Supervised by: Rita Kimijima-Dennemeyer, BA (Hons). Rita recently graduated from the University of Oxford having read Psychology, Philosophy, and Linguistics. She has a particularly interest in clinical psychology, mental health policy, and the ethics of mental health treatment, and she intends to pursue a masters degree in this field.

Abstract 

The excessive use of digital media has emerged as a prominent concern in society, and has been universally recognised for the substantial changes it has caused in our daily routines and lifestyle patterns. It is worth noting that a considerable 42 percent of individuals using electronic devices report experiencing adverse effects on their mental health as a result of this technology use (American Psychological Association, 2017). Our research paper aims to address the question: does screen time truly have detrimental impacts on our cognitive abilities – specifically attention spans? We thoroughly examine the influence of digital media on four age groups: young children, older children, teenagers, and adults. Furthermore, we investigate whether excessive screen time is directly contributing to the rise of Attention Deficit Hyperactivity Disorder (ADHD) within contemporary society.

Introduction 

Attention Deficit Hyperactivity Disorder (ADHD), formerly known as Attention Deficit Disorder (ADD), has emerged as a prevalent neurodevelopmental disorder in the modern-day world. ADHD now impacts roughly 1 in 10 children in America (Centers for Disease Control and Prevention, 2021), making it the most commonly diagnosed psychiatric disorder among this particular demographic. Recent comprehensive research, however, is challenging prevailing misconceptions surrounding ADHD, emphasising its impact on individuals across all age ranges. Researchers and medical professionals are increasingly recognising that ADHD is not solely a behaviour disorder characterised by excessive hyperactivity in youth. A prior, flawed understanding of the disorder would likely portray an easily-distracted, fidgety preschooler as the typical representation of an individual with ADHD. However, the neurodevelopmental condition is now understood as a cognitive disorder that can potentially emerge during adolescence or adulthood, primarily due to the illness’ impairments of the mind’s executive functions, or self-management system, which are still maturing in young children (Brown, 2008). As individuals face increasing demands and intricate tasks later in life, those whose brains are affected by this cognitive disorder will struggle to effectively fulfil these responsibilities. 

ADHD is characterised by persistent challenges across multiple domains, including: activation, focus, effort, emotions, memory, and action (Brown, 2008). These difficulties are chronic and affect individuals in their daily lives. Individuals exhibiting traits of ADHD such as excessive inattention, hyperactivity, and impulsivity will frequently experience poor time management, severe procrastination, disorganisation, inability to sustain effort, fragmented short-term memory, and difficulty comprehending social cues or managing intense emotions (Wilens & Spencer, 2010).

If an individual undergoes a psychiatric evaluation and receives a clinical diagnosis of ADHD, a medical professional can administer treatment. Medication options may include psychostimulants such as methylphenidate and amphetamine or non-stimulants such as atomoxetine and clonidine, depending upon the patient’s body chemistry (Mechler et al., 2022). 

Wilens & Spencer (2010) reports that 2% of preschool aged children, 9% of older children, 11% of teens, and 5% of adults now have ADHD diagnoses. This recent rise in diagnosis rate can be attributed to several factors, though it is most commonly thought to be triggered by the simultaneous increase in technology use, which has introduced a fast-paced, information-bombarded nature of life. 

Parallel to the increase of worldwide ADHD diagnoses, individuals now spend an average of 7.5 hours each day looking at screens, marking a significant 6-hour increase from the 1990s (Rideout et al., 2010).  Analysts have established technology usage as leading to the following outcomes: increased excitability in children, displacement of crucial learning opportunities, poorer sleep quality, likelihood of the mind to multitask, and greater desire for immediate satisfaction (Tamana et al., 2019). This paper will investigate the nature of the relationship between rising rates of ADHD and excessive screen time, inquiring as to whether digital media is responsible for the decline of our attention spans.

Shrinking Attention in Young Children 

The increasing apprehension surrounding our daily dependence on technology is becoming inescapable, and society is witnessing a heightened level of unease for a particular vulnerable demographic: young children. It comes as no surprise that parents across the globe are increasingly concerned with addressing concerns over technology usage. 

Bearing this issue in mind, Cheng et al. (2010) conducted research on the effects of the exponential increase in screen time on young children. The study found that young children are now spending a daily average of 2.5 hours watching television, a significant jump from the 1.32 hour daily average of two decades ago. While screens were limited only to televisions in 1997, by 2014, a vast array of mobile devices began making their way into the hands of children, including but not limited to: smartphones, iPads, electronic readers, and children’s learning devices. Children aged 0-2 years now spend a daily average of 2.5 hours in front of the television and an additional 0.5 hours on mobile devices, bringing their daily screen time to approximately 3 hours.

As the prevalence of diagnosed ADHD among young children continues to increase, many individuals have begun to ask: could the exponential increase in screen-time be held accountable for this trend? 

Undoubtedly, this factor warrants careful consideration. Technology has multiplied immensely, and as we forge ahead into the future, we can anticipate the development of even more sophisticated electronic devices. Within the span of a decade, children have become exposed to a wide array of stimuli emerging from their devices. This is particularly harmful to the young mind, since these stimuli inadvertently train young children’s brains to engage in multitasking behaviours, also known as attention shifting. Such behaviours cause young children to seek instant gratification while subjecting themselves to excessive stimulation (Bhat, 2017).

