Gackenbach, J.I. (2015, June). Video Game Play and Nightmare Protection Hypothesis: A Cross Cultural Analysis. Paper presented at the Towards a Science of Consciousness conference, Helsinki, Finland.

1. Video Game Play and Nightmare
Protection Hypothesis: A Cross
Cultural Analysis
Jayne Gackenbach
Department of Psychology
Paper presented at the 2015 Towards a Science
of Consciousness Conference, Helsinki, Finland

2. Acknowledgement
• Support for this research was provided from a
MacEwan University Special Project Grant.
• Thank You for their assistance in data collection.
– Ming-Ni Lee of the National Dong Hwa University;
Department of Counseling and Clinical Psychology;
– Zongkui Zhou of the Central China Normal
University, School of Psychology and
– Gino Yu of Hong Kong Polytechnic University, School
of Design
• Dream Coders
– Alison Ditner & Sarkis Hakopdjanian

3. Introduction
• The overall objective of this study was to
investigate the relationship between culture,
media use and dreams.
• More people use the internet in China than
anywhere else in the world (ITU, 2011),
• The Chinese have the deepest social media
penetration and the largest gaming population in
the world (Cao & Downing, 2008).

4. Mary Meeker; Internet Analyst May 2015
presentation to Code Conference
Internet Use Around the World

5. Internet Penetration

6. Compared to Mobile Phone Use

7. Worldwide Game Users

8. Gaming in China
• Play in Internet Café’s
• Can not afford own PC and game consoles only
became legal in late 2014, but expensive
• PC’s in café’s preloaded
• Pay by hour
• Social network games, Happy Farm

9. Mobile Games

10. Censorship of Games in China
 Violating basic principles of the Constitution
 Threatening national unity, sovereignty and
territorial integrity
 Divulging state secrets
 Threatening state security
 Damaging national sovereignty
 Disturbing social order
 Infringing upon others' rights

11. BUT………………2014 from AppLift

12. Why Study Dreams?
• Attitudes towards dreams
– in west they are seen as not
important
– In east viewed more
positively
• Function of dreams
– Memory consolidation
– Emotional regulation
– Problem solving
– Creative inspiration
• Dreams are
autobiographies
• Response Bias
– Tendency to present oneself
in a positive light
– Not present in dreams, which
while metaphoric, are
relatively free of waking
defense mechanisms.
– Dream records and reports of
dream experiences may offer
a more unobtrusive way to
measure attitudes and
experiences

13. SIMPLE Dream Effects FROM
GAMING
1. No game in dream (63%)
2. Game & Dream (37%)
a. In the dream the dream ego is in the game
world – the dream is the game (63% )
b. In the dream playing a video game is mentioned
c. In the dream games are mentioned

14. Why study gamers dreams?
• Isn’t it all just incorporation?
– Yes gamers dream about games
– And no,
Gamers dreams may show fundamental
structural differences and/or clinically
relevant differences in their dreams

15. Why such ‘great expectations’ of gamers
dreams?
• The most widely experienced VR that can be
very immersive/present is video game play
• Do hours in simulated realities affect other realities?
– Yes, waking reality
• game transfer
• inverse presence
– Yes, dreams

16. Method: Participants
• 451 participants
from Canada
– 135 males and 316
females
• 455 participants
from China
• 119 males and 336
females,
• located in Wuhan,
Taiwan and Hong
Kong
Total 906 participants

17. Measurements
• Demographics
• Video Game Play Questions
• Social Media Questions
• Dream Intensity Scale
• Recent Dream
• Self-construal

18. Procedure
• These scales were posted online through
Qualtric.com
• Informed consent & debriefing statement
• All surveys were offered in English in Canada and in
Hong Kong but in either simple or traditional
Chinese in Hong Kong, Taiwan and Wuhan.
• If participants opted out of the study, or if they
finished the surveys, they were given a debriefing
statement.

