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Precursors of Adolescents' Use of Visual and Audio Devices
During Online Communication
Abstract
Theories of computer-mediated communication typically rest upon the 
assumption that
communication via computers lacks visual and auditory cues. However, 
recent technological
advances, such as webcams and microphones, as well as their increased 
use question this
assumption. Moreover, the question arises of what characterizes 
individuals who use such
devices. Drawing on a survey of 1,060 adolescents, we found that 57% 
of adolescents at least
occasionally used webcams during instant messaging, while 32% at 
least sometimes used
microphones. If adolescents perceived the lack of visual cues in 
online communication to be
important, they used webcams less frequently. For early and middle 
adolescents, greater
levels of social anxiety reduced the use of webcams, whereas higher 
levels of private selfconsciousness
increased it. Our results suggest that the nature of computer-mediated
communication may change considerably in the next years. Theories of 
computer-mediated
communication need to more strongly integrate these changes into 
theory building.
Visual and Audio Devices 2
Precursors of Adolescents' Use of Visual and Audio Devices During 
Online Communication
Theories of computer-mediated communication typically rest on the 
assumption that,
compared with face-to-face communication, communication via computers 
lacks visual and
auditory cues (for recent reviews, see Thurlow, Lengel, & Tomic, 
2004; Walther & Parks,
2002). The lack of visual and auditory cues certainly characterized 
computer-mediated
communication in the 1980's and 1990's, when the reduced cues 
perspective (e.g., Culnan &
Markus, 1987), information richness theory (Daft & Lengel, 1984), 
social information
processing theory (Walther, 1992), social identity/deindividuation 
(SIDE) theory (Spears &
Lea, 1992), and the hyperpersonal communication perspective (Walther, 
1996) were
developed. However, recent technological advancements especially in 
online communication,
such as webcams and microphones, and their easy applicability 
challenge the assumption that
people generally receive fewer visual and auditory cues in 
computer-mediated communication
than in face-to-face communication.
Anecdotal evidence suggests that, particularly among adolescents, the 
use of visual
and audio devices during online communication has increased 
dramatically in the recent years
(Cross, 2003). We are thus witnessing a transition period in which 
one group of adolescents
communicates online in the traditional text-based fashion and another 
group enriches online
communication with audiovisual tools. This transition period provides 
us with a unique
opportunity to study what characterizes adolescents who use visual 
and audio devices during
online communication, as opposed to those who do not. This is the 
general goal of this study.
Although there have been several studies on video-mediated or 
visually enriched
communication (e.g., Finn, Sellen, & Wilbur, 1997; Walther, Slovacek, 
& Tidwell, 2001),
two features of these studies render them less appropriate as 
frameworks for studying the use
of visual and audio devices in online communication. First, in much 
research on videomediated
communication, the visual and auditory cues have been operationalized 
as objective
Visual and Audio Devices 3
characteristics of computer-mediated communication. This 
operationalization implicitly
assumes that particular features of computer-mediated communication 
affect all people to the
same extent. However, people's subjective perceptions of media 
characteristics have been
shown to be more influential than objective features of a medium, in 
particular with respect to
the use of communication media (Carlson & Zmud, 1999; Fulk, Schmitz, 
& Steinfield, 1990;
Ruggiero, 2000). Second, previous research has conceptualized visual 
and auditory cues as
situational influences on how communication via computers develops 
and which effects it
elicits (e.g., Gale, 1991; Whittaker & O'Connaill, 1997; Williams, 
1977). Thereby, it has
ignored the fact that the personality characteristics of a user may 
determine first whether
visual and audio devices in online communication are used at all. The 
specific goal of this
study is to investigate (a) how adolescents' subjective perceptions 
of online communication
and (b) how personality characteristics influence their use of visual 
and audio devices during
online communication.
We have selected adolescents as study subjects because they are the 
defining users of
the Internet (Madden & Rainie, 2003). They communicate online more 
frequently and
competently than adults and they more strongly integrate online 
communication into their
social lives (Gross, Juvonen, & Gable, 2002; Wolak, Mitchell, & 
Finkelhor, 2002). The
current changes in the bandwidth of online communication, that is, 
the multiplicity of
communication modes, may therefore be most visible in this age group 
(Cross, 2003). Partly
as a result of our focus on adolescents, in this study we deal with 
online communication via
instant messengers. Instant messaging has become increasingly popular 
among adolescents
and has replaced other forms of computer-mediated communication such 
as email, message
boards, and chat rooms. Most importantly, however, instant messengers 
enable users to easily
increase the bandwidth of online communication by adding visual or 
audio devices. By visual
and audio devices we mean webcams and microphones.
Visual and Audio Devices 4
Perceived Importance of Lacking Visual and Auditory Cues
Adolescents may differ in their perceptions of how important they 
consider the lack of
visual and auditory cues during online communication. Whereas some 
adolescents may attach
importance to the absence of visual and auditory cues, others may 
feel that they cannot
express themselves clearly enough in solely text-based communication. 