Prolonged exposure to screens profoundly affects the executive functions of a child, particularly concentration and focus. Executive functions are the part of cognition that manages decision-making processes, including selecting the stimuli worthy of attention. Immersing young children in a digital world and exposing them to an abundance of stimulation places an excessive demand on their still-maturing executive functions. According to Bhat (2017), this heightened stimulation leads neurotypical children to experience an inability to focus, in a similar way to that commonly observed in children with ADHD. Consequently, the average young child becomes highly susceptible to distractions, compromising their ability to engage in long-term tasks. 

ADHD stands as the most frequently diagnosed psychiatric disorder among young children, with approximately 4.5 million official diagnoses over the past two decades. Meanwhile, countless others remain untreated. Simultaneously, technology usage and the prevalence of ADHD have undergone a parallel increase, with the disorder currently increasing at a rate of 35%. According to the Centers for Disease Control and Prevention (2021), 11% of children worldwide have received an ADHD diagnosis. 

Numerous studies have aimed to evaluate the precise relationship between screen time among toddlers (aged 0 to 3) and the occurrence of ADHD symptoms. In one study in Japan, researchers employed the Strengths and Difficulties Questionnaire (SDQ) to assess the impact of TV exposure on behavioural outcomes. The study found a positive correlation between watching television at 18 months and the development of ADHD at 30 months (Cheng et al., 2010). 

Likewise, the Chinese Longhua Children Cohort Study conducted an electronic survey that was completed by the caregivers of over 42,000 young children. Parents assessed the presence of multiple hyperactive factors in their children, such as excitability, impulsivity, restlessness, and distractibility on a scale of 0-3, with 0 being never, and 3 being very frequently. The researchers calculated the mean score of these factors and indicated that a hyperactivity index exceeding 1.5 was associated with hyperactive behaviour. The study found that longer daily screen times for toddlers corresponded to higher hyperactivity index scores and increased hyperactive behaviour. Furthermore, the study revealed that toddlers with a daily screen time exceeding 90 minutes were prone to experiencing ADHD symptoms by the age of 3 (Wu et al., 2022).

In addition to these findings, excess technology use in households affects children who have already received an ADHD diagnosis. Lo et al. (2015), for example, tested the effects of a bedroom TV on youth with ADD/ADHD. The researchers analysed data from the National Survey of Children’s Health and discovered that roughly 60% of diagnosed ADD/ADHD youths had a television in their bedroom, which resulted in a daily screen time that was greater by an average of 25 minutes. For a young child who has received a diagnosis of an attention-deficit disorder, surpassing the recommended daily limit of 2 hours of screen time can significantly exacerbate their attention and behavioural difficulties (Guram & Heinz, 2017). Due to their tendency to concentrate on stimuli that offer immediate gratification (i.e. television), parents often feel inclined to grant them extended screen time in order to provide mental stimulation (Bhat, 2017). However, this well-intended approach inadvertently deprives the child of their ability to engage in vital learning experiences and social interactions, thereby amplifying their ADHD symptoms. 

Shrinking Attention in School-Aged Children 

The issue of shrinking attention spans can be seen across developmental stages, including in children transitioning to school-age. Technology and attention show their effect on children within society, especially on their productivity and ability to work within societal constraints (Vedechkina & Borgonovi, 2021). The impacts of technology use on early development, such as its correlation with increased cases of ADHD, have lasting effects on structural organisation and neural connections. These effects carry into the classroom, and technology use continues to activate addiction pathways through the release of dopamine to give children a neural reward. Thus, technology use induces the same feeling one gets after eating a bite of food or petting a dog, effectively altering the emotional, social, and cognitive abilities of children over extended patterns of use (Haynes, 2018). With that being said, the effects of technology can be harnessed to aid in attention and learning, particularly in children within an academic environment. As technology develops, there are new resources for children that allow for individual differences and needs to be met — an educational resource that has not been available to generations past. 

Video games, television, and general technology use often go hand-in-hand with both the personal and academic lives of school-aged children today. For instance, 50% of American children watch two or more hours of television a day (Obel et al., 2004). However, it has been shown in a report by the University of North Carolina that only 10% of children who are exposed to excessive amounts of television (7+ hours) report attention issues (Foster & Watkins, 2010).  This research demonstrates the sheer amount of technology, specifically television and similar video content, that is needed to affect children and their attentional development. It is clear from this specific study that excessive amounts of technology are potential causes for shrinking attention spans, but technology use in general does not seem to have a significant effect.

Additionally, video games are often viewed as an extension of television, offering a more interactive experience. While technology provides limited active participation or engagement for children, video games offer an experience that forces users to engage in content and make decisions, while also utilising and building neural connections in the motor cortex (Vedechkina & Borgonovi, 2021).

Video games and television both have similar stimuli, including fast-moving frames and bright imagery. However, the Rochester Center for Brain Imaging concludes that the decision-making and visual attention required in video games strengthens the neural connections required for top-down information processing — that is, using old or previously encoded information to interpret new information (Bavelier et al., 2012). However, there are drawbacks to the strengthening of this specific process. Through top-down processing, a subject only relates incoming sensory stimuli with stimuli they have previously encountered (Doebel & Zelazo, 2013). This can lead to errors in cognition and thinking, such as the representative heuristic, where subjects make assumptions based on how something matches their preconceived prototype, which is based on stereotypes and information they have previously encountered and now generalise (Doebel & Zelazo, 2013). While video games may be strengthening the quick and relatively low-effort top-down processing, it may also be downplaying the importance of concentrated sensory analysis and synthesis needed in more cognitively complex situations, such as when learning a new concept in class (Doebel & Zelazo, 2013). On the other hand, visuospatial selective attention (the ability to choose and process visual information) is improved through playing video games. This is shown through the comparison of the hit rates and responses to periodic visual stimulation in children playing first-person shooter games (which require consistent movement) and more physically passive role-playing games (Krishnan et al., 2013).    

