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Mood repair is a well-established function of media usage implying distraction from negative mood and the modification of unpleasant arousal states. Recent studies have found interactive media, in particular computer games, to be more effective in repairing mood than noninteractive media. It has been suggested that this is due to the higher task demand of interactive media distracting the players from negative feelings. Yet interactive media have also been found to increase arousal, which can also be seen as a cause for successful mood repair. It remains an open question which mechanism or to which degree both mechanisms—distraction and arousal regulation—account for mood repair via interactive media. The current study was designed to examine this so far unanswered question. We analyzed how effectively negative moods were regulated after a computer game, after a gameplay video, and without media consumption (control group). Mood repair, physiological arousal (positive change in electrodermal activity), and subjective arousal were assessed. Results confirmed that computer games led to a higher degree of mood repair and that this repair was a function of task demand as well as arousal characteristics. Results are discussed in terms of arousal regulation and intervention potential in interactive media.
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Psychology of Popular Media Culture
Eating Ghosts: The Underlying Mechanisms of Mood
Repair via Interactive and Noninteractive Media
Diana Rieger, Lena Frischlich, Tim Wulf, Gary Bente, and Julia Kneer
Online First Publication, March 17, 2014. http://dx.doi.org/10.1037/ppm0000018
CITATION
Rieger, D., Frischlich, L., Wulf, T., Bente, G., & Kneer, J. (2014, March 17). Eating Ghosts: The
Underlying Mechanisms of Mood Repair via Interactive and Noninteractive Media.
Psychology of Popular Media Culture. Advance online publication.
http://dx.doi.org/10.1037/ppm0000018
Eating Ghosts: The Underlying Mechanisms of Mood Repair via
Interactive and Noninteractive Media
Diana Rieger, Lena Frischlich, Tim Wulf,
and Gary Bente
University of Cologne
Julia Kneer
Erasmus University Rotterdam
Mood repair is a well-established function of media usage implying distraction from
negative mood and the modification of unpleasant arousal states. Recent studies have
found interactive media, in particular computer games, to be more effective in repairing
mood than noninteractive media. It has been suggested that this is due to the higher task
demand of interactive media distracting the players from negative feelings. Yet inter-
active media have also been found to increase arousal, which can also be seen as a
cause for successful mood repair. It remains an open question which mechanism or to
which degree both mechanisms— distraction and arousal regulation—account for mood
repair via interactive media. The current study was designed to examine this so far
unanswered question. We analyzed how effectively negative moods were regulated
after a computer game, after a gameplay video, and without media consumption
(control group). Mood repair, physiological arousal (positive change in electrodermal
activity), and subjective arousal were assessed. Results confirmed that computer games
led to a higher degree of mood repair and that this repair was a function of task demand
as well as arousal characteristics. Results are discussed in terms of arousal regulation
and intervention potential in interactive media.
Keywords:
mood management theory, computer games, mood repair, physiological arousal
“If Pac-man had affected us as kids, we’d all
be running around in dark rooms, munching
pills and listening to repetitive electronic mu-
sic.”
1
Media is increasingly dominating our every-
day life. For instance, the average American
uses some form of media for 9.5 h per day
(Leckart, 2009). Although media reports have
always emphasized the possible link between
media consumption and negative outcomes
such as violence and aggression, recent research
has also demonstrated the positive effects that
media bring along (Ferguson, 2010). Although
stated as a possible violent video game in the
80s (Klein, 1984), according to the quote by the
English comedian and satirist Marcus Brick-
stocke, not everybody who played Pacman was
affected in a potential negative way. More than
that, past studies suggest that media may have
many positive effects, for instance with regard
to the management of negative moods to restore
and maintain positive mood states (as suggested
within the mood management theory, MMT;
Zillmann, 2004; Zillmann & Bryant, 1985). En-
tertainment media do particularly well in sup-
porting this regulation process. However, their
1
This quote was made by the English comedian and
satirist Marcus Brickstocke. It is claimed to be one of his
best known jokes. It is meant as an ironic commentary on
the controversy concerning the influence of video games on
children.
Diana Rieger, Lena Frischlich, Tim Wulf, and Gary
Bente, Department of Psychology, Social Psychology II:
Media and Communication, University of Cologne, Co-
logne, Germany; Julia Kneer, Department of Media and
Communication, Erasmus University Rotterdam, Rotter-
dam, The Netherlands.
The authors express their gratitude to Christian Schneider
and Sabine Päsler for their help during data collection and
the fruitful discussions during the realization of this study.
Correspondence concerning this article should be ad-
dressed to Diana Rieger, Department of Psychology, Commu-
nication and Media Psychology, University of Cologne, Rich-
ard-Strauss-Street 2, 50931 Cologne, Germany. E-mail: diana.
rieger@uni-koeln.de
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Psychology of Popular Media Culture © 2014 American Psychological Association
2014, Vol. 3, No. 1, 000 2160-4134/14/$12.00 DOI: 10.1037/ppm0000018
1
effectiveness depends on the type of media that
people engage in (Zillmann, 1988a, 1988b).
So far, most research has been conducted on
noninteractive media, for instance by compar-
ing different TV programs and movie genres
(Bryant & Zillmann, 1984; Meadowcroft &
Zillmann, 1987), or on music (Knobloch & Zill-
mann, 2002; Schramm, 2005). Yet, interactive
media, mainly computer games, have become
an important part of the current entertainment
landscape (Nielsen, 2012). Moreover, Olson
(2010) provided evidence that adolescents even
name “regulating feelings” as one of the main
motivations to engage in video game play. Ac-
cordingly, a growing body of evidence for the
effectiveness of computer games to attenuate
negative moods exists (Bowman & Tamborini,
2012; Chen & Raney, 2009; Ferguson & Rueda,
2010; Valadez & Ferguson, 2012).
In a recent study, Reinecke et al. (2012)
suggested that mood management processes
rely on two basic mechanisms: (1) distraction
from the negative mood and (2) the process of
mood repair itself by addressing the cause of
the negative mood. While distraction is consid-
ered as a function of the intervention potential
of the medium (e.g., its interactivity), the pro-
cess of mood repair has been understood as a
physiological homeostasis restoration (Bryant
& Davies, 2006), such as higher arousal when
someone is bored, or by lowering reported
stress levels.
Computer games provide higher intervention
potential such as higher task demands in com-
parison with noninteractive media (Bowman &
Tamborini, 2012) and thus might be more ef-
fective in distracting from noxious moods.
However, computer games are also accompa-
nied by higher arousal properties than noninter-
active formats (Ravaja, Saari, Salminen, Laarni,
& Kallinen, 2006; Reinecke & Trepte, 2008).
Other authors even argue that the arousal char-
acteristics of computer games are responsible
for their effective mood repair function (Bryant
& Davies, 2006; Chen & Raney, 2009; Raney,
Smith, & Baker, 2006). Increased arousal due to
playing a computer game might be perceived as
rather energizing and positive when compared
with inactive states. Especially, for deactivated
moods such as sadness (Russell, 2003), playing
computer games is most plausible beneficial
(Dillman-Carpentier et al., 2008).
The two mentioned underlying mechanisms,
namely, distraction and addressing the cause of
a negative mood, can be activated differently
depending on aspects of the medium. As out-
lined earlier, the interactivity of the media stim-
ulus for instance determines the intervention
potential and further influences arousal proper-
ties. Until now, no study directly compared
characteristics of interactive and noninteractive
media with regard to their contribution to a
mood repair process.
