the gamer - CIG 2014

Transcrição

The social fabric of virtual life
Social scientific research on the use and
effects of digital games
Thorsten Quandt • Department of Communication
• WWU Münster
Institut für Kommunikationswissenschaft | Prof. Thorsten Quandt
Digital games in society
‣
‣
‣
‣
‣
diversification of user groups
different types of gaming
gaming becomes more social
games as big business
change in focus of interest, end
of ,moral panic‘?
2
„
Digital games - still controversial
Some studies have yielded nonsignificant video game effects, just
as some smoking studies failed to find a significant link to lung
cancer. But when one combines all relevant empirical studies
using meta-analytic techniques, (...) effects emerge with
considerable consistency.
„
Anderson (2003)
We did not find associations between electronic games use
and conduct problems, which could reflect the lower
exposure to games and/or greater parental restrictions on
age-appropriate content for games compared with TV.
Parkes et al., an 11.000 person study (2013)
3
Digital games - still controversial
„
„
Gamification is the infusion of game mechanics, game
design techniques and/or game style into anything.
Gamification.org (2011)
Gamification is (marketing) bullshit.
Ian Bogost (2011)
4
Digital games historically
‣
first computer game: Noughts & crosses (Alexander S. Douglas, 1952).
‣
first multiplayer video game: Tennis for Two (William A. Higginbotham,
1958)
‣
Spacewar! (Steven Russell, 1962), distributed in universities and research
labs on large mainframe computers
‣
Computer Space (Nolan Bushnell, 1971), first commercial Arcade game
‣
Pong (Ralph Baer/Nolan Bushnell/Allan Alcorn, 1971)
‣
.... in the meantime: Atari VCS, C 64, PC Gaming, various console
generations etc. pp.
=> More than 60 years of computer games history.
5
Digital games as a social-scientific research object
‣
late 1990s, more interest from social scientists and academics from the
humanities in digital games (in parallel with mainstream success of PC
gaming and a new generation of video games)
‣
2003: Terra Nova blog, features a lot of scientists and their thoughts
about games (founded by Ted Castronova, Julian Dibbell, Dan Hunter and
Greg Lastowka)
‣
2003: DiGRA (Digital Games Research Association) was established,
founding president Frans Mäyrä, with a mixture of humanities and social
sciences people
‣
other international groups, founded in ,mainstream‘ comm/media studies:
ICA Game Studies Interest Group (founding chair: John Sherry), ECREA
TWG Digital Games Research (founding chair: Thorsten Quandt)
6
Digital games research: International survey
‣
October 2012, collaboration of DiGRA, ECREA TWG, ICA SIG
‣
Goal: to obtain a clearer picture of the people involved in research into
digital games: their backgrounds, types of activities, perceptions of the field
and ideas for future directions
‣
Distributed to organization members, mailing lists, social media (Gamesnetwork list: 1500 members, ICA SIG members: around 200,
ECREA TWG members: 82/180 via Facebook)
‣
initially 792 responses, 544 participants in final data set
(Authored by: Jan Van Looy, Thorsten Quandt, Jens Vogelgesang, Malte Elson,
James D. Ivory, Frans Mäyrä, Mia L. Consalvo)
7
Nationality
21,7%
25,9%
2,2%
2,2%
2,9%
3,5%
US
Germany
Canada
Finland
UK
Netherlands
Brazil
Sweden
Belgium
France
Australia
Portugal
Other
11,4%
3,9%
4,0%
4,2%
7,0%
4,8%
6,3%
N = 544
8
Background
4,0%
3,9%
17,1%
11,2%
6,8%
13,1%
Media Studies
Communication Studies
Psychology
Sociology
Educational Sciences
Humanities
Arts
Engineering
Design
Computer Sciences
Other
4,8%
10,3%
11,8%
11,2%
5,9%
N = 544
9
Strongly Agree
5
4,36
4,19
4
4,06
3,69
3,20
3
2,61
2,21
2
1,64
Strongly Disagree 1
t
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eg
N
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im
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si
Ag
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H
N = 544
th
l
a
10
Component
1
2
3
The poten,al of using digital games in educa,on is promising.
0,845
-‐0,087
0,033
The poten,al of using digital games in health is promising.
