Donkey Kong in the room: videogames experience on inattention blindness (Vallett et al., 2013)

Several months ago, Jamie Madigan (Psychology of Video Games) blogged about inattention blindness in video games, his explanation of the phenomenon is spot on and so I suggest you read his blog before continuing. A few earlier months, I picked up an article by David Vallett (University of Nevada Las Vegas) and his colleagues on this very topic. I forgot about it until it showed up again in the newest issue of Computers in Human Behavior.


Early studies of visual attention noted a phenomenon termed ‘inattention blindness’ – the inability of participants to see clear stimuli enter the visual field when attending to something else in that field – and sought to expand the understanding of the phenomenon (Neisser & Becklen, 1975; Simons & Chabris, 1999; Stoffregen, Baldwin, & Flynn, 1993). Other research has focused on the changes to the human brain and cognitive functions as a result of video game play, both in positive and negative contexts (Howard- Jones, Ott, van Leeuwen, and De Smedt (2010)). This quasi-experimental study sought to corroborate some of the findings that tie together these seemingly disparate lines of research, adapting the methodology of the most cited inattention blindness experiment (Simons & Chabris, 1999).

It’s Black Friday and if you want to experience inattention blindness in a videogame, I suggest Papers, Please.

There are a good number of studies on visual attention and videogames that examined at various aspects of visual attention, but the authors took a rather simple approach by replicating a seminal study by Daniel Simons (University of Illinois) and Christopher Chabris (Union College) in order to examine inattention blindness. With the information about videogames and cognition so far, the authors hypothesized that videogame experience will impact people’s ability to see the gorilla. Furthermore, they hypothesized that participants who primarily play ‘action’ videogames are more likely to see the gorilla than others.


Participants: 49 participants. 23 were undergraduate students, age range from 18 to 34. 28 were high school students who attended a summer camp on information technology, age range from 14 to 18. The authors argued that confounding factor of age was not an issue as visual attention is normally developed by adolescence.  With so few participants, I was a bit uncomfortable about the study being under-powered, but apparently so was the original study. Good thing they replicated it.


Videogame experience: participants were asked how many hours per week, on average, they played videogames. What type (genres) of videogames they typically play. The authors categorized the types into two: action consisted of first-person shooters, side scrolling, action/adventure, and first-person RPGs and non-action consisted of sports, puzzle, strategy.

Attention Deficit disorder: participants were asked if they were diagnosed with Attention Deficit Disorder and if yes, whether they were taking medication. No explanation given.


Participants first watch the invisible gorilla video. They were asked either to counter the number of passes made by the white team or the number of times the basketball bounced by the white team.  Unfortunately, the authors failed to mention which version of the gorilla video they used as there were two versions in the original study: opaque (as shown in this blog) and transparent. Furthermore, the authors made statements from Simon & Chabris’ findings that 8% of participants who monitored the white team noticed the gorilla versus the 43% among those who monitored the black team, when I could not find such numbers in the original paper.

Afterwards, they were asked similar questions used by Simons and Chabris (1999):

a) How many passes (bounces) were made by the white shirt team?

b) While you were doing the counting, did you notice anything unusual on the video?

c) Did you notice anything other than the six players?

d) Did you see anyone else (besides the six players) appear on the video?

e) Did you see a gorilla walk across the screen?


23 participants noticed the gorilla, and 18 participants counted the number of passes or bounce correctly. 40 out of 49 participants stated they had played videogames and 30 of whom were categorized as typically playing action videogames.

The authors conducted logistic regression as many variables (e.g., did they saw a gorilla?, type of game typically play, etc.) are categorical. The predictor variables were ADD diagnosis, number of hours of videogame play, type of videogames play, whether the number of passes were accurate, and whether they played videogames (where did that come from?). The results revealed that action gamers were 16 times more likely to notice the gorilla than non-action gamers. Other predictor variables were not significant.


The take home message was that gamers who typically play action videogames are more likely to notice the gorilla and less likely to be affected inattention blindness.

My impression of the study is skeptical due to many methodological holes in the paper. The  aforementioned omission of which version of the gorilla video they used. The under-powered sample size which could distort their results. Their statistical analysis omitted the instructions given to the participants. They were asked to count the number of passes or the number of times a basketball bounces, Simon and Chabris (1999) found differences in those instructions as the latter one was harder and made noticing the gorilla even harder. The authors not mentioning whether there is such difference is concerning. I had to ask why they gave such instructions to the participant and did not bother examining whether such instructions mattered. Fourth, the authors asked the participants what they typically play which is a rather vague and gross measure, of which it can be confounded that some gamers like to play multiple genres.

Vallett, D. B., Lamb, R. L., & Annetta, L. A. (2013). The gorilla in the room: The impacts of video-game play on visual attention. Computers in Human Behavior, 29 (6), 2183-2187. DOI:10.1016/j.chb.2013.05.001

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