within-subjects experiment was conducted to investigate the emotional effects of
color in film and television clips. The
study involved obtaining physiological measures (skin conductance, heart rate,
and facial muscle movement) during the presentation of 54 short (6 s) film clips
to the study’s 34 participants (16 women, 18 men).
Self-report measures of the participants’ emotional reactions were also
obtained. Results indicate that the
influence of color appears in the self-reports of emotional experience, but in
none of the physiological measures. These
results suggest that people feel, or consciously believe they feel, that color
pictures are more pleasing and exciting than monochrome versions of the same
images, yet there is no difference in their visceral reactions.
The implications of this dissociation of emotional responses are
since Marshal McLuhan (1964) put forth his provocative aphorism, the medium is
the message, media scholars have been interested in the form a message takes as
well as its content. Though McLuhan
may have overstated the significance of form or medium characteristics (and
understated that of content), he aptly recognized that the influence of media
stems, at least in part, from how messages are presented.
The distinction between form and content and its use in analyzing
communication existed long before McLuhan (Campbell, 1841), but he deserves
credit for recognizing its heuristic value in the examination of (the then new)
electronic media. As media evolve, the concept continues to prove valuable as
an entrée into research on the nature of media and their influence.
great deal of scholarship has flowed from McLuhan’s seminal idea, research in
recent years has gone beyond simply describing the various formal
characteristics and labeling different media as either hot or cool, to
investigating the impact of message forms.
Using a social scientific approach, researchers have begun to articulate
the role that non-content, or formal, attributes of film and television messages
play in influencing people’s psychological responses.
For example, studies have shown that picture motion can affect people’s
cognitive and emotional responses (Detenber, Simons, & Bennett, 1998;
Reeves, Thorson, Rothschild, McDonald, Hirsch, & Goldstein, 1985; Simons,
Detenber, Roedema, & Reiss, 1999). Likewise,
research indicates that image size influences message processing and the viewing
experience (Detenber & Reeves, 1996; Lombard, 1995; Reeves, Lang, Kim, &
Tatar, 1999)1. In
addition to assessing the psychological significance of formal characteristics,
these studies have also documented the impact of particular content attributes
and some of the ways that form and content interact (e.g., Lombard, Reich, Grabe,
Campanella, & Ditton, in press). In
general, form seems to play a lesser role than content in determining
psychological responses, yet the influence of these formal attributes is
consistent. It also appears that particular formal characteristics have
their greatest impact with certain types of messages. In other words, it is specific interactions of form and
content that influence responses.
media continue to change, their impact on individuals needs to be assessed.
Investigating the psychological significance of formal properties and
their interaction with message content is essential to a complete understanding
of how media effects occur. The present study is an attempt at such an investigation.
The perception of
color is essential to our visual experience. It provides information that helps us understand the physical
world and influences how we feel. Accordingly,
a great deal has been written about the nature of color, the perception of it
and its aesthetic considerations (Albers, 1987; Birren, 1978; Gombrich, 1960).
In terms of mass media research, color has been the subject of
investigations into learning and memory, persuasion, perception and emotional
impact. It has also been studied in the context of both moving and
still pictures. Unfortunately,
though the literature on color is extensive, it does not present a uniform set
of findings or a consistent perspective on the influence of color.
Indeed, it is the inconclusive nature of research on color that motivates
Early studies on the
cognitive effects of color in television presentations indicate that people paid
more attention to the details of a television news program when they viewed in
black and white (Scanlon, 1967, 1970). On the other hand, Shaps and Guest (1968) found that more
details were recalled from television commercials when they were in color.
Related research on still pictures suggests that in certain contexts
color does produce memory advantages (Borges, Stepnowsky, and Holt, 1977; Chute,
1980). However, a study by Kiphart,
Sjogren and Cross (1984) suggests that picture recognition is not influenced by
color. In their study of magazine photographs, Gilbert and Schleuder
(1990) also found no advantage for color in terms of recognition accuracy.
Their data did indicate however, that image processing was speeded up by
color. In terms of guiding
attention through a newspaper, color has some influence, but mostly it interacts
with content and design (Garcia & Stark, 1991).