Strikingly, this
intuitively plausible individual difference has never been 
investigated in research on online
communication. More importantly, in its implicit assumption that 
there are no individual
differences in the perceived importance of lacking visual and 
auditory cues in online
communication, research has supported a somewhat deterministic 
conceptualization of the
influence of this lack on online communication. Allowing the 
perceived importance of visual
and auditory cues to vary individually may enable us to gain new 
insights into why
adolescents use visual and audio devices. We therefore hypothesize 
that adolescents will use
visual devices less frequently if they consider the lack of visual 
cues in online communication
more important (Hypothesis 1a). Likewise, we hypothesize a negative 
impact of adolescents'
perceived importance of lacking auditory cues on their use of audio 
devices (Hypothesis 1b).
Perceived Facilitation of Online Disinhibition
Social-influence theory and channel-expansion theory have shown that 
the study of
how individuals subjectively perceive the richness of information 
technologies improves our
understanding of information technology use in organizations (Carlson 
& Zmud, 1999; Fulk,
1993; Fulk et al., 1990). However, research on online communication 
has not yet devoted
much attention to subjective user perceptions of online communication 
characteristics. For
example, it is often theoretically emphasized that online 
communication increases disinhibited
behavior because, due to the lack of visual and auditory cues, 
individuals may feel less
inhibited than in a face-to-face setting (Cooper & Sportolari, 1997; 
Suler, 2004). Although
this presumption has also been confirmed empirically (Joinson, 2001; 
Leung, 2002; Kiesler,
Visual and Audio Devices 5
1986), it is unclear to what extent people equally experience that 
online communication
facilitates disinhibited behavior. Uses-and-gratifications research 
has demonstrated that
perceptions of media characteristics vary widely, which subsequently 
affects the use of media
(for review, see Ruggiero, 2000). Therefore, it may be worthwhile to 
investigate differences
in perceptions of whether online communication facilitates 
disinhibited behavior. These
perceptions may affect the extent to which visual and audio devices 
are used during online
communication. Given that the lack of visual and auditory cues is 
seen as essential for the
development of online disinhibited behavior (Spears & Lea, 1992; 
Suler, 2004), adolescents'
perception that online communication encourages disinhibited behavior 
can be expected to
reduce their use of visual and audio devices during online 
communication. Therefore, we
hypothesize: As adolescents perceive online communication to 
facilitate disinhibited
behavior, the use of visual devices will decrease (Hypothesis 2a). 
Likewise, as adolescents
perceive online communication to facilitate disinhibited behavior, 
the use of audio devices
will decrease (Hypothesis 2b).
Social Anxiety
Generally, socially anxious people feel nervous and distressed in 
social interactions
and are easily embarrassed in face-to-face communication (Cheek & 
Buss, 1981; Maltby &
Day, 2000). Internet research has shown that the socially anxious 
consider Internet
communication more appropriate than face-to-face communication to 
present their true self
(Amichai-Hamburger, Wainapel, & Fox, 2002; McKenna, Green, & Gleason, 
2002). Scholars
have explained this finding with the particular appeal that the lack 
of visual and auditory cues
in online communication exerts on socially anxious people (McKenna & 
Bargh, 2000). As a
result, people with high social anxiety should use visual and audio 
devices in online
communication less frequently than people with low social anxiety.
Visual and Audio Devices 6
For adolescents, however, a more complex pattern may arise. 
Adolescent theories
generally agree that early adolescents are more insecure about their 
social self than middle or
late adolescents (Harter, 1999; Schaffer, 1996). Early adolescents 
often engage in imaginative
audience behavior (Elkind & Bowen, 1979). They are inclined to 
distorted perceptions of how
they appear in the eyes of others and often overestimate the extent 
to which others watch and
evaluate them (Erikson, 1963; Harter, 1999). Webcams and microphones 
may reinforce these
inclinations. If, additionally, individuals are socially anxious, the 
use of these devices may be
especially uncomfortable for them. Consequently, we expect an 
interaction effect between age
and social anxiety on both the use of webcams and microphones: Early 
adolescents who are
socially anxious will use visual and audio devices less frequently 
than late adolescents who
are socially anxious. Thus, we hypothesize that the effect of social 
anxiety on the use of (a)
visual and (b) audio devices will be more negative for early 
adolescents than for late
adolescents (Hypotheses 3a and 3b).
Private and Public Self-consciousness
Both private and public self-consciousness describe a process of self-focused
attention. However, whereas private self-consciousness "refers to the 
dispositional tendency
to focus attention on the more private and covert aspects of oneself" 
(Franzoi & Davis, 1985,
p. 769), public consciousness relates to the dispositional tendency 
to direct attention toward
the self as a social object (Fenigstein, Scheier, & Buss, 1975). 
People high in private selfconsciousness
typically have more accurate self-knowledge and are thus better equipped to
open up to others. As a result, high levels of private 
self-consciousness increase the amount of
personal information people share with others and lead to greater 
self-disclosure (Franzoi &
Davis, 1985; Franzoi, Davis, & Young, 1985). People high in public 
self-consciousness are
likely to see themselves as the object of others' attention and 
consider others' opinions about
themselves important. In comparison with individuals low in this 
trait, they consequently put
Visual and Audio Devices 7
more emphasis on outer appearance and are better able to predict 
their impression on others
(Miller & Cox, 1982; Solomon & Schopler, 1982; Tobey & Tunnell, 1981).
