Digital Media and Behavioural Addiction: Where does use become Problematic?
Creators: name: Tullett-Prado, Deon
Publisher: name: RMIT University
Year: 2025
Subjects: classificationCode: 520302
subject: Clinical psychology

description: Background: Digital media has proliferated through the cultures of the developed world to the point where it touches nearly every facet of modern life. While its benefits are undeniable, concerns have abounded regarding its possible negative effects on wellbeing, especially for individuals exhibiting problematic digital media use (PDMU). PDMU is often conceptualized using the behavioural addiction model, which likens it to substance addiction. According to this model, compulsive and impulsive behaviours driven by digital media dependency lead to adverse consequences similar to those experienced in substance abuse. Despite its widespread use, the behavioural addiction model faces criticism regarding its validity and applicability, sparking a need for deeper investigation. Research objectives: This PhD project, structured as a PhD with Publications, is designed to assess the structure of Problematic Digital Media Use (PDMU). The overarching research objective (ORO) is to determine the structure of PDMU and establish its alignment with the behavioural addiction model. To achieve this, the project sets forth four specific objectives: firstly, to identify the manifestations of Internet Gaming Disorder (IGD); secondly, to delineate the manifestations of Social Media Addiction (SMA); thirdly, to explore the interactions between the symptoms of SMA and IGD and their impact on comorbidity and well-being; and fourthly, to develop strategies for clinicians to manage digital media use effectively, thereby maximizing positive outcomes and minimizing negative effects. Research questions: To achieve the research objectives, a series of research questions have been formulated to guide both the overall investigation and the specific areas of interest. The overall research question (ORQ) asks, “What is the structure of PDMU, and does it support the behavioural addiction model?” This is complemented by specific research questions focused on the nuances of digital addictions: (SRQ1) “What are the expressions of Internet Gaming Disorder and how do they relate to wellbeing?”; (SRQ2) “What are the expressions of Social Media Addiction and how do they relate to comorbid addiction?”; (SRQ3) “In what ways do the symptoms of Social Media Addiction interact among themselves and influence comorbid distress, both cross-sectionally and over time?”; and (SRQ4) “In what ways do the symptoms of Internet Gaming Disorder interact among themselves and influence comorbid distress, both cross-sectionally and over time?”. Methods: To address the specific research questions, this PhD project presents four research studies using three different datasets. Each employed survey data gathered from archival datasets in the case of empirical study one [n = 1032, Mage = 24, SDage = 7, males = 503 (48.7%), females = 529, (51.3%)], and through this projects own data collection in the case of empirical studies two [n = 968, Mage = 29.5, SDage = 9.36, males = 622 (64.3%), females = 315, (32.5%)], three and four [n = 462, Mage = 30.8, SDage = 9.23, males= 320 (69.3%), females=134, (29%)]. In empirical studies one and two, participants were measured on their experience of IGD and SMA symptoms respectively, before latent class analysis was undertaken to identify any homogenous subgroups of participants within the data and examine how they experienced IGD/SMA, profiling IGD and SMA experience as per SRQ1&amp;2. Subsequent chi-square analyses for empirical study one and ANOVA analyses for empirical study two were employed to fulfil the second conditions of these questions, examining whether any identified subgroups also differed in terms of their experience of risk factors and comorbidities. In empirical studies three and four, participants were measured on their experience of IGD and SMA symptoms respectively, with their experience of distress measured secondarily. Subsequently, longitudinal network analysis was undertaken to determine how each symptom of IGD/SMA respectively interacted with eachother, answering the routes by which they influenced eachother, and how IGD/SMA interact with distress, both cross-sectionally and across time answering SRQ3&amp;4.
 Results: For both IGD and SMA in empirical studies 1 and 2, distinct, severity subgroups of symptom experience were discovered and their associations with numerous indicators of wellbeing assessed. Social engagement was negatively associated with higher risk classes of IGD. Furthermore, a hierarchy of substance/behavioural addictions associations with SMA risk class was identified, with internet and shopping addiction bearing the strongest positive association with high SMA risk class. This both established concurrent validity and provided insights into the nature of PDMU fulfilling the ORQ. In empirical studies 3 and 4, Both the IGD and SMA symptoms formed stable networks cross-sectionally and longitudinally, distinct from distress, but linked to it via mood-modification. These results allow for more granular examination of the relationship between varying symptoms of IGD and SMA, and their association with distress, allowing for examination of the nature of PDMU answering the ORQ. Conclusion: The results of this PhD project support the validity of the behavioural addiction conceptualization of problematic digital media use (PDMU). Differing symptoms show greater predictive validity across internet gaming disorder (IGD) and social media addiction (SMA), with mood modification serving as the linking symptom to comorbid mental illness. Specifically, empirical studies 1 and 2 identified distinct expressions of IGD and SMA, respectively, with varying severity levels. Results suggest a single, unitary behavioural addiction model for PDMU. Additionally, empirical studies 3 and 4 found that symptoms of SMA and IGD cluster more tightly amongst themselves than with distress, contradicting theories of them being secondary symptoms. Despite fluctuations in mean levels over time, both IGD and SMA remain stable in symptom presentation, underscoring their interconnected nature. Overall, these findings enhance our understanding of PDMU and reinforce the behavioural addiction model in its context. Originality/value: This PhD project provides a novel, comprehensive examination of PDMU by integrating profiling, network modelling, and longitudinal analysis. The findings support the behavioural addiction model, demonstrating that IGD and SMA are distinct yet interconnected behavioural addictions with stable symptom networks and specific pathways to distress. By addressing long-standing debates, this research contributes to the theoretical understanding of PDMU and equips clinicians with actionable insights for treatment and prevention. These results have implications for clinical practice, policy development, and the broader understanding of how digital media impacts mental health.