The current study therefore aims at examin-
ing how both processes, that is, distraction (by
the intervention potential of a medium) and
regulating the cause (by the arousal regulation
characteristics of a medium), contribute to
mood repair via interactive and noninteractive
media. In the following sections, we will first
describe the basic assumptions of MMT and
their implications for the regulation of negative
mood states. Based on these assumptions, we
will review recent studies on both processes
suggested by Reinecke et al. (2012). While dis-
traction might facilitate the regulation of a neg-
ative mood through task load and involvement,
addressing the cause of a negative mood can
contribute to mood repair through arousal char-
acteristics.
Mood Management Theory
The basic assumption in MMT (Zillmann,
1988a, 1988b; Zillmann & Bryant, 1985) is that
humans have a hedonic motivation to terminate
negative and to strive for more positive moods
(Knobloch-Westerwick, 2006), and postulates
that moderate levels of arousal are perceived
as more pleasurable than either high or low ones
(Zillmann, 1988b). Four main dimensions are
described to influence the mood management
process (Bryant & Davies, 2006): (1) hedonic
valence, (2) behavioral affinity, (3) intervention
potential, and (4) arousal regulation. In partic-
ular, the latter two dimensions are important for
the understanding of mood management via in-
teractive media.
Intervention potential describes the power of
a media stimulus to break into people’s current
cognitions and to disrupt the actual emotional
experience: the higher the intervention poten-
tial, the better a media content is able to direct
attention away. According to Zillmann (1988a,
1988b), in very aversive states, users choose
2 RIEGER, FRISCHLICH, WULF, BENTE, AND KNEER
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media content with a high intervention poten-
tial.
According to the mechanism of arousal regu-
lation, people choose media stimuli to regulate
and neutralize their arousal. It has been suggested
that people in conditions of overstimulation (such
as stress) choose calming media stimuli. In con-
trast, in conditions of understimulation (such as
boredom), they prefer arousing or exciting stimuli
(Bryant & Zillmann, 1984).
MMT’s Underlying Processes
Reinecke and colleagues (2012) recently in-
troduced the idea that the mood management
mechanisms represent two underlying pro-
cesses: (a) “those that simply distract an indi-
vidual from negative mood” and (b) “those that
address its cause through repair” (p. 438). On
this point, Reinecke et al. (2012) subsume he-
donic valence, behavioral affinity, as well as
intervention potential under this first process.
With regard to the second process, such an
explanation might explain why negative media
stimuli can have beneficial outcomes such as
mood repair. Friedman, Gordis, and Förster
(2012), for instance, found participants in a sad
mood to more often choose sad music address-
ing the cause of their mood. They asked their
participants for their music choices and the rea-
son behind them. In the sad condition, partici-
pants reported that they had chosen songs that
made it more likely to think about the heart-
rending imagery that had elicited their actual
feelings (Friedman et al., 2012). Their explana-
tion is that in some personal or societal con-
texts, it is more normatively appropriate to lis-
ten to sad songs (e.g., after a funeral). Acting
normatively correct, in turn, makes people feel
good, which serves their hedonic wish to regu-
late negative states. This is also in line with
Raghunathan and Corfman (2004), who posit
that people being in a sad mood seek for pleas-
ant stimuli that are perceived as suitable to
compensate for the sad mood. According to
these studies, acting in an appropriate way can
in the long run be pleasant and improve a sad
mood. In the current study, we also relied on an
induction of sadness to be able to relate our
results to former similar studies (Dillman-
Carpentier et al., 2008; Friedman et al., 2012;
Raghunathan & Corfman, 2004).
Acknowledging the fact that negative mood
can result from a failure to satisfy basic psy-
chological needs, Reinecke et al. (2012) dem-
onstrated that satisfying those needs that were
originally responsible for the negative mood
can lead to mood repair. In their study, they
thwarted participants’ intrinsic needs through
a false feedback task that was thought to
thwart the need for competence and auton-
omy. The authors argue that higher task de-
mands in interactive media are able to provide
the individual with a greater feeling of com-
petence and autonomy. Accordingly, the re-
sults demonstrate that participants chose me-
dia stimuli with higher task demands that
were able to satisfy those needs. This choice
in consequence led to higher levels of enjoy-
ment and was able to improve the partici-
pants’ mood.
Therefore, the second process may be
driven by arousal regulation, as by regulating
their arousal, people directly address the
cause of their negative state (e.g., understimu-
lation) (Bryant & Zillmann, 1984). If, for
instance, a low arousal state is the core of a
negative mood, then increasing arousal could
therefore be considered to “attack” the cause
of the negative mood itself and therefore re-
pair it. In consequence, arousal regulation
might play an important part in this regula-
tion of the cause process.
As proposed in MMT, both processes, inde-
pendent of their impact, however lead to bene-
ficial effects for the management of one’s neg-
ative mood. Within mood repair, the increase of
positive and the decrease of negative mood have
to be distinguished. For instance, Chen and
Raney (2009) found that all forms of entertain-
ment media were able to restore a positive
mood. However, only interactive media led to
decreases in negative moods. We therefore ex-
pect:
H1a: Decreases in negative mood are
higher after the use of interactive media
compared with noninteractive media fol-
lowed by a nonmedium control condition.
H1b: Positive mood increases irrespective
of interactivity of the medium.
In addition to assuming general beneficial
effects of media for mood repair, we believe
that both processes suggested by Reinecke et al.
3EATING GHOSTS
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(2012) contribute to mood repair via distinct
mechanisms.
Distraction
We conceive the first process, distraction, to
be driven by the intervention potential of a
medium, as it can direct attention away from a
negative mood (Zillmann, 1988b). Compatible
with the assumption of intervention potential to
contribute to mood management, research has
found that more interactivity has a beneficial
effect on mood repair processes (Bowman &
Tamborini, 2012). Bowman (2010) found that
video games (flight simulators) were more suc-
cessful in repairing noxious moods than their
noninteractive equivalents (watching a flight
simulation without own controls).
Further, former studies already found a
higher intervention potential to be beneficial
(Bowman & Tamborini, 2012), as it offers a
higher task load than noninteractive stimuli.
Therewith it creates a higher cognitive load and
can direct the attention away from the negative
mood (Bryant & Davies, 2006). Interactive for-
mats therefore are expected to induce higher
task load compared with a noninteractive for-
mat.
In line with this, directing attention away
from the negative emotion should also affect
involvement with the former emotion-inducing
situation. Witmer and Singer (1998) described
involvement as “a psychological state experi-
enced as a consequence of focusing one’s en-
ergy and attention on a coherent set of stimuli or
meaningfully related activities and events” (p.
227). As different types of media are often used
and designed to induce emotional situations in
their viewers (Gross & Levenson, 1995;
Schaefer, Nils, Sanchez, & Philippot, 2010), the
amount of involvement with the media stimuli
can be used to explain the emotional engage-
ment of the viewer. In the present study, a
negative emotion was induced by confronting
participants with a movie clip that had been
pretested to induce sadness (Schaefer et al.,
2010). Involvement with the emotion-inducing
movie was thus considered to represent atten-
tion paid to the negative emotion.
In terms of MMT, a higher intervention po-
tential should direct attention (and correspon-
dent involvement) away from the cause of the
negative emotional state. With regard to mood
repair in interactive media, greater intervention
potential is thought to demand more cognitive
resources of the user (Bowman & Tamborini,
2012) and should thus result in less involvement
with the negative emotional state, and the emo-
tion-inducing situation after engaging in an in-
teractive computer game. Therefore, we pro-
pose:
H2a: Interactive media induce a higher
task load compared with noninteractive
media followed by a no-media control con-
dition.
