Gackenbach, J.I. (2010, May). Dreams and Video Game Play. Paper presented at the annual meeting of the Canadian Game Studies Association, Montreal.

1. Dreams and Video Game Play
Jayne Gackenbach
Athabasca University
2010 Canadian Game Studies Association
Montreal, Quebec
gackenbachj@macewan.ca
Gackenbach, J.I. (2010, May). Dreams and Video Game Play. Paper
presented at the annual meeting of the Canadian Game Studies
Association, Montreal.

2. Why are dreams important?
• Rich history across most cultures
• Royal road to the unconscious – Freud
– While opened up dreams as important, he also
pathologized them
• With discovery of REM sleep and the sleep
laboratory, dreams entered science
• While not local only to REM, those that are
most recalled and most often puzzled about
are typically REM dreams

3. Why are dreams important?
• Function of dreams increasingly clear
– Evolutionary threat/play (Revonsuo; Humphrey)
– Emotional Regulation, especially negative
emotions (Kramer; Nielsen; Zadra)
– Memory integration & consolidation (Stickgold)
– Problem-solving, creative inspiration (Barrett)
– Metacognition (LaBerge; Kahan; Kahn)
• All this serves personal and interpersonal
needs if shared and processed

4. • Media saturated society
– Video game play represents the most immersive and
interactive media experience
• Isn’t it all just incorporation?
– Yes gamers dream about games
– And no,
• Example of value of studying gamers dreams...
Why study gamers dreams?
Gamers dreams show fundamental
structural differences

5. Presence in Games and Dreams
• Dreams have been called the “gold standard”
for presence (sense of being there) in VR and
games (Revonsuo; Moller & Barbera)
• Never measured until now (Gackenbach &
Rosie, 2010)
– Played Mirror’s Edge before sleep in lab
– Gathered dreams for next two weeks
– Presence measured after game and after dreams

6. • Presence sum score NO DIFFERENCE
• Items (12) got 4 differences 8 NO DIFFERENCE:
– The dream/game caused real feelings and emotions for me.
(Dream > Game)
– Overall how much did the things/people in the dream/game
look like they would if you had experienced them in waking
reality? (Dream > Game)
– How much did you feel like the events of the dream/game
were happening to you? (Dream > Game)
– How often did you feel "My body was in bed, but my mind was
inside my dream" or "My body was in this room, but my mind
was inside the environment I saw/heard"? (Game > Dream)
Presence in Games and Dreams

7. Gamer Defined
• Play video games on average several times a
week
• Typical playing session more than 1 or 2 hours
• Played 50 or more video games over your
lifetime
• Been playing video games since before grade
three
Type of Game Preferred only considered in latest
studies, seemed to make no difference 5 years ago

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

9. 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.

10. Lucid – Control Dreams & Gaming
• Subject #014: Lucidity triggered by an event
Michael: Well, once Jean Grey (a marvel comic
and video game character) got loose and started
killing people, I was like this is really weird this is
probably a dream and it was like right after that she
showed up and I told myself that I need to wake
up. I thought that something bad was supposed to
happen and I didn’t want it to happen so I should
wake up.
Gackenbach, et al. (2009)

11. 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

12. 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

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

14. Methodological Refinement
• Previous studies long term retrospective memory
• Collected 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 (N=152) for analysis were chosen if:
– Last night
– Rested (had typical amount of sleep)

15. Factor 1
Clarity of dream -.001
Lucidity .391
Type of Observer (hi=3rd per) .121
Control .527
Nightmare .185
Electronic media .025
mean of audio only media (phone, radio, CD/mp3) .436
mean of audio and video media (TV/DVD, movie) .413
mean of interactive media (computer/internet, vid gm) .718
gamer groups (0 = non-gamer, 1 = low, 2 = mod, 3 = high) .653
Last night, rested dreams, N = 152
Principal Component Factor Analysis
on Dream, Gamer and Media Use

16. 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
Self selection?
Yes and No

17. Bottom Line
• Gaming is too wide
spread to reduce to
purely self selection
• There is increasing
social pressure to play
• Gaming is only one
part of our networked
life
Percent growth in US 2006-2007

18. Original Dream Content Analysis
• 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.
• Those that lead to further research were:
• characters, aggression and misfortune.
• Gackenbach, J.I., Matty, I., Kuruvilla, B., Samaha, A. N., Zederayko, A.,
Olischefski, J. & Von Stackelberg, H. (2009). Video game play: Waking and
dreaming consciousness. S. Krippner (Ed.), Perchance To Dream, Hauppauge,
NY: Nova Science Publishers, p. 239-253.
27 gamers
56 dreams
male norms

19. Significant Differences
from Male Norms
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.

20. 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

21. Dream Aggression
• Smaller number of
dreams with
aggression (32% vs
47%)
• Yet more intense
aggression (namely
physical aggression,
86% vs 50%) when it
happened

22. Dream Aggression Example
Subject 002- Dream 6
“… 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…”.

23. 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

24. Dream Bizarreness
• Gackenbach, J. I., Kuruvilla, B., & Dopko, R.
(2009). Video game play and dream
bizarreness. Dreaming, 19(4), 218-231.
• Gackenbach, J.I. & Dopko, R. (in submission).
The Relationship between Video Game Play,
Dream Bizarreness, and Creativity.
Consciousness and Cognition.

