Gackenbach, J.I. (2009, June). Dreams and Video Game Play. Planary Session paper presented at Toward a Science of Consciousness : Investigating Inner Experience – Brain, Mind, Technology, Hong Kong, China

1. Dreams and Video Game Play
Jayne Gackenbach
MacEwan College
Gackenbach, J.I. (2009, June). Dreams and Video
Game Play. Planary Session paper presented at
Toward a Science of Consciousness : Investigating
Inner Experience – Brain, Mind, Technology, Hong
Kong, China

4. My son’s 20th
birthday party
My Interest in Video Games
Began…….

5. Games I’m
Playing

6. Hard Core Gamer
• Play video games on average several times a
week
• Typical playing session more than 2 hours
• Been playing video games since before grade
three
• Played 50 or more video games over your
lifetime

7. Dream Dimensions Examined
•Lucid and Control Dreams
•Bizarreness and Creativity
•Nightmares and Threat
Simulation

8. Lucid – Control Dreams
• Gackenbach, J.I. (2006). Video game play and lucid
dreams: Implications for the development of
consciousness. Dreaming, 16(2), 96-110.
• Gackenbach, J.I. & Kuruvilla, B. (2008). Video game
play effects on dreams: Self-evaluation and content
analysis. Eludamos. Journal for Computer Game
Culture. 2(2), 169-186.
• Gackenbach, J.I. (2009). Video Game Play and
Consciousness Development: A Replication and
Extension. International Journal of Dream Research,
2(1), 3-11.

9. Control Dreaming
In Class Data Collection
2.05
2.1
2.15
2.2
2.25
2.3
2.35
2.4
2.45
2.5
Low Video
Game Play
Medium Video
Game Play
High Video
Game Play
ControlDreaming
2=
rarely
3=
sometimes

10. In Class Data Collection
2.3
2.35
2.4
2.45
2.5
2.55
2.6
2.65
2.7
2.75
Low Video
Game Play
Medium Video
Game Play
High Video
Game Play
LucidDreamingFrequency
Lucid Dreaming
2=
rarely
3=
sometimes

11. Methodological Refinement
• Gackenbach, J.I. (2009) Electronic
media and lucid-control dreams:
Morning after reports. Dreaming,
19(1), 1-6.

12. Background
• previous studies showing lucid dreams
associated with video game play
• Based on reflections on dream history
• Need recent dream reports
• Video game play only one form of
electronic media in wide use today

13. Online Questionnaire
• Dream report and when
• Normal sleep length and rested amount
• Questions on media use history and media
used the day before dream
• Questions reflecting about dream reported
• Dreams for analysis were chosen if:
– Last night
– Rested (had typical amount of sleep)
– N = 152

14. 1 2 3 4 5
Clarity of dream
-.001 -.446 -.104 .162 .699
Lucidity
.391 -.469 -.292 .208 -.143
Type of Observer (hi=3rd per)
.121 -.259 .293 .611 -.494
Control .527 -.303 -.495 -.088 .064
Nightmare
.185 -.262 .575 .397 .285
Electronic media
.025 .531 -.393 .574 -.013
mean of audio only media
(phone, radio, CD/mp3)
.436 .257 .551 -.200 .114
mean of audio and video
media (TV/DVD, movie)
.413 .518 -.105 .291 .288
mean of interactive media
(computer/internet, vid gm) .718 .208 .069 -.110 .056
gamer groups (0 = non-
gamer, 1 = low, 2 = mod, 3 = .653 -.103 -.004 -.231 -.273
Extraction Method: Principal Component Analysis.Last night, rested
dreams, N = 152

15. Parallels video gaming/lucidity
• Video game Play
1. video games
technologically
constructed
alternative realities
2. Video gaming has been
associated with
improved spatial skills
3. Low motion sickness
needed to play a lot
4. High absorption is
reported by players
• Lucid/control dreams
1. Dream worlds
biologically constructed
alternative realities
2. Lucid dreamers show
better spatial skills
3. Lucid dreamers have
better vestibular
systems (not susceptible
to motion sickness)
4. Meditation is highly
associated with lucidity
and is training in
developing one pointed
absorption

16. Hard Core Gamer Interviews
• Gackenbach, J.I., Matty, Ian, Kuruvilla, Beena,
Samaha, Ashley Nicole Zederayko, Alexis &
Olischefski, Jordan, (in press). Video game play:
Waking and dreaming consciousness. Stanley
Krippner (Ed.), Perchance To Dream, Nova.
• Gackenbach, J.I., Matty, Ian, Kuruvilla, Beena,
Samaha, Ashley Nicole Zederayko, Alexis, &
Olischefski, Jordan (in submission). Video Game Play:
Waking and dreaming consciousness explored
through interviews of hard core players. International
Journal of Dream Research.