H2b: Interactive media reduce the atten-
tion directed toward the causes of a nox-
ious mood best wherefore involvement
with the emotion-inducing situation is least
in the interactive condition.
Addressing the Cause
With regard to the second process, thought to
be driven by arousal regulation, evidence for the
effect of interactivity on arousal regulation is
mixed. Computer games are more attention-
grabbing than noninteractive media (Grodal,
2000). They were also found to elicit higher
levels of physiological arousal (Ravaja et al.,
2006; Reinecke & Trepte, 2008) as well as
subjective arousal (Bowman & Tamborini,
2012). We therefore expect to clarify the char-
acteristics by distinguishing between (1) physi-
ological (objective) arousal and (2) subjectively
reported arousal.
Concerning subjectively reported arousal, in
the original formulation of MMT, a homeostatic
level of arousal has been presented as a desired
state. However, Bryant and Zillmann (Bryant &
Zillmann, 1984) found that young adults pre-
ferred stimulating over relaxing TV programs,
which was explained by the age of participants.
Applying this to interactive media, computer
games are thought to be especially suitable to
serve as a medium by which pleasurable levels
of arousal can be achieved (Bowman & Tam-
borini, 2012). Especially under conditions of
deactivated negative states such as depression
following frustration (Ferguson and Rueda
(2010) or sadness as a major emotion in depres-
sion (Leventhal, 2008), computer games might
be able to reactivate the players and thus lead to
a more activated, vital state (Ravaja et al.,
2006).
4 RIEGER, FRISCHLICH, WULF, BENTE, AND KNEER
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Supporting this assumption, Dillman-Carpen-
tier et al. (2008) found that exciting media (such
as playing a computer game) improved a de-
pressed mood. Valadez and Ferguson (2012)
demonstrated this effect to be independent of
playing time; even shorter periods of engage-
ment with a video game were able to decrease a
depressive mood. Hence, we expected the sub-
jective arousal to increase with the interactivity
of the medium. We further conceive the subjec-
tively reported arousal to represent the general
activation (vitality) the individual feels as a
response to an engagement with a medium. Vi-
tality reflects the energy subjectively available
to the individual. Vitality can be conceptualized
and operationalized as a subjectively reported
energetic arousal (Thayer, 1989) and represents
a significant indicator of psychological well-
being (Ryan & Frederick, 1997). Furthermore,
it represents the crucial outcome of successful
mood repair and has been described as an im-
portant part of positive media effects in other
lines of research (Reinecke, Klatt, & Krämer,
2011).
Based on this research, we expected both
physiological as well as subjective arousal to
be higher in an interactive setting than in a
comparable noninteractive setting. We hy-
pothesize.
H3a: With regard to physiological arousal,
interactive media lead to higher levels
compared with a noninteractive media
condition and a nonmedia control condi-
tion.
H3b: For subjective arousal, interactive
media lead to higher levels than a non-
interactive media condition and a control
condition.
Factors Contributing to Mood Repair
Finally, the current study also aimed at dis-
entangling the specific process underlying
mood management via interactive versus non-
interactive media and examined the contribu-
tion of intervention potential and arousal regu-
lation to it. We asked which factors mostly
contribute to mood repair. To our knowledge,
no study so far asked for the specific contribu-
tors, as in comparing them in terms of a distrac-
tion and addressing the cause process. There-
fore, we formulated the following research
question:
RQ1: Is mood repair driven by factors of
intervention potential (namely, task load
and involvement)? Or is it driven by fac-
tors of arousal regulation (namely, physi-
ological and subjective arousal)?
Method
We aimed to examine the mood management
of a sad mood via interactive and noninteractive
media, asking participants to actively play a
computer game, to watch a gameplay video of
the same computer game, or to wait for the
same duration. To investigate the subprocesses
of mood management, intervention potential
and arousal regulation were assessed as depen-
dent variables.
The current study thus realized a 3 (Condi-
tion: Game Playing [interactive] vs. Gameplay
video [noninteractive] vs. Control) 3 (Time:
Baseline vs. t1 vs. t2) design with the last as
repeated measurement factor.
Power Analyses
A priori effect size was calculated by using
data obtained from similar research by Bowman
and Tamborini (2012) as well as Chen and
Raney (2009), which both provided evidence
for an average effect size of f .31. A power
analysis performed with G
Power indicated that
54 participants would provide adequate power
(.95) in an analysis of variance (ANOVA)
with between- and within-subject factors.
Sample
Seventy-six participants took part in the
study. One participant had to be excluded due to
not reporting negative emotions after the nega-
tive mood induction. The remaining N 75 (45
female) were randomly assigned to the condi-
tions: 24 played Pacman, 24 watched the game-
play video, and 27 had a pause.
The mean age was 26.86 (SD 7.86) years.
Approximately three-quarters (73.3%) were
university students and the rest had already fin-
ished their studies at university. Gender was
equally distributed among the different condi-
tions,
2
(2, N 74) 0.90, p .64.
5EATING GHOSTS
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Materials
Mood induction. The current study relied
on an induction of sadness relate it to former
research using similar inductions (Chen, Zhou,
& Bryant, 2007; Friedman et al., 2012; Raghu-
nathan & Corfman, 2004). We chose a sadness/
loss-related mood induction via movies (Gross
& Levenson, 1995). The accordant scene was
taken from “City of Angels” (Silberling, 1998),
which was pretested across a broad population
(Schaefer et al., 2010).
Interactivity. For the condition in which
interactivity was high, participants played Pac-
man (Namco, 1980). Pacman was chosen due to
its simple structure and its popularity. Because
Bowman and Tamborini (2012) found game
play skills to have an impact on mood repair, we
chose a game that was easy to play even for
nonplayers. Furthermore, the “worlds” designed
inside computer games can be very complex
and equal game outcomes for different players
are unlikely. The restricted world of Pacman
increases the likelihood of similar game out-
comes in terms of losses and wins irrespective
of playing skills.
Comparing different levels of interactivity
involves methodological challenges, as de-
scribed, for instance, by Reinecke and col-
leagues (2011). To account for internal vali-
dity in the noninteractive condition, we
recorded a video of someone playing Pacman
that participants had to watch for the same
amount of time. By using a gameplay video,
2
it was ensured that participants saw the same
stimulus, resembling the real game in terms of
audiovisual elements without featuring the
same interactive elements.
As far as external validity is concerned, this
operationalization can also be regarded as ac-
ceptable. Consalvo (2003) argues that walk-
throughs—“detailed guides to how a player
should play a game sequentially . . . (p. 327)—
are narratives for games and therefore a cultural
product— existent in the media landscape.
There are also written walkthroughs and re-
corded gameplays (Ashton & Newman, 2010).
Many walkthroughs and similar formats (both
written and audiovisual) are uploaded on
gamesfaqs.com or youtube.com. There are even
gameplay videos of Pacman, and communica-
tion about the movement behavior of the
“ghosts.” One gameplay video of “Ms. Pac-
man” (http://www.youtube.com/watch?v
cVH1mCc5EvU) received 1,235,444 clicks
(until October 10, 2012).
Measures
Mood repair. Dependent variables in-
cluded the assessment of the emotional state
after the induction (t1) and once again after the
media intervention (t2) to measure mood regu-
lation. Mood was assessed via two subscales of
the SES (SES
3
; Hampel, 1977) (happy mood,
e.g., “happy” and depressed mood, e.g., “sad”).
The adjectives of the scale were rated on a
7-point scale from 1 ( do not at all feel that
way)to7( totally feel that way).
