RESEARCH METHOD COHEN ok

238 INTERNET-BASED RESEARCH AND COMPUTER USAGE
non-volunteers in an Internet survey is to contact
them by email (assuming that their email addresses
are known), e.g. a class of students, a group of
teachers. However, email addresses themselves do
not give the researcher any indication of the
sample characteristics (e.g. age, sex, nationality
etc).
Watt (1997) suggests that there are three types
of Internet sample:
an unrestricted sample: anyone can complete
the questionnaire, but it may have limited
representativeness
a screened sample: quotas are placed on the
subsample categories and types (e.g. gender,
income, job responsibility etc.)
a recruited sample: respondents complete a
preliminary classification questionnaire and
then, based on the data provided in them,
are recruited or not.
Response rate for an Internet survey is typically
lower than for a paper-based survey, as is the
rate of completion of the whole survey (Reips
2002a). Witmer et al. (1999:147)reportthatfor
a paper-based survey the response could be as
high as 50 per cent and as low as 20 per cent;
for an Internet survey it could be as low as 10
per cent or even lower. Dillman et al. (1998b)
report a study that found that 84 per cent of a
sample completed a particular paper-based survey,
while only 68 per cent of a sample completed
the same survey online. Solomon (2001) reported
that response rates to an Internet-based survey
are lower than for their equivalent mail surveys.
However, this issue is compounded because in an
Internet-based survey, there is no real knowledge
of the population or the sample, unless only specific
people have been approached (e.g. through email).
In the same study Witmer et al. foundthatshort
versions of an Internet-based questionnaire did not
produce a significantly higher response rate than
the long version (p. 155). Solomon (2001) suggests
that response rates can be improved through the
use of personalized email, follow-up reminders, the
use of simple formats and pre-notification of the
intent to survey.
Reips (2002a) provides some useful guidelines
for increasing response rates on an Internet
survey. He suggests that response rates can be
increased by utilizing the multiple site entry
technique, i.e. having several web sites and
postings on several discussion groups that link
potential participants or web surfers to the
web site containing the questionnaire. Reips
(2002a: 249) also suggests utilizing a ‘high hurdle’
technique, where ‘motivationally adverse factors
are announced or concentrated as close to the
beginning’ as possible, so that any potential
dropouts will self-select at the start rather than
during the data collection. A ‘high hurdle’
technique, he suggests, comprises:
Seriousness: inform the participants that the
research is serious and rigorous.
Personalization: ask for an email address or
contact details and personal information.
Impression of control: inform participants that
their identity is traceable.
Patience: loading time: use image files to reduce
loading time of Web pages.
Patience: long texts: place most of the text in the
first page, and successively reduce the amount
on each subsequent page.
Duration: inform participants how long the
survey will take.
Privacy: inform the participants that some
personal information will be sought.
Preconditions: indicate the requirements for
particular software.
Technical pretests: conduct tests of compatibility
of software.
Rewards: indicate that any rewards/incentives
are contingent on full completion of the survey.
Of course, some of these strategies could backfire
on the researcher (e.g. the disclosure of personal
and traceable details), but the principle here is
that it is better for the participant not to take part
in the first place rather than to drop out during the
process. Indeed Frick et al.(1999)foundthatearly
dropout was not increased by asking for personal
information at the beginning. In relation to online
experiments they found that ‘the tendency of leaving
the experiment when personal information is