx/books/edition/The_SAGE_Handbook_of_Qualitative_Researc/8XmCEAAAQBAJ?hl=es&gbpv=1&pg=PT16&printsec=frontcover Hegel, G. W. F. (1971). Fenomenología del Espíritu (Obra original publicada en 1807). Fondo de Cultura Económica. https://share.google/OjLQFgQ5ga46OOABD Jiménez-León, R. (2026). Orígenes y planteamientos de la investigación cualitativa para los negocios: Desarrollo de un programa de investigación lakotosiano [Presentación]. Universidad Juárez Autónoma de Tabasco. https://hdl.handle.net/10481/109538 Meyer, J., W. & Rowan, B. (1977). Institutionalized organizations: Formal structure as myth and ceremony. American Journal of Sociology, 83(2), 340-363. https://share.google/ZiD4tdpwY6m4400q9 Miller, D. (1995). Teoría del conocimiento. En D. Miller (Ed.) Popper: Escritos selectos (pp.10-70). Fondo de Cultura Económica. https://share.google/z84aZLEZ1FYjcCozo Mohammad-AlQhtani, F. (2025). Knowledge management for research innovation in universities for sustainable development: a qualitative approach. Sustainability,17(6), 2481. https://doi.org/10.3390/su17062481 Scott, W. R. (2008). Institutions and organizations: Ideas and interest. Sage Publications. https://share.google/mB5vlN1G7a6lHGKra Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Sage. https://share.google/bdV8MZUdK8o1sxGhi Tarko-Kassa, E. & Jing, N. (2025). Knowledge Management Practices in the Universities: A Qualitative Inquiry. Sage Open, 15(3), 1-16. https://doi.org/10.1177/21582440251357152 Universidad Juárez Autónoma de Tabasco. (2026, 21 de enero). Instalación del Comité de Ética para el uso de la IA en el entorno universitario [Video]. Facebook. https://www.facebook.com/ujat.mx/videos/2467682383647817 Vyas, P. (2024). Knowledge management and higher education institute: Review & topic analysis. Journal of Open Innovation: Technology, Market, and Complexity, 10(100349), 1-9.https://doi.org/10.1016/j.joitmc.2024.100349 22. Research in Higher Education
Ignite Talk Research on the Education Model of “Integration of Specialization and Innovation” in High-Level Research Universities: Challenges and Pathways for Development Huazhong University of Science and Technology, China Presenting Author:This study investigates the education model and implementation mechanisms of the integration of specialization and innovation, abbreviated as ISI, in high level research universities, addressing institution level demands for cultivating high level, versatile talents under innovation driven development agendas. In the knowledge economy, universities are expected to develop graduates with strong disciplinary foundations alongside innovation capability and entrepreneurial literacy. In practice, however, structural barriers continue to constrain collaboration among universities, industry and government within higher education innovation ecosystems. Disciplinary education and innovation and entrepreneurship education are also frequently arranged in parallel rather than integrated through coherent institutional design, curriculum architecture and resource allocation. These constraints make it difficult for universities to establish a sustainable and consistent talent development system that can translate reform aspirations into demonstrable improvements in educational quality and innovation outcomes. Although existing studies have offered valuable discussions from the perspectives of entrepreneurship education, university industry engagement and curriculum reform, there remains limited conceptual clarity and mechanism oriented evidence regarding ISI as a systemic education model, particularly its conceptual boundaries, internal logic and organizationalized pathways of implementation in high level research universities. The guiding research question is as follows: under the development goals and governance conditions of high level research universities, what mechanisms and structural constraints shape the effective implementation of ISI, and how do these factors operate through the alignment of curricula, faculty capacity and practice platforms to influence talent cultivation quality and the development of innovation and entrepreneurship competencies. The study aims to clarify the conceptual essence of ISI by emphasizing that ISI is not a simple combination of courses or an accumulation of extracurricular activities, but a systemic coupling and mutual reinforcement among disciplinary learning, innovation training and entrepreneurial practice. It further seeks to identify the major bottlenecks that impede ISI implementation across curriculum design, faculty development and practice platform construction, and to propose actionable and transferable pathways for institutional improvement that support research universities in upgrading talent cultivation and