among beta testers ( 14.172%) than
among regular users ( 9.539%).
Computer Self-Efficacy
and Privacy Perception
We assessed users’ computer self-efficacy and privacy perceptions through
dedicated questions in an optional
questionnaire, covering installation-related actions like displaying the target installation folder.
Each ESET software installation included an option for changing installation folder. Beta testers and regular users
thus had to click on the “change installation folder” link on one of the screens
during the installation process to go to
the respective screen. This action was
also the only way a user could see the default installation folder, not otherwise
displayed. Only a few participants did
this, with beta testers visiting the screen
more than twice as often as regular users, with 1.1% of regular users and 2.6%
of beta testers. This difference was statistically significant, though the effect
size was negligible, with χ2( 1) = 1215.180,
ϕc = 0.046, p < 0.001, and N = 576,170.
Computer self-efficacy and digital
skills. We included two questions to
help us assess users’ digital skills:
Do you consider yourself a skilled
computer user? Likert scale from 1
(not at all skilled) to 6 (extremely
skilled); and
Regarding this computer, are you an
IT technician? Y/N. Participating beta
testers were more often IT technicians,
with χ2( 1) = 285.988, ϕc = 0.110, p < 0.001,
and N = 23,607, judging themselves
more skilled than regular users, at
Mbeta = 4. 46, SD = 1.313; Mstandard = 4. 18;
SD = 1.473; t-test ( 22,631) = − 11.743;
p < 0.001; d = 0.200; and N = 22,633.
Privacy perceptions. The last part of
the questionnaire asked about how private data is stored in users’ computers,
how sensitive users are regarding their
privacy, and users’ beliefs about the
computer being generally a safe device.
We measured all items on a six-point
Likert scale ranging from 1 (not at all)
to 6 (extremely private/sensitive/safe)
by asking:
˲ Do you consider the data in this
computer private?;
˲ In general, are you sensitive about
your privacy?; and
˲ In general, do you consider com-
puters to be safe devices against
online attacks (such as viruses, hack-
ing, and phishing)?
Beta testers and regular users alike
reported the same average level of
private data in their computers, with
Mbeta = 4.678, SD = 1.419; Mstandard = 4.690,
SD = 1.560; t-test ( 24,323) = 0.504;
p = 0.614, and N = 24,325, and both quite
similar in being privacy sensitive, with
Mbeta = 4.755, SD = 1.376; Mstandard = 4.809;
SD = 1.492; t-test ( 23 976) = 2.272; p < 0.05;
d = 0.037, N = 23,978. We found only
one small difference in their evaluations
of general computer safety: Beta testers
considered computers slightly safer
than did regular users, with (Mbeta = 4.098,
SD = 1.712; Mstandard = 3.902; SD = 1.819;
t-test ( 23 832) = − 6.784; p < 0.001; d = 0.111,
N = 23,834). We observed that beta testers
consider themselves more skilled as IT
users and the computer as a safer device than do regular users. This might
suggest they were aware of security
risks associated with computer use
and felt capable of addressing them.
Study Limitations
Some limitations beyond our control
could have influenced these results.
Despite our careful cleaning process,
we could not be completely sure that
each record corresponded to a unique
participant/device. For example, the
OS version was based on the Windows
system variable “current version” that
did not differentiate end user and server products. However, we assumed the
number of servers in the study was negligible, as the installed base of ESET
systems was, at the time, designed
for end-user devices. We also lacked
details of participants’ devices, technological measures that might have
shown more nuanced configuration
discrepancies.
The relatively small ratio of users
completing the questionnaire could
also have represented other limita-
tions. First, self-selection and non-re-
sponse bias might have skewed our re-
sults. For example, most study
participants reported at least some col-
lege education and could have thus
been expected to be able to recognize
the value of user feedback better and
be more willing to complete a product-
related questionnaire. However, they
did not differ in terms of hardware or
software from those skipping the ques-
tionnaire altogether. We had only a few
represented countries. Only Iran, India,
Egypt, and the U.S. were represented in
both subsamples.
ESET has subsequently begun to investigate these issues with respect to
product localization and usability, where
country differences likely play a role.
Gender and age. Figure 4 includes
basic information regarding demography. In both subsamples, males represented the vast majority of study participants, though there were more females
among regular users than among beta
testers, with χ2( 1) = 277.493, ϕc = 0.099,
p < 0.001, and N = 28,328.
Regular users were on average older
than beta testers, with Mbeta = 32. 96,
SD = 12.974; Mstandard = 35. 74, SD = 16.327;
t-test ( 25 938) = 11.108; p < 0.001; d = 0.195,
and N = 28,940. Due to the wide range
of ages among study participants— 11
to 80—we categorized all ages into seven groups to analyze the differences in
more informative ways, as in Figure 4.
For example, there were significantly
more beta testers than regular users
ages 21 and 50, while the opposite applied to other categories, with χ2( 6) =
366.286, ϕc = 0.119, p < 0.001.
Education. Education attainment
reflected a consistent pattern in both
subsamples, with college being represented most and primary school least.
The pattern was consistent even when
we omitted the youngest users, or those
who could not have yet reached higher
education. Beta testers were more represented in secondary education than
regular users, but the effect size was
small, with χ2( 6) = 237.085, ϕc = 0.038,
p < 0.001, and N = 26,354.
Other demographic insights. We
combined the demographic data of
study participants to determine how
well beta testers also represented
various demographic segments of
regular users. Combining seven categories of age, gender, and education
helped us identify 42 unique combinations. Only two were present in the
sample of regular users (none among
beta testers), both female, ages 71 to 80,
one with primary (Nstandard = 4), the other
with college education (Nstandard = 109).
Remaining combinations were present in both subsamples, with a fairly
similar distribution. The greatest difference we found was among males,
ages 31 to 40, with college education,
who were represented more often