This differentiation between happy and de-
pressed mood allowed investigating the direc-
tion of mood repair effects (increase in happy
mood vs. decrease in depressed mood vs. both).
To account for these differential effects,
changes on the happy mood subscale will be
labeled as increase in positive mood; changes
on the depressed mood subscale will be referred
to as decrease in negative mood (Table 1).
Task load. Task load was assessed by ask-
ing participants for the perceived effort on a
7-perceived-point Likert scale ranging from 1
( not all demanding)to7( absolutely de-
manding).
Involvement. To investigate how deeply
involved with the negative mood induction par-
ticipants would still feel after having been dis-
tracted by one of the media stimuli (or the
control condition), we asked for involvement
after the interactivity manipulation.
Involvement was assessed via the involve-
ment subscale (␣⫽.80) of the Measurements,
2
We are aware of the fact that terms like walkthrough,
playthrough, let’s play, and gameplay are used synony-
mously on some occasions, and there is constant debate in
online forums about their differentiation. In this article, we
use gameplay video and refer to a recording of a short
sequence of somebody playing the corresponding game
without any comments, solution-orientation, or demonstra-
tion purpose.
3
German Skala zur Einschätzung der Stimmung (SES)
(scale for mood assessment). The SES consists of several
subscales to assess different aspects of mood. In this study,
we used the happy mood, depressed mood, and deactivation
subscale (see subjective arousal measure). (for more infor-
mation about the usage of the scale, see Gerrards-Hesse,
Spies, & Hesse, 1994; Hesse, Spies, Hänze, & Gerrards-
Hesse, 1992)
6 RIEGER, FRISCHLICH, WULF, BENTE, AND KNEER
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Effects, Conditions Spatial Presence Question-
naire (Vorderer et al., 2004). The wording was
adjusted to represent involvement with the
movie (e.g., “the presented story in the movie
was thought-provoking”). The scale was an-
swered on a 5-point Likert scale from 1 ( Ido
not agree at all)to5( I fully agree).
Physiological arousal. Arousal in terms of
electrodermal activity (EDA) was recorded us-
ing finger sensors (Wild Devine IOM, 2006).
EDA is defined as the electrical activity of the
skin that varies due to processes (neuronal ac-
tivation) in the autonomic nervous system. It is
considered to be a linear correlate to arousal
(Lang, 1995) and reflects both emotional re-
sponse and cognitive activity (Boucsein, 1992).
According to Ravaja (2004, p. 212), it is an
excellent description of “[the]drive state or [the]
nonspecific energizer of behavior, something that
describes the intensity of an experience but not its
quality.” EDA is found to be a sensitive and
reliable indicator especially for the emotional
component of arousal (Grings & Dawson, 1978;
Ravaja, 2004). It is especially useful to investigate
the effects of media stimuli and their activating
potentials (Bente & Feist, 2000).
To account for changes in EDA as a conse-
quence of media content, the EDA positive
change (EPC) indicator was calculated (Leiner,
Fahr, & Früh, 2012). This parameter indicates the
sum of all peak amplitudes per instance (e.g., a
media stimulus). To reduce statistical noise, we
first downsampled the data to 10 Hz and then
applied a moving median (moving window of 0.5
s) before calculating EPC (Leiner et al., 2012).
Subjective arousal. To assess subjective
arousal, the activation/deactivation subscale of
the SES (Hampel, 1977) was applied. It consists
of four items that were answered on a 7-point
scale ranging from 1 ( do not at all feel that
way)to7( totally feel that way). Table 1
displays the accordant items and reliabilities.
Procedure
The study took place at a large university in
Germany. They were equipped with finger sen-
sors Wild Devine, 2006) to measure physiolog-
ical arousal. To create a baseline recording for
arousal measures, all participants were first
asked to watch a picture of a tree for 90 s while
listening to calm ambient music.
A baseline of physiological arousal was re-
corded. Subsequently, participants were asked
to watch a scene from the movie “City of An-
gels” (Silberling, 1998) to induce a sad mood as
in previous studies (Schaefer et al., 2010). To
check the experimental manipulation, mood and
subjective arousal were measured directly after
the movie (t1). The participants were then ran-
domly assigned to one of the two experimental
conditions or the control condition with a vary-
ing task load (each lasting for 5 min): they
either played Pacman, or watched a gameplay
video of Pacman. To account for time effects, a
third (control) condition was added to contrast
media-induced mood repair with regulation of the
mood via nonmediated activities (no task load).
Participants in this control condition were not ex-
posed to media stimuli and were asked to take a
break until the experiment proceeded. After the
experimental manipulation, subjective arousal and
mood were assessed for the second time (t2).
Arousal in terms of EDA was also recorded dur-
ing the emotion-inducing movie clip (t1) as well
as during the media intervention (t2).
Results
Mood Repair
Our first hypothesis predicted that mood re-
pair would be greater following an interactive
compared with a noninteractive stimulus or no
media stimulus. To test mood repair via differ-
Table 1
Reliability (Cronbach’s Alpha) and Items for the SES Subscales
Scales t1 t2 Items
Depressed mood .87 .86 Sad, gloomy, sorrowful, grieved
Happy mood .86 .91 Happy, funny, cheerful, lively
Deactivation
a
.81 .81 Awake, lethargic, lazy, slow
a
The deactivation subscale was reverse-coded to resemble an “activation” score (except for
the item “awake”).
7EATING GHOSTS
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ent media, two 3 (Condition: Game vs. Game-
play vs. Break) 2 (Time: T1 vs. T2)
ANOVAs were calculated with mood serving as
the repeated measurement factor and the happy/
depressed, respectively, mood subscale serving
as the dependent variable. Subsequent analyses
were conducted via independent t tests.
Increases in positive mood. As predicted
in H1a, the analysis for increases in positive
mood revealed a significant main effect for
Time, indicating that all participants reported an
increase in happy mood at T2, F(1, 72) 26.78,
p .001,
p
2
.27. This effect was not char-
acterized by an interaction with the respective
Condition, F 1. All three conditions led to an
increase in happy mood in participants (M
t1
2.60, SD 1.27; M
t2
3.44, SD 1.37).
Decreases in negative mood. The analysis
for decreases in negative mood revealed a signif-
icant main effect for Time, indicating that all
participants regulated their mood, F(1, 72) 162.
82, p .001,
p
2
.69. As predicted, the decrease
in negative mood depended on the Condition,
F(2, 72) 6.62, p .01,
p
2
.16 (Figure 1).
Planned single comparisons revealed that there
were significant differences in the mood at T2,
both between the game and the gameplay video,
t(46) ⫽⫺2.55, p .01, d 0.74, as well as
between the game and the control condition,
t(49) ⫽⫺3.43, p .001, d ⫽⫺0.98. The non-
interactive condition did not significantly differ
from the control condition, t 1 (Table 2).
As predicted, interactive media did not dif-
ferentially affect the increase in positive mood
(H1a). However, they were more effective in
attenuating negative mood than noninteractive
media or the control condition (H1b).
Distraction
Univariate 3 (Condition: Game vs. Gameplay
vs. Break) ANOVAs for the dependent variables
task load and involvement were conducted. Sub-
sequent analyses were conducted via independent
t tests. See Table 3 for the descriptives.
Task load. H2a expected task load to in-
crease with interactivity of the medium. The
Figure 1. Mood repair (depressed mood subscale) after mood induction (t1) and after
experimental manipulation (t2) split by condition. Error bars represent standard errors.