These improvements to attention can also be seen in schools. Children who moderately game (less than 1 hour per week) have more control of their cognitive activities, which leads to a decrease in impulsive or distracted behaviour in a classroom setting (Pujol et al., 2016).  However, the content of the games also greatly affects the cognitive outcomes; violent games or games that require little active engagement increase distraction and even violent behaviours in classrooms (Pujol et al., 2016). This transfer of skills (or lack thereof) most likely occurs due to activation of overlapping brain areas, particularly in areas overlapping with the frontoparietal network, motor cortex, and occipital lobe, as well as relying on what cognitive skills are being used and exercised regularly (Bavelier et al., 2012). All of these centres are involved in interpreting sensory information and synthesising it. The occipital lobe ingests and interprets visual stimuli, sending electrical impulses to the frontoparietal network and motor cortex to further create and send electrical impulses that trigger movement or sudden response (Bavelier et al., 2012). As these areas are exercised through first-person shooter and physically interactive video games, there is correlation between use of these games and ability to encode and react to incoming stimuli. This thus explains the relationship between active gaming and increased control over stimuli processing in students.

Similar to video games, short-form video content shares the features of quickly-changing frames and attractive visual stimuli such as bright colours. These features, along with the general format of quick information and entertainment, have all been correlated with the shrinking of attention, as children receive a dopamine reward while ingesting this content (Zaveri, 2023). Dopamine is often used in reward systems, such as eating or physical contact, but has also been shown to be present during social interactions (Haynes, 2018). When the brain — particularly that of a child without a developed prefrontal cortex — views short-form video content, they are rewarded with dopamine, as it is interpreted as a social interaction on a cognitive level (Haynes, 2018). 

As short-form video content, particularly the social media app TikTok, has gained popularity, it has also greatly changed attention patterns in younger generations. In a series of surveys by the Pew Research Center, it was found that 1.4 million minors under the age of thirteen use TikTok, despite the company’s age restriction which aims to restrict usage of the app in children under thirteen (Vogels et al., 2022). This type of content consists of videos that often have instant attention-grabbing stimuli, such as bright graphics or gregarious claims (Zaveri, 2023). These videos typically are three minutes or less, requiring users to quickly process information and move on (Zaveri, 2023). Consuming content on apps like TikTok has been compared to an experiment by psychologist B.F. Skinner, where rats were rewarded with food for pushing a lever (Zaveri, 2023). It was deducted that the rats made a neurological connection between the pushing of the lever and the presence of food, viewing food as a reward. The rats were observed to have spikes of dopamine whenever the food was presented, and eventually abandoned daily activities such as sleep and exercise in order to continually push the lever and receive a reward. It has been shown that these short-form videos operate on the same reward system, since there is a consistent dopamine release when absorbing the content (Petrillo, 2021). This means that children are seeking these videos as a reward, possibly disrupting other tasks, such as schoolwork, that do not guarantee the same reward of dopamine (Petrillo, 2021).

Similarly, because short-form video often operates in a ten-second to three-minute period, creators are forced to boil down large amounts of information into a very short timeframe (Zaveri, 2023). When consumed by school-aged children, this has the capacity to completely alter attention spans. When paired with the dopamine release short-form videos trigger, children adapt to only hold full attention for extremely short amounts of time. This is caused by an addiction pathway similar to alcoholism or drug use — each time one accesses short-form video content, it takes more dopamine to feel the physical effects (Vedechkina & Borgonovi, 2021).  More and more ingestion of content is required as time goes on, which in the case of short-form video, means that one needs to continue scrolling after each seconds-long video to feel a dopamine rush. Children are chasing their next dopamine release, which provides feelings of rush and reward to the entire body. In order to achieve this, they require the close-to-constant turnover of information (Vedechkina & Borgonovi, 2021). The prefrontal cortex is responsible for impulse control, but it is typically not developed until the age of twenty-one.  This causes impaired executive functioning in children, meaning that they have less control over their ability to show self-control or focus amongst distractions. When there is a significant dopamine release due to consumption of short-form video content, the prefrontal cortex of school-aged children cannot properly regulate the impulse control needed to modulate the addictive behaviours (Petrillo, 2021). An addiction to short-form media is essentially an addiction to the constant influx of information presented in the attractive content which is made available by apps like TikTok (Petrillo, 2021). When children can only receive a dopamine hit if they are constantly being exposed to new information, attention spans decrease, as they will abandon information that is not being presented quickly or attractively (Petrillo, 2021). 

The effects of video games, television, and short-term video content carry over to the classroom. As explained above, the chasing of dopamine release combined with an underdeveloped prefrontal cortex contributes to the shortening of available time and attention for the processing of academic content (Vedechkina & Borgonovi, 2021). As children absorb academic information, they utilise both working and long-term memory. Working memory has the function of using sensory information to complete a task, while long-term memory is the storage space for previously-experienced information, though information must be rehearsed to be stored in the  long-term memory, and then correctly retrieved (Cowan, 2008). As lessons and academic information often needs to be encoded into long-term memory, it is becoming increasingly difficult for students to absorb information, as long-term information processing requires maintenance and rehearsal. Children no longer have the attention spans required to process and transfer information from working memory into long-term memory, which can lengthen the amount of time required to reach the same level of performance. This was seen in a classroom study that measured the amount of times students accessed alternate forms of technology while reading an assigned passage (Vedechkina & Borgonovi, 2021). However, technology has not been seen to affect the accuracy of information absorbed, showing that while it may take longer for students to process the information, accuracy remains intact (Vedechkina & Borgonovi, 2021). 