0,844
-‐0,061
0,004
Digital games can have beneficial effects on their users.
0,677
0,254
0,063
I see myself as a gamer.
0,089
0,823
-‐0,050
I used to see myself as a gamer.
-‐0,022
0,736
0,075
I have never ac,vely played digital games myself (R)
0,007
0,719
-‐0,189
The addic,on effects of DG are a problem for society.
0,020
-‐0,096
0,789
The effects of DG on aggression behavior are a problem for society.
0,073
-‐0,235
0,754
Digital games can have harmful effects on their users.
0,009
0,154
0,719
PCA, Varimax Rota/on with Kaiser Normaliza/on, Components 1-‐3 explain 61,715 % of Variance
11
Estimated means of factor scores
0,700
0,618
0,400
0,350
0,293
0,176
0
-0,077
-0,291
-0,350
-0,405
-0,477
-0,700
*
ci
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ol
So
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nit
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n
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ir n sci syc
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P
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gi pu
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E om
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(Uni, N=491, controlled for: gender, time/gaming, years in DG research, DG courses some/all)
*
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12
‣
Games researchers are typically male, in their mid-thirties, work at a university,
and have a social-scientific background. On an average, they work on digital
games for 6 years now, and they play one hour of digital games per day
themselves. Half of them come from the US, Germany, Canada or Finland.
‣
They do dismiss the idea that games generally have a negative impact on
society; they rather see positive effects, for example on culture, education and
health.
‣
Among the various disciplinary groups, educational scientists and psychologist
in games research have a more positive view of gaming, while sociologists
have a more critical view (although they are all positive in general).
13
Research project
„The social fabric of virtual life“
(ERC SOFOGA 240864)
ERC project: The social fabric of virtual life
Research of the ,in game‘ and ,out of the game experience‘ and their
interdependencies; social aspects of gaming; panel study over 3 years of
research; project supported by the European Research Council (ERC) with
1,84 million Euros over the course of 5 years
‣
Expert interviews (Politics, Industry, relevant Actors)
‣
Representative survey (50.000 omnibus, 5000 panel, 3 y.)
‣
Network analysis RL/VL
‣
Guided interviews (User)
‣
In game observations, experiments
15
The survey
Omnibus study, diffusion study, CATI
‣ N= 50.000, subsequent calibration studies (N=1000)
Panel, three waves, CATI
‣ 1: N = 5000, Spring 2011
‣ 2: N = 2500, Spring 2012
‣ 3: N = 1100, Spring 2013
representative sample of German gamers aged 14 and above
Institut für Kommunikationswissenschaft | Chair
Prof. Thorsten
of Online Quandt
Communication
The survey - Main Scales/Sub-Projects
Addic%on
•
•
•
•
•
Use PaOerns
-‐ VG
-‐ Other Media
Spare ,me ac,vi,es
Problema,c Use
Success
-‐ Academic
-‐ Occupa,onal
Life Sa,sfac,on
Aggression
•
Buss & Perry
-‐ Physical aggression
-‐ Verbal aggression
-‐ Anger
Sociality
•
•
•
•
•
Institut für Kommunikationswissenschaft | Chair
Prof. Thorsten
of Online Quandt
Communication
Social Networks
Social Support
Loneliness
Self-‐Esteem
Social Skills
Cul%va%on
•
•
militarism
sexism
Findings (I).
Some simple descriptives.
Some base data
Computer and console players (diffusion/age group)
100%
33 %
50 %
71 %
83 %
90 %
Non-‐Gamers
Gamers
75%
67%
50%
50%
25%
29%
17%
10%
0%
14-‐17
18-‐29
30-‐49
Age (y.)
50-‐64
65 +
n = 50.012
GameStat 2011, Bus
19
Some base data: age & use time
Average use time (all players x = 49,8 minutes per day)
100
90
minutes per day
80
73,2
70
63,6
60
50
40
40,8
42,6
30-49
50-64
45,6
x = 49,8
30
20
10
0
14-17
18-29
age (years)
65+
n = 4.505
GameStat 2011, Panel
20
It‘s not about the time... but still...
Game use (in minutes)
280
269,4
210
140
70
35,4
0
Normal User
Extreme User
n = 4.505
GameStat 2011, Panel
21
... there are differences not only in use time...
