Excerpt from: “The Attention Economy: Is ADHD-Like Behavior the New Normal?”

 This document is an excerpt from an in-progress independent research paper examining the relationship between adolescent attention, ADHD-like behavioral dynamics, and contemporary digital media environments. The full manuscript is currently under development. This excerpt includes selected sections intended to demonstrate my analytical framework, engagement with neuroscience and behavioral literature, and broader research interests.

Introduction

Myself, and I’m sure others included, can relate to feeling attention fragmentation in all aspects of their lives. In high school, I can recall feeling motivated to exert myself and utilize my intelligence to its maximum. I would stay up for hours finishing school work, extracurricular projects, and use my spare time to nurture my personality in productive ways. Recently, I’ve noticed a dissonance. In many sectors of my life, whether professional, educational, or personal, my attention feels fragmented and assigned manually - only exacted when things have a time constraint or are of the utmost urgency. I don’t feel the motivation to exert my intelligence, and don’t know what to exert it upon, let alone how to convince myself to go about doing so. I associated this feeling previously to pure laziness or, at most, cognitive freeze. The kicker is, when I feel unmotivated, I know what I should be doing and even more, how to do it. The tasks just seem to stack up and I can’t seem to muster up the energy to prioritize them. I started to postulate a theory of sorts, wanting to incorporate many different areas of research that I’d touched upon in the past, but never got around to prioritizing. This paper aims to dissect “the new normal” of increasing ADHD-like symptoms in generations of teens and young adults, where they might originate from, how these behaviors manifest in the market, and what that means for the future of diagnosis and consumption.

What is ADHD

ADHD is a neurodevelopmental dissonance that involves how specific brain circuits manage attention, motivation, reward, and executive function. The two biggest systems involved in ADHD are the dysregulation of Dopamine and Norepinephrine and differences in the Prefrontal Cortex. ADHD is strongly tied to lower or inconsistent dopamine and norepinephrine signaling in key brain pathways. Dopamine regulates motivation, reward anticipation, and task initiation. With ADHD, dopamine release is usually weaker or less predictable, meaning that in practice, it would be harder to start “boring” tasks, would cause a hyperfocus on interesting tasks, and create a strong urge toward instant gratification and rapid reward-seeking behaviors. Norepinephrine, similarly, helps to sustain alertness, focus, and mental effort. In ADHD scenarios, norepinephrine pathways may not maintain stable activity, causing attention drifts, “zoning out”, or brain “freezes” - where you feel unable to conduct certain activities. In these instances, one will know what to do, but can’t seem to do it. 

The second difference is within the Prefrontal Cortex, which is responsible for executive functions, which are usually weaker or less consistently activated with ADHD. Functions such as working memory, planning and organization, emotional regulation, delayed gratification, and time perception are affected. When the activation of the PFC is inconsistent, people with ADHD might forget steps mid-task, lose track of time, feel emotions more intensely, struggle with transitions, and become a “jack of all trades, master of none” - many tasks are initiated, but few are completed. Additionally, there is substantial overactivity in the Default Mode Network - which is the “mind wandering mode”. In neurotypical brains, the task-positive network (TPN) suppresses the DMN when focusing. In ADHD brains, the DMN stays active even during tasks, causing intrusive thoughts, daydreaming, and impulsive switches. One would experience difficulty “staying in the present” and feel mentally elsewhere even when trying to concentrate. Further, there are issues within the Basal Ganglia and Motivation Loops. The Basal Ganglia help with task switching, reward sensitivity, and action initiation. With ADHD, these circuits show delayed signal transmission, overreaction or underreaction to rewards, and difficulty shifting gears between tasks. In practice, it helps to explain why beginning tasks is the largest obstacle, why a state of hyperfocus often occurs while engaged, and motivation at all feels inconsistent - “all or nothing”.

 

A Steep Increase?

I’ve observed a steep increase in these behaviors within my peers. I assumed it to be normal, which, in a way, it is, but it felt incorrect to normalize. I decided to do some research on this finding, and my ideas were vindicated. National survey data within the United States indicate that ADHD diagnoses among children have significantly grown over recent decades. In 2022, 11.4% of U.S Children aged 3-17 had been diagnosed with ADHD, which is about 7.1 Million kids, an intensive uprise compared to the 1 million diagnosed in 2016. The National Center for Health Statistics corroborates this data, their survey showing similar patterns with substantial percentages among boys and girls. A 2025 systematic review and meta-analysis of global data confirms this persistent increase in ADHD prevalence among children and adolescents among many countries over recent decades.

Of course, there are reasons to doubt the correlation of this data and the causation analysis that I’ve proposed. There are systematic reviews showing evidence of overdiagnosis, particularly in milder cases in which the benefits of diagnosis and medication may be less clear. Additionally, studies have shown that younger children relative to their classmates are more likely to be diagnosed with ADHD, suggesting that immaturity weighed at scale is sometimes mistaken for neurodevelopmental disorders. Specifically, children in the youngest month of school eligibility years were more than twice as likely to get ADHD diagnoses compared to children in the oldest months, despite identical behaviors. There is evidence that a large percentage of ADHD diagnosis in school-aged children and adolescents may be attributed to normal developmental differences due to age, about 20% being potentially misdiagnosed.

