Introduction: Interactive Media and Mental Health

The worldwide increase in mental health problems among adolescents and young adults over the last several decades has often been attributed to the use of internet and interactive screen technologies, such as social media and video games [1, 2]. In response to such discourse, society, popular media, and even some scientists have often adopted a polarized approach which either consists of pathologizing technology and screen use (e.g., equating screen-based activities to “digital drugs”) or of dismissing concerns about screen use as manifestations of moral panic (e.g., viewing psychological problems related to screen-based activities as social constructions). However, neither of these approaches captures the complexity of digital behaviors and their relationship with mental health. Multiple factors, including individual differences (e.g., in personality traits or coping strategies, [3,4,5,6], the nature of the impact itself [7, 8] as well as a range of mediating variables [9, 10] influence these associations). Moreover, specific algorithms, design features and affordances of digital platforms may contribute to the development of problematic uses, particularly among vulnerable individuals [11,12,13].

Meta-analyses of the relationship between video gaming (VG) and mental health point to significant heterogeneity in moderating influences [14, 15]. This heterogeneity is not inherently problematic – it reflects the diverse ways in which mental health challenges manifest and are influenced by different personal and contextual factors. Gaming motives, self-regulation skills, and the benefits individuals seek from gaming often outperform time spent gaming in predicting both risk and resilience (e.g., [3, 4, 16]). A recent meta-analysis of longitudinal studies [17] highlighted that while gaming time is often associated with problematic gaming behaviors, such as internet gaming disorder (IGD) [DSM-5], other factors – particularly personality traits acting as risk factors (e.g., neuroticism) or protective factors (e.g., conscientiousness) – play an important role. Interestingly, aspects like parent–child relationships appeared to have a comparatively weaker influence. However, these findings warrant caution, as many effect sizes were extracted from zero-order correlations averaged over time, raising questions about the temporal relationships and thus potentially the causal nature of these influences.

Depression and anxiety have been shown to moderate the relationship between gaming intensity and disordered gaming, potentially intensifying gaming’s emotional rewards and contributing to the development of disordered use [18]. Although incorporating such mental health variables substantially improves the explanatory power of predictive models, clinical practice places less emphasis on explained variance and more on the diagnostic validity and clinical utility of assessment tools like the IGD criteria [19] — particularly their ability to distinguish pathological gaming from high engagement [20, 21].

Similar conclusions emerge for social media (SM). A recent review shows that time spent on SM does explain 6% of the variance in problematic use [22]. Motivations, activities, and behaviors are better predictors of SM effects than frequency or time spent [22,23,24]. Evidence for a causal association between time spent on SM and psychological ill-being is weak and heterogeneous, with cross-sectional effect sizes ranging from −0.57 to + 0.59 [25]. While the clinical utility and diagnostic criteria of social media use disorder has yet to be fully recognized [26], the ICD-11 criteria for Gaming Disorder may be a good starting point to develop a standardized conceptualization [27,28,29].

The scarcity of causal evidence is unsurprising since truly causal designs would be unethical; one could not force someone to use interactive media if negative consequences (e.g., addictive or compulsive usage) were predicted. Standard scientific tools can only indirectly probe that putative relationship between screen time and mental health [30] and underlying risk factors, such as sleep disturbances [31], which have been recognized as the strongest predictor of mental illness in adolescents [32]. We must confront the ambiguity of the causal question itself and the difficulty of defining a reference group to determine the harmfulness of digital media use behaviors [33]. Beyond causality, however, screen time remains the most consistent and strongest risk factor for problematic interactive media use, though not the most relevant conceptually and methodologically [34]. High involvement, however, is not equal to problematic involvement [35] and reducing screen time may not effectively address the issue of problematic usage and its negative impact on mental health [36,37,38].

