Social media (SM) use has become ubiquitous in adolescent life, raising concerns about its impact on their mental health. While research has identified links between excessive SM use and negative mental health outcomes, the relationship remains complex. The authors propose a novel function-based framework and algorithm that aids clinicians in evaluating SM use, independent of platform-specific knowledge. By eliciting the patterns of engagement and social interactions, the proposed framework aims to identify associated risk and resilience factors, thereby informing screening, assessment, and intervention strategies for adolescents in this ever-growing digital landscape.
Key points
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Social media use continues to evolve rapidly, yet efforts lag in evaluating its use and understanding its impact on adolescents.
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The authors propose a function-based framework that assists clinicians in identifying specific use patterns among adolescents.
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The authors guide readers through an algorithmic approach to implement the framework and assess for individualized risk and resilience profiles.
Introduction
Caleb, a 16 year old transgender male with a history of depression and gender dysphoria presents with his family for a follow-up visit. Exchanging greetings, you quickly notice that Caleb is glued to his phone screen, oblivious to the conversation going on. As he scrolls through intricately curated TikTok videos of chiseled jaws and sculpted bodies, a Snapchat notification opens to a 5 second transient image of his school friend, interrupting this stream of perfection. This scene has become a motif in this digital revolution as more and more teens gain instant access to the Internet through their smartphones.
It is almost impossible to find an adolescent without a smartphone. A 2023 survey conducted by Pew Research Center found that almost 95% of adolescents in the United States had access to a smartphone at home. A Common Sense Media Census report showed that up to 88% of teenagers owned smartphones in 2021, compared to 67% in 2015. With over 9 in 10 reporting daily Internet usage, adolescents in the United States have been averaging 4.8 hours of screen time per day. Unsurprisingly, the percentage of teens who are online “almost constantly” has nearly doubled since 2014 to 2015 from 24% to 46% in 2023. , This digital revolution contributed to the rapid rise and adoption of SM, especially among adolescents. As you accompany Caleb to your office, you wonder to yourself: what are the implications of Caleb’s social media (SM) use?
Adolescence represents a critical period of development during which teens acquire a sense of self and foster peer-relationships. Many researchers have highlighted a possible link between this rise in SM use and the increase in prevalence of depression, anxiety, suicide, and risky behavior. , However, the strength of this association remains in question. One thing is clear: SM is here to stay. Therefore, screening for SM use patterns in adolescents is essential to developing a more nuanced assessment of their mental health and well-being.
The problem with evaluating SM use is that teens adopt platforms at a much more rapid pace compared to the development of research or clinical practice. The authors use “platform” to refer to any social media application or Web site such as Instagram or TikTok. Although the overarching trend shows a dramatic rise in SM use, a closer look at platform-specific preferences paints a more complex picture. SM giants such as MySpace and Friendster have been replaced by emerging players such as TikTok and Instagram. These new platforms influence online trends and shape real-life narratives, especially in the pediatric population. To address this problem, the authors consider a function-based framework to evaluate SM use, focused on usage patterns as well as related risk and resiliency factors. They hope this framework can guide clinical screening, assessment, and intervention in the future.
A function-based framework for understanding usage patterns
Since the 1990s, SM modalities have transformed from static Web sites into dynamic and interactive applications with functions such as image sharing. Much of the evidence examining the link between SM usage and mental health indices focuses on “screen time” as the variable mediating this relationship without accounting for other variables captured in it. Relying solely on-screen time is one dimensional and fails to consider the intricacies of their usage. A function-based framework assessment can identify similar SM behaviors across platforms yet remains generalizable and adaptable enough to survive the rapid evolution of the space.
The framework, summarized in Fig. 1 , allows clinicians to understand the most salient usage variables utilizing the questions “What? How? and Who?”. The result is a personalized usage pattern that enables clinicians to probe for potential risk and resiliency factors specific to that adolescent. In this study, we expand upon each of the variables and explain how a clinician can use this framework in depth.
What? Identifying function-based platform engagement
Identifying which platforms a teenager uses, or how much time they spend on them, is only partially helpful. Identifying SM functions provides clinicians with an anchor point to better understand adolescent online activities. While there are various SM functions, our framework focuses on the following 5: (1) social networking (SN), (2) image sharing, (3) video sharing, (4) livestreaming, and (5) messaging. For more detailed descriptions of these functions refer to Sood and Avari After identifying the platforms, a clinician can explore the functions used and content the adolescent enjoys browsing, as illustrated in Table 1 . To facilitate engagement, a clinician can and should use their computers to look up and co-watch content during the visit.
| Step 1: Identify platforms: | |
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| Step 2: Identify functions: | |
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| Step 3: Explore topics of interest within each function: | |
| Social Networking |
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| Image Sharing |
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| Video Sharing |
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| Live Streaming |
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| Messaging |
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How? The spectrum of engagement: examining social media usage behavior from scrolling to posting
The variety of activities offered by SM platforms naturally leads to the stratification of young users based on their “types of use” onto a spectrum of engagement. This continuum can be conceptualized in the bidirectional concept of consumption and contribution ( Fig. 2 ). Consumption is the process of receiving information via various forms of media such as video or images. This is analogous to passive SM use. Contribution consists of active SM use such as engagement with and creation of content, including “liking,” commenting, sharing, posting, and “going live.”
Most adolescents engage in both consumption and contribution behaviors. Consumptive SM use can take form in 2 ways: mindless scrolling and goal-directed browsing. Scrolling through a personalized homepage without purpose has been associated with negative emotions. , On the other hand, seeking out meaningful connections or content may be related to positive emotions and development. When evaluating contribution, a clinician should differentiate the extent and frequency of engagement. Reacting to and sharing videos provide a different level of social exposure than posting original content and therefore have different risk profiles. Examining ways in which adolescents interact on SM will assist a clinician in identifying risk and resilience factors associated with each type of use. Table 2 offers questions that will assist in characterizing these patterns of usage.
| General questions: | |
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| Function-specific questions | |
| Social Networking |
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| Image Sharing |
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| Video Sharing |
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| Live Streaming |
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| Direct Messaging |
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| Special Features |
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Who? Assessing relational interactions on social media
Adolescents engage in a wide range of online exchanges, ranging from intimate interactions to cursory engagements with online strangers. During these exchanges, they are actively exposed to content shaped not only by their interests, but also by the individuals they follow. As a clinician, characterizing these online interactions can shed light on how adolescents perceive themselves.
Differentiating between the types of interactions, that is, public (acquaintances, strangers) versus private (friends, family), is helpful in further stratifying risk and resilience factors associated with an adolescent’s SM use. , Lyyra and colleagues analyzed data collected from Finnish adolescents as part of the Health Behavior in School-aged Children study in 2018 and found that 22% of adolescents communicated with friends they met through the Internet and 13% reported online communication with complete strangers. In that same study, the authors discovered that online communication with people adolescents know in person was correlated with positive outcomes while communication with online friends or strangers was negatively associated with well-being indicators measured such as loneliness, and problematic SM use. Conversely, some authors argue that, particularly in marginalized populations such as lesbian, gay, bisexual, transgender and queer (LGBTQ) adolescents, interacting with strangers in supportive communities provides a safe space to learn more about themselves, form friendships, and gain information about sexual health. Further research is required to evaluate the complex relationship between these interactions and mental health indices. Table 3 offers questions that aid in exploring these relationships.
| Passive Use | Active Use | |
|---|---|---|
| Social Networking |
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| Image Sharing |
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| Video Sharing |
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| Live Streaming |
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| Messaging |
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