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The Relationship Between Cognition and Media Behavior

October 17, 2018

Matthew Cain, Research Psychologist


Matthew Cain, PhD

Research Psychologist, U.S. Army Natick Soldier Research, Development, & Engineering Center; Visiting scientist in the Gabrieli Lab, MIT Department of Brain and Cognitive Sciences

Susanne Baumgartner, PhD

Susanne Baumgartner, PhD

Assistant Professor and Researcher, Amsterdam School of Communication Research, ASCoR, Center for Research on Children, Adolescents, and the Media, University of Amsterdam

Daphne Bavelier, PhD

Daphne Bavelier, PhD

Professor in the School of Psychology and Education Sciences, Director of the Brain and Learning Laboratory, University of Geneva, Switzerland

Jason Chein, PhD

Jason Chein, PhD

Associate Professor, Department of Psychology, Director of the Brain Research and Imaging Center, Temple University

Steve Lee, PhD

Steve Lee, PhD

Professor, Department of Psychology, ADHD and Development Laboratory, University of California Los Angeles


Dr. Bavelier: (Disclosure: Dr. Bavelier is a scientific advisor to Akili Interactive and Red Bull, and also has relationships with Riot Games and Logitech.)

Content, context, and delivery interfaces matter.  So do features of the interaction.  A recent study by Rich Meyer compared classroom learning through normal computer interaction and through a VR headset.  The VR interaction produced much more engagement, but less learning.  We need to match the technologies we use to the outcomes we seek. Even among video games, different games have different effects.

A meta-analysis has been performed on research regarding how voluntarily playing first- and third-person shooter games – action video games – impacts cognition.  Habitual action video game players showed about a one-half standard deviation improvement in cognition over those who don’t generally play a lot of video games.  In training studies, if you force subjects to play an action game, and compare them to a control group playing an active control game, there is also positive cognitive effect.  It is a smaller effect (about a third of a standard deviation), but still better than those produced by most interventions.

Action video game play changes the top-down frontoparietal network of attention.  This network becomes more efficient in the service of switching or maintaining attention depending on the task goals.  No one game component seems responsible for producing this effect.  It seems to come from the combined effect of multiple game components.  When it comes to learning and brain plasticity, game components fall into two main categories. First, enabling factors or shared factors across video games that facilitate learning, including variable entry learning; incremental learning; reward (rather than punishment); building self-mastery and self-confidence; and motivation and arousal.  Second, what we term action factors: pacing (making decisions under time constraints); load on divided attention (such a dynamic, multi-target display); flexible shift of focus; need for prediction and error monitoring; and a rich environment that prevent automatization.  Layering these game elements in the right way within an educational video game explains why it is so hard to create a good video game.

Dr. Chein: We can’t talk about media cognition unless we talk about the different kinds of media interaction in question.  Neither can we talk about cognition as a singular construct.  Instead, we need to consider how its particular subdomains may be impacted by our variable interactions with media technology.

Delayed gratification is one subdomain of cognition.  There is some correlational evidence that our digital media habits are producing a society (and more particularly, a society of children) incapable of delayed gratification.  They are immediacy-oriented and unable to plan for the future.  A lab study combined objective measures of smartphone use time and subjective reports of smart phone checking and weekly minutes on social media.  Heavier phone users were more likely to discount the value of a reward over time.

Neuroimaging is being used to look for the mechanisms behind this pattern.  It has revealed both that time spent using media correlates positively with certain specific neurological characteristics, and correlates negatively with others. There is not, however, any reliable evidence on directionality.  We don’t know if media behaviors are changing our inclination to hold out for larger, later rewards, or whether our pre-existing preference for near-term rewards is leading us to engage more with media.

Memory is another area of concern.  There is compelling, and even causally compelling, evidence that while we are engaged with digital media technologies, we are less able to form memories of experiences.  For example, the Betsy Sparrow labs study in Science showed that when people were handed information, but knew that they could access it on a computer later, they tended to remember the information’s location but not its content.  This has been described as “digital amnesia” or “the Google Effect”.  Other research shows that people who rely on GPS systems tend not to form very strong cognitive maps or learn the routes they follow.  Another study found that people who toured a museum and took pictures of certain objects remembered those objects less well than the ones they saw only with their eyes.  Despite these examples of an acute effect, there is no evidence that digital media use causes deficits in working memory or long-term memory.