19. Translation Issues
• A subset of Chinese dreams from
Taiwan were translated by two
translators, Yue and Coco
• These separate translations were
examined in two ways:
–word count
–dream coding

20. Translation Issues: Word Count
Response ID for dream #words/dr
eam
English Yue
#words/dre
am English
Coco
R_dpqcrRXXMv7pR4x 286 270
R_3R869XlIb8OKLt3 382 409
R_4Jbn42TqmczLKAd 398 351
R_9NQPxzJBYnj7R3f 154 119
R_8HZ8uSgPJIoWiZT 216 200
R_51oDBtMeBje4DZP* 173 620
R_cIVptVKDCxtL8wt 265 234
R_bkqqv4iUI3ilYWx 120 112
R_6eOjMZ2IG5pad3D 61 49
R_ene0XcKzrCFC45f 154 146
Average all 10 dreams 221 251
Average without outlier* 226 210
Correlation for
#words/dream
with outlier = 0.52,
nonsignificant
Correlation for
#words/dream
without outlier =
0.98, p<.0001

21. Translation Issues:
HVDC Dream Content Analysis
Response ID for dream Sarah HVDC coder Ali HVDC coder
R_dpqcrRXXMv7pR4x 35/49= 71% 32/44=72.7%.
R_3R869XlIb8OKLt3 42/49= 86% 33/47=70.2%
R_4Jbn42TqmczLKAd 50/64= 78% 44/55=84.3%
R_9NQPxzJBYnj7R3f 22/25= 88% 17/19 = 89.5%
R_8HZ8uSgPJIoWiZT 34/38=89% 33/40=82.5%
R_51oDBtMeBje4DZP* 26/58=45% 26/60=43.3%
R_cIVptVKDCxtL8wt 30/44=68% 32/40=80%
R_bkqqv4iUI3ilYWx 12/15=80% 7/8=87.5%
R_6eOjMZ2IG5pad3D 13/15=87% 6/7=85.7%
R_ene0XcKzrCFC45f 28/31=90% 18/26=69.2%
Average all 10 dreams 78.2% 76.49%
Average without
outlier*
81.9% 80.2%

22. Summary of Translation Issues
• While there were translation differences they made very little
impact on the final product of dream coding.
• None-the-less the translation issues were substantive enough
to warrant a second examination of the dreams by the
primary translator, Yue.
• She was given instructions to look for missed segments of
dreams, missed words, and possible mistranslations.
• She was provided with feedback
– commentary a third translator on translation,
– the 10 dreams from the other translator, Coco, and
– the commentary on coding issue from one of the dream coders, Ali

23. Further Summary
• Yue was particularly well qualified to continue in the role
of primary translator, not only because her native
language is Chinese, but also she was a psychology major
at a nearby university and had taken a course on dreams.
– she is experienced with not only translation issues,
– but those that are unique to dreams.
– she chose to use first person tense in many of the dreams while
other less experienced translators may not have made that
choice.
• Almost all dream transcripts in English speak in first person and
indeed speaks to a major function of dreams, memory consolidation.
• That said this could be a culture issue like the one with time
referents.

24. Post Dream Self Report of Emotions
Factor Analysis with Scores Saved
1 general negative
emotions 2 fear
3 positive
emotions
Anger .824 .131 .023
Awe .150 .087 .650
Arousal (Sexual) .158 -.046 .743
Anxiety .362 .772 -.003
Fear .243 .892 -.045
Guilt .505 .276 .222
Frustration .726 .317 -.043
Sadness .681 .359 .004
Hatred .771 .183 .123
Happines -.088 -.249 .725
Jealously .605 -.046 .387
Embarrassment .472 .352 .249
Ecstasy .106 .207 .708
Terror .184 .866 .022

25. Correlations between self reported emotion
factor scores & judges threat coding
threat simulation codes with
high score is more threat
objective threat,
subjective
threat, no threat
aggressive
harm through
nonagg harm
Number of
targets of
threat (high =
lots)
High threat to
self through
low threat to
self
self report of dream
emotions factor 1 scores
general negative emotions
Pearson Correlation
.110** .061 .048 .061
Sig. (2-tailed)
.010 .150 .261 .151
N
552 552 552 552
self report of dream
emotions factor 2 fear
Pearson Correlation
.501** .479** .472** .518**
Sig. (2-tailed)
.000 .000 .000 .000
N
552 552 552 552
self report of dream
emotions factor 3
happiness
Pearson Correlation
-.235** -.227** -.215** -.213**
Sig. (2-tailed)
.000 .000 .000 .000
N
552 552 552 552