17. Participants
• Solicited through on campus posters and
emails in early 2006
• 25 men and two women interviewed
• 85% were 25 years of age or younger
• Hour interviews asking
– Experiences of self during play
– Dreams of gaming
– Altered States of consciousness related to play
• Collected 56 dreams

18. The interview
• absorption, bodily sense, time
“You’ve probably seen people play video games and they’re moving
their whole body along with the controller, with the screen, I think
there is that where you’re put in the game and you’re obviously
more concerned with the movements on the screen than with your
own sense of being, so yeah I would definitely say that the focus
shifts to movement on the game and within the game” – s16
“People will say things to me and I just don’t respond, or it will take
me longer to notice that I’m tired or hungry or have to pee or
whatever, all I can say is that you get the blinders on, like I’m really
focused on what I’m doing in the game
and it totally outweighs what’s going on around you” – s16

19. Factor Analysis
Variables 1 2 3 4
words in dream (hi is lot) .071 .789 .283 .095
palpable recoded (hi is lot) .187 .669 -.115 -.517
balance emotions (hi is lot) .889 .045 .213 .096
video game dreams (hi is lot) -.454 .306 .517 -.121
media dreams (hi is lot) .203 -.124 .785 .003
lucid dreams (hi is lot) -.079 .714 .027 .262
sense of self location in dream (hi is watcher & lo is
self in body)
.026 .206 -.131 .869
emotions of watcher in dream (hi neutral) .945 .076 -.048 -.156
mean of control variables ((hi is lot) -.016 .377 .659 -.096

20. Hall &Van de Castle Coding System
• Frequency equals intensity
• High inter-rater reliability
• Well developed norms
• Uses categories which are pertinent to waking
concerns that may influence dreaming.
•Character (Number, Gender, Identity,
Age)
•Social Interactions (Aggression,
Friendliness, Sexual)
•Activities (Movement, Verbal activity,
Visual activity)
•Striving (Success, Failure)
•Misfortune/Good Fortune
(Sickness, Falling, Winning)
•Emotions (Apprehension, Confusion,
Happiness)
•Physical Surroundings (Settings
and Objects)
•Descriptive Elements (Color, Size,
Velocity)
27 gamers
56 dreams
males norms

21. Significant Differences
from Male Norms
Fewer friends (16% vs
31%) yet more dead or
imaginary characters
appearing in dream
reports (21% vs 0%).
Why be human in a
game? They have fewer
powers than other types
of creatures.

22. Dead or Imaginary Characters
Subject 001- Dream 11
“I dreamt I was a character is Underworld 2, it was a
werewolf character and then I became a 3rd person. It
was the two main characters, it was the vampire girl
and a hybrid werewolf character and I was another
werewolf character beside them and we went into a
vampire coven and we got to the weapons section of
the vampire coven and then I woke up”
• Later looked at bizarreness due
to this finding

23. Dream Aggression
• Smaller number of
dreams with
aggression (32% vs
47%)
• yet more intense
aggression (namely
physical aggression,
86% vs 50%) in
those dreams that did
contain it.

24. Dream Aggression Example
Subject 002- Dream 6
“…so I went outside with my cat and shot these
criminals that were trying to eat my dad and they were
on top of my dad trying to eat his arms and he was
fighting them off, and they were trying to hold him
down and bite his shoulders and there was blood and
stuff. And it was a very graphic shootout for a dream; it
was very blood and guts ya know? And when I ran out
of ammunition there was like pistol whipping and stuff
going on and that one sticks out in my mind because it
was very graphic…”.

25. Dream Misfortunes Fewer
Misfortunes
(7% vs 36%)
Fewer Bodily
Misfortunes
(0% vs 29%)
Thus less victim /more control
Aggression and
misfortune
findings lead to
threat simulation
and nightmare
questions

26. Dream Bizarreness
• Gackenbach, J.I., Kuruvilla, B. & Dopko, R. (in
submission). Video game play and dream
bizarreness. Dreaming.
• Dopko, R. & Gackenbach, J.I. (2009, June).
Video Game Play, Dream Bizarreness and
Creativity. Paper to be presented at the
annual meeting of the International
Association for the Study of Dreams, Chicago,
ILL.