strengthening innovation ecosystems. The study is grounded in triple helix theory and collaboration theory, which together inform an analytical framework connecting the external collaborative ecosystem to the internal educational system. The external dimension highlights resource flows, boundary spanning and institutional arrangements among universities, industry and government, explaining why the co construction of practice platforms and the sustained provision of project based learning opportunities are often shaped by responsibility allocation, governance structure and incentive compatibility. The internal dimension foregrounds cross school and cross departmental coordination, resource integration and assessment and incentive regimes, explaining how weak curriculum alignment, underdeveloped learning outcomes oriented assessment loops and the shortage of dual competency faculty jointly constitute institutional bottlenecks. On this basis, ISI implementation is conceptualized as a coordinated improvement across theoretical curricula, faculty supply and development, and practice activities and platform construction, providing a systematic lens for analyzing challenges and development pathways. The empirical setting draws on five high level research universities in China, offering evidence and implications that speak to broader debates on talent cultivation reform in research intensive higher education. Methodology, Methods, Research Instruments or Sources Used This study adopts a mixed methods design to strengthen both explanatory depth and evidentiary robustness regarding ISI as a systemic education model. Empirical work is situated in five high level research universities in China, which enables comparison across institutional contexts while retaining sensitivity to variation in organizational conditions. The qualitative component relies on semi structured in depth interviews with 37 participants, including students and educational administrators from relevant management departments, in order to capture process level evidence on institutional arrangements and implementation dynamics. Interview materials focus on top level design and responsibility allocation, curriculum alignment and teaching assessment reform, faculty development and incentive support, and the logic and governance of practice platform co construction. Qualitative data are analyzed using thematic analysis, with iterative cycles of coding and theme refinement to build an explanatory account of mechanisms and structural constraints. The resulting themes are then interpreted through the lenses of triple helix theory and collaboration theory to enhance analytical coherence and transferability. The quantitative component draws on 1,226 cross sectional survey responses to examine the overall status of ISI implementation and its key determinants. Survey measures are organized around the three operational dimensions of ISI, namely curriculum integration quality, dual competency faculty support, and practice platform collaboration, and include outcome indicators related to the development of innovation and entrepreneurship capabilities, such as learning engagement in innovation and entrepreneurship activities, perceived competence gains, and innovation and entrepreneurship self efficacy. Quantitative analyses employ descriptive statistics and multiple regression models to identify association patterns and constraint pathways among core variables. Mixed method integration follows an explanatory integration strategy, using quantitative patterns as a structural map and qualitative narratives to explain how institutional mechanisms and contextual conditions produce the observed relationships. Ethical procedures are strictly followed throughout the study, including informed consent, anonymization, and responsible data management. Conclusions, Expected Outcomes or Findings The findings indicate that ISI implementation in high level research universities is characterized by clear reform aspirations alongside insufficient institutionalization and mechanism based support. Although universities emphasize ISI as a central mission for upgrading talent cultivation and strengthening innovation capacity, implementation remains constrained by several structural bottlenecks. A first challenge is the absence of institutionally distinctive and operational top level designs in some universities, which leads to weak alignment among reform objectives, responsibility allocation and execution mechanisms. A second challenge lies in delayed curriculum and assessment reforms, as disciplinary courses and innovation and entrepreneurship courses often lack structured linkage and a robust learning outcomes oriented assessment loop. A third challenge concerns the shortage