Extreme Gamers (3+ h/day)
1
0,5
0
-0,5
-1
g
le
Ro
yin
Pla
St
eg
t
a
r
r
y
te
o
o
Sh
rt
y
Spo
M
c
usi
&
le
t
Par
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ogi
&
zz
Pu
L
22
Findings (II).
Addiction and
problematic behavior.
Addiction scale
‣
based on Gaming Addiction Scale (GAS) by Lemmens (7 items
with highest factor loadings derived from 21 item scale)
‣
items: 5 point Likert scale: 0 (never), 1 (almost never), 2
(sometimes), 3 (often) and 4 (very often)
‣
Cronbach`s alpha: .72; confirmatory factor analysis - single-factor
model, acceptable model fit: (Satorra–Bentler scale correction, d.f.
= 14) = 51.9, P < 0.01; root mean square error of approximation
(RMSEA) = 0.03; standardized root mean square residual (SRMR) =
0.02; comparative fit index (CFI) = 0.97
24
Addiction scale
‣
Did you think about playing a game all day long? (salience)
‣
Did you play longer than intended? (tolerance)
‣
Did you play games to forget about real life? (mood modification)
‣
Have you failed when trying to reduce game time? (relapse)
‣
Have you felt bad, when you were unable to play? (withdrawal)
‣
Did you have fights with other (e.g. family, friends) over your time spent on
games? (conflict)
‣
Have you neglected other important activities
(e.g. school, work, sports) because you were
playing games? (problems)
25
Addiction scale
other scales used here:
‣
Personality traits: social competence (California Psychological
Inventory), Berlin Social Support Scale, General Self-Efficacy
Expectations Scale, Aggression Scales (Buss & Perry, Neo
Personality Inventory)
‣
Life satisfaction
‣
Gaming related variables (frequency, genre preferences)
26
Findings: Addiction
Table 2 Game Addiction Scale (GAS): item description, scale means and prevalence
mean: 0.62 on a
scale from 0 to 4!
Adolescents (14–18)
How often during the last six months . . .
(n = 562)
Did you think about playing a game all day long?
(salience)
Did you play longer than intended? (tolerance)
Did you play games to forget about real life? (mood
modification)
Have you failed when trying to reduce game time?
(relapse)
Have you felt bad, when you were unable to play?
(withdrawal)
0.62 (0.54, 0.69)
1.54 (1.45, 1.64)
0.31 (0.25, 0.37)
0.45 (0.38, 0.52)
0.34 (0.29, 0.40)
27
0.8
0.4
0.0
0.4
Density
0.8
1.2
Adults (18-39
(18−39) y.)
Adults
1.2
Adolescents(14-17
(14−17)y.)
Adolescents
0.0
Density
Findings: Addiction
1
2
3
4
5
n=580, Addicted: 0.2%, Problematic: 7.6%
1
2
3
4
5
n=1866, Addicted: 0.2%, Problematic: 3.2%
28
Mean GAS score
Proportion problematic users (%)
Proportion addicted users (%)
1.63 (1.59, 1.68)
7.6 (5.6, 10.1)
0.2 (0.1, 0.5)
1.46 (1.44, 1.48)
3.3 (2.5, 4.2)
0.2 (0.1, 0.4)
1.40 (1.38, 1.42)
3.0 (2.3, 3.8)
0.2 (0.1, 0.5)
Multi-group
structural
modeling
Means and proportions (point
estimates and 95%equation
confidence intervals);
items were scored on a five-point Likert scale from 0 (never) to 4 (very often).
Table 3 Relationships between the Game Addiction Scale (GAS), psychological and gaming-related variables.