27. • Domhoff – 2007 meta-
analysis
– dreams are more coherent,
patterned and thoughtful
than previously suggested
– still some bizarreness in
adult dreams
– far less than what was
expected based
Illusion of Dream Bizarreness

28. Methods
• Study 1: Recent Dreams
–Self reported dream questions
–Various media use information
• Study 2: Two Week Online Dream Diary
–Features that were bizarre for subject
–Various media use information
– Torrance Test of Creative Thinking (TTCT)
• Verbal and the figural tests

29. Bizarreness Content Analysis
• Revonsuo and Salmivalli Content Analysis
(1995)
–Three bizarre types:
• vague
• discontinuous
• incongruent
– Distorted
– Exotic
– Impossible

30. Covariates: sex, # words in dream, & # of hours of media use day before
Unusual
(subject)
Bizarre
(judges)
Nonbizarre
(judges)
Low Game Group High Game Group

31. Example of High Judges Dream
Bizarreness Rating for Gamer
• “I remember being in a room with my brother and his
friend, the room was filled with soft triangular blocks
of different colors. They were transparent, and we
talked about how the blocks might represent each of
us. They thought i would be the orange blocks, though
I though I was the green ones. I thought my brother
was the blue blocks. We started throwing the blocks
out the window, and I remember looking out the
window. The yard outside resembled a construction
site which I had worked on over the summer, and I
could see the blocks we threw out the window. They
were now opaque and white, and blew in the wind like
styrofoam..” Response 35(Subject 48, High gamer).

32. Creativity Tests
Figural TTCT- directions
Stimulus
figure
Low creativity
High creativity
from a high
gamer

33. Verbal TTCT Example
• Given an improbable situation- Clouds had
strings attached to them which hang down to
earth. What would happen?
– Low originality (Low Game Group):
• People would climb up to the clouds
• The strings would get tangled from the wind
– High originality (High Game Group):
• People would use the strings to pull teeth- just tie
and yank
• Farmers could tie rain clouds over their crops

34. Results: Torrance Test of Creative
Thinking (TTCT)
• No significant difference for verbal test
–Sex difference
• Significant differences for figural test
favoring high gamer group
–Overall mean score
–Index score for entire test
–Other subscale differences

35. 1 2 3 4 5 6
gamer group (1=lo;2=hi) .411 -.534 .251 .215 .394 -.019
sex of subject (1=M;2=F) -.287 .683 -.337 -.123 .024 .196
Discontinuous bizarre mean
.369 .562 .448 -.003 .140 -.332
Vague bizarre mean .252 .021 .451 -.466 .065 .580
Distorted incongrous bizarre mean
.036 .803 .052 .180 .024 -.214
Exotic incongrous bizarre mean
.709 .207 .320 -.207 -.211 -.043
Impossible incongrous bizarre
mean
.567 -.148 .608 .028 -.141 -.144
Nonbizarre mean -.005 .771 .279 .221 .101 .161
average of sums of unusual
elements in dreams .766 .082 -.542 -.231 .011 .077
average of sums of attributions of
unusual elements in dreams due
to all media
.766 .082 -.542 -.231 .011 .077
average media use thought to be
in dream
.161 .026 -.387 -.161 .621 -.401
sum all media use predream
(includes other) .168 .134 -.069 .459 .471 .498
verbal creativity sum .331 .071 -.392 .401 -.579 .028
Figural creativity sum .410 -.148 -.042 .709 .005 .037

36. Nightmares & Threat Simulation
• Gackenbach, J.I. & Kuruvilla, B. (2008). The
relationship between video game play and
threat simulation dreams. Dreaming, 18(4),
236-256.

37. Threat Simulation Theory
• dreaming is an adaptive process with an
evolutionary foundation (Revonsuo, 2000).
• dreaming allows us to simulate threatening
situations in the safety of a virtual
environment of dreams.
• continued practice would allow an individual
to better prepare for these possibly dangerous
instances, were they to arise in the waking
world

38. Dreams Collected
• Online Questionnaires
• night before dreams only,
– average hours since dream to recollection being
under one hour
• minimum word count of 40 words
• 98 participants/dreams
– 35 males
– 63 females

39. 1 2 3 4 5 6 7
sex of subject: Male=1; female=2 -.011 -.589 .024 .501 .243 .104 .006
Z-score for gamer type -.015 .453 .268 -.356 -.419 .336 .120
mean objective rating of video game .040 .901 -.033 .057 .243 -.121 -.003
percent of maximum length of play score .047 .817 -.041 .089 .277 -.290 .135
type of game sum favorite + current -.029 .458 -.208 .235 -.234 .443 -.411
Mean for TV violence rating .368 .132 .352 .388 -.392 .136 .300
Mean movie violence rating .333 .189 -.059 .446 -.475 -.077 .425
threat simulation present=2, absent=1 .917 -.090 .135 -.101 -.092 -.040 -.172
nature of threat recoded no harm to aggressive .903 -.060 .152 -.057 -.010 -.126 -.228
sum of the number of threats from target threat .936 -.080 .084 .015 -.040 -.037 -.148
severity of threat recoded, none to life threat .908 -.097 .087 -.071 -.117 -.070 -.138
dream .119 .085 .131 .818 .264 -.051 -.101
lucidity in dream -.062 .129 .770 .103 .264 .262 -.094
Observer point of view in dream .137 -.074 .575 -.219 .119 -.426 .345
control in dream .143 .054 .512 -.176 .401 .469 .091
Was dream a nightmare .690 -.023 -.416 -.083 .141 .272 .312
dream scariness .526 -.034 -.470 -.069 .419 .300 .417

40. Nightmares versus Bad Dreams
• Le, H. & Gackenbach, J. (2009). Nightmares of
Video Game Players: What do They Look Like?
Paper to be presented at the annual meeting
of the International Association for the Study
of Dreams, Chicago, ILL.