As technology continues to improve and become accessible to the average consumer, it is clear that many children will now always have access to video games, television, and evolving forms of social media and short-form entertainment. While there are a few benefits of specific types of technology, such as educational video games, it is clear that this volume of information that children are exposed to today impacts their cognitive development and ability. This eventually impacts how they operate within their schools and societal systems when engaging in tasks that require attention and memory processing. We can see, specifically in observational classroom studies, that children are turning to technology over schoolwork and accessing social media sites, videos, and games during class time (Vedechkina & Borgonovi, 2021). As their exposure increases, the addiction pathway deepens, and children need to consume more media in order to feel the same dopamine release, impacting the amount and quality of the attention that they can give to other tasks like schoolwork, which do not offer the same dopamine reward (Vedechkina & Borgonovi, 2021). 

Shrinking Attention in Teens 

Studies show that rates of social media usage among teens continue to grow. In fact, approximately three quarters of teens own a smartphone, 24% describe themselves as “constantly connected” to the Internet (Lenhart, 2015), and 50% say they are addicted to their phones (Felt & Robb, 2016).

Surfing the Internet has become a substitute for many other activities such as reading, sports, games, etc. Thus, the lack of participation caused by Internet surfing might condition children when it comes to non-preferred tasks.

In the current age of technology, teenagers have been exposed to many platforms such as MySpace, Facebook, Instagram, Twitter and more. Teenagers used to like going out into public places and talking to their friends. Now, teens have become very addicted to social media, which could decrease their attention spans and hurt the environment around them (Humida., 2015). 

A study conducted by Kubesch et al. (2009), which focused on 7th grade teenagers from Germany, has indicated how to increase the attention spans of teenagers. The study found that physical exercise can increase a teen’s attention in the face of distraction, leading to high potential in great academic performances (Feng, 2022).

However, time spent on social media is mostly influenced by attention spans. The higher the attention span, the lower amount of time students spend on social media. Furthermore, attention span was said to have been highly correlated with factors that influence student behaviour (Paul et al., 2012). Every day new technologies are being developed and it is one of the biggest factors of global development. People are comfortable with these technologies, even though it may separate young and old people (Aziz, 2019). One study showed that heavy media users were better at multitasking than light media users (Alzahabi & Becker, 2013). This is relevant to another concern that teenagers’ abilities to multitask either online or offline could also shorten their attention spans. This indicates that technology can aid a teenager’s learning when it helps them to  reach a goal. Otherwise, if it does not help teens reach their goal, then the technology is dysfunctional and could lead to many problems.

Research has shown that 2500 teenagers with ADHD developed the disorder because of the overuse of technology. Only 5.9% were naturally born with ADHD, while 81% developed it after 24 months of the overuse of technology. The lure of social networks is high for teenagers because they are trying to build their relationships and social structures online (Zimlich, 2018).

Unfortunately, not only has digital technology decreased attention spans in teens, it has also negatively influenced their well-being. Orben and Przybylski (2019) have documented negative tendencies in well-being related to technology use in a bigger database. However, other authors have said that this relationship is so small that it could be negligible. Furthermore, a new study on the relationship between media use and academic performance among students from ages 4-18 have reported that there was no significant relationship. Moreover, there is some data that shows that video gaming in both children and teens is associated with great academic performances (Wagner & Uncapher, 2018).

Shrinking Attention in Young Adults

There are quite a few noticeable changes during development into adulthood. Often, people start or continue to crave a sense of community as they are beginning to enter university or the workforce, and they have increased control over executive functioning as the prefrontal cortex reaches maturity. In contrast to children and teenagers, young adults are engaging not only in recreational technology, but technology as a part of their education and career. This may significantly impact attention as these young adults enter society. 

Firstly, one can look towards the impact of Internet usage on young adults, who often use the internet as a resource academically and professionally. As lives in the developed world become dependent on the Internet, it has become clear that there is a connection between Internet usage and cognitive operation. 

For one, the constant flow of information provided by the Internet can significantly impact sustained attention. People using the Internet for work or school often use a form of “multimedia multitasking”, which implies that one is receiving information from many different sources — perhaps reading an article and watching a television show at the same time (Matthews et al., 2022). This concept has been shown to significantly decrease the ability to concentrate for sustained amounts of time and studies have even shown that including content such as advertisements within articles can have the same effect on attention reduction (Matthews et al., 2022). For instance, there have been observed structural changes in centres that control attention, reward systems, and impulse control, such as the prefrontal cortex, that are believed to be caused by the constant access to information that the Internet offers (El Archi et al., 2022). It was also found that adults previously diagnosed with ADHD/ADD experienced heightened symptoms when exposed to the Internet for extended periods of time (El Archi et al., 2022).  

Similarly, when looking towards online learning that is common for workplaces and universities, there is a correlation between lessened motivation and attention and increased work online (Balan & Montemayor, 2020). A qualitative survey conducted by Mapua University, asking university students to rate their affinity towards online learning, as well as their attention and motivation, showed that when university students were grouped based on their feelings towards online learning, there was a correlation between their attention and motivation levels (Balan & Montemayor , 2020). The results of this study showed that students found methods of asynchronous learning, where they could focus on one piece of stimulus at a time at their own pace, easier to focus on than a synchronous method of online learning (Balan & Montemayor, 2020). This evidence may indicate that students are able to maintain attention for longer periods of time when they can control when stimuli is presented (Balan & Montemayor, 2020).

