This is a presentation made at the annual meeting of the Canadian Game Studies Association. A version of it will also be presented at the International Association for the Study of Dreams later in June.

1. Gaming, Social Media
and Typical Dreams
Jayne Gackenbach and
Arielle Boyes
Grant MacEwan University
Paper presented at the annual meeting of the Canadian Game Studies,
Victoria, BC. June, 2013

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. Dreams are Brains at Work While “Off-line”
• Like a computer which is not in use
thus no input (i.e., keyboard, scan,
etc) yet CPU still at work
• During sleep the brain is off line,
minimal sensory input, but lots of
processing of information ongoing

4. 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 but need not be as dreams
still do their ‘job’
• Unobtrusive way to examine psychological processes

5. • 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,
Why study gamers dreams?
Gamers dreams may show
fundamental structural differences in
their dreams

6. 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)
– Presence sum scores from game and dream resulted in
FEW DIFFERENCES between sense of being there
while playing a video game and being there in a dream –
High End Gamers

7. • increasing immersion and interactivity of
the other forms of electronic media
engagement may also cross this
waking/sleeping boundary.
• Social media use most focused upon today
• examine the typical dreams of both gamers
and social media users.
Additional Virtual Realities

8. Participants
• Research participant pool from western
Canadian university (74%)
– 2% course credit
• Online public access site (26%)
• Gender
– Males = 175
– Females = 507

9. Scales Administered
• Demographics: gender, age, marital
status, and race/ethnicity.
• Video Game History: frequency of play,
length of typical play session, number of
games played over a life time, and age
when began playing, preferred genre,
video game reading and social habits, and
questions about their play during the 24
hours prior to filling out the questionnaire.

10. Scales Administered
• Electronic Media Use Questionnaire:
– cell phone use,
– computer and other media use, and
– social media use.
• The items were drawn from various PEW
research polls as well as other
communication studies surveys on media
use.

11. Scales Administered
• Typical Dream Questionnaire:
– This 60-item questionnaire
– investigates the dimensional structure of
dreams by asking the respondent to indicate
how frequently they have had each type of
dream experience.
– This survey was normed on Canadian college
students.

12. Scales Administered
• Boundary Questionnaire (subset of sample):
– personality inventory developed by Hartmann (1984)
– 18-item short form
– Psychological boundaries refers to a personality trait
concerning the degree of separateness (“thickness”) or
connection (“thinness”) between mental functions and
processes.
• Thin boundaries are associated with open-mindedness,
sensitivity, vulnerability, creativity, and artistic ability. People
with thin boundaries may tend to confuse fantasy and reality
and tend to have a fluid sense of identity, so that they tend to
merge or lose themselves in their relations with others.
• People with thick boundaries differentiate clearly between
reality and fantasy and between self and other, and tend to
prefer well-defined social structures

13. Boundary Hypothesis
• It might be that those who spend more time in
virtual realms do so because they have thin
boundaries and thus can get more immersed in
the online activities.
• Alternatively spending a lot of time in VR type
realms could lead to a thinning of boundaries
• In any case a positive association is expected
between high end online use and thin boundaries
• What typical dreams may also be so associated
is unknown.

14. Results
• Separate varimax rotated factor analyses
on each set of variables
– Gaming
– Social media use
– Typical dreams
• For each group of questions factor scores
were saved and then entered into a final
factor analysis with boundary sum scores

15. How often do you typically play video games? .803
How long is your typical playing session? .687
How many different video games in any format have you played? .620
How old were you when you played your first video game? .016
weighted action genre mean x presence mean (106) -.014
weighted adventure genre mean x presence mean (99) .259
weighted RPG genre mean x presence mean (95) .280
weighted sport genre mean x presence mean (82) -.077
weighted casual genre mean x presence mean (70) -.341
read books, comics, blogs, and/or news reports about video games? .560
think about a video game outside of the time you are playing? .820
talk about video games with friends online or off? .801
watch videos about games or gaming related topics? .805
Were you playing a video game in the 24 hours prior questionnaire? .661
computer use -Games (e.g., The Sims, Diablo) .700
SMU profile -Game based (e.g., X-box Live, Playstation Network) .451
SMU length.-Game based (e.g., X-box Live, Playstation Network) .444
SMU frequency .-Game based (e.g., X-box Live, Playstation
Network)
.487
SMU reasons...-Keeping up with game related status, news &
updates
.535
social...-Play or talk about video games together .768
• Gamer
items
varimax
rotated
(yellow is
cutoff of .4)
• Factor 1 =
hard core
gamer