These results from personality psychology suggest that both 
individuals high in
private self-consciousness and individuals high in public 
self-consciousness should be more
comfortable with presenting themselves during online communication 
through visual or audio
modes. However, private and public self-consciousness may not operate 
independently of
each other. People high in both private and public self-consciousness 
are less willing to share
personal information than people high in either private or public 
self-consciousness (Shaffer
& Tomarelli, 1989). More specifically, in a study on self-disclosure 
in computer-mediated
communication, Joinson (2001) found that self-disclosure was highest 
for people high in
private and low in public self-consciousness and for those low in 
private and high in public
self-consciousness. We assume that the use of visual and audio 
devices in online
communication is comparable with verbal self-disclosure because both 
visual and audio
devices, as well as verbal self-disclosure involve individuals' 
tendency to present information
about themselves. In line with Joinson (2001), we expect an 
interaction effect between private
and public self-consciousness on adolescents' use of visual and audio 
devices during online
communication. Specifically, we hypothesize that adolescents who 
either are high in private
and low in public self-consciousness or are high in public and low in 
private selfconsciousness
will use (a) visual and (b) audio devices more frequently than their
counterparts (Hypotheses 4a and 4b).
Method
Sample and Procedure
We conducted a survey among 1,174 adolescents between 12 and 17 years 
of age (M =
14.5, SD = 1.6, 52% girls). The adolescents were recruited from 6 
elementary, middle and
high schools in the Netherlands. The schools were chosen in such a 
way that they represented
Visual and Audio Devices 8
adolescents across all levels of socioeconomic status. Because we are 
interested in the use of
visual and audio devices during online communication, for this study 
we selected only
adolescents who had ever used instant messaging (n = 1,060, 90%).
Measures – Dependent and Independent Variables
Use of visual and audio devices during online communication. We asked the
respondents how often they used a webcam or a microphone during 
instant messaging.
Response categories ranged from 1 (never) to 4 (always).
Perceived importance of lacking visual cues. Respondents were asked 
to what extent
they considered it important that, during instant messaging, (1) 
"...others cannot see what your
face looks like"; (2) "...others cannot see that you are angry"; (3) 
"...others cannot see that you
are nervous"; (4) "...others cannot see that your are disappointed"; 
(5) "...others cannot see
that you are doing something else at the same time"; (6) "...others 
cannot see what clothes you
are wearing". The response categories for each of the items ranged 
from 1 (not important at
all) to 5 (very important). The 6 items formed a one-dimensional 
scale, with a Cronbach's
alpha of .84.
Perceived importance of lacking auditory cues. To operationalize adolescents'
perceived importance of auditory cues, we used 4 items. Three of the 
items were comparable
to items (2), (3), and (4) of the perceived importance of lacking 
visual cues scale, only
adjusted for audio cues ("...others cannot hear that..."). In 
addition, we used the item "...others
cannot hear how your voice sounds". The 4 items formed a 
one-dimensional scale, with a
Cronbach's alpha of .86.
Perceived facilitation of disinhibition online. We measured this 
construct with three
items: (1) "During instant messaging, I feel less constrained to use 
certain words than in a
face-to-face meeting"; (2) "During instant messaging, I feel less 
restricted to talk about certain
things than in a face-to-face meeting" and (3) "During instant 
messaging I feel more free to
Visual and Audio Devices 9
talk about things than in a face-to-face meeting". The anchors of the 
response categories were
1 (completely disagree) and 5 (completely agree). The 3 items formed 
a one-dimensional
scale, with a Cronbach's alpha of .77.
Social anxiety. The construct was measured with items from the Social 
avoidance and
distress – new people subscale of the Social Anxiety Scale for 
Adolescents (La Greca &
Lopez, 1998). From the original scale, we selected the four items 
with the highest factor
loadings. The response categories for each of the items ranged from 1 
(completely disagree)
to 5 (completely agree). The 4 items formed a one-dimensional scale, 
with a Cronbach's alpha
of .78.
Private and public self-consciousness. We used items from the private 
and public selfconsciousness
subscale that belong to the Fenigstein Self-Consciousness Scale (Fenigstein et
al., 1975). The response categories for each of the items ranged from 
1 (completely disagree)
to 5 (completely agree). The sub-scales have successfully been 
employed to measure private
and public self-consciousness among adolescents (Rankin, Lane, 
Gibbons, & Gerrard, 2004).
However, based on research regarding the factor structure of the 
scales (Cramer, 2000; Dillard
& Hunter, 1989), we removed 4 items from the original private 
self-consciousness scale and 2
items from the public self-consciousness scale, because those items 
have been shown to only
unreliably define the constructs. Private self-consciousness was 
eventually operationalized
with 6 items, and public self-consciousness with 5 items. A factor 
analysis with varimax
rotation yielded two independent factors with an explained variance 
of 55%. Cronbach's alpha
was .80 for the private self-consciousness scale and .82 for the 
public self-consciousness
scale.
Measures – Control Variables
There are at least five potentially alternative explanations of why 
adolescents may use
visual and audio devices when communicating online. First, the use of 
visual and auditory
Visual and Audio Devices 10
cues may simply be the result of more experience with instant 
messaging. Second, the use of
such devices may be easier when talking with close friends online. 