Despite their appeal, restrictive policy responses like China’s playtime mandate to reduce heavy gaming [38], the Belgian loot box regulation [39], and, more recently, smartphone school policies in Australia [36], see also [40] have shown limited, but not zero, efficacy so far. While more time may be needed to assess their impact, the “prohibition” approach has mostly failed when applied to media use [41], calling for more personalized strategies. Although effective at reducing screen time [42,43,44,45], some strategies have not improved mental health in excessive gamers [38]. A recent randomized controlled trial found that screen time reductions in students were associated with small to medium improvements in depressive symptoms, stress, sleep quality, and well-being, but both screen time and mental health increased and returned to baseline after the intervention [46]. Current evidence on “digital detox” interventions is limited and inconsistent [47], with no consensus on a precise definition and great variability in effectiveness. Interventions focused on reducing, rather than eliminating, social media or smartphone use appear more beneficial for well-being. However, effects differ by outcome type, duration, and individual factors such as age, gender, and context. Given these variations, high-quality, empirical research is needed to determine when, for whom, and why/how "digital detox" interventions are effective.

Our goal is to provide a narrative review of the literature on digital media effects, focusing on relevant psychological constructs, self-determination theory and the dual model of passion, and discuss their impact from a social and ecological perspective.

Methods

This selective narrative review of the literature involved the following steps. The first step involved formulating and refining the research question and objectives. This allowed us to converge on 3 major constructs of interest: (a) self-determination theory and basic needs satisfaction, (b) the dualistic model of passions and (c) environmental/contextual influences, which were approached from an ecological systems’ perspective. Then, the first author conducted a literature search using keywords related to the constructs considered. References considered as relevant by the first author were further reviewed and summarized. Additional references were then identified and added by the other authors, based on their knowledge and their own literature searches.

Results

Addictive vs. Problematic Use

Although it is important to differentiate between problematic and addictive usage patterns, it is not an intuitive distinction. Addictive use is a clinical construct referring to the repetitive or continuous engagement in pleasurable (but unnecessary) behaviors despite harmful consequences and often associated with symptoms of loss of control and functional impairment. This has been reflected in ICD-11 categorization of addictive behaviors among addictive disorders category, namely for Gaming disorder and Gambling disorder. Addictive pattern of use implies neurobiological mechanisms related to reward processing (reinforcement learning, habit formation), and impulse control. Motives can be driven sometimes by maladaptive coping, poor self-regulation, or situational stress [48]. Problematic use is an intermediate pattern of dysfunctional use not reaching diagnostic requirement for a disorder. It refers to patterns of use that can interfere with or impair healthy function, such as sleep, nutrition, relationships, and productivity. Depending on the field of practice or research or population age groups, there can be reluctance to use the term addiction, and over-pathologization of digital media is to be carefully considered and avoided. Problematic use is a term that is also preferred to account for excessive online behaviors not conceptualized as addictive behaviors (e.g., when an over-involvement in social network sites or videogames is a maladaptive coping behavior displayed to face psychological distress or unmet needs) [49, 50].

Understanding Interactive Media Use in Ecological Context

Similar conclusions have been reached regarding the effects on well-being of time spent in non-technology-mediated activities. Working long hours has been linked to poorer well-being, however, this relationship varies considerably across working populations based on the nature of the job, working conditions, worker age, gender, and other factors [51]. Isolating causal influences is particularly difficult because working hours are moderated by complex, mostly bidirectional and non-linear relationships with both individual differences in self-determination goals [52] and social factors [53], which differ across work contexts [54]. In screen media use, a similar contextualization appears to be needed.

Several recent studies point to a non-linear relationship between interactive media consumption and mental health, with an inverted U-shape where moderate consumption shows some benefits but sustained consumption shows negative impact [55]. A challenging feature of this work is that the inflection point, the transition from beneficial to harmful, varies across types of media and online activities (1h/day for smartphone vs. 2-3 hours/day for video games, [51]) and effects (well-being vs depression vs anxiety). Moreover, the strength of the relationships may vary over time and depend on the time unit of the analysis (e.g., days, weeks, months, or years, [52, 53]).