of dual competency faculty, while faculty development supports and incentive systems remain inadequate for strengthening cross boundary teaching and practice oriented mentoring capacities. A fourth challenge is the limited capacity to co construct and sustainably operate practice platforms, as university industry government collaboration continues to face barriers in resource integration, governance arrangements and long term incentive alignment. Drawing on triple helix and collaboration perspectives, the study argues that improving ISI quality requires simultaneous progress in the external collaborative ecosystem and the internal collaborative education model. Externally, clearer accountability arrangements and governance optimization are needed to enhance platform co building efficiency and resource accessibility. Internally, universities should strengthen cross departmental resource integration and align assessment and incentives to improve the coherence of curricula, faculty capability and practice opportunities. The study contributes a transferable analytical framework for ISI and offers actionable implications for curriculum reform, faculty development and practice platform governance in high level research universities. References Carlos, J. V., Marco, C., & Carlos, S. (2024). Social entrepreneurship and complex thinking: An exploratory educational innovation proposal for acquiring and scaling competencies. Higher Education, Skills and Work-Based Learning, 14(3), 694–710. Etzkowitz, H., & Leydesdorff, L. (1995). The triple helix university–industry–government relations: A laboratory for knowledge-based economic development. EASST Review, 14, 14–19. Fayolle, A. (2013). Personal views on the future of entrepreneurship education. Entrepreneurship & Regional Development, 25(7–8), 692–701. Jones, B., & Iredale, N. (2010). Enterprise education as pedagogy. Education + Training, 52(1), 7–19. Macías, P. N., Tierno, G. L., & Nicolás, D. L. V. (2023). Educational innovation boosting students’ entrepreneurial intentions. SAGE Open, 13(3), 1–14. Mars, M. M., & Metcalfe, A. S. (2009). Entrepreneurship education. ASHE Higher Education Report, 34(5), 1–83. Mizanur, M. R., Alain, F., & Paul, L. D. (2024). Predicting graduate students’ entrepreneurial intentions through innovative teaching in entrepreneurship education: A SEM–ANN approach. Education + Training, 66(2–3), 273–301. Sinha, M., Shekhar, & Valeri, M. (2024). How does entrepreneurship education promote creativity and innovation? International Journal of Technology Enhanced Learning, 16(1), 1–18. Wilms, S. M. B., Højgaard, L. J., & Mathilde, K. (2020). To share or not to share: A study of educational dilemmas regarding the promotion of creativity and innovation in entrepreneurship education. Scandinavian Journal of Educational Research, 64(2), 211–226. 22. Research in Higher Education
Paper Examining the Mediating Role of Mind Wandering in the Relationship Between Self-Control and Short Video Addiction in University Students Afyon Kocatepe University, Turkey (Türkiye) Presenting Author:Short video platforms (TikTok, Reels, Shorts) are applications that continuously stimulate individuals' attention and concentration systems through rapid, intense, and rewarding stimuli (Kurtça & Laçin, 2025). Watching short videos allows individuals to escape from stress and alleviate negative emotions, while providing quick access to information tailored to their preferences with low cognitive engagement (Dong et al., 2023). With the rapid global spread of short video applications, people's lives, social interactions, and entertainment are increasingly influenced by these platforms (Qu et al., 2023; Zhao & Kou, 2024). University students, representing the youth demographic, are among the most frequent users of short video applications (Cheng et al., 2023). Excessive and uncontrolled use of short video applications can lead to various negative effects, including the development of behavioral addictions (Ye et al., 2022; Zhang et al., 2019). Longitudinal studies reveal that in both Eastern and Western societies, the fast-paced content streams of short video platforms reinforce compulsive use and attention-related difficulties (van Driel et al., 2022; Zhao & Wagner, 2023). In a study conducted in Türkiye, it is stated that short video addiction is associated with distractibility and impulsivity (Kurtça & Laçin, 2025). These findings point to the importance and necessity of examining the relationships between short video addiction, mind wandering, and self-control within a model framework. The results of the study conducted by Yan et al. (2024) show that an increasing trend toward mobile phone short video addiction can negatively affect self-control and reduce executive