Predictors of Chlamydia Trachomatis Testing: Perceived Norms, Susceptibility, Changes in Partner Status & Underestimation of Own Risk
BACKGROUND:
It
is hard to convince people to participate in chlamydia screening programs
outside the clinical setting. In two earlier studies (BMC Public Health.
2013;13:1091; J Med Internet Res. 2014;16(1):e24), we identified explicit and
implicit determinants of chlamydia screening behavior and attempted,
unsuccessfully, to improve participation rates by optimizing the recruitment
letter. In the present study, we examined the links between a number of
social-cognitive determinants (e.g., stereotypical beliefs about a person with
chlamydia, intentions, changes in partner status), and self-reported chlamydia
testing behavior six months after the initial study.
METHODS:
The
present study is a follow-up to our first study (T0). We assessed self-reported
testing behavior 6 months after the first measure by means of an online
questionnaire (T1; N = 269). Furthermore, at T1, we measured the
social-cognitive determinants in more detail, and explored the influence of
stereotypical beliefs and any changes in partner status during this six month
period.
RESULTS:
In total,
25 (9.1 %) of the participants tested for chlamydia at some point during
the six months between baseline (T0) and follow up (T1). Testing behavior was
influenced by testing intentions in combination with changes in risk behavior.
The higher the participants' own numbers of partners ever, the higher they
estimated the number of partners of the stereotypical person with chlamydia.
Testing intentions were most strongly predicted by perceived norms and
susceptibility, and having had multiple partners in the last 6 months
(R(2) = .41).
CONCLUSION:
The
most relevant determinants for testing intentions and behavior were
susceptibility, subjective norms and changes in partner status. We found a
systematic tendency for individuals to underestimate their own risk, especially
the risk of inconsistent condom use. Future research should focus on more
promising alternatives to population-based interventions, such as online interventions,
screening in primary care, the rescreening of positives, and clinic-based
interventions. This future research should also focus on making testing easier
and reducing barriers to testing, as well as using social and sexual networks
in order to reach more people.
Below: Logic Model of Predictors of Testing Intention and Behavior
- 1Department of Work & Social Psychology, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands. Gill.tenHoor@MaastrichtUniversity.nl.
- 2Department of Work & Social Psychology, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands. r.ruiter@maastrichtuniversity.nl.
- 3STI AIDS Netherlands, Keizersgracht 390, 1016GB, Amsterdam, The Netherlands. JvanBergen@soaaids.nl.
- 4Department of General Practice, AMC-University of Amsterdam, P.O. Box 19268, 1000GG, Amsterdam, Netherlands. JvanBergen@soaaids.nl.
- 5Department of Sexual Health, Infectious Disease and Environmental Health, Public Health Service South Limburg, P.O. Box 2022, 6160HA, Geleen, The Netherlands. Christian.Hoebe@ggdzl.nl.
- 6Department of Medical Microbiology, Maastricht University, P.O. Box 5800, 6202AZ, Maastricht, The Netherlands. Christian.Hoebe@ggdzl.nl.
- 7Department of Sexual Health, Infectious Disease and Environmental Health, Public Health Service South Limburg, P.O. Box 2022, 6160HA, Geleen, The Netherlands. Nicole.Dukers@ggdzl.nl.
- 8Department of Medical Microbiology, Maastricht University, P.O. Box 5800, 6202AZ, Maastricht, The Netherlands. Nicole.Dukers@ggdzl.nl.
- 9Department of Work & Social Psychology, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands. g.kok@maastrichtuniversity.nl.
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