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