Additionally, young adults also make up a majority of social media’s user base (Auxier & Anderson, 2021). According to the Pew Research Center, 84% of adults aged 18-29 say that they have downloaded a social media app (Auxier & Anderson, 2021). This type of media provides users with a dopamine reward; as users scroll and swipe, they get a hit of dopamine, which over time creates an addictive pathway that inhibits impulse control within the prefrontal cortex (Matthews et al., 2022). This inhibition paired with dopamine is what causes one to want to keep scrolling or open Instagram during a boring meeting, particularly in adults under the age of twenty-one, whose prefrontal cortices have yet to fully develop, making them more susceptible to dopamine hits and impulsivity (Matthews et al., 2022). When people are used to being fed information quickly and then swiping to the next set of information, it can make it incredibly difficult to maintain attention for long periods of time when information is not quickly changing or being presented attractively (Matthews et al., 2022).  

Shrinking Attention in Adults 

The influence of technology is just as relevant when considering factors that affect adult attention spans as in any other age group. Studies have revealed how frequent use of digital technology may have a significant impact — both negative and positive — on adult attention spans (Small et al., 2020). 

According to Ofcom (2022), 20% of adults spend more than 40 hours per week online (Korte, 2020). More adults are relying on smartphones and the Internet for an increasing number of tasks that would have previously been undertaken by their memory systems (appointment calendars, reminders, phone books, etc.) and other cognitive faculties (calculators, maps etc.). Several studies have investigated whether a reliance on this technology is also having a negative impact on their attention spans (Wilmer et al., 2017)​​.

Although ADHD may be more commonly diagnosed at a young age, the symptoms of ADHD persist into adulthood in roughly half of the children diagnosed with the condition (Panagiotidi & Overton, 2018). Since ADHD occurs in 2.5% of adults, it is worth considering the potentially harmful effects of extensive screen time and technology use, which has been associated with attention deficit symptoms (Faraone et al., 2021). 

Greater ADHD symptoms were reported in adults aged 18 to 70 years with problematic Internet use. However, while excessive screen time may lead to symptoms similar to ADHD, addiction to such technologies as the Internet and video gaming are currently labelled by the DSM-5 as Internet Gaming Disorder. 

Nevertheless, the evidence drawing a link between technology use and reduced attention in adults is compelling. A study on undergraduate students at Kuwait University investigated whether fear of missing out (FOMO) demonstrated by smartphone use during lectures was a predictor for attention distraction and learning disengagement among the students. Using three scales — an attention distraction scale, a learning disengagement scale, and a fear of missing out scale — the study revealed that higher levels of fear of missing out (FOMO) among students was strongly correlated with both attention distraction and learning disengagement (Al-Furaih & Al-Awidi, 2021). Another study which explored the relationship between smartphone addiction risk, problematic smartphone use, and ADHD symptoms in a sample of 273 healthy adults found that younger adults with symptoms of inattention were more likely to develop smartphone addiction (Panagiotidi & Overton, 2022).

In their study of 37 women and 17 men aged between 18 and 46, Thornton et al. (2014) discovered that the “mere presence” of a mobile phone produced “diminished attention and deficits in task-performance, especially for tasks with greater attentional and cognitive demands.” Meanwhile, Stothart et al. (2015) found that mobile phone notifications alone had a significantly disruptive effect on an attention-demanding task, even when participants did not even interact with their mobile devices. Technology has also enabled media to be consumed simultaneously; this has become known as “media multitasking” (Cain & Mitroff, 2011). Cain and Mitroff’s (2011) study proposes attentional differences between Heavy Media Multitaskers (HMMs) and Low Media Multitaskers (LMMs) arguing that LMMs were able to use top down cognitive processes to improve their performance in a singleton distractor task with low working memory demands, whereas HMMs where unable to use top-down processes to improve their performance and continued to maintain a wider attentional scope even when instructed otherwise.

Such studies continue to raise the question as to whether adults’ overuse and over-reliance on technologies such as smartphones are having a negative effect on attention spans.

The neurotransmitter dopamine is released during experiences in which people experience pleasure, such as eating delicious food, partaking in sexual activity or taking drugs. Studies have shown that winning a video game level, or hearing a notification sound from their smartphone also triggers dopamine release (Reed et al., 2015). Since the increase of dopamine in the body is more likely to reinforce behaviours, it may therefore play a prominent role in addiction to drugs, sex and even to technology (Reed et al., 2015). However, studies have also shown that significantly low amounts of dopamine in the brain are often associated with symptoms of ADHD. Kim et al.’s (2011) study revealed “reduced levels of dopamine D2 receptor availability in subdivisions of the striatum including the bilateral dorsal caudate and right putamen” in individuals suffering from Internet addiction compared with controls. This may shed some light on why playing video games or using the Internet may help to ease some of the symptoms of dopamine deficit (Nieoullon, 2002). Furthermore, over time, too much release of dopamine in the brain can cause a deficit where users experience less pleasure when they are not indulging in the activity which triggers dopamine release (such as interacting with social media or video gaming) since dopamine levels are pushed below baseline (McNamara, 2021).

However, with regards to the more mature brain, specific video games, apps, and alternative online tools have been shown to strengthen certain cognitive abilities. An ageing population will result in higher numbers of dementia sufferers. These patients are likely to have impaired memory, and will become more easily distracted due to their shortening attention spans (Hamdy et al., 2017). There has therefore been much excitement over the potential of brain training to increase cognitive function and the attention spans of older brains through technology (Shah et al., 2017). 

