The relationship of habit and deficient serf-regulation was further
clarified. Habit perhaps indicates a failure of the first of the three
subfunctions of serf-regulation proposed by SCT, self-observation. As
such, this aspect of unregulated media behavior is closely related to
notions of automaticity (Bargh & Gollwitzer, 1994). Deficient
self-regulation derives from the failure of the judgmental and
self-reactive subprocesses of self-regulation. It reflects a conscious
failure of self-control wherein individuals struggle with themselves to
judge their own behavior against appropriate standards and to apply
incentives to moderate their consumption. The findings supported the
proposed theoretical relationship between the two constructs wherein
deficient self-regulation adds to habit strength.
Internet self-efficacy causally preceded Internet usage and was in
turn determined by prior Internet experience as it was in previous
college student samples (Eastin & LaRose, 2000). The hypothesized
relationship between self-efficacy and habit strength was not observed,
falling just short of statistical significance. It appears that
self-efficacy acts on habit strength through expected outcomes. The
inattentiveness to one's own behavior that signals habit formation
thus could be more determined by a gradual cessation of active thinking
about outcomes/gratifications rather than inattentiveness accompanying
task mastery.
The lack of a causal connection between experience and habit
strength, despite a significant zero-order correlation (r = .30, p <
.001), belies the rival "tautology hypothesis" about the role
of habit in human behavior; namely, that habit is "just" prior
behavior and that relationships between two measures of behavior are not
theoretically meaningful. An alternative causal model in which a direct
link from experience (prior behavior) to usage (current behavior) was
hypothesize also failed to produce a significant relationship, and did
not diminish the causal link between habit and usage, again despite a
highly significant zero-order correlation (r = .35, p < .001) between
experience and usage. These findings suggest that habit strength indeed
has an impact on behavior that can be described in social cognitive
terms.
The Internet emerges from the present study as something of a
distinctive medium, but perhaps not in ways previously described. It is
not primarily a social medium (e.g., Papacharissi & Rubin, 2000),
but also a medium through which enjoyable activity, self-reactive,
monetary, novel (i.e., informational), and, above all, status incentives
can be obtained. That the Internet is a medium of social interaction is
indisputable, but a question now arises as to the purpose of the social
interaction. Prior research surrounding the Internet Paradox (Kraut,
Patterson, Lundmark, Kiesler, Mukophadhyay, & Scherlis, 1998)
focused on social interaction as a means of securing social support and
thereby improving psychological well-being. Now it appears that social
status, not social support, might be the prime mover in Internet usage.
Perhaps by finding like-minded individuals on the Internet and
expressing ourselves in those venues we enhance our social status. Or,
recalling Turkle's (1995) Life on the Screen ethnography, perhaps
the Internet is a means of constantly exploring and trying out new,
improved versions of our selves. From this we should begin to
empirically explore online personal development (as self or with virtual
others) as well as social maintenance (a support mechanism).
Limitations
The generalizability of the present research is limited by the
geographic scope of the sample. The sample contained disproportionately
small representations of young people and males. As a one-shot survey
study, the direction of causation cannot be established. Indeed, within
SCT reciprocal causation is recognized. For example, self-efficacy is a
precondition for successful performance of a behavior, but successful
performance also increases self-efficacy.
Implications for Further Research
Internet usage was broadly defined. Future research might
distinguish Internet applications (e.g., e-mail vs online chat),
functions (e.g., entertainment vs news Web sites), or settings (e.g.,
work vs leisure). However, in keeping with the operational procedures
recommended in SCT, it will be important to match the explanatory
constructs (e.g., expected e-mail outcomes, e-mail self-efficacy, e-mail
habits, etc.) to achieve satisfactory results.
Habit strength, deficient self-regulation, and self-efficacy might
extend to other forms of media attendance. Many media consumption
behaviors (e.g., tuning in the evening news) would seem to be
habit-prone. While few mass media require skills as complex as the
Internet, there are perhaps parallel media self-efficacy constraints.
Anyone who has ever given up recording a favorite show because
programming the recorder was "too much hassle" may be said to
suffer from a self-efficacy deficit. Television addiction has been
described (by Kubey & Csikszentmihalyi, 2002) in the same terms of
behavioral addiction that underlie deficient self-regulation. Here, we
found the construct useful in explaining media attendance in a normal
population of media consumers; perhaps that would extend to other media
as well.
The present research suggests new departures from uses and
gratifications traditions. Redefining gratifications as expected
outcomes may have merit on both conceptual and operational levels.
Secondly, gratification dimensions from previous research may have
neglected some potentially important variables, particularly the status
that media attendance may confer. Third, habit strength appears to be a
distinct construct from gratifications, as early conceptualizations
(e.g., Palmgreen et al., 1985, p. 17) observed, but later research
neglected.
More fundamentally, the present findings suggest that active
selection of media that best meet personal needs is not the sole
mechanism explaining media attendance. Active selection dominates when
new media alternatives appear or when personal routines are disrupted.
Self-efficacy beliefs about one's ability to utilize alternative
media channels may also contribute to media selection. Thereafter,
repeated consumption is increasingly habitual and automatic as we turn
our attention elsewhere. Once habits are established, users no longer
think through whether one alternative or another is a better way of
obtaining a particular outcome. Users still monitor their overall level
of Internet usage and apply self-reactive incentives to adjust the
amount to appropriate levels, as defined by personal or social norms.
But some users may lose the power to self-regulate, perhaps through a
process of operant conditioning (cf. LaRose et al., 2003) to
self-reactive outcomes, and in extreme cases they might develop a media
dependency. SCT provides a framework for integrating uses and
gratifications mechanisms with these competing influences on individual
media attendance.
Table 1
Confirmatory Factor Analysis and Scale Results
Scale/Item Mean S.D. beta
Expected Outcomes:
Activity Outcomes [chi square] = 7.9,
df = 2, [alpha] = .79 4.55 1.40
Cheer myself up 4.10 1.70 1.00
Play a game I like 4.30 2.09 .98
Feel entertained 5.12 1.48 .77
Hear music I like 4.67 1.82 .75
Monetary Outcomes [chi square] = .1,
df = 1, [alpha] = .73 4.53 1.28
Find bargains on products and services 4.88 1.64 1.00
Save time shopping 4.51 1.96 .73
Get free information that would
otherwise cost me money 5.17 1.52 .47
Get products for free 3.55 1.71 .41
Novel Outcomes [chi square] = .5,
df = 2, [alpha] = .73 5.54 1.00
Get immediate knowledge of big news events 5.78 1.49 1.00
Find a wealth of information 5.98 1.11 .99
Find new interactive features 4.51 1.60 .84
Obtain information that I can't
find elsewhere 5.89 1.14 .62
Social Outcomes [chi square] = 2.9,
df = 2, [alpha] = .89 3.75 1.60
Get support from others 3.69 1.79 1.00
Find something to talk about 3.93 1.86 .96
Feel like I belong to a group 3.36 1.75 .95
Maintain a relationship I value 4.01 1.92 .72
Find others who respect my views 3.67 1.68 .76
Find people like me 3.96 1.57 .61
Provide help to others 4.57 1.69 .64
Self Reactive Outcomes [chi square] = 3.9,
df = 4, [alpha] = .79 4.34 1.21
Relieve boredom 4.64 1.87 1.00
Find a way to pass the time 5.22 1.58 .83
Feel less lonely 3.39 1.68 .52
Forget my problems 3.50 1.68 .50
Feel relaxed 4.98 1.29 .34
Status Outcomes [chi square] = 5.3,
df = 4, [alpha] = .77 4.32 1.17
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