16. How often do you typically play video games? .291
How long is your typical playing session? .215
How many different video games in any format have you played? .373
How old were you when you played your first video game? .465
weighted action genre mean x presence mean (106) .257
weighted adventure genre mean x presence mean (99) -.157
weighted RPG genre mean x presence mean (95) -.046
weighted sport genre mean x presence mean (82) .033
weighted casual genre mean x presence mean (70) -.020
read books, comics, blogs, and/or news reports about video games? .047
think about a video game outside of the time you are playing? .167
talk about video games with friends online or off? .237
watch videos about games or gaming related topics? .160
Were you playing a video game in the 24 hours prior questionnaire? .155
computer use -Games (e.g., The Sims, Diablo) .085
SMU profile -Game based (e.g., X-box Live, Playstation Network) .749
SMU length.-Game based (e.g., X-box Live, Playstation Network) .758
SMU frequency .-Game based (e.g., X-box Live, Playstation Network) .679
SMU reasons...-Keeping up with game related status, news & updates .193
social...-Play or talk about video games together .242
• Varimax
rotated
(yellow is
cutoff of .4)
• Factor 2 =
young start
social

17. How often do you typically play video games? .091
How long is your typical playing session? .113
How many different video games in any format have you
played?
.134
How old were you when you played your first video game? .023
weighted action genre mean x presence mean (106) .706
weighted adventure genre mean x presence mean (99) .076
weighted RPG genre mean x presence mean (95) .449
weighted sport genre mean x presence mean (82) .150
weighted casual genre mean x presence mean (70) -.875
read books, comics, blogs, and/or news reports about video
games?
.230
think about a video game outside of the time you are playing? .117
talk about video games with friends online or off? .158
watch videos about games or gaming related topics? .044
Were you playing a video game in the 24 hours prior
questionnaire?
.058
computer use -Games (e.g., The Sims, Diablo) .010
SMU profile -Game based (e.g., X-box Live, Playstation
Network)
.171
SMU length.-Game based (e.g., X-box Live, Playstation
Network)
.154
• Varimax
rotated
(yellow is
cutoff of .4)
• Factor 3 =
genre: high
presence
type games
favorite &
NOT casual

18. How often do you typically play video games? .169
How long is your typical playing session? .113
How many different video games in any format have you
played?
.211
How old were you when you played your first video game? .410
weighted action genre mean x presence mean (106) -.047
weighted adventure genre mean x presence mean (99) .810
weighted RPG genre mean x presence mean (95) -.468
weighted sport genre mean x presence mean (82) -.112
weighted casual genre mean x presence mean (70) -.185
read books, comics, blogs, and/or news reports about video
games?
-.103
think about a video game outside of the time you are playing? .107
talk about video games with friends online or off? .023
watch videos about games or gaming related topics? .025
Were you playing a video game in the 24 hours prior
questionnaire?
.180
computer use -Games (e.g., The Sims, Diablo) .028
SMU profile -Game based (e.g., X-box Live, Playstation
Network)
-.081
SMU length.-Game based (e.g., X-box Live, Playstation
Network)
-.122
• Varimax
rotated
(yellow is
cutoff of .4)
• Factor 4 =
genre:
adventure
but not
RPGs,
young start

19. How often do you typically play video games? -.057
How long is your typical playing session? .049
How many different video games in any format have you
played?
.063
How old were you when you played your first video game? .368
weighted action genre mean x presence mean (106) -.056
weighted adventure genre mean x presence mean (99) .075
weighted RPG genre mean x presence mean (95) .535
weighted sport genre mean x presence mean (82) -.844
weighted casual genre mean x presence mean (70) .070
read books, comics, blogs, and/or news reports about video
games?
.032
think about a video game outside of the time you are playing? .112
talk about video games with friends online or off? .081
watch videos about games or gaming related topics? .110
Were you playing a video game in the 24 hours prior
questionnaire?
-.075
computer use -Games (e.g., The Sims, Diablo) .128
SMU profile -Game based (e.g., X-box Live, Playstation
Network)
-.022
SMU length.-Game based (e.g., X-box Live, Playstation
Network)
-.046
• Varimax
rotated
(yellow is
cutoff of .4)
• Factor 5 =
genre: RPG
not sport
favorite