Results from the same study also showed that color does not influence
reading. In summary, it appears
that color in mediated presentations does affect cognitive processing, at least
some of the time.
In terms of
emotional reactions, the influence of color versus black and white has also been
studied in relation to both still and moving images.
A study by Gardner and Cohen (1966) indicates that monochromatic
newspaper ads were less attractive to people than the same ads that had some
color. The effect of color seems to
depend in part on the content of the picture, though.
Out of 52 images, Winn and Everett (1979) found significant differences
in the evaluation of color versus monochrome for only five pictures.
Similarly, a recent study that used physiological measures of emotion in
addition to self-reports found some differences between color and black and
white for particular still images, but failed to find any overall significant
difference (Bradley, Axelrad, Codispoti, Cuthbert, & Lang, 1998).
Participants in the study by Garcia and Stark (1991) however, clearly
stated a preference for color in their newspapers.
For moving images,
results from social scientific studies on the emotional significance of color
are also mixed. The studies by
Scanlon (1967, 1970) suggested that color positively influenced liking of the
television presentation. Similarly,
Donohue (1973) found that color increased perceptions of aesthetic quality in
political TV advertisements, though women tended to be more influenced then men.
A study by Perse, Pavitt and Burggraf (1991), on the other hand, failed
to find any differences due to color in emotional reactions to scenes from
feature films. Furthermore, the differences in responses to colorized films
reported by Sherman and Dominick (1988) were only marginally significant.
Even though people say they prefer color television to black and white,
participants in a study by Thurman, Ball, Hammack and Walker (1983) actually
spent more time watching black and white programming than color.
The only conclusion that can be drawn from these studies is that the
influence of color in media presentations is not straightforward.
Film theory has also
addressed the role of color, and offers another perspective on its influence.
In general, film theorists contend that color can evoke potent emotional
responses in viewers and is therefore one of the director’s most important
tools. For example, Giannetti (1987) says that, “color tends to be
a subconscious element in film. It’s
strongly emotional in its appeal, expressive and atmospheric rather than
conspicuous or intellectual” (p. 21). According
to Zettl (1990), color serves three functions in film and television:
informational, compositional and expressive.
The information color provides can be literal or symbolic.
In either case, it tells us something more about an object or event. Directors also use color to control and shift emphasis within
the frame. Arranging colors in
harmonious and contrasting ways is part of the art of composition.
Lastly, color is used to make viewers feel a specific way (Zettl, 1990).
Though Zettl and others offer many suggestions and guidelines on the use
of color for various ends, they admit there is no universal validity for these
‘rules of thumb.’ As Bordwell
and Thompson (1989) acknowledge, good or appropriate use of color always depends
on the context.
In contrast to
color, little has been written about the influence of black and white, or
monochrome, film and television presentations on emotional responses.
One notable exception is desaturation theory (Zettl, 1990) which states
that for certain types of scenes desaturated colors, or black and white, can
produce stronger emotional reactions. For
events that are “extremely internal,
such as an intimate love scene, a mother nursing her baby, [or] a wounded
soldier waiting helplessly on a battlefield” color may actually dampen
viewers’ emotions (p. 79, emphasis in original).
Zettl (1990) suggests that color makes these kinds of internal events
external and does not allow people to get involved emotionally.
According to desaturation theory, color leads people to look at rather
than into a scene. Black and white,
on the other hand, “invites the audience… to fill in the missing
elements,” and typically leads to a more profound emotional experience of the
event portrayed (Zettl, 1990, p.80). While
desaturation theory seems quite plausible, it has not been empirically tested.
One of the goals of this study is to see if the theory applies to brief
film and television clips.
are two primary theoretical frameworks that exist in the study of emotion.
One conceptualizes emotions discretely or categorically (Izard, 1977;
Plutchik, 1980; Ortony, Clore & Collins, 1988) while the other regards
emotion as a dimensional construct (Lang, 1995; Osgood, Suci, & Tannenbaum,
1957; Russell, & Mehrabian, 1977). In
general, dimensional approaches posit two or three dimensions that underlie all
emotions. The two most commonly used are autonomic arousal and hedonic
valence. A third, less frequently
used dimension, is dominance or control. Researchers
typically describe the dimension of autonomic arousal as a continuous range of
affective response that varies from high to low.