Table 2
Means and Standard Deviations for DV Mood
Repair (Positive and Negative Mood Subscales)
Dependent
variable
t1 t2
MSDMSD
Positive mood
Game 2.67 1.27 3.78 1.17
Gameplay video 2.63 1.18 3.47 1.41
Control 2.53 1.38 3.12 1.48
Negative mood
Game 4.06 1.15 1.79 0.84
Gameplay video 4.21 1.44 2.58 1.27
Control 3.96 1.47 2.85 1.29
Note. Time of assessment: t1 was assessed after mood in-
duction; t2 was assessed after the experimental manipulation.
8 RIEGER, FRISCHLICH, WULF, BENTE, AND KNEER
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analysis depicted a significant main effect, F(2,
65) 9.96, p .001,
p
2
.24. Planned single
comparisons revealed the expected differences
(Table 3): Playing Pacman induced a higher
task load than both watching a gameplay video,
t(46) 2.35, p .05, d 0.68, and resting,
t(49) 5.45, d 1.51. Engaging in the non-
interactive medium also induced higher task
load, than did the control condition, t(49)
2.69, p .05, d 0.75. This pattern followed
a linear trend, F
linear
(1, 65) 19.92, p .001.
H2a was thus supported.
Involvement. As expected in H2b, the
main effect reached significance, F(1, 66)
13.17, p .001,
p
2
.29. Planned single
comparisons confirmed the significant differ-
ence between those playing Pacman, those
watching the gameplay video, t(46) ⫽⫺5.55,
p .001, d ⫽⫺1.60, and those in the control
condition, t(49) 4.45, p .001, d 1.26
(Table 3). Participants who watched the game-
play video were still more involved with the sad
movie than participants who were resting, but
this difference failed to reach significance,
t(49) 1.45, p .15.
Addressing the Cause
Physiological arousal (EPC). To test the
characteristics of objective arousal during distrac-
tive media consumption, a 3 (Condition) 3
(Time: Baseline vs. Emotion-Inducing Movie vs.
Experimental Manipulation) mixed ANOVA with
the latter serving as within-subject factor with
EPC as dependent variable was calculated. Single
comparisons were conducted via independent and
paired sample t tests.
A higher physiological arousal in the interac-
tive than in the noninteractive media or the
control condition was expected (H3a). Results
showed a significant main effect for Time, F(2,
144) 57.21, p .001,
p
2
.44. All three
points in time (baseline, movie, and experimen-
tal manipulation) differed with regard to their
arousal patterns. The expected interaction be-
tween Condition and Time was observed, F(4,
144) 6.17, p .001,
p
2
.15. The main
effect for Condition did not reach significance,
F(1, 144) 1.45, p .24. Analyzing the in-
teraction, there were no significant differences
during Baseline measurement, F 1, nor dur-
ing Emotion Induction via the Movie, F 1.
Significant differences between the three condi-
tions only emerged during Experimental Ma-
nipulation, F(2, 72) 7.19, p .001,
p
2
.17
(Figure 2).
Planned single comparisons calculated for
arousal during the manipulation showed that those
who played Pacman had a significantly increased
EPC in comparison with those who rested, t(49)
4.58, p .001, d 1.26. However, there were no
differences in EPC between Pacman players and
those watching Pacman, t 1. In addition, the
gameplay video condition differed from the con-
trol condition, t(29.28) 2.77, p .01, d 0.79.
This effect followed a linear pattern, F
linear
(1,
72) 12.15, p .001 (see Table 4 for all means
and standard deviations). H3a was thus only par-
tially supported: Both media conditions led to
higher physiological arousal than the control con-
dition. However, the interactive and noninterac-
tive conditions did not differ significantly from
each other.
Subjective arousal. Further, a higher sub-
jective arousal in the interactive as compared with
the noninteractive and the control condition was
expected (H3b). Changes in subjective arousal
were tested in a 3 (Condition) 2 (Time)
ANOVA with the last one serving as the repeated
measurement factor. Neither the main effect for
Time, F(1, 72) 3.52, p .07, nor the main
effect for Condition, F 1, reached significance.
There was however a significant interaction be-
tween Condition and Time, F(2, 72) 3.24, p
.05,
p
2
.08. Planned single comparisons using
dependent t tests per condition were calculated.
The results confirmed the expectations. Only in
the condition in which participants actively played
a computer game did subjective arousal signifi-
cantly increase, t(23) ⫽⫺2.64, p .05, dz
0.54. Neither after watching the gameplay
video, t 1, nor in the control condition, t(26)
1.33, ns, did participants report an increased
subjective arousal (see Table 4 for all means and
standard deviations). H3b was thus only partially
Table 3
Means and Standard Deviations for DV Task Load
and Involvement Split by Condition
Condition
Task Load Involvement
MSDMSD
Game 4.04 1.68 1.94 0.56
Gameplay video 2.92 1.64 3.01 0.76
Control 1.85 1.17 2.72 0.68
9EATING GHOSTS
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supported; the interactive condition led to changes
in subjective arousal, whereas neither the nonin-
teractive nor the control condition evoked any
changes in subjective arousal.
Factors Contributing to Mood Repair
To test for the differential impact of interven-
tion potential and arousal regulation on mood re-
pair, a regression analysis (forced entry) was cal-
culated with task load, involvement during movie
clip, physiological arousal, and subjective arousal
as predictors. To assess mood repair as dependent
variable (DV), we calculated a change score (de-
pressed mood subscale T2 depressed mood
subscale T1).
Results show that only task load (␤⫽⫺.25,
T ⫽⫺2.13, p .05) and subjective arousal
(␤⫽⫺.31, T ⫽⫺2.76, p .01) were signif-
icant predictors for mood repair (R
2
.14,
R
adj
2
.10, p .05). In contrast, neither EPC
during the experimental manipulation (␤⫽.13,
T 1.08, p .28) nor involvement with the
emotion-inducing movie (␤⫽.07, T .64, p
.52) were found to be significant predictors.
Discussion
Our study investigated the effects of interac-
tive and noninteractive media offerings on
mood repair in terms of increased positive and
Figure 2. EPC measures for baseline, mood induction, and media intervention split by
conditions. Error bars represent standard errors.
Table 4
Means and Standard Deviations for DVs Subjective and Physiological Arousal
Baseline t1 t2
Dependent variables M SD M SD M SD
Subjective arousal
Game 4.60 1.50 5.07 1.31
Gameplay video 4.95 1.15 4.82 1.16
Control 4.60 1.33 4.78 1.28
Physiological arousal
Game 1,280.44 751.12 5,141.95 3,906.50 8,350.27 4,345.47
Gameplay video 1,718.18 2,405.94 5,303.17 4,782.53 7,672.82 6,280.78
Control 1,640.29 2,008.87 5,514.68 4,971.97 3,887.62 2,461.41
Note. Time of assessment: Baseline was assessed after a short introduction to the study; t1 was assessed after mood
induction; t2 was assessed after media intervention (or control condition).
10 RIEGER, FRISCHLICH, WULF, BENTE, AND KNEER
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decreased negative affect after media consump-
tion. More specifically, we aimed at examining
the extension of MMT by Reinecke and col-
leagues (2012), who suggested main mecha-
nisms driving mood repair via media, (1) dis-
traction and (2) regulation of the negative cause,
and applied this idea to the comparison of in-
teractive and noninteractive media.
Distraction
Distraction from a negative mood can be
driven by the intervention potential of a stimu-
lus. We therefore analyzed task load of media
stimuli and involvement with the movie used to
induce a negative mood. Addressing the cause
refers to the regulation of the direct cause of an
aversive state and was addressed in terms of
subjective and objective arousal. Additionally,
we analyzed the specific contributions of task
load, persisting involvement with the emotion-
inducing situation, and physiological as well as
subjectively reported arousal to the overall
mood repair.