41. Method
• Participants
– 231 low- and 222 high end gamers
• Instruments
– Media usage questionnaire
– Impactful dreams questionnaire (Lucid,
Nightmares, Mystical, and Bad dreams)
• Content Analysis
– Hall and Van de Castle’s method for content
analysis (HVDC)

42. HVDC Aggression Sum Score
Gaming Groups (1=low; 2=high)
2.001.00
EstimatedMarginalMeans
1.75
1.50
1.25
1.00
0.75
2.00
1.00
1=bad 2=ntmr
Estimated Marginal Means of aggression sum
Nightmares
Bad Dreams
Low Game Group High Game Group

43. Example for the Aggression Score
1. I used to play World of Warcraft extensively. Recently, I
deactivated my subscription and quit playing. In my dream, my
younger brother was on my computer, playing my character,
exploring the changes in the world since I had last participated. I
attempted to force him off the computer, and he acquiesced after
some minor violence. I am the stronger of the two of us by some
degree, and this is a frequent occurence. However, as I was
preparing to play, I felt his hands grip me around the throat, which
then turned my body to face him. He was looming over me, my
throat was in his vice like hands, and I could not escape. He was
whispering to me "Now with a flick of my fingers I fling your life
away." I was terrified, and jerked awake. (Subject 534:
Nightmare; High Gamer)

44. HVDC Misfortune Sum Score
Gaming Groups (1=low; 2=high)
2.001.00
EstimatedMarginalMeans
0.3
0.25
0.2
0.15
0.1
2.00
1.00
1=bad 2=ntmr
Estimated Marginal Means of misfortune body
Bad Dreams
Nightmares
Low Game Group High Game Group

45. Judge Rated Emotionality (HVDC)
• Consistent
findings with
previous
research
• Nightmares were
more
pronounced with
negative
emotions than in
bad dreams
• Interaction not
significant
(p=.136)
Gaming Groups (1=low; 2=high)
2.001.00
EstimatedMarginalMeans
0.7
0.6
0.5
0.4
0.3
2.
1.
1=bad 2=
Estimated Marginal Means of emotion negative
Bad Dreams
Nightmares
Low Game Group High Game Group

46. Self-Rated Emotionality Scale of
Dream
• Self rated emotions: anger, awe, sexual
arousal, anxiety, fear, guilt, frustration,
sadness, hatred, happiness, jealousy, and
embarrassment
• Negative emotions (anxiety, frustration, and
fear) were found to be higher in bad dreams
for high-end gamers
• While positive emotions (sexual arousal and
happiness) were found to be greater in
nightmares for high end gamers!!!

47. Gaming Groups (1=low; 2=high)
2.001.00
EstimatedMarginalMeans
2.25
2
1.75
1.5
1.25
2.00
1.00
1=bad 2=ntmr
Estimated Marginal Means of Emotion & Intensity: anxiety
Gaming Groups (1=low; 2=high)
2.001.00
EstimatedMarginalMeans
4.2
4
3.8
3.6
3.4
3.2
3
1=bad
Estimated Marginal Means of Emotion & Intensity: happiness
Self Reported Emotions: Sample Subscales
Bad Dreams
Nightmares
Bad Dreams
Nightmares
Low Game
Group
High Game
Group
Low Game
Group
High Game
Group
Anxiety Happiness

48. Participant - Observer Gamer
Opinion of how video games
enter into dreams
• Lucidity, bizarreness, yes.
Aggression, sometimes.
• nightmares very rare
• 3rd person
“I’ve just noticed that sometimes I’m just there as a hovering
spirit watching things go on and I don’t really have a role … I
don’t even pop up in my dreams, it’s just like I’m watching a
movie … I feel emotion definitely regardless of whether or not
I’m the person involved” – s16

49. Conclusions & Implications
• Lucidity/control
– Do these preliminary results imply that
lucid/control dreaming will become widespread
given the saturation of media?
• Bizarreness
– Are gamers semantic networks more diverse?
• Aggression/Threat Simulation
– What is happening to gamers nightmares?