That is, at one end of the dimension people feel energized, excited, and
aroused and at the other they feel calm, unaroused, or peaceful.
Valence is usually characterized as ranging from pleasant or positive
valence at one pole, to unpleasant or negative valence at the other. These two dimensions, valence and arousal, account for most
of the independent variance in emotional responses (Greenwald, Cook, & Lang,
1989), and can be used to effectively discriminate between emotional responses.
of the benefits of the dimensional view of emotion is that particular
physiological measures have specific relationships with the two primary
dimensions. Skin conductance
response (SCR) indexes autonomic arousal, while facial muscle movement (i.e.,
electromyographic, or EMG, activity) and heart rate reveal differences in
valence. In the context of watching
moving images, zygomatic activity and heart rate acceleration occurs in response
to pleasant stimuli, while unpleasant stimuli are accompanied by corrugator
activity and heart-rate slowing (Detenber, Simons, & Bennett, 1998; Lang,
1994; Simons, Detenber & Reiss, in press).
Likewise, as people experience arousal their sweat glands become active
and skin conductance responses (SCR) become larger and more frequent (Dawson,
Schell, & Filion, 1990; Hopkins & Fletcher, 1994).
can be measured in different ways. In
the experiment presented here, we focused on subjective and physiological
manifestations. The subjective
experience of emotion was assessed using the Self-Assessment Manikin (SAM; Lang,
1980). This measure, a form of
semantic differential scale, requires subjects to introspect and consciously
report on their feelings of arousal and hedonic valence.
To assess emotion’s physiological sequelae, we measured facial EMG,
skin conductance and heart rate. Each
of these measures yields information about a different aspect of emotional
experience, but in general, affective judgments and physiological measures are
highly correlated (Greenwald et al., 1989; Lang, Greenwald, Bradley, & Hamm,
1993). Though the self-report and
physiological measures are expected to converge, the physiological measures
provide an added benefit – they are less sensitive to any demand
characteristics that might be operative during the experiment and, therefore,
are less susceptible to impression management.
present study was designed to explore the relationship between color and
people’s emotional responses to film and television clips.
Based on desaturation theory, we expect that the monochrome versions of
the images would elicit stronger emotional reactions than the color versions
would. This emotional intensity
should appear in greater self-reports of arousal and greater SCRs.
It is also likely that the stronger emotional reactions will manifest
themselves in more extreme responses on the valence measures (self-report,
facial EMG and heart rate). That
is, the positive images will seem more positive and the negative images will
seem more negative when they are seen in black and white.
Lastly, based on prior research, we anticipate that the formal attribute
manipulated in the study would interact with the content of the moving images.
This experiment had three within-subject factors: color, clip valence and clip arousal. Two models were run simultaneously, each with a formal and content variable. That is, the study used both a 2 (color, black and white) X 3 (positive, neutral and negative valence) and a 2 (color, monochrome) X 3 (low, medium and high arousal) within-subject design. The categorical emotion variables were created from the self-report ratings of each dimension (see below). The basic design called for each participant to view 27 film clips in both color and in black & white while physiological measures were taken. Immediately after viewing each of the 54 clips, subjects rated their emotional reactions.
Thirty-five undergraduate students at the University of Delaware received partial credit toward the research participation component of their introductory psychology course or extra credit in their mass communication course. Potential subjects were disqualified if they reported any form of color blindness. Data from one of the final 35 participants was eliminated from the study due to technical problems during data collection. The final sample of 34 consisted of 18 males and 16 females with a mean age of 20.5 years (sd=2.68).
stimuli consisted of 27 short scenes, or clips, extracted from films and
television programs. The clips
chosen for use in the present study were a portion of a much larger set
previously standardized by Detenber (1995).
Of the present subset of 27 moving images, 24 were identical to those
used by Detenber et al. (1998). Each
clip contained a single shot (no edits) of some scene or object.
The selection of images was based upon ratings obtained from the
standardization sample on categories appearing in the International Affective
Picture System (IAPS; Lang, Ohman, & Vaitl, 1988).