Overall, our findings confirmed the predic-
tions. Mood repair followed a linear pattern,
depending on the interactivity of the medium.
Mood repair was most successful in the condi-
tion in which individuals were active (playing
Pacman) and decreased in the inactive condition
(watching the gameplay video) to the control
condition (H1b). This is in line with previous
finding that interactive games led to higher
mood repair than did noninteractive conditions
of the same game (Bowman & Tamborini,
2012).
We further differentiated between changes in
positive mood as well as in negative mood. Our
results demonstrate that all three experimental
conditions led to increases in positive mood. A
negative mood in contrast was only decreased in
the interactive playing condition. By taking
both changes in happy and depressed mood into
account, our results replicate findings by Chen
and Raney (2009). They found that a positive
mood was increased by all media conditions but
a negative mood only decreased when playing
an interactive Wii game.
Concerning the intervention potential, results
confirmed that subjective task load was higher
in interactive media than in noninteractive me-
dia (H2a), again supporting the results by Bow-
man and Tamborini (2012). Furthermore, our
results demonstrate that interactive media lead
to greater distraction from the negative emo-
tion; participants reported less involvement
with the sadness-inducing movie after playing
Pacman (H2b). This is in line with research
showing that higher task demands are better in
regulating negative moods (Van Dillen &
Koole, 2007) and that more demanding media
are better for distraction (Bowman & Tambo-
rini, 2012; Chen & Raney, 2009). However, it
cannot be concluded that higher task load is
beneficial in general. Interactive media and their
characteristics were found to have many posi-
tive effects, such as greater feelings of enjoy-
ment (Grodal, 2000; Reinecke et al., 2012) or
presence (Steuer, 1992). Nevertheless, Bowman
and Tamborini (2012) found a curvilinear rela-
tionship between task demand and mood repair.
Too much task demand led to frustration and
thus had detrimental effects on mood repair.
Due to the characteristics of Pacman, in our
study task, demand was unlikely to be too high.
Indeed task load was evaluated as only low to
medium-high in all conditions (scale range:
1–7, observed M 2.89, SD 1.74).
Addressing the Cause
Concerning the arousal regulation, our study
revealed that (a) both media conditions led to
greater physiological arousal, and (b) only the
interactive media condition led to an increase in
self-reported arousal. The results for physiolog-
ical arousal connect to research by Ravaja et al.
(2006); however, we found similar levels of
EPC for both interactive and noninteractive me-
dia. Playing a game or watching a gameplay
video both elicited more physiological arousal
than taking a break (control condition). One
possible explanation is that watching somebody
actively engage in a computer game, whether it
involves winning or losing, activates a similar
arousal in the viewer than it would in the player
due to identification processes (Oatley, 1995).
Another idea points toward the sensitivity of a
measure like EDA (Ravaja, 2004): as sound and
video characteristics were the same in both con-
ditions (interactive and noninteractive), the
“eating” sound and corresponding moving pic-
tures in the noninteractive condition were
enough to evoke similar EDA patterns. To clar-
ify the nature of this finding, future research
should investigate possible reasons for arousal
11EATING GHOSTS
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characteristics of interactive and noninteractive
media.
In addition, the results for subjectively re-
ported arousal support Bowman and Tambori-
ni’s (2012) findings, by providing additional
evidence that interactive media are better in
shaping one’s subjective arousal. Moderately
negative arousal patterns for sadness (Russell,
2003) were successfully regulated via playing
Pacman, reflected in higher vitality reported in
this condition (H3a). In accordance with re-
search on the recovery potential of interactive
media (Reinecke et al., 2011), our results con-
firmed interactive media to provide more vital-
ity than noninteractive media and hence most
plausible to foster recovery from work strain
and general well-being. Olson (2010), for in-
stance, also provided evidence that adolescents’
motivation to play video games is driven by
their potential to regulate feelings and to reduce
stress. In a similar vein, Nabi, Finnerty, Dom-
schke, and Hull (2006) demonstrated that peo-
ple use media to cope with emotions associated
with distressing personal situations. Future re-
search should expand this finding by investigat-
ing which levels of physiological arousal are
perceived as exciting or enjoyable and could
thus lead to positive effects such as mood re-
pair, or even recovery (Reinecke, 2009a, 2009b;
Reinecke et al., 2011).
Directions for Future Work
These results however also trigger questions
about the exact relationship between arousal
regulation and intervention potential within the
framework of MMT. Our results contribute to
the idea that both intervention potential and
arousal regulation are important for overall
mood repair: Task load and subjective arousal
both were significant predictors to explain
mood repair (RQ1). This is in line with Bryant
and Davies (2006) or Raney et al., (2006), who
argued that computer games are effective in
repairing mood due to their arousal characteris-
tics. In contrast, Bowman and Tamborini (2012)
found that mood repair was more likely a func-
tion of increased task demand (intervention po-
tential). These divergent findings as well as our
own results suggest that future research is
needed to test the interplay between arousal
regulation and intervention potential.
As the present study was one of the first to
apply physiological arousal in MMT settings
using both interactive and noninteractive media,
future studies should also consider this method-
ology to reveal the physiological reactions
when engaging in media stimuli. For instance,
Vorderer (2000) argues that computer games
demand more cognitive and tactile engagement
than noninteractive media (or even other inter-
active media). Physical engagement can prompt
experiences of presence (Bowman & Tambo-
rini, 2012) and thus has a high probability to
disrupt ruminative thoughts. In a related vein,
Klimmt and Hartmann (2006) noted that com-
puter games are specifically designed to de-
mand physical input from the user in order for
the game to progress, increasing their interven-
tion potential when compared with less de-
manding media such as TV. This physical en-
gagement of the user becomes most obvious
when considering video games such as Wii (by
Nintendo, 2006), Xbox360 Kinect (by Mi-
crosoft, 2010) or Playstation Move (by Sony
Computer Entertainment, 2009). Because motor
movements have already been found to help in
regulating negative emotions (Morrow & No-
len-Hoeksema, 1990), modes in which both
physical movement and media consumption are
possible should have a high potential for posi-
tive outcomes, one of them being mood repair
(Chen & Raney, 2009).
Limitations
Several limitations of the present study
should be noted. First of all we only distin-
guished between high and low levels of inter-
vention potential. Future research should add
conditions with an even higher intervention po-
tential (e.g., tactile intervention, e.g., playing
Wii) and an additional moderate intervention
potential.
In addition, it has to be noted that testing
mood repair under laboratory conditions always
neglects MMT’s underlying assumption of the
“selective exposure” hypothesis (Zillmann &
Bryant, 1985). The media users learn both con-
sciously and unconsciously which media con-
tent helps them best repair their negative state.
Thus, quasi-experimental designs or field stud-
ies are needed to investigate, in less artificial
settings, whether people in a negative mood
would prefer the highest intervention potential.
12 RIEGER, FRISCHLICH, WULF, BENTE, AND KNEER
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In a related vein, our noninteractive condition
was a gameplay video. Although these videos
are usually consumed on YouTube, this condi-
tion is not an exact equivalent of watching TV.
It has to be noted that a gameplay video condi-
tion for a game like Pacman does not resemble
gameplay videos of more recent, modern
games. However, our results found for physio-
logical arousal seem to demonstrate that even a
gameplay video of a monotonous game like
Pacman is able to increase arousal and thereby
hints at a potential engagement of the viewer.