control in the area of attention functions. In this context, self-control is defined as the ability to manage one's emotions, thoughts, and behaviors to ensure harmony between oneself and one's environment (Nebioğlu et al., 2012). Self-control plays a central role in most decision-making processes and human behavior (David & Roberts, 2025). Volitional processes facilitate self-controlled behavior and involve learned metacognitive strategies such as planning and attention redirection. In contrast, impulsive processes weaken self-controlled behavior and involve reward sensitivity, emotion seeking, and desires (Duckworth & Steinberg, 2015). Watching short TikTok videos, typically 30-60 seconds long, weakens self-control, which is associated with increased phone addiction (David & Roberts, 2025). A study conducted with Chinese adolescents found that increased addiction to short videos was positively correlated with decreased attention control (Ye et al., 2025). These results indicate that although excessive use of short video applications has negative effects on individuals, users spend significant amounts of time on these platforms, and strict self-regulation of usage time is needed (Ye et al., 2025). Another variable thought to be linked to short video addiction and self-control is mind wandering. Mind wandering is described as individuals engaging in various inner thoughts, dreams, and emotions that are irrelevant to the task at hand rather than paying attention to the task at hand (Smallwood & Schooler, 2006). Mind wandering has many effects on individuals. A study by Li et al. (2025) revealed that mind wandering is linked to hyperactivity-impulsivity and internet addiction. Mobile phone addiction and fatigue appear to be linked to individuals experiencing mind wandering (Lian et al., 2022). Studies have shown that individuals who experience flow while watching short videos tend to engage in more mind-wandering (Yayla & Çelikci, 2025). It has been found that individuals with short video addiction may have more difficulty maintaining attention, experience more attention deficits while watching short videos, and their concentration may be impaired due to the intervention (Chen et al., 2023). Because of these reasons, the purpose of this study is to examine the mediating role of mind wandering in the relationship between self-control and short video addiction in university students. Methodology, Methods, Research Instruments or Sources Used Research Design The study is structured using a correlational design. A correlational design is used to explore relationships among two or more variables, assess whether variables mutually influence each other, and investigate their combined effects (Creswell, 2017). Structural equation modeling (SEM) is utilized to analyze the relationships among these variables and to evaluate the model's validity, which is constructed based on the theoretical framework. In this study, short video addiction was identified as the dependent variable, self-control as the independent variable, and mind wandering as the mediating variable. The mediating model constructed with these three variables was examined within the framework of structural equation modeling. Participants It was conducted with a sample of 280 Turkish university students from different universities and departments, selected through convenience sampling. Research Instruments Data were collected using a personal information form, the Short Video Addiction Scale, the Brief Multidimensional Self-Control Scale, and the Mind Wandering Scale. Short Video Addiction Scale: The scale was developed by Ye et al. (2022). The scale was adapted to Turkish by Türk & Yıldırım (2024). The scale consists of 10 items and a single sub-dimension. The increase in the score obtained from the scale indicates that the individual's short video addiction increases. The Cronbach alpha internal consistency reliability coefficient was .82. In this study, the Cronbach alpha was .85. Brief Multidimensional Self-Control Scale: The scale was developed by Nilsen et al. (2020) and adapted to Turkish by Koç et al. (2023). The scale consists of 8 items and 2 sub-dimensions (inhibition and initiation). The Cronbach alpha internal consistency reliability coefficient was found to be .70. In this study, the Cronbach alpha value was calculated as .75. Mind Wandering Questionnaire: The scale was developed by Mrazek et al. (2013). The scale was adapted to Turkish culture by Sezgin (2020). The five items (e.g., "I cannot give my full attention while doing my work") are rated on a six-point scale from 1 (never) to 6 (always) with scores ranging from 5 to 30. The higher the score, the greater the mind wandering. The Cronbach alpha internal consistency reliability