An important shift is to reconceptualize problematic interactive media use as a problem of behavioral regulation rather than as an addictive disorder. This aligns with recent proposals suggesting that specific design features contribute to dysregulated usage [11, 12]. Although many clinicians would agree that the addiction formulation from the 1990s is no longer (and may have never been) accurate or productive in today’s digital ecosystem, problematic media use patterns remain generally conceived as addictive disorders, requiring prevention and intervention on the harmful activity (e.g., playing video games or using SM). In many cases, problematic interactive media usage can be viewed as a coping mechanism to alleviate negative affective states (e.g., anxiety, depression, loneliness) or to compensate for frustrated needs [54,55,56,57]. In those situations, targeting the technology-mediated activity would result in ineffective or unnecessary treatment [58,59,60]. 

Clinicians feel ill-prepared for helping the increasing number of tweens and teens struggling with problematic interactive media use. The addiction model is currently the most influential when it comes to diagnose, assess, and treat problematic online behaviors. Moreover, gaming disorder is defined as an addictive disorder in ICD-11. However, alternative etiological models are also being considered to account for problematic online behaviors (Obsessive-compulsive disorders, impulse-control disorders, or simply maladaptive coping strategies) [61,62,63]. Detractors of the addiction model have argued that this model can create a dilemma when the goal of addiction treatment is abstinence or reduced/controlled use. Since interactive media has become a necessary tool for effective functioning and an important resource for leisure, learning, connecting, and communicating, over-pathologizing digital products should be avoided (for an example on gaming, see [64]). Thus, even the restriction of specific devices, applications, or platforms, is not a realistic or desirable option. Healthcare and education trainees need the necessary information to recognize problematic interactive media use sufficiently early, and strategies to empower the youth to self-regulate and use interactive in media productively and healthily ways.

We argue that the relationships between media use and mental health will only be unraveled by taking into consideration behavioral motivators and social contexts [3, 65,66,67], as well as their temporal dynamics [68]. For example, a depressed teen with efficient self-regulation skills may be less affected by negative SM feedback than one with weaker self-regulation skills; creating different paths to both problematic use and potential intervention points [69]. Those relationships are supported by longitudinal studies highlighting how different personality traits in youth (e.g., disinhibition) influence the development of problematic interactive media behaviors later on [70].

Understanding Motivators and Social Contexts of Screen Use

Motivations driving what we choose to invest our time and attention on can be understood through the self-determination theory (SDT, [71]). Individuals tend to favor activities that satisfy their needs of autonomy, competence, or social relatedness, each of which contributes to their personal growth and self-development. If need satisfaction can motivate individuals to spend more time on some activities, does it also contribute to increased problematic activities or behaviors? A second framework that helps differentiate high consumption from problematic use is the dualistic model of passion [72, 73], which distinguishes between “harmonious” and “obsessive” passions. In a nutshell, people with harmonious passion have a strong connection with an activity that typically fulfills basic needs like those conceptualized in the SDT but does not interfere with other aspects of their lives. In contrast, people with obsessive passion pursue an activity in uncontrolled and inflexible ways to compensate for frustrated needs, ultimately promoting negative consequences and functional impairment [74]. Recent work by Infanti et al. [75] supports the idea that (1) these two types of passion are helpful at the user level (to differentiate types of gamers) and (2) at the variable level (to map types of passion to different symptoms). At the user level, this framework allows better differentiation between risky gamers (who showed high levels of both harmonious and obsessive passion), engaged gamers (who showed predominantly harmonious passion), and casual gamers who scored low on both types of passion. Phenomenological analysis of interviews also suggest that while players seeking medical support for their gaming report that gaming interferes with what they want to be, do or have throughout life, professional e-sport players instead report their gaming to be integrated into self throughout life [76]. At the variable level, harmonious passion was positively associated with manifestations such as salience, mood modification, tolerance (which are typically not able to distinguish engagement from addiction, see [20, 35], and low levels of conflict, while obsessive passion was more strongly associated with manifestations of withdrawal, conflict, and relapse/loss of control).