Future studies should consider comparable for-
mats within games and on TV to investigate
both media in their usual appearance. For in-
stance, Maass, Klöpper, Michel, and Lohaus
(2011) compared participants watching the
movie Doom and participants playing the game
Doom (by Id Software, 2004) to have a compa-
rable narration. Following a similar experimen-
tal manipulation, Reinecke et al. (2012) also
argued that it has the merit of creating condi-
tions in which interactive and noninteractive
media stimuli remain comparable by varying
only one feature (e.g., the level of user demand).
Furthermore, Pacman does not resemble
modern computer games and their immersive
power and appeal. In Vorderer’s (2000) terms,
the interactive elements of Pacman are consid-
ered rather low compared with other more elab-
orate computer games. Pacman does not have
many narrative elements and is thus not able to
elicit narrative transportation (Green & Brock,
2000) or immersion (Steuer, 1992). It is never-
theless an interesting experiment to relate these
concepts to mood repair via interactive media.
The results found for Pacman more strongly
relate to modern mobile or browser games that
are played “on the go,” on the way to work or
while waiting for the bus.
Concerning the mood induction it has to be
pointed out that in our design, we induced
sadness in all participants. However, it can be
assumed that people being “sadder” have a
greater need to regulate this negative state
than people who feel only moderately sad (see
research on emotion regulation; Van Dillen &
Koole, 2007). For instance, in a related re-
search field, Reinecke, Hartmann, and Eden
(in press) showed that participants who felt
ego-depleted recovered less via the use of
media. Future research should thus consider
different levels of a negative mood so as to
investigate whether the extent of a negative
mood predicts the amount of intervention po-
tential needed to repair this mood.
It also has to be pointed out that the induction
of sadness refers to a very specific emotional
state and hence results are not easily extendable
to other negative moods. For instance, Raghu-
nathan and Corfman (2004) differentiated be-
tween mood repair from sadness and mood re-
pair from anxiety. They found sadness to trigger
seeking pleasurable stimuli to repair the mood.
Anxiety in contrast was found to stimulate seek-
ing attentiveness to information, which is more
in accordance with affect-as-information theory
(Fiedler & Bless, 2001; Schwarz & Clore,
1998).
As Raghunathan and Corfman (2004) posit,
sadness prepares individuals to look for plea-
surable stimuli because they might be per-
ceived as suitable to compensate for the lost
object. Our results found for involvement
with the emotion-inducing movie point to-
ward the idea that interactive media are more
effective in directing attention away from the
loss.
However, the same authors also note that
anxiety is a state driven by uncertainty and a
lack of control. Thus, anxiety primes individu-
als to become more attentive to prevent a neg-
ative outcome (Raghunathan & Corfman,
2004). The regulation of an anxious state might
therefore lead to different mood repair charac-
teristics. Although our results stemming from
an induction of sadness are in line with former
research in the tradition of MMT, they cannot
be generalized to other emotions. Future studies
should also take the idea of other states and
theoretical explanations such as the affect-as-
information theories (Schwarz & Clore, 1998)
into account.
In a related note, sadness is considered to be
a negative valenced but deactivated state (Rus-
sell, 2003). To more strongly disentangle va-
lence and arousal aspects of moods and their
specific regulation characteristics, future studies
should think about other inductions of valence
and arousal states. Ferguson and Rueda (2010)
for instance used the paced auditory serial ad-
dition task (PASAT; Gronwall, 1977) to induce
frustration. By using a more activated negative
state, it could be tested whether again task load
and subjective arousal are the main predictors of
mood repair or whether in those cases, other
13EATING GHOSTS
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factors such as the physiological arousal play a
bigger role.
4
Moreover, thinking about two di-
mensions of mood (arousal and valence) sheds
light on the necessity to include third variables
in future studies to analyze mood repair via
computer games. Assuming that computer
games can increase energetic as well as physi-
ological arousal, it would additionally be im-
portant to ensure that computer games are fur-
ther able to change the hedonic valence in the
mood of the player. Consequently, factors that
are able to shape the way hedonic valence is
affected should be taken into account, such as,
for instance, success while playing (Klimmt,
2006; Klimmt & Hartmann, 2006; Klimmt,
Schmid, & Orthmann, 2009) or the satisfaction
of personal needs (Reinecke et al., 2012; Tam-
borini, Bowman, Eden, Grizzard, & Organ,
2010; Tamborini et al., 2011).
Conclusion
Although studies conducted in the 80s con-
cluded that due to Pacman, as a prototypical
example of computer games at that time, chil-
dren forget about reality and real-life problems
(Klein, 1984), our study sheds light on the pos-
itive effects of games such as Pacman. The
results demonstrated that mood management is
most effective when engaging in interactive me-
dia. We found that playing a computer game led
(1) to the highest mood repair, (2) to the least
involvement with the negative emotion-induc-
ing movie clip, and (3) to the highest physio-
logical arousal. It further led to feelings of in-
creased energy after playing. Computer games
can thus be considered effective in attenuating
negative states by directing attention away from
the unwanted mood, and by eliciting higher
levels of arousal.
Because 58% of Americans play video games
(ESA, 2012), research should continue to inves-
tigate the potential effects on the audiences. The
current study lines up with other studies trying
to show the impact of interactivity to have ben-
eficial effects such as mood repair or even an
increased vitality. However, this line of research
is also of importance to, for instance, clinical
settings to find the best circumstances for de-
pressed or burned-out individuals to recover. In
a recent review, Primack et al. (2012) also em-
phasized the role of computer games in thera-
peutic contexts. They concluded that interactive
media are useful in both psychological and
physical therapies and can contribute to im-
proved health outcomes.
4
To control for the arousal dimension of mood, in the
current study, we also assessed two items associated with
experiences of tense arousal (Thayer, 1989) (e.g., “ex-
hausted”). Results show that at T1, no difference between
conditions emerged, F 1(M 3.35, SD 1.48), neither
at T2: F 1(M 2.80, SD 1.31). However, the main
effect for time was significant, F(1, 72) 11.67, p .001,
p
2
.14. All participants were less stressed after the ex-
perimental manipulation. Even at T1, “tense arousal” was
only moderate (below scale mean), which reflects the in-
duction of a deactivated negative emotion (sadness). Add-
ing this variable to the regression analysis did not change
the results.
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17EATING GHOSTS
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... Des Weiteren bestehen mannigfaltige Möglichkeiten mit dem Gerät zu interagieren, was es besonders geeignet zur Emotionsregulierung gemäß der MMT (Zillmann, 1988) macht (Rieger, Frischlich, Wulf, Bente & Kneer, 2015). Der soziale Austausch mit anderen oder der Konsum von Medieninhalten kann den Gemütszustand von Benutzer/-innen verbessern (Köster, 2016;Hoffner & Lee, 2015;Walsh, White & Young, 2008;Grassi, Gaggiolo & Riva, 2009;Wei & Lo, 2006). ...
... Auch im Hinblick auf die MMT (Zillmann, 1988) bieten Mobiltelefone mit SPA eine bessere Emotionsregulierung aufgrund höherer Innovation (Dupré, Tcherkassof & Dubios, 2015), Interaktion (Rieger, Frischlich, Wulf, Bente & Kneer, 2015) und Belustigung (Rzepka, 2019;Moussawi, 2018). Also ist es denkbar, dass bei gleicher Nutzungshäufigkeit Nutzer/-innen von Mobiltelefonen mit SPA mehr positive und weniger negative Emotionen aufweisen und diese auf das Mobiltelefon übertragen. ...