coefficient was .75. In this study, the Cronbach alpha value was .87. Analysis Procedure Independent group t-tests, One-Way ANOVA, Pearson Product-Moment Correlation, Path Analysis, and Bootstrapping Analysis were used to analyze the data. Conclusions, Expected Outcomes or Findings The results indicate significant relationships between university students' short video addiction, mind wandering, and self-control levels. Moreover, based on the structural equation model developed, mind wandering was found to play a partial mediating role in the relationship between self-control and short video addiction. These results suggest that university students with lower self-control experience more mind wandering and that individuals with both lower self-control and frequent mind wandering have higher levels of short video addiction. According to one-way ANOVA results, individuals who use smartphones for 7 hours or more have a higher incidence of short video addiction compared to those who use them for 2-3 hours or 4-6 hours. Furthermore, individuals who use smartphones for 2-3 hours have higher self-control compared to those who use them for 4-6 hours or more, and those who use them for 7 hours or more. In terms of mind wandering, individuals who used smartphones for 7 hours or more a day had higher levels than those who used them for 2-3 or 4-6 hours. According to the results of the independent sample t-test, it was found that individuals' levels of short video addiction, mind wandering, and self-control did not differ according to gender and income level. The findings are discussed and interpreted in the context of the relevant literature. These results show that short video addiction, which has become widespread worldwide, is an important issue that needs to be studied, particularly among university students, representing a young population. In experimental studies aimed at reducing individuals' short video addiction, attempting to enhance their self-control and attention levels may be effective. References Chen, Y., Li, M., Guo, F., & Wang, X. (2023). The effect of short-form video addiction on users’ attention. Behaviour & Information Technology, 42(16), 2893-2910. https://doi.org/10.1080/0144929X.2022.2151512 Cheng, X., Su, X., Yang, B., Zarifis, A., & Mou, J. (2023). Understanding users’ negative emotions and continuous usage intention in short video platforms. Electronic Commerce Research and Applications, 58, 101244. doi: 10.1016/j.elerap.2023.101244 Dong, W. H., Wang, W. J., Wang, X. C., and Li, W. Q. (2023). The occurrence mechanism of short video indulgence from the perspective of human-computer interaction. Adv. Psychol. Sci. 31, 2337–2349. doi: 10.3724/SP.J.1042.2023.02337 Koç, H., Şimşir Gökalp, Z., & Seki, T. (2023). The relationships between self-control and distress among the emerging adults: A serial mediating roles of fear of missing out and social media addiction. Emerging Adulthood, 11(3), 626–638. https://doi.org/10.1177/21676968231151776 Li, Y., Zhang, Z., Cui, L., Wang, Y., Guo, H., Wang, J., ... & Wang, X. (2025). The role of mind wandering and anxiety in the association between internet addiction and hyperactivity-impulsivity: A serial mediation model. BMC Psychology, 13(1), 345. Lian, S., Bai, X., Zhu, X., Sun, X., & Zhou, Z. (2022). How and for whom is mobile phone addiction associated with mind wandering: the mediating role of fatigue and moderating role of rumination. International journal of environmental research and public health, 19(23), 15886. Qu, D. Y., Liu, B. W., & Jia, L. X. (2023). The longitudinal relationships between short video addiction and depressive symptoms: a cross-lagged panel network analysis. Comput. Hum. Behav. 152:108059. doi: 10.1016/j.chb.2023.108059 van Driel, I. I., Pouwels, J. L., & Keijsers, L. (2022). Short-form video and problematic use among teachers: A longitudinal study. New Media and Society, 24(10), 2265–2284. Yan, T., Su, C., Xue, W., Hu, Y., & Zhou, H. (2024). Mobile phone short video use negatively impacts attention functions: an EEG study. Frontiers in Human Neuroscience, 18, 1383913. Ye, J. H., Zheng, J., Nong, W., & Yang, X. (2025). Potential Effect of Short Video Usage Intensity on Short Video Addiction, Perceived Mood Enhancement ('TikTok Brain'), and Attention Control among Chinese Adolescents. International Journal of Mental Health Promotion, 27(3). Zhao, Z., & Kou, Y. (2024) Effects of loneliness on short video addiction among college students: The chain mediating role of social support and physical activity. Front. Public Health 12:1484117. doi: 10.3389/fpubh.2024.1484117 Zhao, X., & Wagner, J. (2023). Algorithmic feeds and compulsive use of short videos: Evidence from longitudinal research. Media Psychology, 26(2), 123–142. | ||