Third, adolescents may use
visual and audio devices much more frequently, either when they are 
alone or when they
communicate online while friends are present. Fourth, due to 
developmental transitions, early
adolescence is a critical time for seeking new experiences 
(Brinthaupt & Lipka, 2002; Harter,
1999). Particularly among early adolescents, visual and auditory 
tools in online
communication may stimulate the search for such experiences. Finally, 
although Leung
(2004) has recently found no gender differences in the general 
frequency of instant messaging
among adolescents, related research on personal Internet homepages 
suggests that males more
often opt for more sophisticated web-based technologies (Döring, 
2002). This may also apply
to the use of visual and audio devices in online communication. Boys 
may therefore be more
likely than girls to use visual and audio devices during online communication.
Based on these five alternative explanations, we controlled for the 
following variables:
(1) experience with instant messaging, operationalized as an additive 
index of the
standardized variables frequency, intensity, and rate of instant 
messaging, as well as the
number of contacts per day (Cronbach's alpha = .66); (2) the number 
of adolescents' contact
persons in instant messaging that they considered close friends; (3) 
the frequency of instant
messaging while being alone and while being together with friends. 
(Response categories for
these variables ranged from 0 [never] to 4 [always]); (4) age; and 
(5) gender, with 0 coded as
boy and 1 coded as girl.
Data Analysis
In order to test the extent to which the hypothesized influences 
could be confirmed
empirically, we ran hierarchical multiple regressions for each 
dependent variable (i.e., the use
of webcams and the use of microphones). In a first step, we entered 
the main effects, in a
second step we entered the interaction effects to study to what 
extent the interaction effects
Visual and Audio Devices 11
would significantly increase the explanatory power of the model 
(Cohen & Cohen, 1983). To
avoid multi-collinearity problems, we centered the variables 
constituting the interaction terms
around the mean (Aiken & West, 1991). Furthermore, we post-hoc probed 
the interaction
effects for significant differences from zero. Aiken and West (1991) 
recommend selecting, for
the moderating variable (e.g., age), values corresponding with the 
centered mean, with one
standard deviation below the mean, and with one standard deviation 
above the mean.
Subsequently, the conditional slopes of the focal independent 
variable (e.g., social anxiety)
along with the pertinent standard errors can be calculated. The 
resulting t-values indicate
whether the conditional slopes differ significantly from zero.
Results
Descriptive Analyses
Four percent of the adolescents said they always used a webcam while instant
messaging. Fifteen percent reported frequent use of a webcam, and 38% 
said that they used
webcams at least occasionally. The remaining 43% of adolescents never 
used webcams
during instant messaging. As for the use of microphones, 2% percent 
of the adolescents
reported that they always used a microphone during instant messaging. 
Six percent of the
adolescents used a microphone often, and 24% of them used a 
microphone occasionally.
Finally, 68% of the adolescents never used a microphone when instant 
messaging.
Explanatory Analyses – Use of Visual Devices (webcams)
Hypothesis 1a predicted that adolescents would use visual devices 
less frequently, if
they considered the lacking visual cues in online communication 
important. Table 1 shows a
significant negative impact of the perceived importance of lacking 
visual cues on the use of
visual devices (b = -.04, p < .05). The more important the lack of 
visual cues was to
adolescents, the less frequently they used visual devices during 
online communication.
Hypothesis 1a was thus confirmed. However, we did not find support 
for Hypothesis 2a:
Visual and Audio Devices 12
Adolescents' perception of the extent to which online communication 
facilitates disinhibited
behavior did not influence the use of visual devices.
Hypothesis 3a predicted that the effect of social anxiety on the use 
of visual devices
would be more negative for young adolescents than for old 
adolescents. As the interaction
model for visual devices in Table 1 indicates, there was a 
significant interaction effect
between social anxiety and age on the use of visual devices (b = .04, 
p < .05). This interaction
effect increased the explanatory power of the model by a significant 
0.4%, F (1,1046) = 4.77,
p < .05 (Note that the 1% increase of the explained variance in Table 
1 is due to rounding).
The younger the adolescents were, the more negative the influence of 
social anxiety on the
use of visual devices. Thus, social anxiety reduced the use of visual 
devices most strongly
among early adolescents. This effect leveled off in the older age groups.
Post-hoc probing showed that the conditional slopes at one standard 
deviation below
the age mean, t (1,045)= -0.151/0.053 = -2.85, p < .05, and at the 
age mean, t (1,045)= -
0.07/0.035 = -2.00, p < .05, were significantly different from zero, 
whereas the slope at one
standard deviation above the age mean was not (t (1,045)= 0.011/0.048 
= 0.23, n.s.). This
more rigorous testing of the interaction effect thus confirms that, 
as hypothesized, only for
early and middle adolescents, social anxiety exerted a negative 
effect on the use of visual
devices. Hypothesis 3a was supported.
Hypothesis 4a specified that adolescents who either are high in 
private selfconsciousness
and low in public self-consciousness or are low in public self-consciousness
and high in private self-consciousness would use visual devices more 
often than their
counterparts. This hypothesis was not supported. There was no 
significant interaction effect
between private and public self-consciousness (b = -.02, n.s.). 