For instance, fMRI scans show that older adults, who are unfamiliar with the Internet and learn to utilise computer programs and video games may experience improved attention and other cognitive abilities (Small et al., 2020). This study was carried out by asking older and middle aged participants (55 to 74 years) to perform specific, mentally challenging tasks (e.g., Internet searching), while recording neural activity in activated brain areas (left inferior frontal, temporal, posterior cingulate, parietal, and occipital regions), which are responsible for controlling various cognitive functions, including memory and attention. The researchers concluded that online searching and other technological strategies can be a form of brain exercise as they strengthened the participants’ cognitive abilities (Small et al., 2020). Anguera et al. (2013) trained participants ranging from 60 and 85 years old in multitasking by playing a NeuroRacer video game, which requires participants to respond to random signals that appear while controlling a car on winding roads, testing their multitasking abilities. These technological games required the adults to employ sustained attention. They found that individuals trained in multitasking (driving and sign reading) attained higher performance scores than those achieved by the untrained 20 year old control group.

Discussion

From this research, it was found that overall, technology such as video games, television, and social media all have some sort of negative correlation with attention spans. Firstly, when looking at children, it was found that the dopamine reward system was involved with screen time and technology use. Dopamine is a neurotransmitter that plays a central role in the brain’s reward system and is vital for various cognitive functions, including attention, as well as motivation. This has the ability to create addictive pathways if repeatedly exposed to rewarding stimuli, altering attentional patterns as children seek instant gratification. Similarly, teenagers are found to have similar addictive pathways as a result of technology, but also experience large social issues as a result, such as issues with attention when talking to friends or doing homework. Though young people under the age of 21 are generally more susceptible to long-term effects — such as elevated ADHD/ADD symptoms — due to their underdeveloped prefrontal cortexes, the dopamine release associated with screen time causes adults to develop an “addiction” to the constant influx of information at their fingertips. Adults exposed to elevated amounts of screen time are also prone to developing addictive tendencies to technology, specifically in a work setting, where adults frequently media-multitask.    

To date, the link between increased exposure to technology such as screen time and ADHD is correlational rather than causal (Reed, 2019). While many researchers often compare Internet-naive participants to experienced technology users, this is arguably a confounded approach as there are many other potential variables to consider (e.g., age, gender and living situations) that cannot be controlled, all of which have an influence on behaviour and cognition (Wilmer et al., 2017). Hence, we cannot draw the conclusion that technology causes ADHD symptoms, particularly because  ADHD is also widely attributed to genetics, with a 74% heritability rate (Faraone & Larsson, 2019), rather than to the overuse of technology. The few experimental studies which have explored the relationship between technology and attention span have only investigated the short term effects on attention and cognition of technology usage in the moment, rather than long-term impacts (Wilmer et al., 2017).

Conclusion

Our research has established an evident correlation between digital media use and the prevalence of ADHD in contemporary society. This applies for all age demographics, depending on the setting, such as being in school or in a workplace. The earlier we immerse our children’s underdeveloped minds in digital media, offering them instant fulfilment, the higher the likelihood that an attention-deficit disorder will emerge as they mature. This inhibits individuals from focusing their selective attention on a particular task, as well as reduces their divided and sustained attention. Although it could be argued that immersing oneself into media-related tasks increases one’s dopamine levels, which could alleviate the dopamine deficit in individuals with ADHD, many research studies investigate how increasing one’s dopamine levels during media-related activities can lead to addiction instead. 

However, technology has not always been proven to have a negative effect. For example, multitasking has become increasingly important, especially in a work setting, as we process large sets of data at a much faster rate. Studies suggest that technology usage can yield improvements in individuals’ divided attention. Additionally, some studies have found that older adults who engage in regular computer use have better cognitive function and attention than those who do not.

Altogether, the research we have discussed suggests that in order to study the effects of technology on attention spans, we must consider the different types of attention in all age demographics.

Al-Furaih, S. A. A., & Al-Awidi, H. M. (2020). Fear of missing out (FoMO) among undergraduate students in relation to attention distraction and learning disengagement in lectures. Education and Information Technologies, 26(2). https://doi.org/10.1007/s10639-020-10361-7

American Psychological Association. (2017). Stress in America: Coping with Change – Part 2 [Brochure]. https://www.apa.org/news/press/releases/stress/2017/technology-social-media.pdf

Alzahabi, R., & Becker, M.W. (2013). The association between media multitasking, task switching, and dual-task performance. Journal of Experimental Psychology: Human Perception and Performance, 39(5), 1485-1495. https://doi.org/10.1037/a0031208

Anguera, J. A., Boccanfuso, J., Rintoul, J. L., Al-Hashimi, O., Faraji, F., Janowich, J., Kong, E., Larraburo, Y., Rolle, C., Johnston, E., &Gazzaley, A. (2013). Video game training enhances cognitive control in older adults. Nature, 501(7465), 97–101. https://doi.org/10.1038/nature12486

Aziz, S. A. A. (2019). Addiction on technology toward kids and teenagers development. Journal of Computing Technologies and Creative Content (JTec), 4(2). http://jtec.org.my/index.php/JTeC/article/view/148

Benvenuti, M., Wright, M., Naslund, J., & Miers., A. C. (2023). How technology use is changing adolescents’ behaviours and their social, physical, and cognitive development. Current Psychology, 42, 16466-16469. https://link.springer.com/article/10.1007/s12144-023-04254-4.