Some claim that digital media use may adversely impact attention.  At least in specific cases, evidence suggests that the opposite is true.   Some video game literature supports this contention.  Research on training and multi-tasking indicates that subjecting someone to multi-task training can generalize to broader attentional performance.  Several labs have explored the use of computerized tasks to teach people how to hold information in the face of interference.  On the other side of this argument, there is correlational (and thus, non-causal) evidence that heavy media multitaskers perform less well on attentional tasks.  

Dr. Lee: Attention deficit hyperactivity disorder (“ADHD”) consists of both naturally occurring individual differences and hyperactivity and impulsivity.  More broadly, it is the latent construct reflected by the nine symptoms of inattention and nine symptoms of hyperactivity with which it is conventionally associated.  It is best conceptualized as a continuum (across which genetic and environmental influences operative continuously).  The disorder of ADHD is the quantitative extreme of this latent construct.  That being said, there are important decisions (for example, about clinical services and educational accommodations) that are contingent upon a categorical diagnosis being made. Risk factors in this area must reflect both the dimensional and categorical perspectives.   

A small, but important, meta-analysis in developmental psychology showed positive correlations between digital media usage and attention problems, and a smaller correlation with impulsivity in particular.  Longitudinal studies produced smaller effect sizes than cross-sectional ones.  Studies included in the meta-analysis also varied substantially with respect to sample, the use of co-variants, and other methodological attributes.  Nevertheless, this is a benchmark in the literature.

In a recent study of about 150 high-risk adolescents with at least one symptom of DSM-4 conduct disorder, digital media usage was inversely associated with anxiety and depression, and positively associated with ADHD and conduct problems.  (Baseline digital media usage predicted conduct and poor self-regulation, but not ADHD specifically.)  The effects were small, but significant. Note, however, that the findings were very time-sensitive. Detailed scrutiny is needed to understand the specific findings with respect to concurrent effects, effects occurring within a short period of time after digital media usage, and longer-term predictions.

Another recent study used data from about 2500 high school students in metropolitan Los Angeles to look at the prospective association between digital media usage and adolescents’ self-reported ADHD.  Any student who satisfied the diagnostic criteria for ADHD was excluded from the study.  Of the 2500 initial study subjects, 2300 were followed for 24 months.

In that study, the participants were asked to describe their digital media usage in terms of 14 different behaviors.  Their responses generated a score that reflected the frequency of each of those behaviors.  The study was controlled for youth depression, delinquency, and family history of substance abuse.  Various methodological limitations (reliance on self-reporting, absence of parent interviews, lack of norms for rating scales) limited the predictive power of the story.  It could not predict whether a student without ADHD would develop it.  It could, however, predict a discrete outcome: whether an adolescent would self-report six or more symptoms of inattention and/or six or more symptoms of hyperactivity and impulsivity.  High-frequency digital usage did positively predict positive ADHD symptom criteria status.  It also predicted the number of ADHD symptoms and their severity.

This field needs greater methodological diversity.  It needs to identify likely causal mechanisms and plausible mediators the underlie cross-time predictions.  Only then can we directly answer the question of whether the things that digital media does to children may be causing ADHD.

Dr. Baumgartner: In a 2009 study, twenty Stanford students who were identified as high media multi-taskers performed worse on various cognitive tasks than their low media multi-tasker counterparts.  This proved nothing about causation.  It only identified the fact that media multitasking is related to cognitive problems. It could be that people who already had particular cognitive problems are more likely to be media multitaskers.

A recent meta-analysis tried to replicate the findings of the 2009 study.  It found a small effect between media multitasking and some (but not all) specific cognitive processing styles; that is, potential cognitive disadvantages for some tasks, but not for others.  Some studies actually have shown positive effects.  None of them indicated anything about causality.