25. • 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

26. 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
• Revonsuo & Salmivalli Content Analysis

27. Covariates: sex, # words in dream, # hours of video game play day before dream
Dreams were 279 from low end gamers and 162 from high end gamers
Unusual
(subject)
Bizarre
(judges)
Non-bizarre
(judges)
Low Game Group High Game Group

28. Torrance Tests of Creative Thinking
• No gamer group difference for verbal test
• Significant differences for figural test
favoring high gamer group

29. 1 2 3 4 5
Game history sum of z-scores -.317 .748 -.260 .097 -.026
Mean # hours played video game pre-dreams -.304 .699 -.188 -.125 -.156
Sex of subject (1=M; 2=F) .402 -.640 .282 -.115 -.047
Average number of words in dreams .885 .183 -.145 .095 -.050
Number of dream reported in diary .490 .213 .135 .518 .117
Dream recall sum of z-scores -.158 .150 .256 .652 .282
Discontinuous bizarreness mean .708 .256 -.102 -.294 -.210
Vague bizarreness mean .350 .168 -.409 .016 .656
Incongrous overall bizarreness mean .647 .473 .075 -.302 .085
Non-bizarreness mean .813 -.038 .054 .266 -.222
Average of sums of dream unusual elements .016 .240 .572 -.422 .534
Verbal creativity sum .005 .186 .799 .007 -.037
Figural creativity sum -.097 .563 .428 .073 -.331
Gaming, Bizarreness & Creativity

30. Factor Analysis on Game Play, Lucid
Related Dream & Bizarreness Variables
Video game history (freq, length, # games, age begin) .760 -.214 .377 .101
Video Games played day before dream .694 -.127 .467 -.025
Recent Dream - Lucidity .305 -.258 -.746 -.158
Recent Dream - Type of Observer (Hi=observer) .271 -.028 -.060 -.806
Recent Dream - Control .570 -.239 -.447 .215
nonbizarreness mean .071 .706 -.035 -.119
vagueness variables mean .322 .371 .129 .196
discontinuous mean .047 .642 -.187 .242
Incongruous distorted sum .324 .384 -.043 -.311
Incongruous exotic sum .378 .482 -.159 .051
Incongruous impossible sum .282 -.121 -.243 .355
Gackenbach, J.I. & Hunt, H. (2010, April). Video Game Play and Lucid Dreaming as Socially
Constructed Meditative Absorption. Paper to be presented at the biannual meeting entitled
"Toward a Science of Consciousness" sponsored by the University of Arizona, Tucson, Arizona.

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

32. 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

33. 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

34. 1 2
Sex of subject: Male=1; female=2 -.011 -.589
Z-score for gamer type -.015 .453
Mean objective rating of video game .040 .901
Percent of maximum length of play score .047 .817
Type of game sum favorite + current -.029 .458
Mean for TV violence rating .368 .132
Mean movie violence rating .333 .189
Threat simulation present=2, absent=1 .917 -.090
Nature of threat recoded no harm to aggressive .903 -.060
Sum of the number of threats from target threat .936 -.080
Severity of threat recoded, none to life threat .908 -.097
Dream recall .119 .085
Lucidity in dream -.062 .129
Observer point of view in dream .137 -.074
Control in dream .143 .054
Was dream a nightmare .690 -.023
Dream scariness .526 -.034
Dream violence .511 .314
Principle
Component
Factor
Analysis of
Media,
Threat
Simulation
Intensity,
and Dream
Self
Evaluation
Variables

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

36. 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)

37. 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

38. 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

39. Judge Rated Emotionality (HVDC)
• Consistent findings with previous
research
• Nightmares had more negative
emotions than bad dreams
• No interaction with gaming group

40. 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!!!

41. Hall & Van de Castle Content Analysis of Lucid vs
Nonlucid Dreams of Gamers from 4 Previous Studies
Gender Dream Row totals
male Lucid 53
male nonlucid 219
female Lucid 27
female nonlucid 131
total 430
Gackenbach, J.I. & Hunt, H. (2010, April). Video Game Play and Lucid Dreaming as Socially
Constructed Meditative Absorption. Paper to be presented at the biannual meeting entitled
"Toward a Science of Consciousness" sponsored by the University of Arizona, Tucson, Arizona.

42. Lucidity Dream Type Differences among Gamers
Significant difference variables All gamers
Nonlucids
All gamers
Lucids
Social Interaction Percents
Aggressor Percent 26% 44%
Settings
Familiar Setting Percent 50% 35%
Self-Concept Percents
Self-Negativity Percent 85% 65%
Dreamer-Involved Success Percent 38% 77%
Dreams with at Least One:
Sexuality 03% 10%
Success 07% 14%

43. 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

44. 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
– Does gaming protect the person against
nightmares?

45. For more information....
• Email for slides and/or papers:
– gackenbachj@macewan.ca or www.slideshare.com
• Some of presentation summarized in this book
chapter
– Gackenbach, J.I., Kuruvilla, B., Dopko, R. & Le, H.
(2010). Chapter 5: Dreams and video game play. In F.
Columbus (Ed.), Computer Games: Learning
Objectives, Cognitive Performance and Effects on
Development, Hauppauge, NY: Nova Science
Publishers.