26. Regressions onto Self Reported
Emotions
• Kept regressions as self reports of predictors and
self reports of predicted
• In dream research while a correlation as just seen
between self reports and judges reports, it’s not
perfect what a dreamer sees in their dream
relative to what a judge sees in a dream
• Variables examined:
– Media use
– Dream Intensity Subscales
– Culture
– Gender

27. Defining Video Game Participation
Component
1
How often do you typically play video
games?
.822
How long is your typical playing session? .760
How old were you when you played your
first video game?
.564
How many different video games in any
format have you played to date?
.818

28. Social Media Participation
• North American
Facebook
Linkedin
Twitter
Tumblr
Instagram
Myspace
Youtube
Google+
Pinterest
Other
• Chinese
Qzone
Sina Weibo
Neteasse Weibo
Tencent Weibo
Renren
Kaixin
Kaixin011
Youku Tudou
Baidu
Douban
Tianya
Maopu
Guoke
Zhihu
Other
Social Media
sum of means
of North
American &
Chinese with
zeros entered
into blanks

29. Background of Dream Intensity Scale
oDeveloped in Hong Kong on Chinese by
Calvin Yu (2010)
oConceptualized as a trait variable composed
of multiple dimensions
oSelf-report scale containing 23 items
oTranslation to English was done by author
for publication in Dreaming

30. Dream Intensity Scale: Subscales
• Regular dreams subscale score
– 1 Dream awareness
– 2 Recalling main dream content
– 5 Multiple dreams
• Bad dreams subscale score
– 3 Nightmares
– 4 Nightmare awakening
• Major modalities subscale
score
– 10 Colors
– 11 Sounds
– 14 Emotions
• Minor modalities subscale
score
– 12 Odors
– 13 Tastes
• Dream work subscale score
– 17 Condensation
– 18 Displacement
– 20 Animal symbolism
– 21 Inanimate object symbolism
• Paramnesia subscale
– 22 De´ ja` vu
– 23 Dream-reality confusion
• Lucid dreaming subscale score
– 6 Awareness of being in a dream
– 7 Self-scripted dreams
• Autosuggestion subscale
score
– 8 Reconnecting with dreams
– 9 Reexperience wishful dreams

31. Culture and Gender
• Culture
– self construal: sum
independent/individualistic
– self construal: sum
interdependent/collectivist
– Data source
(1=China;2=Canada)
• Gender
– male=1; female=2

32. Stepwise Regressions onto Self Report
Emotion Factor Scores From Recent Dream
Media Use Variables
Social media sum of means of North American & Chinese
Vdeo game variables (4; freq, len, num, age began) factor score
At what age approximately did you start using social networking sites?
How old were you when you played your first video game?
Dream Intensity Subscales
Dream Intensity: major modalities subscale mean
Dream Intensity: minor modalities subscale mean
Dream Intensity: dream work subscale mean
Dream Intensity: paramnesia subscale mean
Dream Intensity: lucid dream subscale mean
Dream Intensity: autosuggestion subscale mean
Culture
Self construal: sum independent
Self construal: sum interdependent/collectivist
Data source (1=china;2=Canada)
Gender
Male=1; female=2

33. Stepwise Regressions onto Self Report
Fear Factor Scores
Model Variables Entered
1 Data source 1=China;2=Canada
2 Dream Intensity: Bad dream subscale mean
3 Sex (male=1; female=2)
4 Social media sum of means of North
American & Chinese
5 Dream Intensity: autosuggestion subscale
mean
6 Dream Intensity: lucid dream subscale mean

34. Stepwise Regressions onto Self Report
General Negative Emotions (sans fear)
Model Variables Entered
1 Data source 1=China;2=Canada
2 Self construal: sum independent
3 Dream Intensity: lucid dream subscale mean
4 Video game variables factor score

35. Stepwise Regressions onto Self Report
Happiness Factor Score
Model Variables Entered
1 Sex (male=1; female=2)
2 Dream Intensity: dream work subscale mean
3 Social media sum of means of North American &
Chinese
4 At what age approximately did you start using
social networking sites?
5 Dream Intensity: autosuggestion subscale mean

36. Conclusions Regarding Media
• Fear is associated with threat in dreams
– Social media one predictor (among Canadians)
• Other negative emotions are not so associated
– Gaming one predictor (among Canadians)
• Happiness not associated with threat
– Social media one predictor

37. Slides available at
• www.spiritwatch.com
• http://academic.macewan.ca/gackenb
achj/