Game Addiction Scale
Gaming frequency
Online multi-player game use
Preference for role-playing games
Preference for first-person shooter games
Physical aggression
Anger aggression
Self-efficacy
Social support
Sociability
Life satisfaction
Younger adults (19–39)
Older adults (40+)
(n = 562)
(n = 1809)
(n = 1836)
0.34 (0.27, 0.41)
0.23 (0.15, 0.30)
0.11 (0.02, 0.19)
0.26a (0.18, 0.33)
0.30 (0.22, 0.37)
0.32a (0.25, 0.40)
-0.21 (-0.29, -0.13)
-0.32a (-0.39, -0.25)
-0.24a (-0.32, -0.16)
-0.19 (-0.27, -0.11)
0.33 (0.29, 0.37)
0.23 (0.19, 0.28)
0.19 (0.14, 0.23)
0.17 (0.13, 0.22)
0.20 (0.15, 0.24)
0.19 (0.15, 0.23)
-0.15 (-0.19, -0.10)
-0.13 (-0.18, -0.09)
-0.13 (-0.18, -0.09)
-0.24 (-0.29, -0.20)
0.36 (0.32, 0.40)
0.24 (0.20, 0.28)
0.12 (0.07, 0.16)
0.08 (0.03, 0.13)
0.22 (0.18, 0.26)
0.22 (0.18, 0.26)
-0.15 (-0.19, -0.10)
-0.15 (-0.19, -0.10)
-0.10 (-0.15, -0.05)
-0.26 (-0.30, -0.22)
Pearson’s correlation coefficients and 95% confidence intervals. aSignificant difference between two or more groups. Multiple-group structural equation
model with metric invariance between groups (equal factor loadings). Multiple linear regression (MLR) estimation, Satorra–Bentler scaled c2
(d.f. = 1218) 1631.4, P < 0.01, comparative fit index (CFI) 0.97, standardized root mean square residual (SRMR) 0.03, root mean square error of
approximation (RMSEA) 0.02.
who prefer first-person shooters are more likely to be
29
relationship is more pronounced among adolescents than
Means and proportions (point estimates and 95% confidence intervals); items were scored on a five-point
Table 3 Relationships
between the Game Addiction Scale (GAS), psychological and gamingCorrelational
analysis
Game Addiction Scale
Gaming frequency
Online multi-player game use
Preference for role-playing games
Preference for first-person shooter games
Physical aggression
Anger aggression
Self-efficacy
Social support
Sociability
Life satisfaction
Younger adults
(n = 562)
(n = 1809)
0.34 (0.27, 0.41)
0.23 (0.15, 0.30)
0.11 (0.02, 0.19)
0.26a (0.18, 0.33)
0.30 (0.22, 0.37)
0.32a (0.25, 0.40)
-0.21 (-0.29, -0.13)
-0.32a (-0.39, -0.25)
-0.24a (-0.32, -0.16)
-0.19 (-0.27, -0.11)
0.33 (0.29,
0.23 (0.19,
0.19 (0.14,
0.17 (0.13,
0.20 (0.15,
0.19 (0.15,
-0.15 (-0.19
-0.13 (-0.18
-0.13 (-0.18
-0.24 (-0.29
30
Pearson’s correlation coefficients and 95% confidence intervals. aSignificant difference between two or mor
LONGITUDINAL PATTERNS OF PROBLEMATIC COMPUTER GAME USE
Table 2
Longitudinal
patterns
Longitudinal patterns of problematic and unproblematic game use
Types
Stable
unproblematic
Starters
Stable
problematic
Stoppers
Inconsistent
T1
T2
unproblematic unproblematic
T3
N
unproblematic 826
%
91.6 (89.5, 93.3)
unproblematic unproblematic
problematic
13
1.4 (0.8, 2.5)
unproblematic
problematic
problematic
2
0.2 (0.1, 0.8)
problematic
problematic
problematic
9
1.0 (0.5, 2.0)
problematic
problematic
unproblematic
2
0.2 (0.1, 0.8)
problematic unproblematic
unproblematic
22
2.4 (1.6, 3.7)
problematic
unproblematic
16
1.8 (1.1, 2.9)
problematic unproblematic
problematic
1
0.1 (0.1, 0.7)
unproblematic
N = 902; Missings, n = 11
Summing up: Addiction
Findings (SEM modeling, multi-group cross-lagged/autoregressive models):
‣
low prevalence of stable problematic use (-> stability of behavior could be
considered a prerequisite of addiction)
‣
no systematic interdependencies between problematic gaming and
psycho-social well-being (in contrast to Gentile et al. 2011)
‣
no typical downward-spiral, no systematic negative changes (consistent
with Van Rooji et al. 2011)
‣
only a small group of problematic gamers; that group seems to differ from
the rest of the gamers
32
Findings (III).