Bhat, J. (2017). Attention spans in the age of technology. NAMI: National Alliance on Mental Illness. https://www.nami.org/Blogs/NAMI-Blog/August-2017/Attention-Spans-in-the-Age-of-Technology 

Brown, T. E. (2008). ADD/ADHD and impaired executive function in clinical practice. Current Psychiatry Reports, 10(5), 407–411. https://doi.org/10.1007/s11920-008-0065-7

Calvert, J., & Abadia, R. (2020). Impact of immersing university and high school students in educational linear narratives using virtual reality technology. Computers & Education, 159(104005), 104005. https://doi.org/10.1016/j.compedu.2020.104005

Cardoso-Leite, P., Buchard, A., Tissieres, I., Mussack, D., & Bavelier, D. (2021). Media use, attention, mental health and academic performance among 8 to 12 year old children. PLOS ONE, 16(11), e0259163. https://doi.org/10.1371/journal.pone.0259163

Centres for Disease Control and Prevention. (2021). Data and statistics about ADHD. https://www.cdc.gov/ncbddd/adhd/data.html

Cheng, S., Maeda, T., Yoichi, S., Yamagata, Z., Tomiwa, K., & Japan Children’s Study Group. (2010). Early television exposure and children’s behavioural and social outcomes at age 30 months. Journal of Epidemiology, 20(Supplement_II), S482–S489. https://doi.org/10.2188/jea.je20090179

Ciccarelli, S. K., & Noland, J. (2013). Psychology : DSM 5 (5th ed.). Boston: Pearson.

El Archi, S., Barrault, S., Brunault, P., Ribadier, A., & Varescon, I. (2022). Co-occurrence of adult ADHD symptoms and problematic Internet use and its links with impulsivity, emotion regulation, anxiety, and depression. Frontiers in Psychiatry, 13. https://doi.org/10.3389/fpsyt.2022.792206

Faraone, S. (2021). The World Federation of ADHD International Consensus Statement: 208 evidence-based conclusions about the disorder. Neuroscience & Biobehavioral Reviews, 128(128). https://doi.org/10.1016/j.neubiorev.2021.01.022

Faraone, S. V. & Larsson, H. (2019). Genetics of attention deficit hyperactivity disorder. Molecular Psychiatry, 24(4), 562–575. https://doi.org/10.1038/s41380-018-0070-0

Felt, L.J. & Robb, M.B. (2016). Technology addiction: concern, controversy, and finding balance. Common Sense. https://www.commonsensemedia.org/research/technology-addiction-concern-controversy-and-finding-balance

Feng, H. (2022). How sports help the teens’ cognitive development (reading performance). International Journal of Scientific Advances, 3(5). https://doi.org/10.51542/ijscia.v3i5.4

Guram, S., & Heinz, P. (2017). Media use in children: American Academy of Pediatrics recommendations 2016. Archives of Disease in Childhood – Education & Practice Edition, 103(2), 99–101. https://doi.org/10.1136/archdischild-2017-312969

Hamdy, R. C., Lewis, J. V., Kinser, A., Depelteau, A., Copeland, R., Kendall-Wilson, T., & Whalen, K. (2017). Too many choices confuse patients with dementia. Gerontology and Geriatric Medicine, 3(3), 233372141772058. https://doi.org/10.1177/2333721417720585 

Humida, T. (2015) New media and network society: teens are more into social media – is that addiction? IOSR Journal of Humanities and Social Science, 20(3), 68-78. DOI: 10.9790/0837-20386878

Kim, S. H., Baik, S. H., Park, C. S., Kim, S. J., Choi, S. W., & Kim, S. E. (2011). Reduced striatal dopamine D2 receptors in people with Internet addiction. NeuroReport, 22(8), 407–411. https://doi.org/10.1097/WNR.0b013e328346e16e

Korte, M. (2020). The impact of the digital revolution on human brain and behaviour: where do we stand? Dialogues in Clinical Neuroscience, 22(2), 101–111. https://doi.org/10.31887/DCNS.2020.22.2/mkorte

Kubesch, S., Walk, L., Spitzer, M., Kammer, T., Lainburg, A., Heim, R., Hille, K. (2009). A 30-minute physical education program improves students‘ executive attention. Mind, Brain, and Education, 3(4) 235-242. https://doi.org/10.1111/j.1751-228X.2009.01076.x

Kühn, S., Lorenz, R. C., Weichenberger, M., Becker, M., Haesner, M., O’Sullivan, J., Steinert A., Steinhagen-Thiessen, E., Brandhorst, S., Bremer, T. & Gallinat, J. (2017). Taking control! Structural and behavioural plasticity in response to game-based inhibition training in older adults. NeuroImage, 156, 199–206. https://doi.org/10.1016/j.neuroimage.2017.05.026

Lenhart, A. (2015). Teens, social media & technology overview 2015. Pew Research Center. https://policycommons.net/artifacts/619187/teens-social-media-technology-overview-2015/1600266/

Li, D., Sham, P. C., Owen, M. J., & He, L. (2006). Meta-analysis shows significant association between dopamine system genes and attention deficit hyperactivity disorder (ADHD). Human Molecular Genetics, 15(14), 2276–2284. https://doi.org/10.1093/hmg/ddl152

Lo, C. B., Waring, M. E., Pagoto, S. L., & Lemon, S. C. (2015). A television in the bedroom is associated with higher weekday screen time among youth with attention deficit hyperactivity disorder (ADD/ADHD). Preventive Medicine Reports, 2, 1–3. https://doi.org/10.1016/j.pmedr.2014.11.001