20. Gaming Factor Analysis
• Factor 1 = hard core gamer
• Factor 2 = young start social
• Factor 3 = genre: high presence type
games favourite & not casual
• Factor 4 = genre: adventure but not RPGs,
young start
• Factor 5 = genre: RPG not sport favorite

21. Varimax rotated (.5 cutoff in yellow) 1
cell use 1 basic (own+activity sum) .008
cell use 2 activity sum (last 30 days) blank=0 .157
cell use 3 social media sum .586
cell use 4 during watching TV/DVD (last 30 days) sum .267
CELL average day how many text messages .118
VIDEO total hours a day, watch any type of television/video (i.e. live, internet,
smart phone, DVR, netflix, VOD, you tube).
.082
MUSIC hours a day,do you listen to music (i.e., MP3 player, radio, TV musi9c,
phone)
.086
MOVIES do you go to in theatres a month? .040
SMU sum of activities .593
SMU sum of profiles (facebk, linkedin, twitter, game, instagrm, tumblr, pinterest,
other)
.913
SMU mean length of use .815
SMU mean frequency of use .805
SMU facebook, mean of frequency of activities .197
SMU reasons use sum blank=0 .268
facebook how many people on friends.. .113
YouTube or Vimeo watch frequency .054
communicate with people sum of frequencies .046
Media Use Factor Analysis
Factor 1 = SMU general

22. Varimax rotated (.5 cutoff in yellow) 2
cell use 1 basic (own+activity sum) .808
cell use 2 activity sum (last 30 days) blank=0 .748
cell use 3 social media sum .553
cell use 4 during watching TV/DVD (last 30 days) sum .661
cell average day how many text messages .574
VIDEO total hours a day, watch any type of television/video (i.e. live, internet,
smart phone, DVR, netflix, VOD, you tube).
.017
MUSIC hours a day,do you listen to music (i.e., MP3 player, radio, TV musi9c,
phone)
-.008
MOVIES do you go to in theatres a month? .213
SMU sum of activities .193
SMU sum of profiles (facebk, linkedin, twitter, game, instagrm, tumblr, pinterest,
other)
.072
SMU mean length of use .090
SMU mean frequency of use .211
SMU facebook, mean of frequency of activities .187
SMU reasons use sum blank=0 .163
facebook how many people on friends.. .204
YouTube or Vimeo watch frequency -.067
communicate with people sum of frequencies .475
Media Use Factor Analysis
Factor 2 = Cell Phone
Use

23. Varimax rotated (.5 cutoff in yellow ) 3
cell use 1 basic (own+activity sum) .061
cell use 2 activity sum (last 30 days) blank=0 .083
cell use 3 social media sum .210
cell use 4 during watching TV/DVD (last 30 days) sum .062
CELL average day how many text messages .250
VIDEO total hours a day, watch any type of television/video (i.e. live, internet,
smart phone, DVR, netflix, VOD, you tube).
-.094
MUSIC hours a day,do you listen to music (i.e., MP3 player, radio, TV musi9c,
phone)
.035
MOVIES do you go to in theatres a month? .182
SMU sum of activities .281
SMU sum of profiles (facebk, linkedin, twitter, game, instagrm, tumblr, pinterest,
other)
.084
SMU mean length of use -.038
SMU mean frequency of use .185
SMU facebook, mean of frequency of activities .852
SMU reasons use sum blank=0 .112
facebook how many people on friends.. .868
YouTube or Vimeo watch frequency -.027
communicate with people sum of frequencies .272
Media Use Factor Analysis
Factor 3 = Facebook