To facilitate the formation of valence and arousal categories for
statistical analysis, the final 27 clips were associated with a wide range of
ratings on the emotion dimensions of primary interest in the present study
(i.e., valence and arousal).
stimuli were presented for 6 s and were either monochrome (i.e., black and
white; b/w) or color versions of the same clip.
The monochrome version of each clip was created by desaturating the
original color version. That is,
using a digital video editing system, the chroma was reduced to zero. All clips, along with an additional graphic instructing
subjects to perform the ratings task, were stored on a video laser disc that was
connected to a Macintosh computer. Stimuli
were presented to subjects in one of four orders embedded in a Hypercard program
used by the Macintosh to control the sequence and the timing of stimulus
presentation. For two of the four
presentation orders, we created
both random clip sequences and a random color-monochrome precedence order (i.e.,
whether the color or monochrome version was shown first).
The other two sequences had the same clip order, but reversed the
color-monochrome precedence to counterbalance the variable.
Although the orders were based on random sequences, they were constrained
to insure that the color and monochrome images were never presented on
indicated their emotional reactions to each stimulus by providing valence,
arousal and dominance ratings in response to each of the 54 moving images on a
nine-point paper and pencil version of Lang’s Self-Assessment Manikin (SAM;
Lang, 1980). Using the SAM, valence
is rated by marking on or between five graphics depicting the manikin with
facial expressions ranging from a broad smile to a severe frown.
Arousal is rated similarly using five graphics depicting the manikin at
different levels of visceral agitation, and dominance is rated using manikins
which differ in size or prominence in the graphics panel they occupy.
Having subjects mark on or between the graphics allows for more finely
tuned ratings and yields a nine-point scale for each dimension.
Physiological recording. Heart-rate was obtained by attaching a Grass Photoelectric
Transducer Model PPS to the subject’s right ear lobe. The photocell output was fed into a Grass Model 7P1 Low Level
DC Preamplifier and Model 7D Driver Amplifier (Bandpass = 1.6 - 3.0 Hz) and then
into a series of Coulbourn logic modules for the determination of interbeat
conductance responses were recorded using a Coulbourn Model S21-22 constant
voltage (.5V) skin conductance coupler. Prior
to recording, the palm of the nonpreferred hand was cleansed with distilled
water. Beckman Standard (0.5 cm2)
Ag/AgCl electrodes were then placed on the thenar and hypothenar eminence of the
palm with Johnson & Johnson KY Jelly used as electrolyte.
(EMG) recordings from the face were obtained by placing Med-Associates miniature
Ag/AgCl electrodes over the subject’s left zygomatic and corrugator muscles.
The raw EMG (Bandpass = 3 - 500 Hz) was full-wave rectified and
integrated (TC=50 ms) using a Grass Model 7P3 Wideband Amplifier/Integrator.
provided with a brief description of the stimuli, the ratings task and the
recording techniques and then signed an informed consent form.
EMG and skin conductance electrodes were then affixed on their respective
recording sites, and the subject was led to an adjacent room equipped with a
comfortable arm chair positioned approximately 1.4 m in front of the viewing
device (SONY 20" Color Monitor). The
photocell was attached to the ear and the quality of the physiological
recordings was inspected. Subjects
then received the complete set of instructions and two 'neutral' practice trials
were delivered. The experiment
began if the instructions were understood, if the ratings task was completed
properly during the practice trials and if the physiological recordings were
free of obvious noise and artifact.
proper consisted of 54 trials under the control of two laboratory computers -- a
486 PC that initiated each trial and collected the physiological data and the
Macintosh that controlled the laser disc player. At the completion of each 6 s clip, the viewing screen was
dark for 1s, and then the instruction to rate their response was presented for 4
s. Subjects were instructed to rate
their emotional response to the image on the three dimensions (valence, arousal,
dominance) quickly, and to return their eyes to the viewing screen prior to the
appearance of the next image. The
interstimulus interval varied randomly from 17 to 27 s.
Physiological data collection began 2 s prior to the delivery of each
image and continued for 10 s. At
the half-way point in the experiment, the experimenter reentered the viewing
room to provide a short break for the subject and to ensure that the subject was
on the appropriate page in the ratings booklet.
