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The Impact of Media on Cognitive Fitness

Explore the relationship between media consumption and cognitive abilities. Discover how different types of media, content, context, and delivery interface can affect attention, memory, and academic success. Experts discuss the cognitive profiles of habitual action video game players and the potential for cognitive benefits through intervention studies.

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The Impact of Media on Cognitive Fitness

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

  2. Melina Uncapher, PhD, Education Program at Neuroscape, University of California San Francisco

  3. 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

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

  5. Meta-analysis of action video games impact on cognition(Jan 2000- Dec 2015) Benoit Bediou • 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

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

  7. Meta-analysis of action video games impact on cognition(Jan 2000- Dec 2015) Benoit Bediou • What is the cognitive profile of habitual action video game players (N = 3789; K = 90)? • Hedges’ G = 0.55 (in children and young adults) • 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

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

  9. Features of the interactivity – What’s special to interactivity in action VG? Enabling factors: • 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 (5HT) - 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 • ….. Catch Trials

  10. 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

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

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

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

  14. 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 Henkel, 2013 No evidence of lasting change in the nature of long-term memory functioning

  15. 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?...

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

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

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

  19. Digital Media (DM) and youth ADHD • Aim: Prospective association of DM and ADHD in 2500 Los Angeles area high school students without ADHD (Ra et al., 2018, JAMA) • Followed prospectively for 6-24 months (N = 2300 at 24 month) • Number of high-frequency digital media (DM) activities (e.g., browsing, texting, social media) • 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 • High frequency DM positively predicted positive ADHD symptom criteria status • High frequency DM positively predicted ADHD symptoms (dimensionally) • Models were robust to missing data procedures, different covariates, etc.

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

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

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

  23. Between-person (cross-sectional) Longitudinal study 1,444 Dutchadolescentsaged 12 to 15 1-year, 3 assessments + Attention problems +Academic distractibility - Academic performance (grades) +Sleepproblems

  24. Within-person (longitudinal) Longitudinal study 1,444 Dutchadolescentsaged 12 to 15 1-year, 3 assessments + Attention problems +Academic distractibility - Academic performance (grades) +Sleepproblems onlyamongearlyadolescents onlyamongearlyadolescent girls T1 T2 ` T3

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