Presentation on theme: "Hall and Van de Castle Content Analysis of Gamer Dreams Beena Kuruvilla Grant MacEwan College."— Presentation transcript:
Hall and Van de Castle Content Analysis of Gamer Dreams Beena Kuruvilla Grant 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)
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 Norms 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…”.
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 least one 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)
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, from http://www.dreamresearch.net/.
SubscaleInterview series Male Norms p vs. males N for Inter- views N for Male Norms Characters Male/Female Percent 67%.93745873 Familiarity Percent 58%45%*.026811108 Friends Percent 16%31%**.002811108 Family Percent 15%12%.429811108 Dead & Imaginary Percent 21%00%**.000921180 Animal Percent 04%06%.485921180 Social Interaction Percents Aggression/Friendlin ess Percent 100%59%**.00025546 Aggressor Percent 33%40%.59818253 Physical Aggression Percent 86%50%**.00035402
SubscaleInterview series Male Norms p vs. males N for Interviews N for Male Norms Settings Indoor Setting Percent47%48%.80543586 Familiar Setting Percent 56%62%.56032320 Self-Concept Percents Self-Negativity Percent84%65%*.02825809 Bodily Misfortunes Percent 00%29%*.0244205 Negative Emotions Percent 81%80%.94116282 Dreamer-Involved Success Percent 40%51%.49610141 Torso/Anatomy Percent27%31%.72022246
SubscaleIntervie w series Male Norms p vs. males N for Inter- views N for Male Norms Dreams with at Least One: Aggression32%47%*.02357500 Friendliness02%38%**.00057500 Sexuality00%12%**.00057500 Misfortune07%36%**.00057500 Good Fortune00%06%**.00057500 Success09%15%.16557500 Failure09%15%.14257500 Striving18%27%.10257500