Matthews, N., Mattingley, J. B., & Dux, P. E. (2022). Media-multitasking and cognitive control across the lifespan. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-022-07777-1

Mechler, K., Banaschewski, T., Hohmann, S., & Häge, A. (2022). Evidence-based pharmacological treatment options for ADHD in children and adolescents. Pharmacology & Therapeutics, 230, 107940. https://doi.org/10.1016/j.pharmthera.2021.107940

Mills, K. (Host). (2023) Why our attention spans are shrinking, with Gloria Mark, PhD [Audio podcast episode]. In Speaking of Psychology. American Psychological Association. https://www.apa.org/news/podcasts/speaking-of-psychology/attention-spans

Nieoullon, A. (2002). Dopamine and the regulation of cognition and attention. Progress in Neurobiology, 67(1), 53–83. https://doi.org/10.1016/s0301-0082(02)00011-4

Ofcom. (2022). Adults’ Media Use and Attitudes Report 2022. Ofcom. https://www.ofcom.org.uk/__data/assets/pdf_file/0020/234362/adults-media-use-and-attitudes-report-2022.pdf

Orben, A. & Przybylski, A.K. (2019). The association between adolescent well-being and digital technology use. Nature Human Behaviour, 3, 173-182 (2019). https://doi.org/10.1038/s41562-018-0506-1

Panagiotidi, M., & Overton, P. (2018). The relationship between internet addiction, attention deficit hyperactivity symptoms and online activities in adults. Comprehensive Psychiatry, 87, 7–11. https://doi.org/10.1016/j.comppsych.2018.08.004

Panagiotidi, M., & Overton, P. (2020). Attention deficit hyperactivity symptoms predict problematic mobile phone use. Current Psychology, 41(5), 2765–2771. https://doi.org/10.1007/s12144-020-00785-2

Paul, J. A., Baker, H. M., & Cochran, J. D. (2012). Effect of online social networking on student academic performance. Computers in Human Behavior, 28(6), 2117–2127. https://doi.org/10.1016/j.chb.2012.06.016

Ra, C. K., Cho, J., Stone, M. D., De La Cerda, J., Goldenson, N. I., Moroney, E., Tung, I., Lee, S. S., & Leventhal, A. M. (2018). Association of digital media use with subsequent symptoms of attention-deficit/hyperactivity disorder among adolescents. JAMA, 320(3), 255. https://doi.org/10.1001/jama.2018.8931

Reed, P. (2019). Does excessive screen time cause ADHD? Psychology Today. https://www.psychologytoday.com/us/blog/digital-world-real-world/201906/does-excessive-screen-time-cause-adhd

Reed, P., Osborne, L. A., Romano, M., & Truzoli, R. (2015). Higher impulsivity after exposure to the internet for individuals with high but not low levels of self-reported problematic internet behaviours. Computers in Human Behavior, 49(49), 512–516. https://doi.org/10.1016/j.chb.2015.03.064

Rideout, V.J., Foehr, U.G., & Roberts, D.F. (2010). Generation M2: media in the lives of 8- to 18-year-olds. The Henry J. Kaiser Family Foundation. https://files.eric.ed.gov/fulltext/ED527859.pdf

Shah, T. M., Weinborn, M., Verdile, G., Sohrabi, H. R., & Martins, R. N. (2017). Enhancing cognitive functioning in healthly older adults: a systematic review of the clinical significance of commercially available computerised cognitive training in preventing cognitive decline. Neuropsychology Review, 27(1), 62–80. https://doi.org/10.1007/s11065-016-9338-9

Small, G., Lee, J., Kaufman, A., Jalil, J., Siddarth, P., Gaddipati, H., Moody T. D., Bookheimer, S. Y. (2020). Brain health consequences of digital technology use. Dialogues in Clinical Neuroscience, 22(2), 179–187. https://doi.org/10.31887/dcns.2020.22.2/gsmall

Tamana, S. K., Ezeugwu, V., Chikuma, J., Lefebvre, D. L., Azad, M. B., Moraes, T. J., … Mandhane, P. J. (2019). Screen-time is associated with inattention problems in preschoolers: Results from the CHILD birth cohort study. PLOS ONE, 14(4), e0213995. https://doi.org/10.1371/journal.pone.0213995

Vedechkina, M., & Borgonovi, F. (2021). A review of evidence on the role of digital technology in shaping attention and cognitive control in children. Frontiers in Psychology, 12, 1-22. https://doi.org/10.3389/fpsyg.2021.611155

Wagner, A. & Uncapher, M. (2018). Minds and brains of media multitaskers: current findings and future directions. PNAS, 115(40), 9889-9896. https://doi.org/10.1073/pnas.1611612115

Wilens, T. E., & Spencer, T. J. (2010). Understanding Attention-Deficit/Hyperactivity Disorder from childhood to adulthood. Postgraduate Medicine, 122(5), 97–109. https://doi.org/10.3810/pgm.2010.09.2206

Wu, J.-B., Yin, X.-N., Qiu, S.-Y., Wen, G.-M., Yang, W.-K., Zhang, J.-Y., Zhao, Y.-F, Wang, X., Hong, X.-B., & Jing, J. (2022). Association between screen time and hyperactive behaviours in children under 3 years in China. Frontiers in Psychiatry, 13. https://doi.org/10.3389/fpsyt.2022.977879

Zimlich, R. (2018). Teenagers plus heavy screen time equals ADHD? Contemporary Pediatrics, 35(10), 36-37.