hall and van de castle content analysis of gamer dreams beena kuruvilla grant macewan college
TRANSCRIPT
Hall and Van de Castle Content
Analysis of Gamer Dreams
Beena KuruvillaGrant MacEwan
College
Hall and Van de Castle Coding System
8 General Categories•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)
Hall and Van de Castle Coding System
Calvin Hall & Robert Van de Castle (1966).
Intricate coding system relying solely on dream reports to determine the meaning of a dream.
One assumption: Frequency equals intensity
Allows for high inter-rater reliability, has well developed norms, and uses categories which are pertinent to waking concerns that may influence dreaming.
(Domhoff, 1996)
Hall and Van de Castle Coding System
DreamSAT spreadsheet (Schneider & Domhoff,
2006) Percentages and rates Group profiles
( N=27, 56 dreams - males norms only)
(Dreamresearch.net)
h vs.males
-.01+.26
-.36+.09
+.83-.08
0-.13
+.80
+.09-.47
-.15
-.04-.11
+.45
+.02-.22
-.08
-.32
-.70-.75
-.49-.19
-.21-.23
-1.0 -0.8 -0.6 -0.4 -0.2 0 +0.2 +0.4 +0.6 +0.8 +1.0
Male/Female Percent
Friends Percent
Dead & Imaginary Percent
Befriender Percent
Physical Aggression Percent
A/C Index
S/C Index
Indoor Setting Percent
Bodily Misfortunes Percent
Dreamer-Involved Success Percent
Friendliness
Misfortune
Success
Striving
Significant Differences from Male Norms
Fewer friends (16% vs 31%, p<0.002) yet more dead or imaginary characters appearing in dream reports (21% vs 0%, p<0.000).
Why be human in a game? They have fewer powers than other types of creatures.
Significant Differences from Male Norms
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”
Significant Differences from Male Norms
Greater percentage of self-negativity (84% vs 65%, p<0.028)
Smaller number of dreams with aggression (32% vs 47%, p<0.023) yet more intense aggression (namely physical aggression, 86% vs 50%, p<0.000) in those dreams that did contain it.
Significant Differences from Male NormsSubject 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…”.
Significant Differences from Male Norms
Fewer Misfortunes (7% vs 36%, p<0.000)Fewer Bodily Misfortunes(0% vs 29%, p<0.024)
Significant Differences from Male Norms
Misfortunes and Nightmares Subject 010- Dream 5 “…it was just you run around and whoever kills the most guys
wins the map or whatever. But in the dream it was divided into teams and there was a giant cannon which wasn’t in the game but they were in the dream and they were pixilated so it looked like someone had drawn them and everything interacted, like it didn’t in that particular game environment, like everything was very simple, I’d walk up to something and you know the switch would move, and it was basically 2 sides to a conflict and we were bombarding eachother. Like I had all the powers of the character like I could jump really high and I could switch guns and shoot things, and it was rewarding.”
Significant Differences from Male Norms
Dreams with at leastone instance: Fewer friendliness (2% vs 38%, p<0.000)
Fewer sexuality (0% vs 12%, p<0.000)
Fewer good fortunes (0% vs 6%, p<0.000)
Similarities with Male Norms
Success Failure Striving Family members
Conclusion More negative social/emotional (n=7) than positive elements (n=4)
Most no differences in scales
Theoretical Implications
Emotional Regulation - Negative emotion (self-negativity) - Positive emotion (more familiar characters and fewer misfortunes) Evolutionary theories of threat
prevalence (Revonsuo & Valli, 2000)
Practice for waking life (Bulkeley, 2004)
THE END
References
Bulkeley, Kelly (2004). Dreaming is play II: Revonsuo’s threat simulation theory in
Ludic context. Sleep and Hypnosis, 6(3), 119-129.
Domhoff, G. W. (1996). Finding meaning in
dreams: A quantative approach. New York:Plenum Press. Domhoff, G.W. (2007, May). Retrieved June 15,
2007, fromhttp://www.dreamresearch.net/.
Subscale Interview series
Male Norms
p vs.males
N for Inter-views
N for Male Norms
Characters
Male/Female Percent 67% 67% .937 45 873
Familiarity Percent 58% 45% * .026 81 1108
Friends Percent 16% 31% ** .002 81 1108
Family Percent 15% 12% .429 81 1108
Dead & Imaginary Percent
21% 00% ** .000 92 1180
Animal Percent 04% 06% .485 92 1180
Social Interaction Percents
Aggression/Friendliness Percent
100% 59% ** .000 25 546
Aggressor Percent 33% 40% .598 18 253
Physical Aggression Percent
86% 50% ** .000 35 402
Subscale Interview series
Male Norms
p vs.males
N for Interviews
N for Male Norms
Settings
Indoor Setting Percent 47% 48% .805 43 586
Familiar Setting Percent
56% 62% .560 32 320
Self-Concept Percents
Self-Negativity Percent 84% 65% * .028 25 809
Bodily Misfortunes Percent
00% 29% * .024 4 205
Negative Emotions Percent
81% 80% .941 16 282
Dreamer-Involved Success Percent
40% 51% .496 10 141
Torso/Anatomy Percent
27% 31% .720 22 246
Subscale Interview series
Male Norms
p vs.males
N for Inter-views
N for Male Norms
Dreams with at Least One:
Aggression 32% 47% * .023 57 500
Friendliness 02% 38% ** .000 57 500
Sexuality 00% 12% ** .000 57 500
Misfortune 07% 36% ** .000 57 500
Good Fortune 00% 06% ** .000 57 500
Success 09% 15% .165 57 500
Failure 09% 15% .142 57 500
Striving 18% 27% .102 57 500