24. Varimax rotated (.5 cutoff in yellow) 4
cell use 1 basic (own+activity sum) -.061
cell use 2 activity sum (last 30 days) blank=0 .014
cell use 3 social media sum -.015
cell use 4 during watching TV/DVD (last 30 days) sum .179
CELL average day how many text messages .134
VIDEO total hours a day, watch any type of television/video (i.e. live, internet,
smart phone, DVR, netflix, VOD, you tube).
.773
MUSIC hours a day,do you listen to music (i.e., MP3 player, radio, TV musi9c,
phone)
.703
MOVIES do you go to in theatres a month? .531
SMU sum of activities -.004
SMU sum of profiles (facebk, linkedin, twitter, game, instagrm, tumblr, pinterest,
other)
.092
SMU mean length of use .062
SMU mean frequency of use .166
SMU facebook, mean of frequency of activities .069
SMU reasons use sum blank=0 .180
facebook how many people on friends.. .007
YouTube or Vimeo watch frequency .003
communicate with people sum of frequencies .139
Media Use Factor Analysis
Factor 4 = General
Media Use

25. Varimax rotated (.5 cutoff in yellow) 5
cell use 1 basic (own+activity sum) -.021
cell use 2 activity sum (last 30 days) blank=0 .084
cell use 3 social media sum -.031
cell use 4 during watching TV/DVD (last 30 days) sum .084
CELL average day how many text messages -.014
VIDEO total hours a day, watch any type of television/video (i.e. live, internet,
smart phone, DVR, netflix, VOD, you tube).
.137
MUSIC hours a day,do you listen to music (i.e., MP3 player, radio, TV musi9c,
phone)
.153
MOVIES do you go to in theatres a month? -.173
SMU sum of activities .367
SMU sum of profiles (facebk, linkedin, twitter, game, instagrm, tumblr, pinterest,
other)
.074
SMU mean length of use .198
SMU mean frequency of use -.025
SMU facebook, mean of frequency of activities .179
SMU reasons use sum .539
facebook how many people on friends.. -.030
YouTube or Vimeo watch frequency .792
communicate with people sum of frequencies .418
Media Use Factor Analysis
Factor 5 = You Tube +
SMU reasons

26. Media Use (SMU) Factor Analysis
• Factor 1 = SMU general
• Factor 2 = cell phone
• Factor 3 = Facebook
• Factor 4 = general media use
• Factor 5 = you tube + SMU reasons

27. Typical Dreams Questionnaire
• TDQ factor 1 disaster – flood, tornado, earthquakes
• TDQ factor 2 magic/mythology – flying, magic powers, superior,
creatures
• TDQ factor 3 chase/fear – chase, frozen, falling, trying again
• TDQ factor 4 murder – attacked, killed, see self dead, killing
• TDQ factor 5 REM sleep paralysis – unable move, presence in room,
smothered
• TDQ factor 6 failure – fail exam, late, loss control vehicle, school
• TDQ factor 7 alien life – UFO, ET’s, travel to planet
• TDQ factor 8 embarrassing – wrong dress, nude, teeth out
• TDQ factor 9 dead – dead person is alive
• TDQ factor 10 positive experiences – delicious food, find money
• TDQ factor 11 epiphany – angel, encounter God
• TDQ factor 12 self-transformation – being opposite sex, being
object

28. Media Use, Typical Dreams, Boundaries FA
• Boundary Questionnaire:
• Factor 2 = hard core gamer magic/myth dreams and THIN
boundaries
• Factor 6 = general SMU associated with REM sleep paralysis
and THIN boundaries
• Nightmares:
• Factor 3 = NOT a hard core gamer but heavy Facebooker
associated with chase dreams
• Factor 5 = NOT playing high presence (hard core) games
associated with dreams of disaster (nightmare protection
factor)

29. Media Use, Typical Dreams, Boundaries FA
• Factor 7 = You Tube watcher associated with positive
and epiphany dream experiences
• Factor 8 = Cell phone use associated with
embarrassing dreams
• Factor 10 = General media use associated with murder
in dreams
• Factor 1 = female role play gamers (who did NOT
begin young or convert to social media) dreams of self
transformation
• Factor 4 = adventure genre not RPG (young start)
associated with dreams of failure and alien life

30. Conclusions
• It may be that gaming not only protects
against nightmares (males/action genre)
but also is associated with thin boundaries
and magical/mythic dreams
• Facebooking associated with classic
nightmare (chase)
• While SMU heavy use is also associated
with thin boundaries but a different
negative dream experience, REM sleep
paralysis