However, as the main effect
model for webcams in Table 1 shows, private consciousness affected 
the use of visual devices
regardless of the levels of public self-consciousness (b = .09, p < 
.01). With increasing private
Visual and Audio Devices 13
self-consciousness, adolescents were more likely to use visual 
devices during online
communication. Public self-consciousness had no significant main effect.
Three of the control variables significantly affected the use of 
visual devices. Early
adolescents used visual devices during online communication more 
often than late
adolescents. Adolescents who generally communicated online more often 
also used webcams
more frequently. Moreover, if adolescents communicated online in the 
presence of friends,
they were more likely to use visual devices.
Explanatory Analyses – Use of Audio devices (Microphones)
Table 1 indicates that there was no support for the hypothesized influences on
adolescents' use of audio devices. Hypotheses 1b, 2b, 3b, and 4b had 
to be rejected. However,
four control variables significantly predicted the use of audio 
devices during online
communication. Early adolescents used audio devices more often than 
late adolescents, and
boys did so more often than girls. The more frequently adolescents 
were alone during online
communication, the more likely they were to use audio devices. 
Finally, the more experience
adolescents had with instant messaging, the more often they used a microphone.
Discussion
This study has shown that the use of visual devices, in particular, 
has become a
pervasive phenomenon in adolescent online communication. More than half of the
adolescents used a webcam, at least occasionally, during instant 
messaging. The results
regarding the use of auditory cues are less distinct, but also 
suggest that computer-mediated
communication, with its traditional emphasis on text-only 
information, has undergone a
fundamental change. This study has also demonstrated that the use of 
visual devices does not
occur evenly among adolescents, but attracts certain types of 
adolescents more than others.
Our findings on the prevalence and precursors of visual and, to a 
lesser extent, audio devices
Visual and Audio Devices 14
in adolescent online communication may improve our understanding of a 
new phenomenon.
They may also challenge existing theories of computer-mediated communication.
Understanding the Use of Visual and Audio devices in Online Communication
Previous research on computer-mediated communication has implicitly
conceptualized the lack of visual and auditory cues as a homogeneous 
influence on people's
interaction via the computer. Essentially, studies have been based on 
the implicit assumption
that the lack of visual and auditory cues in computer-mediated 
communication is of equal
importance to all people and to their decision of whether and how to 
communicate online.
This study is the first to have translated this homogeneity 
assumption into a researchable
variable. We conceptualized the use of visual and auditory cues as 
being influenced by
adolescents' subjective perception of how important the lack of 
visual and auditory cues in
computer-mediated communication are to them. Indeed, adolescents who 
considered the lack
of visual cues in online communication as more important were less 
likely to use webcams
than adolescents to whom the lack of visual cues was less important. 
This result was obtained
even though we controlled for a number of rival explanations.
Our findings are in line with several theories from organizational 
communication
(Carlson & Zmud, 1999; Fulk, 1993; Fulk et al., 1990) and 
uses-and-gratifications research
(Ruggiero, 2000) that have shown that individual perceptions of media 
characteristics guide
media use more strongly than objective media features. Our result 
suggests that we need to be
cautious when generalizing from the objective features of 
computer-mediated communication
to whether and how people actually interact via computers. Rather, we 
need to more strongly
take into account people's subjective perceptions of 
computer-mediated communication.
The perceived importance of reduced auditory cues did not affect 
whether adolescents
used microphones. The finding, that the perceived importance of 
lacking cues only affected
the use of webcams and not the use of microphones, may be explained 
with the differential
Visual and Audio Devices 15
importance of auditory and visual information to human beings. There 
is sufficient research
evidence that, to human beings, visual information is more revealing 
than auditory
information (e.g., Argyle & Cook, 1976). This is reflected in our 
finding that adolescents
attached significantly lower importance to the lack of auditory (M = 
2.16, SD = .90) than to
the lack of visual cues in online communication (M = 2.29, SD = .83), 
t(1095) = 7.67, p <
.001. Thus, the perceived lack of visual cues in online communication 
may generally be more
relevant to online communication than the perceived lack of auditory cues.
In contrast to our expectations, the perceived facilitation of online 
disinhibition did not
affect the use of visual and auditory cues. What is more, zero-order 
correlations indicated a
positive relationship of this perception and the use of webcams (r = 
.10, p < .01), whereas we
had predicted a negative one. In the multiple regression analysis, 
the influence of online
disinhibition on the use of webcams only marginally failed to be 
significant with two-tailed
significance testing, t (1,047) = 1.8, p = .07 (Note that the values 
of the regression coefficients
and their standard errors in Table 1 are rounded). Therefore, we can 
tentatively conclude that
a relationship between this perception and the use of webcams may not 
be completely
illusionary, but different from what we predicted. Adolescents may 
perceive that online
communication facilitates disinhibition, and yet use webcams. In this 
case, the perception
may reflect a more abstract awareness of what characterizes online 
communication, but does
not influence actual behavior. Clearly, we need more research on this 
issue, but our finding
tentatively suggests a sophisticated, hybrid user who knows the 
characteristics of online
communication well without paying much attention to them in his/her 
actual online
communication.