Although time spent remains, unsurprisingly, the most consistent and strongest correlate of problem gaming, it provides little in the way of an explanation. Numerous studies have documented reciprocal links between time spent gaming and problem gaming (or life satisfaction), with motivation and basic needs satisfaction, acting as moderating factors [77,78,79]. For example, gaming to escape reality seems to be associated with longer play times and more problematic behaviors [57, 72, 73], suggesting that the mental health problems preceded the onset of problematic use, and that gaming was used as a coping strategy to self-soothe — recognizing in some studies PG symptoms sometimes precede the onset of mental health problems(e.g., [80]). Similarly, reciprocal links between social media use and well-being [8] can be better understood by relating particular behaviors and design features that promote these behaviors with basic needs satisfaction [4, 11, 81]. For example, social media can help teens explore their sense of identity and build more autonomy from their parents [82]. Similarly, gaming for social compensation may have mitigated the experienced emotional distress for some people during the COVID-19-related lockdown [83, 84]. 

Similar patterns of findings have been observed at work: job characteristics (e.g., salary, hierarchy, work-life balance, job demands) and social identity factors (e.g., feedback and expectations from peers, family, cultural values and peers) have been shown to affect both working hours and well-being (i.e., job/life satisfaction, [54], including similar debates surrounding the concept of “work addiction” [85]).

Spending more time in one activity often leads to higher sense of autonomy, higher competence, and typically feeds social relatedness through stronger in-group bonding by being part of a community. The critical question here is why investing time in some consuming activities (e.g., academic research) is conducive to identity building/well-being, while for others (e.g., social media or video game use) it may hinder identity formation and contribute to ill-being? In the next section, we highlight the role of societal values and norms in shaping how the choice of activities bears on self-image [86].

Social Values and Context

Social, environmental, and contextual factors strongly influence behavior and well-being in many domains. Social values and norms shape individuals’ behavior over time [87] (see also [88]’s comment on [89]). Access and quality of education and health systems, neighborhood and built environments, and social and community context all greatly contribute to well-being. In light of this, it might be that excessive involvement in screen-based activities for some be a result of that multi-determined ecosystem. For example, children having access to a screen in their bedroom tend to consume greater total amounts of screen media, which displaces time from other activities, promotes exposure to violent content [90], and contributes to sleep disturbances [91]. Yet, high screen time may instead reflect meaningful engagement with digital tools for learning, social connection, and self-expression, particularly in environments where corresponding offline activities are limited or unequal and in a social context that is becoming heavily based on online presence. This highlights the necessity of going beyond time spent on screen vs non-screen activities and the importance of considering social values, in addition to individual differences and contextual factors, to understand their effects.

An argument can be made that social and environmental influences are fundamentally misaligned for adolescents and young adults when it comes to media use. Teens frequently find themselves navigating between different social circles—each with its own, often contrasting views and expectations about how digital media should be used [92]. At the broadest level, society tends to focus on the risks of interactive media use for young people, shaped by cultural and moral concerns. Within families, schools, and communities, the conversation often centers around control and restriction. This is largely driven by the widening intergenerational digital divide [93]. Parents and children frequently hold conflicting views about interactive media. Many adults are skeptical or uneasy about platforms they do not use or even understand; video games are often dismissed as a waste of time. Watching young people navigate the digital ecosystem can be both fascinating and anxiety-inducing for adults. While these generational divides have long existed, they have become even more pronounced in today’s fast-evolving digital landscape, generating mixed feelings, especially among older adults [94]. Naturally, anxieties and potential resistance can occur with the adoption of emerging technologies [95].

To progress and thrive in the digital ecosystem that we have, we must change how we talk about interactive media—recognizing the real benefits it can offer, even as it challenges some traditional values. At the same time, it is important to acknowledge that it is adults who are building digital tools that can exploit young users’ vulnerabilities. Yet, children and adolescents often get blamed for using these tools in a way that is not perceived as acceptable and are expected to regulate their screen time responsibly. This highlights the need to rethink our societal values, not just in how we educate about media use, but also in how we design technologies to optimize their positive effects on developing minds and behavior [96, 97].