At the conclusion of the experiment, subjects were verbally debriefed and
given a brief written explanation of the experiment along with some relevant
Our data reduction and analysis procedures were identical to those described in Simons et al., 1999. In short, skin conductance and facial EMG channels were sampled at 50 cps. Discrete SCRs that began with an onset latency of 0.5 - 4 s following stimulus onset were identified by visual inspection and quantified as the difference, in uSiemens, between the identified onset point and the peak of the response.
and zygomatic data were expressed as the difference between the mean value
during the 6 s viewing period and the prestimulus mean. A derived 'pattern' score was also computed for each trial by
first standardizing the data for each muscle within subject and then subtracting
the corrugator change from the zygomatic change (Greenwald et al., 1989; Simons
et al, in press). Thus, positive
pattern scores would reflect more smiling and less knitting of the brow while
negative pattern scores would reflect the opposite.
intervals obtained from the photocell were converted to heart-rate in beats per
minute per real-time epoch (500 ms). When
epochs contained portions of two beats, each rate was weighted according to the
fraction of the epoch that it occupied (Graham, 1978).
Heart-rate waveforms were the generated by deviating half-second averages
during the 7 s post-onset epoch from the half-second average immediately
preceding stimulus onset. Fourteen
(7 s) half-second averages, along with the onset point, constituted the
heart-rate data that were then submitted to statistical analysis.
Mean valence and arousal ratings for each of the images were computed collapsing across the monochrome/color dimension. Valence means were then ranked from most positive to least positive, and then the 27-image set was divided into 9 positive, 9 neutral and 9 negative images. Likewise, arousal means were ranked from the lowest to highest and the images were divided into 9 low-, medium- and high-arousal categories, again collapsed across the monochrome/color dimension2. Because the correlation between dominance and valence has exceeded r=0.85 in our previous studies, a separate set of analyses based on dominance categories was deemed redundant with the valence analysis and was not pursued.
of the dependent measures was analyzed twice using a repeated-measures Analysis
of Variance (ANOVA) with Image Category (Valence or Arousal) and Color as the
two within-subject variables. Single-df
orthogonal trends were used to represent the Category variable.
In this analysis, the linear trend (1, 0, -1) is equivalent to the
specific contrast of positive v. negative valence or low v. high arousal,
whereas the quadratic trend (1, -2, 1) is equivalent to the contrast of the
middle category with the two extremes. The
heart-rate analysis also examined single-df orthogonal trends across the
half-second data points to assess the effects of both image Category and Color
and arousal ratings as a function of both valence and arousal categories are
presented in Figure 1.
The two left-hand panels illustrate the impact of the color manipulation
on SAM ratings of valence (top) and arousal (bottom).
Clips in color were rated more positively than monochrome clips overall, F(1,33)=8.69,
p<.01, and this effect was largest for stimuli in the neutral
category, Color X Valence, Fquad(1,33)=17.98, p<.001.
Color clips were also experienced as more arousing than achromatic clips,
F(1,33)=8.32, p<.01. These
differences were small in magnitude, but as the figure indicates, they were
consistent across subjects.
two right-hand panels of Figure 1 illustrate the relationship between valence
and arousal ratings. Both positive
and negative clips were rated as more arousing than the neutral images, Fquad(1,33)=33.43,
p<.001, and negative clips were rated as more arousing than positive
clips, Flin(1,33)=8.62, p<.01.
Likewise, high arousal images were rated as somewhat more positive than
low or medium arousal images. Again,
the relationship was both linear and quadratic, Fquad(1,33)=19.87,
p<.001; Fquad(1,33)=4.84, p<.05.
2 illustrates the relationship between the facial EMG pattern score and both
valence and arousal categories. As
expected, positive clips prompted facial activity that was consistent with
smiling (i.e., a positive pattern score) and negative clips were characterized
by more brow (corrugator) and less smile (zygomatic) activity.
Statistically, the pattern score varied linearly with clip valence, Flin(1,34)=28.25,
p<.001, and did not vary significantly with arousal.