Much of the previous research is based on the theoretical assumption 
that the lack of
visual and auditory cues appeals particularly to socially anxious 
people (McKenna & Bargh,
2000). Consequently, we hypothesized that socially anxious 
adolescents would be less
Visual and Audio Devices 16
inclined to use visual and audio devices during online communication 
than non-socially
anxious adolescents. A main effect of social anxiety was found 
neither for the use of webcams
nor for the use of microphones. However, we did find an interaction 
effect between social
anxiety and age on the use of webcams. Social anxiety decreased the 
use of webcams much
more strongly among early adolescents than among late adolescents. In 
the oldest groups of
adolescents, social anxiety no longer affected the use of webcams. 
The strong negative effect
of social anxiety on the use of webcams among early adolescents may 
be the result of nonaccomplished
developmental tasks in this age group. Early adolescents are most insecure
about their social self and, at the same time, preoccupied with how 
others see and evaluate
them. When social anxiety accompanies this tendency, the use of 
webcams may become
uncomfortable. In contrast, late adolescents are more self-assured 
about their social self and
social anxiety does not seem to affect their use of visual devices 
during online
communication. There is a need to replicate our findings with a 
sample more diverse in terms
of age. The oldest respondents in our sample were 17 years old, but 
our findings suggest that,
for post-adolescents or adults, social anxiety may eventually exert a 
positive impact on the
use of visual devices.
In contrast to existing studies (Joinson, 2001), we did not find an 
interaction effect
between private and public self-consciousness on the use of visual 
and audio devices. This
may partly result from our focus on the use of webcams and 
microphones and not on selfdisclosure
in computer-mediated communication. However, the strong positive main 
effect of
private self-consciousness on the use of webcams concurs with 
research from personality
psychology on how adolescents high in private self-consciousness 
behave in face-to-face
communication with peers (Franzoi & Davis, 1985; Franzoi et al., 
1985). Adolescents high in
private self-consciousness are more introspective and in closer touch 
with their inner life than
adolescents low in that trait. Face-to-face meetings with friends are 
an appropriate outlet for
Visual and Audio Devices 17
opening up and talking about one's inner life. Because 
webcam-supported instant messaging
(which typically takes place with peers) resembles such face-to-face 
meetings, adolescents
high in private self-consciousness may be more likely to add visual 
devices to online
communication.
Challenging Existing Theories of Computer-Mediated Communication
Theories of computer-mediated communication necessarily reflect the 
technological
state of art at the time they were developed. In the 1980's and 
1990's, when the majority of
these theories originated, personal communication via computers was 
to a large extent
asynchronous, anonymous, and text-based. These characteristics have 
influenced our
theorizing about computer-mediated communication. However, at least 
in adolescents'
communication via computers, we are currently witnessing a 
development in which none of
these characteristics holds true anymore. Adolescents communicate 
heavily via instant
messengers and communication via instant messengers is often 
synchronous, non-anonymous,
and enriched with visual cues. Assuming that what we are observing 
among adolescents
anticipates future developments in computer-mediated communication, 
there may be at least
four implications for future theorizing in that field.
First, theories that are based on the assumption that computer-mediated
communication is asynchronous, anonymous, and exclusively text-based 
have to more
strongly take into account the visual and audio modes newly available 
in computer-mediated
communication. Whether computer-mediated communication is 
asynchronous, anonymous,
and exclusively text-based, has become a matter of individual choice 
and we need to study
what governs these choices. Second, because the bandwidth of computer-mediated
communication has become subject to individual decisions, we need to 
more strongly focus
on computer-mediated communication through multiple modes: the 
combined use of textual,
visual, and auditory cues in communication via computers. People no 
longer have to find
Visual and Audio Devices 18
functional equivalents for characteristics of face-to-face 
communication, such as facial
expressions, that cannot be expressed in text-only communication. The 
key question thus
becomes when mode extension takes place; that is, when people decide 
to add visual or audio
modes to text-only communication. Third, the individual choice of 
bandwidth through mode
extension requires us to deal with user's information management more 
thoroughly.
Anonymity may be considered as the extreme end of restrictive 
information management in
computer-mediated communication. But people may gradually disclose 
more information by
increasing the bandwidth of computer-mediated communication, thereby 
changing their
information management. Finally, we know little about which 
consequences the individual
choice of mode extension has on users' experience with communication 
via computers. There
is evidence that computer-mediated communication that is accompanied 
by photos reduces
social attractiveness and affection (Walther et al., 2001). Still, 
the influence of webcams and
microphones may be different, as research on video-mediated 
communication on affection
suggests (for review, see Whittaker & O'Connaill, 1997). This paper 
has shown that
computer-mediated communication may be in a transition period. Much 
of the future promise
of theories of computer-mediated communication lies in an adequate 
reaction to these
changes.
Visual and Audio Devices 19
References
Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and 
interpreting
interactions. Newbury Park, CA: Sage.
Amichai-Hamburger, Y., Wainapel, G., & Fox, S. (2002). "On the 
Internet nobody knows I'm
an introvert": Extraversion, neuroticism, and Internet addiction. 
Cyberpsychology &
Behavior, 5, 125-128.
Argyle, M., & Cook, M. (1976). Gaze and mutual gaze. Cambridge: 
Cambridge University
Press.
Carlson, J. R., & Zmud, R. W. (1999). Channel expansion theory and 
the experiential nature
of media richness perceptions. Academy of Management Journal, 42, 153-170.