There is also research that suggests that underdiagnosis a significant issue as well, statistics showing that about half of individuals who meet ADHD criteria may never receive formal care or get diagnosed - this could be due to limited healthcare in respective regions, societal norms dictating the validity of neurodevelopmental disorders, or adult symptoms that are less disruptive or interpreted differently. Underdiagnosis as a whole is more common than overdiagnosis, especially in overlooked cases. These statistics serve as a counterfactual supplement that might help explain lower cases of ADHD in prior years, but still fails to completely discount the 11.4% increase.

iPad Kids

In the past decade, Big Tech has capitalized on and quietly taken ownership of the socialization of children. Children are online more than ever before, and these numbers continue to increase as social media becomes more accessible. On average, teens and older kids spend around 7 hours and 22 minutes per day on screens, nearly half of their waking hours. Among them, about 41% of these teens exceed 8 hours of screen time daily, with lower income U.S teens averaging around 9 hours and 19 minutes of total screen time daily. The global estimate for all ages is around 6 hours and 40 minutes per day.

Statistics show that we are spending half, if not more, than our waking lives glued to a screen. Teens are online “almost constantly”, this being a self-reported quote from nearly half of the population of U.S. teens. Among them, 63% use TikTok, 55% use Snapchat, and 61% use Instagram, according to the 2025 Pew Research Center fact sheet. In contrast to 2022-2023, teen social media usage has increased by 36%, and continues to skyrocket.

Among the many harmful implications that this has (premature insecurity development, premature health risks of substance and alcohol abuse, premature sexualization), the technological socialization of children could contribute to the steep increase of neurodevelopmental disorder symptoms. Of course, I’m not suggesting causation, but I don’t think correlation is out of the question. Large surveys are finding that higher daily screen use is linked with greater likelihood of ADHD symptoms, among anxiety and depression in kids and teens. A recent study found that children that spend more time on social media platforms that prioritize short-form content develop inattention symptoms over time, distinct from effects of television or video games. In fact, a clinical study of about 528 kids aged 6-12 found that each extra hour of short-form video use was significantly associated with an increase in inattentive behaviors, especially in younger children. Having over 2 hours a day of overall screen time is tied to scores above clinical cutoffs for ADHD-associated inattentive behavior.

The Apex Predator: Platforms

There has also been a significant upshot of digital content that inherently encourages brief, high-frequency engagement patterns that almost train fast-switching and short focus periods. Platforms like TikTok, Instagram Reels, and Youtube Shorts have capitalized on these forms of media and are characterized by their rapid, automatically advancing clips - often 15–30 seconds - designed to maximize engagement. Social platforms similarly deliver frequent notifications that fragment focus and drive task switching. The shared mechanisms across these platforms include infinite autoplay loops, variable reward schedules, algorithmic personalization, and low-friction discovery, all of which reinforce rapid attention switching and sustained engagement with minimal cognitive effort.

The Attention Economy

The attention economy that centers around engagement equates to profit, and modern social media platforms operate on this business model where more time spent means more ads served, causing more revenue. Because human attention is limited, platforms are locked in a zero-sum competition. TikTok’s For You Page exemplified the maximization of ultra-personalized, algorithm-based, short-form video content on watch time. Instagram adopted Reels to avoid losing users to Tiktok, and Snapchat adopted Spotlight to keep younger users engaged by mimicking the prior two platforms. Whichever platform produces the highest “attention yield” ultimately becomes the industry standard, forcing others to either copy or fall behind. 

Tiktok transformed the industry by proving that follow-based feeds were outdated, and that instead, content should follow the “interest graph”. This states that users don’t watch content from people they follow, they watch what the algorithm predicts they’ll like, and these algorithms become smarter with every scroll, pause, rewatch, and like. This system extends user retention, increases dopamine variability by incorporating unpredictable rewards which lead to addictive patterns, and removes friction since discovery is so automatic. Instagram’s Explore and Reels, along with Snapchat’s Spotlight, adopted the same machine-learning model because the data proved that it was the most effective way to retain users and make money. As we’ve seen, short form video is the most addictive form of media ever created, which is why it has become the industry’s core unit of attention. It delivers fast sensory stimulation, triggers repeated dopamine spikes, exploits variable reward schedules (like slot machines), requires minimal cognitive effort, and allows infinite consumption. Once TikTok proved that short-form video maximizes session length, return frequency, and advertising inventory, all platforms shifted toward that format - a classic case of convergent evolution in digital product design. 

The full manuscript extends beyond this excerpt to explore generational differences in digital media exposure, the role of the COVID-19 pandemic in accelerating attention fragmentation, and broader behavioral and market-level implications of attention dynamics. These later sections are more exploratory in nature and are intended to inform future empirical research questions rather than serve as causal claims.