Toward Socially Responsible Design and Education about Interactive Media Use

Interactive media have transformed social interactions, increasing both interpersonal connectivity and exposure to predatory design features and potential harm. Many platforms exploit adolescents’ heightened sensitivity to social rewards and impulsivity through mechanisms such as infinite scrolling, algorithmic reinforcement, and variable rewards, which potentiate compulsive use [11, 91, 92]. Social network “Likes” have been suggested to promote unhealthy social comparison [98], while loot boxes mimic gambling mechanics, increasing engagement and self-reported anxiety [99]. Although regulatory measures such as China’s playtime mandate have had mixed results [39, 42], transparency among technology developers, child health experts, and consumers remains crucial to ensuring developmentally optimal design, while still putting consumer protection at the center [100].

Another key lever is that of education. Countries like France, Finland, Canada, and Singapore have implemented school-based programs that foster critical thinking self-regulation and informed media engagement. Meta-analyses show that such structured interventions can improve resilience and reduce problematic interactive media use behaviors, especially when started early and supported by parental involvement [101, 102]. Media literacy interventions have been shown to improve critical thinking, media knowledge, and self-regulation skills, with small-to-moderate positive effects across various populations [103]. To be most effective, formal media literacy programs must start early, around the age of 5, when children begin to show executive attention better and the ability to separate reality from fantasy. As they start formal schooling, they can naturally adapt to developmental and technological changes, supported at home by parents modeling and fostering the development of healthy media use habits. By pairing ethical technology design with evidence-based education, we can empower youth to navigate digital spaces more intentionally and reduce the risk of harm. Such programs can complement and synergize with programs such as the Bootstrap Project (https://www.internetandme.eu/), which is co-constructed with youth from different cultures and aims at developing evidence-based strategies to enhance critical skills such as emotion regulation, inhibitory control, social competence, or stress regulation [104, 105].

Conclusion: Moving Forward

To move beyond polarized narratives about digital media, we must adopt a nuanced understanding rooted in established psychological frameworks. Self-Determination Theory (SDT) highlights how autonomy, competence, and relatedness shape motivations for media use. The Dualistic Model of Passion helps distinguish between healthy (harmonious) and unhealthy (obsessive) engagement. These motivations, in turn, influence identity formation—especially during adolescence, a critical period of self-concept development.

Furthermore, an ecological perspective reveals that individual behaviors are embedded within layers of influence—family, peers, educational institutions, and societal norms—all of which shape how digital media are used and experienced. Addressing mismatches between youth needs and these social expectations is essential for fostering resilience.

Future efforts should prioritize aligning interactive media use with core psychological needs, supporting harmonious passion, and designing responsible, empowering digital environments. Through such integrative approaches, digital tools can be harnessed to support rather than undermine well-being and identity growth.

Key References

  • Orben A, Przybylski AK, Blakemore SJ, Kievit RA. Windows of developmental sensitivity to social media. Nat Commun. 2022 Mar 28;13(1):1649.

    • A groundbreaking study highlighting sensitive developmental periods when social media use may particularly influence adolescent mental health, shaping future developmental psychology and policy.

  • Flayelle M, Brevers D, King DL, Maurage P, Perales JC, Billieux J. A taxonomy of technology design features that promote potentially addictive online behaviours. Nat Rev Psychol. 2023 Mar;2(3):136–50.

    • This paper proposes a comprehensive taxonomy of persuasive digital design features contributing to potentially addictive behaviors, providing a critical framework for both research and policy.

  • Zhuang X, Zhang Y, Tang X, Ng TK, Lin J, Yang X. Longitudinal modifiable risk and protective factors of internet gaming disorder: A systematic review and meta-analysis. J Behav Addict. 2023 Jun 29;12(2):375–92.

    • Identifies modifiable traits such as personality and self-regulation as key in the development of internet gaming disorder, supporting more personalized interventions.