... Ähnliches gilt hinsichtlich der MMT (Zillmann, 1988). Nutzer/-innen, die SPA sehr häufig nutzen, profitieren von ihrer besonderen Eignung zur Emotionsregulierung (Rzepka, 2019;Moussawi, 2018;Rieger, Frischlich, Wulf, Bente & Kneer, 2015;Dupré, Tcherkassof & Dubios, 2015) in stärkerem Ausmaß. Dies könnte sich auf die emotionale Bewertung der Sprachsteuerung sowie des gesamten Mobiltelefons auswirken. ...
Thesis
Full-text available
Emotionale Bewertungen stellen ein zentrales Element der Nutzungserfahrung dar. Aus diesem Grund untersucht die vorliegende Bachelorarbeit, ob eine hohe Nutzungshäufigkeit von Mobiltelefon oder Sprachsteuerung einen Einfluss auf die emotionalen Aspekte des Benutzererlebens hat. Zu diesem Zweck wurde eine Online-Befragung (N= 836) durchgeführt und mittels Korrelationen, hierarchischen Regressionsanalysen, multivariaten und univariaten Varianzanalysen sowie kanonischen Diskriminanzfunktionen ausgewertet. Die Ergebnisse offenbarten, dass sich Nutzungshäufigkeiten unterschiedlich auf positive und negative Emotionen auswirken. Personen, die ihr Mobiltelefon häufig verwendeten, erfuhren mehr positive Emotionen gegenüber dem Gerät. Negative Emotionen gegenüber dem Mobiltelefon konnten hingegen nicht durch eine häufige Nutzung reduziert werden. Dies konnte unabhängig von dem Ausmaß, in welchem das Mobiltelefon zur zwischenmenschlichen Kommunikation verwendet wurde, beobachtet werden und wurde nicht durch die Nutzungshäufigkeit der Sprachsteuerung moderiert. Dennoch zeigte sich, dass die Nutzungshäufigkeit der Sprachsteuerung sowohl die positiven als auch eingeschränkt die negativen Emotionen gegenüber dem Mobiltelefon beeinflusst, was vermutlich auf eine größere Gesamtnutzung des Mobiltelefons zurückzuführen ist. Insgesamt bestätigt die Studie die Übertragung von Herzbergs Zwei-Faktoren-Theorie auf das Nutzungserleben nur teilweise. Positive Emotionen scheinen einen stärkeren Bezug zum Benutzungserlebnis aufzuweisen, während negative Emotionen wahrscheinlich durch schlechte Gebrauchstauglichkeit hervorgerufen werden. Als Folge dessen wirken sich Nutzungshäufigkeiten vorwiegend auf positive Emotionen aus, doch die gemeinsame Betrachtung von positiven und negativen Emotionen kann einen Unterschied in Bezug auf die Ausprägung negativer Emotionen gegenüber dem Mobiltelefon machen, wie sich bei der Nutzungshäufigkeit der Sprachsteuerung herausstellte.
... All these factors together point toward the idea that interactive narratives can pose more challenges (in terms of structural or content features) to individuals. Relatedly, a simple video game led to higher subjectively reported task load and arousal levels than a noninteractive gameplay video of the same content (Rieger et al., 2015). In their experiment on challenging versus less challenging movies, Bartsch and Hartmann (2017) demonstrated that lower affective and cognitive challenges resulted in more fun (enjoyment). ...
... In light of studies that found interactive narratives to increase donation intentions (Steinemann et al., 2015(Steinemann et al., , 2017, future studies could consider this finding a potential starting point. They could investigate whether interactive choices can then promote other media effects, such as enhancing empathy for certain characters , facilitating recovery (Rieger et al., , 2015, or behaving more morally (Oliver et al., 2012), to name a few. ...
... Reinecke, 2009aReinecke, , 2009b, mood repair (e.g. Reinecke et al., 2012;Rieger et al., 2015), or increases in eudaimonic and hedonic well-being (e.g. Reer & Quandt, 2020). ...
... Reinecke, 2009aReinecke, , 2009b, mood repair (e.g. Reinecke et al., 2012;Rieger et al., 2015), or well-being (e.g. Reer & Quandt, 2020). ...
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Videogames evoke emotions that have implications for in-game performance and enjoyment. However, no measure currently exists to assess discrete emotions in videogame contexts with evidence of validity. The current study tested the factorial and construct validity of responses obtained with a modified version of the Discrete Emotions Questionnaire (DEQ, Harmon-Jones et al., 2016) and tested measurement invariance across player-versus-player-oriented and player-versus-environment-oriented videogame types (DEQ-VG). To ensure the factor structure held across both positive and negative emotional experiences, a total of 2994 participants were asked to recall one positive and one negative emotional experience stemming from a videogame they had recently played and completed the DEQ-VG in reference to each recalled experience. Separate confirmatory factor analyses were conducted for the two recalled emotional events to assess factorial validity. Construct validity was assessed by comparing DEQ-VG scores between positive and negative emotional events. The results supported a 9-factor solution (anger, happiness, fear, excitement, sadness, relaxation, desire, anxiety, and awe), and the responses were invariant across game types. Construct validity was demonstrated by the DEQ-VG scores significantly differing in the expected directions between positive and negative events. These findings support the usefulness of the DEQ-VG for assessing discrete emotions stemming from videogame experiences.
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Prior research on mood management through media consumption has encountered mixed results. This study seeks to address these discrepancies by incorporating time of measurement into the examination of regulatory outcomes and by identifying trait-like cognitive moderators that presumably are involved in the regulation of negative moods. Results showed that sad mood initially fostered longer listening to mood-compatible music but such preference decreased over time, suggesting the merits of considering temporal changes in the mood-repair process. In addition, ruminative trait was found to be a significant factor in how people cope with their sad moods, whereas mood salience was not.
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This quasi-experimental study examined the effects of exposure to a computer game on arousal and subsequent task performance. After inducing a state of low arousal, participants were assigned to experimental or control conditions via self-selection. Members of the experimental group played a computer game for five minutes; subjects in the control group spent the same amount of time awaiting further instructions. Participants who were exposed to the computer game showed significantly higher levels of arousal and performed significantly better on a subsequent cognitive task. The pattern of results was not influenced by the participants' prior experience with the game. The findings indicate that mood-management processes associated with personal media use at the workplace go beyond the alteration of arousal and affect subsequent cognitive performance. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Electrodermal activity is one of the most frequently used psychophysiological evaluations in psychology research. Based on the 1992 edition of this work Electrodermal Activity covers advances in the field since the first publication in 1992. The current volume includes updated information on brain imaging techniques such as PET and fMRI, which provide further insight into the brain mechanisms underlying EDA. In addition, this volume is able to describe more reliably hypotheses that have been successfully tested since the first publication. © Springer Science+Business Media, LLC 2012. All rights reserved.
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We conducted three experiments to rectify methodological limitations of prior studies on selective exposure to music and, thereby, clarify the nature of the impact of sad mood on music preference. In all studies, we experimentally manipulated mood (sad vs. neutral in Experiments 1 and 2; sad vs. neutral vs. happy in Experiment 3) and then assessed participants' preferences for expressively happy versus sad musical selections. To further help illuminate the reasons for their music preferences, we also asked participants to indicate how they believed listening to each song would affect their current emotional state as well as how appropriate they felt it would be to select a given song. Results suggested that individuals in sad moods were not reliably inclined to listen to sad songs, but rather, were strongly averse to listening to happy songs, apparently out of concern that choosing such songs would feel inappropriate. We discuss implications of these findings for theories of selective media exposure and emotion regulation.