Panel The Relationship between Cognition and Media Behavior

Panel: The Relationship between Cognition and Media Behavior Matthew Cain, Ph. D Center for Applied Brain and Cognitive Sciences, Tufts University & U. S. Army Daphne Bavelier, Ph. D Brain and Learning Laboratory, University of Geneva, Switzerland Jason Chein, Ph. D Neurocognition Laboratory, Temple University Steve Lee, Ph. D ADHD and Development Laboratory, University of California Los Angeles Susanne Baumgartner, Ph. D Amsterdam School of Communication Research, University of Amsterdam

Melina Uncapher, Ph. D, Education Program at Neuroscape, University of California San Francisco

Media consumption and cognitive fitness Not all media are created alike! Media type – SM vs VG Content matters Context matters Delivery interface matters Features of the interaction matters

A chance discovery (2003) – First/Third Person Shooter Games C. Shawn Green and Bavelier, 2003 Nature Green and Bavelier, 2003, Nature

Benoit Bediou Meta-analysis of action video games impact on cognition (Jan 2000 - Dec 2015) ü What is the cognitive profile of habitual action video game players (N=3789; K = 90)? Hedges’ G = 0. 55 (in children and young adults) Bediou, Adams, Tipton, Meyer, Green and Bavelier, 2018 Psych Bulletin

ACTION SOCIAL Bediou, Adams, Tipton, Meyer, Green and Bavelier, 2018 Psych Bulletin

Benoit Bediou Meta-analysis of action video games impact on cognition (Jan 2000 - Dec 2015) ü What is the cognitive profile of habitual action video game players (N = 3789; K = 90)? Hedges’ G = 0. 55 (in children and young adults) ü Can cognitive benefits be induced through intervention studies (N = 609; K = 21)? Hedges’ G = 0. 34 (in young adults) Impact of action versus other video games play Bediou, Adams, Tipton, Meyer, Green and Bavelier, 2018 Psych Bulletin

Neural Correlates Catch Trials Julia Focker Remodeling of the top -down fronto-parietal network of attentional control

Features of the interactivity – What’s special to interactivity in action VG? Enabling factors: • • • Catch Trials Variable entry learning (lots of entry levels - novice to expert) Incremental learning (tune task to Ss; small learning steps, level of difficulty) Reward (DA) - as opposed to punishment Self-mastery and self-confidence (5 HT) - desire to learn Motivation & Arousal (Ach) “Action” factors: • Pacing – work under time constraints • Load on divided attention: Dynamic display with many targets to attend to • Flexible shift of focus: Precise visuo-motor requirements in the context of divided attention • Need for prediction and thus error monitoring • Rich environment that prevents automatization • …. .

Media consumption and cognitive fitness Not all media are created alike! Media type – SM vs VG Content matters Context matters Delivery interface matters Features of the interaction matters Need better measures than screen time or total hours media time How to quantify and qualify media consumption

Panel: The Relationship between Cognition and Media Behavior Matthew Cain, Ph. D Center for Applied Brain and Cognitive Sciences, Tufts University & U. S. Army Daphne Bavelier, Ph. D Brain and Learning Laboratory, University of Geneva, Switzerland Jason Chein, Ph. D Neurocognition Laboratory, Temple University Steve Lee, Ph. D ADHD and Development Laboratory, University of California Los Angeles Susanne Baumgartner, Ph. D Amsterdam School of Communication Research, University of Amsterdam

Impacts likely to differ across cognitive domains • Delay of gratification • Attention and Executive Control Claim: Digital media use causes us (and our kids) to be more reward-seeking and immediacy oriented Claim: Habitual involvement with digital media weakens attentional control and diminishes attention span • Memory • Academic Success Claim: Engaging with digital devices impedes the formation of lasting memories and diminishes memory functioning. Claim: Heavier digital media involvement negatively impacts key academic outcomes Wilmer, Sherman, & Chein, 2017

Delay of gratification: DM use causes orientation toward immediate rewards Correlational evidence: Wilmer et al, under review Delay Discounting (log. K) Wilmer & Chein, 2016 Reward Pathway Self-Regulation Pathway r=. 29 Smartphone Usage (Total Time) No evidence indicates that digital media habits cause the predilection to pursue immediate rewards

Memory: DM use impedes memory formation and weakens long-term memory Evidence of acute impacts of digital media use on subsequent memory formation/retention - digital amnesia Sparrow et al. , 2011 Burnett & Lee 2005 No evidence of lasting change in the nature of long-term memory functioning Henkel, 2013

Attention: DM use weakens attentional control and diminishes attention span Experimental evidence of enhanced attention functioning with attentionally-demanding digital tasks Green & Bavelier, 2009, 2012 Dux et al. , 2009 Chein & Morrison, 2010 Correlational evidence of weaker attentional control in heavy media-multitaskers (e. g. , Ophir et al. , 2009) Evidence of lasting change in the attentional functioning? . . . Do these impacts have consequences for academic performance? . . .