  • Marciano L, Lin J, Sato T, Saboor S, Viswanath K. Does social media use make us happy? A meta-analysis on social media and positive well-being outcomes. SSM - Mental Health. 2024 Dec 1;6:100331.

    • Offers an updated and balanced meta-analysis, challenging simplistic narratives and supporting more nuanced assessments of social media’s effects on well-being.

  • Marciano L, Ostroumova M, Schulz PJ, Camerini AL. Digital Media Use and Adolescents’ Mental Health During the Covid-19 Pandemic: A Systematic Review and Meta-Analysis. Frontiers in Public Health [Internet]. 2022 [cited 2022 Sep 3];9.

    • Synthesizes evidence from the pandemic era to reveal how context and vulnerability moderate the mental health impacts of digital media use.

  • Santos RMS, Mendes CG, Sen Bressani GY, de Alcantara Ventura S, de Almeida Nogueira YJ, de Miranda DM, et al. The associations between screen time and mental health in adolescents: a systematic review. BMC Psychology. 2023 Apr 20;11(1):127.

    • Offers a comprehensive synthesis showing that screen time alone is a poor predictor of mental health outcomes without considering mediators and moderators..

  • Hill ED, Kashyap P, Raffanello E, Wang Y, Moffitt TE, Caspi A, et al. Prediction of mental health risk in adolescents. Nat Med. 2025 Mar 5;1–7.

    • This study uses large-scale longitudinal data to identify predictive markers of adolescent mental health, emphasizing the role of digital behaviors alongside sleep and emotion regulation.

  • Lemahieu L, Vander Zwalmen Y, Mennes M, Koster EHW, Vanden Abeele MMP, Poels K. The effects of social media abstinence on affective well-being and life satisfaction: a systematic review and meta-analysis. Sci Rep. 2025 Mar 4;15(1):7581.

    • Reviews the effectiveness of “digital detox” interventions, showing mixed and often limited mental health benefits, underscoring the need for better targeted strategies.

  • Zendle D, Flick C, Gordon-Petrovskaya E, Ballou N, Xiao LY, Drachen A. No evidence that Chinese playtime mandates reduced heavy gaming in one segment of the video games industry. Nat Hum Behav. 2023 Oct;7(10):1753–66.

    • This empirical study critically evaluates a major national policy intervention, finding limited impact, and suggesting the need for more nuanced, context-sensitive regulatory approaches.

  • Marciano L, Jindal S, Viswanath K. Digital Detox and Well-Being. Pediatrics. 2024 Oct 1;154(4):e2024066142.

    • Highlights that while reducing digital use can offer short-term benefits, sustained well-being improvements depend on deeper behavioral and motivational factors.

  • Giardina A, Schimmenti A, Starcevic V, King DL, Di Blasi M, Billieux J. Problematic gaming, social withdrawal, and Escapism: The Compensatory-Dissociative Online Gaming (C-DOG) model. Computers in Human Behavior. 2024 Jun 1;155:108187.

    • Introduces the Compensatory-Dissociative Online Gaming (C-DOG) model, a new framework that explains problematic gaming as a continuum from adaptive "active escapism" to maladaptive "dissociation," emphasizing how individuals use gaming to cope with unmet psychological needs in the physical world. It highlights escapism as a key psychological process distinct from immersion or avoidance, offering clinical insights for assessing and treating gaming-related issues, including social withdrawal conditions like hikikomori.

  • Liu Y, Marciano L. Appnome analysis reveals small or no associations between social media app-specific usage and adolescent well-being. Sci Rep. 2024 Dec 28;14(1):30836.

    • Uses granular app-level data to debunk overgeneralized claims about social media’s negative effects, emphasizing context and content over total time.

  • Infanti A, Valls-Serrano C, Perales JC, Vögele C, Billieux J. Gaming passion contributes to the definition and identification of problematic gaming. Addictive Behaviors. 2023 Dec 1;147:107805.

    • Demonstrates how distinguishing between obsessive and harmonious passion provides better diagnostic clarity in identifying problematic gaming.