What about aggression?
Findings (III): Games and aggression
‣
hundreds of studies on this topic
‣
overall results (still) inconclusive
‣
mostly experimental and cross-sectional studies
‣
ongoing heated debate about the findings, their interpretation and
relevance
34
Games & aggression: Longitudinal studies
‣
11 publications in international peer-reviewed journals that explicitly look
at VVG in international peer-reviewed journals (end of 2013)
‣
overall heterogeneous findings
‣
rather homogeneous sampling: predominantly convenience samples,
mostly children & teenagers, Ø age range 4.8 years
‣
often only one direction of effects tested (typically the socialization
hypothesis)
35
Survey: our measures
‣
demographic data: participant sex, age, and educational level
‣
physical aggression: two items from the German translation of the
physical aggression subscale from the Buss & Perry Aggression
Questionnaire
‣
VG use: self-reported hours per day
‣
VVG use: mean age ratings by German USK for up to 6 games the
respondents currently play
‣
here: analysis of teens and young adults
(14-21)
36
Findings III: Results of aggression analysis
Upper row: 14-‐17, lower row: 18-‐21. N = 276, MLMV estimation, χ2(15, N14-‐17 = 140, N18-‐21 = 136) = 17.92, p = .27, CFI = .99, RMSEA = .04, WRMR=.48, *p < .
05, **p < .01.
37
Findings III: Results of aggression analysis
Third variable
Selection effect with third variable control
Socialization effect with third variable control
Model fit
14-‐17
18-‐21
14-‐17
18-‐21
p
β
β
β
β
Participant sex (n = 276)
.26**
ns
ns
ns
20.69
.35
Education (n = 247)
.34**
ns
ns
ns
18.54
.49
Gaming frequency (n = 273)
.31**
ns
ns
ns
23.38
.22
χ(df)
*p < .05, **p < .01, MLMV estimation
38
Games & aggression: Longitudinal studies
‣
age as an important variable:
proxy for changes in aggression and VG use
(legal) access to games
‣
interindividual differences and intraindividual change should be taken into
account when studying VVG and aggression
‣
potentially underlying 3rd variables? e.g., sensation seeking
39
What do we learn from this?
‣
gaming reaches a wider and more diverse audience than discussed in public
‣
,addiction‘ (in a psychological/medical sense, not to be confused with games
that can have an ,addictive‘ quality for a short time) does not affect a large
majority of gamers, but a small group that differs from the rest
‣
games and aggression are only correlated for young users, and we found only
support for a selection effect (not a socialization effect)
‣
overall, a much more differentiated analysis of differing gamer groups and
sub-populations is necessary; there is no ,the gamer‘ out there (anymore)
‣
science, society and industry alike would benefit from a more nuanced
and ,neutral‘ discussion of games as media entertainment
References
‣
Breuer, J., Festl, R., Vogelgesang, J. & Quandt, T. (2014) Violent video games and physical
aggression: Evidence for a selection effect among adolescents. Psychology of Popular Media
Culture (Accepted).
‣
Domahidi, E. & Quandt, T. (2014). Living in a virtual world? An excessive gamer typology. In
Quandt, T. & Kröger, S. (Eds.), Multiplayer. The social aspects of digital gaming (p. 204-214).
London: Routledge.
‣
Festl, R., Scharkow, M. & Quandt, T. (2013). Problematic computer game use among
adolescents, younger and older adults. Addiction, 108(3), 592-599.
‣
Mäyrä, F., Van Looy, J., & Quandt, T. (2013). Disciplinary Identity of Game Scholars: An Outline.
Proceedings of the 6th DiGRA-Conference "DeFragging Game Studies". Atlanta.
‣
Scharkow, M., Festl, R. & Quandt, T. (2014). Longitudinal patterns of problematic computer
game use among adolescents and adults – a 2-year panel study. Addiction (Online First). doi:
10.1111/add.12662
Thank you!
Thank you!
Prof. Dr. Thorsten Quandt, Institut für
Kommunikationswissenschaft, WWU Münster, Germany
[email protected]
42

the gamer - CIG 2014

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