Panel: The Relationship between Cognition and Media Behavior Matthew Cain, Ph. D Center for Applied Brain and Cognitive Sciences, Tufts University & U. S. Army Daphne Bavelier, Ph. D Brain and Learning Laboratory, University of Geneva, Switzerland Jason Chein, Ph. D Neurocognition Laboratory, Temple University Steve Lee, Ph. D ADHD and Development Laboratory, University of California Los Angeles Susanne Baumgartner, Ph. D Amsterdam School of Communication Research, University of Amsterdam

Attention-deficit/hyperactivity disorder (ADHD) I. Naturally-occurring individual differences in attention problems and hyperactivity-impulsivity II. Best conceptualized as a continuum (Larsson et al. , 2012) I. Genetic and environmental influences on ADHD operate continuously across the continuum II. ADHD the disorder = quantitative extreme III. Categorical approaches are also important (e. g. , clinical services) IV. Search for risk factors must attend to both dimensional and categorical approaches to ADHD

Digital Media (DM) and youth ADHD I. Nikkelen et al. (2014) meta-analysis, Developmental Psychology I. Positive correlations (r =. 32) between DM and attention problems and impulsivity (r =. 11) II. Variation in cross-sectional vs. longitudinal effect sizes III. Significant methodological variation (e. g. , sampling, covariates) II. George et al. (2018), Child Development I. N = 151 high-risk youth assessed at baseline, EMA, and 18 -month follow-up II. Cross-sectional findings I. II. DM inversely associated with anxiety and depression (small, but significant) DM positively associated with ADHD and conduct problems III. Prospective findings I. 18 month conduct problems and poor self-regulation predicted from baseline DM

Digital Media (DM) and youth ADHD I. Aim: Prospective association of DM and ADHD in 2500 Los Angeles area high school students without ADHD (Ra et al. , 2018, JAMA) I. Followed prospectively for 6 -24 months (N = 2300 at 24 month) II. Number of high-frequency digital media (DM) activities (e. g. , browsing, texting, social media) I. III. IV. Activities used “many times per day” vs. all other use patterns (0 -14) Demographic covariates: age, sex, subsidized lunch, race-ethnicity Clinical covariates: youth depression, delinquency + family substance hx Outcomes: ADHD symptom criteria (6 or more sxs of inattention and/or hyperactivity) plus continuous measure of ADHD symptoms I. High frequency DM positively predicted positive ADHD symptom criteria status II. High frequency DM positively predicted ADHD symptoms (dimensionally) III. Models were robust to missing data procedures, different covariates, etc.

What work remains? I. Greater methodological diversity (e. g. , experimental designs) II. Elucidation of causal mechanisms (i. e. , mediators) I. How might DM relate to cognitive changes and psychopathology? II. Candidates? Neurobiological changes, sleep disruption, etc.

Panel: The Relationship between Cognition and Media Behavior Matthew Cain, Ph. D Center for Applied Brain and Cognitive Sciences, Tufts University & U. S. Army Daphne Bavelier, Ph. D Brain and Learning Laboratory, University of Geneva, Switzerland Jason Chein, Ph. D Neurocognition Laboratory, Temple University Steve Lee, Ph. D ADHD and Development Laboratory, University of California Los Angeles Susanne Baumgartner, Ph. D Amsterdam School of Communication Research, University of Amsterdam

Wiradhany, W. , & Nieuwenstein, M. R. (2017). Attention, Perception, & Psychophysics, 79, 2620 -2641.

Longitudinal study 1, 444 Dutch adolescents aged 12 to 15 1 -year, 3 assessments Between-person (cross-sectional) + Attention problems + Academic distractibility - Academic performance (grades) + Sleep problems

Longitudinal study 1, 444 Dutch adolescents aged 12 to 15 1 -year, 3 assessments Within-person (longitudinal) + Attention problems only among early adolescents + Academic distractibility - Academic performance (grades) + Sleep problems T 1 T 2 ` T 3 only among early adolescent girls