This linear relationship between valence and facial EMG pattern was
evident in both of the constituent facial muscles, but in this experiment, the
effect was statistically significant in the zygomatic, Flin(1,34)=20.86,
p<.001, but not quite so for the corrugator, Flin(1,34)=2.75,
ns. Facial expression did
not vary with color, F<1, and color did not interact with either image
valence or arousal, F’s<1.
slowed, beginning shortly after stimulus presentation and remained below
baseline for the duration of the recording interval. The half-second by half-second data are presented in
3 as a function of image valence (left-hand panel), image arousal (center
panel) and color (right-hand panel). The
trend analysis of variance confirmed the reliability of the deceleration with
significant linear (Flin(1,33)=45.09, p<.001) and
quadratic (Fquad(1,33)=7.21, p<.01) trends across
the presentation period accounting for 85% and 8% of the variance across the
half-second data points respectively.
the facial EMG, the heart-rate change was significantly related to the valence
but not the arousal properties of the stimuli.
As in many previous studies (e.g., Greenwald et a., 1989; Simons et al.,
1999) there was a mid-interval acceleratory component that was associated with
the positively valenced stimuli. The
relationship between stimulus valence and heart rate was confirmed by the
significant linear valence X quadratic half-second interaction, Flin(1,33)=5.30,
The impact of the color manipulation on the heart-rate response was weak. The right-hand panel of Figure 3 suggests that color may prompt a more deceleratory response, but this effect did not approach statistical significance, Flin(1,33)=2.31, p>.10. And, there was actually poorer discrimination in heart rate among the three valence categories when the clips were presented in color than when the same clips were presented monochromatically. This effect is illustrated in Figure 4 and supported statistically by a significant three-way interaction among color, valence and quadratic time Fquad(1,33)=5.45, p<.05.
expected, skin conductance response magnitude reflected the arousal properties
of the clips, Flin(1,34)=17.73, p<.001.
As the right-hand panel of Figure 5
illustrates, high-arousal images evoked the largest skin conductance responses.
left-hand panel of Figure 5 depicts the relationship between SCR magnitude and
image valence. There were no
aspects of this relationship that reached statistical significance.
Color did not exert a main effect on the skin conductance response (F<1)
nor did it interact with either valence or arousal.
findings of this study do not support predictions based on desaturation theory.
Furthermore, the results provide a somewhat equivocal view of the
emotional impact of color in moving images.
The data indicate that color, a formal characteristic or presentation
variable, has a small but consistent effect on the subjective experience of
emotion, but no appreciable effect on the physiological component of emotional
experience. The differential influence of color on the two sets of
measures creates an unusual but not unique pattern of emotional response.
In this study, color
affected both the valence and arousal dimensions of emotional experience, but
only in affective judgments. Specifically,
when the film clips were seen in color they elicited self-reports of
significantly greater arousal and more positive ratings than when they were seen
in black and white. Color also
interacted with the content of the clips for the valence dimension, but not for
arousal. Though the absolute
difference in the ratings for color and monochrome versions on the two
dimensions was small, so was the error variance. Hence, they achieved significance.
In contrast, color
had essentially no impact on the visceral aspect of emotional experience.
That is, the participants’ bodies were not acting as though different
emotions were being experienced. While
the data provide some indication that color may influence heart rate, it is
difficult say what this might mean. The
separate heart rate waveforms for color and monochrome clips (Figure 4) reveals
the three-way interaction between color, valence category and quadratic time.
The data indicate that heart-rate deceleration patterns did not reflect
the valence differences in the clips when they were seen in color.
For the monochrome versions of the clips, however, heart rate nicely
delineates the valence categories. This
pattern does not match that found in previous research, nor does it fit with
existing theory or predictions. We
are somewhat at a loss as to what this difference means or why it occurred.
One might be inclined to suggest that color somehow interfered with or
obscured the hedonic nature of the images.
However, this explanation does not comport with the numerous studies that
found nicely discriminated heart-rate waveforms for positive, neutral and
negative color stimuli.
While color did not
have a statistically significant effect on any of the physiological measures,
the content of the film clips did. For
the valence-sensitive measure of facial EMG, positive film clips had higher
scores (i.e., more smiling and less knitting of the brow) and negative clips had
lower scores (more knitting of the brow and less smiling).