Cheek, J. M., & Buss, A. H. (1981). Shyness and socialbility. Journal 
of Personality and
Social Psychology, 41, 330-339.
Cohen, J., & Cohen, P. (1983). Applied mutliple 
regression/correlation analyses for the
behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
Cooper, A., & Sportolari, L. (1997). Romance in Cyberspace: 
Understanding online
attraction. Journal of Sex Education and Therapy, 22, 7-14.
Cramer, K. M. (2000). Comparing the relative fit of various factor 
models of the selfconsciousness
scale in two independent samples. Journal of Personality Assessment,
75(2), 295-307.
Cross, J. (2003). The $40 device you didn't know you needed. 
Retrieved February 15, 2005,
from http://www.extremetech.com/article2/0,1558,1424785,00.asp
Culnan, M. J., & Markus, M. L. (1987). Information technologies. In 
F. M. Jablin, L. L.
Putnam, K. H. Roberts, & L. W. Porter (Eds.), Handbook of organizational
communication: An interdisciplinary perspective (pp. 420-443). 
Newbury Park, CA:
Sage.
Visual and Audio Devices 20
Daft, R. L., & Lengel, R. H. (1984). Information richness: A new 
approach to managerial
behavior and organization design. Research in Organizational 
Behavior, 6, 191-233.
Dillard, J. P., & Hunter, J. E. (1989). On the use and interpretation 
of the emotional empathy
scale, the self-consciousness, and the self-monitoring scale. 
Communication Research,
16, 104-139.
Döring, N. (2002, April). Personal home pages on the web: A review of 
research. Journal of
Computer Mediated Communication, 7(3). Retrieved October 20, 2004, from
http://www.ascusc.org/jcmc/vol7/issue3/doering.html.
Elkind, D., & Bowen, R. (1979). Imaginary audience behavior in 
children and adolescents.
Developmental Psychology, 15, 38-44.
Erikson, E. (1963). Childhood and Society. New York: Norton.
Fenigstein, A., Scheier, M. F., & Buss, A. H. (1975). Public and 
private self-consciousness:
Assessment and theory. Journal of Consulting and Clinical Psychology, 
43, 522-527.
Finn, K. E., Sellen, A. J., & Wilbur, S. B. (Eds.). Video-mediated 
communication. Mahwah,
NJ: Erlbaum
Franzoi, S. L., & Davis, M. H. (1985). Adolescent self-disclosure and 
loneliness: private selfconsciousness
and parental influences. Journal of Personality and Social Psychology,
48, 768-780.
Franzoi, S. L., Davis, M. H., & Young, R. D. (1985). The effects of 
private self-consciousness
and perspective taking on satisfaction with in close relationships. 
Journal of Personality
and Social Psychology, 48(6), 1584-1594.
Fulk, J. (1993). Social construction of communication technology. 
Academy of Management
Journal, 38, 921-950.
Visual and Audio Devices 21
Fulk, J., Schmitz, J., & Steinfield, C. W. (1990). A social influence 
model of technology use.
In J. Fulk & C. W. Steinfield (Eds.), Organizations and communication 
technology (pp.
117-140). Newbury Park: Sage.
Gale, S. (1991). Adding audio and video to an office environment. In 
J. M. Bowers & S. D.
Benford (Eds.), Studies in computer-supported collaborative work: 
theory, practice and
design (pp. 49-62). Amsterdam: North-Holland .
Gross, E. F., Juvonen, J., & Gable, S. L. (2002). Internet use and 
well-being in adolescence.
Journal of Social Issues, 58, 75-90.
Harter, S. (1999). The construction of the self: A developmental 
perspective. New York:
Guilford Press.
Joinson, A. N. (2001). Self-disclosure in computer-mediated 
communication: The role of selfawareness
and visual anonimity. European Journal of Social Psychology, 31, 177-192.
Kiesler, S. (1986). The hidden messages in computer networks. Harvard 
Business Review,
64(3), 58-60.
La Greca, A., & Lopez, N. (1998). Social anxiety among adolescents: 
Linkages with peer
relations and friendships. Journal of Abnormal Child Psychology, 26, 83-94.
Leung, L. (2002). Loneliness, self-disclosure, and ICQ ("I seek you") 
use. Cyberpsychology
& Behavior, 5, 241-251.
Leung, L. (2004). Net-generation attributes and seductive properties 
of the Internet as
predictors of online activities and Internet addiction. 
Cyberpsychology & Behavior, 7,
333-348.
Madden, M., & Rainie, L. (2003). America's online pursuits. The 
changing picture of who's
online and what they do. Washington, D.C.: The Pew Internet & 
American Life Project.
Maltby, J., & Day, L. (2000). The reliability and validity of a 
susceptibility to embarrassment
scale among adults. Personality and Individual Differences, 29, 749-756.
Visual and Audio Devices 22
McKenna, K. Y. A., & Bargh, J. A. (2000). Plan 9 from cyberspace: The 
implications of the
Internet for personality and social psychology. Personality and 
Social Psychology
Review, 4, 57-75.
McKenna, K. Y. A., Green, A. S., & Gleason, M. E. J. (2002). 
Relationship formation on the
Internet: What's the big attraction? Journal of Social Issues, 58, 9-31.