A longitudinal study of almost 1500 Dutch adolescents (ages 12-15) tried to do just that.  Researchers assessed study participants three times in the course of one year.  Cross-sectional analysis basically supported previous studies.  Adolescents who multitask have more attention problems, experience more distraction in academic contexts, and perform worse academically.  They also had more self-reported sleep problems.  As to the longitudinal dimension of the study, the central question was whether media multitasking would lead to an increase or decrease in problems.  A very small longitudinal effect appeared with respect to distractibility (but not grades, and only among early adolescents ages 12-13).  There was also a small adverse longitudinal effect on sleep, too, but only among early adolescent girls.

So, multiple studies provide compelling evidence of mostly negative associations between media multitasking and a wide variety of attention and cognitive processes.  They establish nothing about causation.  We must look at different content, media types, and outcome variables in our search for causal connections.  We also must look at specific individuals, because the phenomena we study are developmentally sensitive.

Dr. Cain: What needs to be done to move this science to the point where it could support recommendations for parents or teachers?

Dr. Bavelier: We don’t have the data needed to make strict recommendations.  Like doctors, we should do no harm.  Adapt and adjust to your kids.  Parents, use technology together with your kids, and talk about it. Ask them what they’re doing with their technologies, and what are the problems.  Earn trust.  

Dr. Baumgartner: Maybe we should start targeting a separate relationship, like helping adolescents to improve their self-regulation so that they can navigate in the media landscape.

Dr. Cain: Does this field’s broad reliance on self-reporting have an effect on what researchers are able to see?

Dr. Bavelier: It’s better if we can get away from self-reporting measures.

Dr. Cain: It’s hard to force somebody to do something that you think might be bad for them.

Dr. Chein: Objective reports often identify inaccuracies in subjective reports.  These arise from individual perceptions.  Nick Allen’s Ears scrubbing tool might be very helpful for pulling in information.  Apple’s newest version of iOS Screen Time component provides rich data about several different types of smartphone use (such as social media, entertainment, and productivity).  This will help researchers to understand not only how much people are using their phones, but more specifically, how they’re using them.

Dr. Cain: Neither “media” nor “cognition” lend themselves to uniform, one-dimensional definitions.  What aspect of cognition does each particular type of media impact the most?

Dr. Bavelier: For action video games, it’s attention control – to stay focused on a task, ignore potential distractions, and recover from distractions quickly.  But this is only one kind of video games.

Dr. Lee:  We think of ADHD as an individual difference trait similar to cognitive ability, height, or personality.  It’s important to make a distinction.  As to the clinical significance of cognitive measure, that distinction has to do with cognitive functioning.  If digital media usage is causal, then to what extent might be affecting actual cognitive functioning in diverse settings?  

Questions and Answers

Audience Comment: (Dimitri Christakis, MD, MPH) Contrary to what Dr. Chein said, there is a published study (by Dr. Lee) that makes the case (at least provisionally, in a longitudinal framework) for studies that show deficits in attention.  One of the strengths of that study is that it didn’t use the clinical diagnosis of ADHD.  According to the literature on executive function and attentional capacity in children, there is no threshold.  The continuous variable of attentional capacity, with no clinical cut point, is the better outcome variable.

Audience Question (Thomas Robinson, MD, MPH): Consider how hard it is to get intentionally therapeutic technologies approved by regulators, and how much easier it is for potentially harmful commercial media products to reach consumers.  In contrast to what happens with medicines, consumers bear the responsibility for proving that the things we’re discussing are harmful after they reach the marketplace.  Is there a role for regulation to confirm that something is not harmful before it’s released into the world?

Dr. Bavelier: The work being done on video games that enhance attention resulted from a chance discovery – an unexpected finding from research on brain plasticity in the deaf.  Those of us doing this work are studying video games for their potential therapeutic effects.  We know that certain components of video games are very addictive; the challenge is to extract the positive  components while leaving aside those leading to problematic use. Game developers didn’t initially know about problematic aspect of their creations, but they do now.  We need to discuss this. We need more industry people in the room to do so.  We can’t do it without them because technology is evolving too fast.

Session Materials