The neutral clips had scores in between (Figure 2).
Each valence group of film clips was significantly different from the
others. Similarly, the arousal-sensitive measure of SCR varied in
response to the arousal quality of the film clips (Figure 5).
Specifically, the clips that were rated as medium arousal elicited
significantly greater SCRs than did the low-arousal clips.
The high-arousal clips elicited significantly greater SCRs than both the
medium- and low-arousal clips. For
heart rate, the waveform for the complete set of stimuli clearly reflects the
valence of the clips (Figure 3). The
pattern of negative clips leading to greater heart rate deceleration followed by
neutral then positive clips is consistent with previous research.
In short, all of these findings are consistent with previous research and
substantiate the validity of the physiological measures.
The discrepancy in
the data of the different measures of emotion does not necessarily mean that the
relationship between color and emotion was spurious or that the study was
flawed. Rather, it could mean one
of several things. First, it is
possible that the self-report measures were more sensitive to changes in emotion
than the physiological measures, and were able to detect apparently small
effects of color. Even though the
error variance was considerably smaller for the SAM measures, it is difficult to
make such a comparison, given how different conscious reflection and physiology
are. Alternatively, self-reports
tend to be more sensitive to demand characteristics than physiological measures.
There may have been something in the experimental procedure (e.g., seeing
both versions of the clips on a single, color monitor) that suggested color
should be experienced differently than black and white.
Although we feel this is unlikely, it remains a possibility.
The third explanation for the dissociation found in the results of the study seems to us the most probable. Emotion manifests itself in three separate systems: the physiological, the psychological (i.e., subjective experience), and the behavioral (i.e., physical actions such as approach and avoidance), and each of these are associated with particular measures (Lang, 1995; Simons et al., in press). Self-reports and physiological measures tap different systems and index different facets of emotion. Though they are often correlated, the different types of measures do not necessarily need to be. In fact, it is not uncommon in emotion research for this kind of dissociation to occur in particular circumstances. For example, subjects often deny any emotional reaction to same-sex erotica, yet their SCRs indicate that they are indeed experiencing arousal. Similarly, some phobics report extremely high levels of emotion when confronted with the object of their fears or asked to imagine it, yet their physiological responses do not reflect the terror they experience. While measures of the three systems of emotion generally converge, situations exist where they do not. It seems likely the results of this study constitute another instance where one aspect of emotion is affected and another is not.
Second, based on the
results of this study, it appears that color’s influence is only manifest in
the conscious evaluation of emotional experience. That is, people believe or “know” that color is somehow
inherently better (i.e., more pleasing and exciting) than black and white and
they are able to tell us so in their self-reports. This belief may be explicitly learned (e.g., the TV
salesperson or product brochure said color is better) or influenced by culture
or social context (e.g., a social norm that says technological advances are
always an improvement). Whatever
the origin of this belief, its impact on the emotional response to color is
apparently limited to the conscious experience of emotion. Despite what our culture or the TV salesperson may say, our
visceral experience of emotion is unaffected by color in moving images.
The pattern of color
effects found in this study differs from results of previous research on the
emotional impact of other formal attributes. In studies of both motion (Detenber et al., 1998; Simons et
al., in press) and screen size (Reeves et al., 1999) significant physiological
effects were found for the arousal dimension in addition to significant
differences in self-reports of arousal. This
kind of convergence across different measures of emotion contributes to our
confidence that certain formal attributes are psychologically meaningful.
However, the absence of convergence in the present study suggests that
color is a weak manipulation, at least compared to the influence of image
content, motion and screen size.
In addition to comments about the influence of
color on emotional responses, a few suggestions can be made for future research
on the effects of color in moving images. Since
it is unclear what, if any, impact color has on heart rate, this relationship
should be explored further. In
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1. For a recent review of the psychological significance of screen size see Grabe, Lombard, Reich, Bracken, & Ditton (1999).
2. The range of SAM valence rating for each category were: Positive (5.91-7.78), neutral (4.51-5.87) and negative (2.40-4.50). The range of SAM arousal means for the three arousal categories were: low (2.38-3.43), medium (3.44-4.16) and high (4.47-5.79).