Miller, L. C., & Cox, C. L. (1982). For appearances' sake: Public 
self-consciousness and
makeup use. Personality and Social Psychology Bulletin, 8, 748-751.
Rankin, J. L., Lane, D. J., Gibbons, F. X., & Gerrard, M. (2004). 
Adolescent selfconsciousness:
Longitudinal age changes and gender differences in two cohorts. Journal
of Research on Adolescence, 14, 1-21.
Ruggiero, T. E. (2000). Uses and gratifications theory in the 21st 
century. Mass
Communication & Society, 3, 3-37.
Schaffer, H. R. (1996). Social development. Malden, MA: Blackwell.
Shaffer, D. R., & Tomarelli, M. M. (1989). When public and private 
self-foci clash: Selfconsciousness
and self-disclosure reciprocity during the acquaintance process. Journal
of Personality and Social Psychology, 56, 765-776.
Solomon, M. R., & Schopler, J. (1982). Self-consciousness and 
clothing. Personality and
Social Psychology Bulletin, 8, 508-514.
Spears, R., & Lea, M. (1992). Social influence and the influence of 
the 'social' in computermediated
communication. In M. Lea (Ed.), Contexts of computer-mediated
communication (pp. 30-65). Hemel Hempstead: Harvester Wheatsheaf.
Suler, J. (2004). The online disinhibition effect. Cyberpsychology & 
Behavior, 7(3), 321-326.
Tapscott, D. (1998). Growing up digitial. The rise of the net 
generation. New York: McGraw-
Hill.
Visual and Audio Devices 23
Thurlow, C., Lengel, L., & Tomic, A. (2004). Computer mediated 
communication. Social
interaction and the Internet. London: Sage.
Tobey, E. L., & Tunnell, G. (1981). Predicting our impressions on 
others: Effects of public
self-consciousness and acting, a self-monitoring subscale. 
Personality and Social
Psychology Bulletin, 7, 661-669.
Walther, J. B. (1992). Interpersonal effects in computer-mediated 
communication: A
relational perspective. Communication Research, 19, 52-90.
Walther, J. B. (1996). Computer-mediated communication. Impersonal, 
interpersonal, and
hyperpersonal interaction. Communication Research, 23, 3-43.
Walther, J. B., & Parks, M. R. (2002). Cues filtered out, cues 
filtered in. Computer-mediated
communication and relationships. In M. L. Knapp & J. A. Daly (Eds.), 
Handbook of
interpersonal communication (pp. 529-563). Thousand Oaks: Sage.
Walther, J. B., Slovacek, C. L., & Tidwell, L. C. (2001). Is a 
picture worth a thousand words?
Photographic images in long-term and short-term computer-mediated 
communication.
Communication Research, 28, 105-134.
Whittaker, S., & O'Connaill, B. (1997). The role of vision in 
face-to-face and mediated
communication. In K. E. Finn, A. J. Sellen & S. B. Wilbur (Eds.), 
Video-mediated
communication (pp. 23-49). Mahwah, NJ: Erlbaum.
Williams, E. (1977). Experimental comparisons of face-to-face and 
mediated communication:
A review. Psychological Bulletin, 84, 963-976.
Wolak, J., Mitchell, K. J., & Finkelhor, D. (2002). Close online 
relationships in a national
sample of adolescents. Adolescence, 37, 441-455.
Table 1
Precursors of Adolescents' Use of Visual and Audio devices
Control variables
Age
Female
IM when friends present
IM when alone
Close friends IM partner
Experience with IM
Perceptual variables
Perceived importance of lacking
visual cues
Perceived importance of lacking
auditory cues
Perceived facilitation of online
disinhibition
Personality variables
Social anxiety
Private self-consciousness
Public self-consciousness
Interaction effects
Social anxiety x Age
Private x public self-consciousness
Constant
R square
* p < .05, ** p < .01, *** p < .001 (two-tailed)
Visual and Audio Devices 24
Visual devices
Interaction
effect model
Main effect
model
b
(SE)
b
(SE)
-.03*
(.02)
-.04*
(.02)
.07
(.05)
.08
(.05)
.09**
(.03)
.09**
(.03)
.06
(.04)
.06
(.04)
.11
(.09)
.11
(.09)
.08***
(.01)
.08***
(.01)
-.06*
(.03)
-.06*
(.03)
.04
(.03)
.05
(.03)
-.07
(.04)
-.06
(.04)
.09**
(.03)
.09**
(.03)
-.06
(.04)
-.07
(.04)
.04*
(.02)
-.02
(.03)
1.24
.19
1.21
.18
Audio devices
Interaction
effect model
Main effect
model
b
(SE)
b
(SE)
-.03*
(.01)
-.03*
(.01)
-.10*
(.04)
-.10*
(.04)
.04
(.03)
.04
(.03)
.10**
(.03)
.10**
(.03)
.12
(.08)
.12
(.08)
.05***
(.01)
.05***
(.01)
-.04
(.03)
-.04
(.03)
.02
(.07)
.03
(.03)
-.01
(.03)
-.01
(.03)
.03
(.02)
.03
(.02)
-.02
(.02)
-.02
(.02)
<.01
(.02)
<.01
(.03)
1.10
.13
1.10
.13