Changes in sexual risk behavior among participants in a PrEP HIV prevention trial
One of the concerns raised regarding the introduction of any new HIV-prevention measure, such as PrEP, is the potential for risk disinhibition or sexual risk compensation. The oral tenofovir HIV prevention trial has been the subject of international discussion in this regard. This article maps the changes in sexual risk behavior among women participating in the oral tenofovir HIV prevention trial in Ghana. Content-driven, thematic analysis was carried out on qualitative data obtained from in-depth interviews with study participants. Growth curve analysis was the primary method used to document trends over time in self-reported sexual behavior collected monthly. Overall, the study found that sexual risk behavior did not increase during the trial. Number of sexual partners and rate of unprotected sex acts decreased across the 12-month period of study enrollment. Certain subgroups of women, however, exhibited different growth curves. Data indicate that the HIV prevention counseling associated with the trial was effective. Counseling during the trial was effective. Different types of counseling and messaging may be needed for different subgroups within a population. These findings also have implications for required sample sizes for future HIV prevention trials where seroconversion is the main outcome.
Changes in Sexual Risk Behavior Among Participants in a PrEP
HIV Prevention Trial
GREG GUEST, PHD,* DOMINICK SHATTUCK, MS,* LAURA JOHNSON, MA,* BETTY AKUMATEY, MPHIL,‡
EDITH ESSIE KEKAWO CLARKE, MD,§ PAI-LIEN CHEN, P
HD,† AND KATHLEEN M. MACQUEEN, PHD*
Background: One of the concerns raised regarding the introduction
of any new HIV-prevention measure, such as PrEP, is the potential for
risk disinhibition or sexual risk compensation. The oral tenofovir HIV
prevention trial has been the subject of international discussion in this
Methods: This article maps the changes in sexual risk behavior
among women participating in the oral tenofovir HIV prevention trial
in Ghana. Content-driven, thematic analysis was carried out on qual-
itative data obtained from in-depth interviews with study participants.
Growth curve analysis was the primary method used to document
trends over time in self-reported sexual behavior collected monthly.
Results: Overall, the study found that sexual risk behavior did not
increase during the trial. Number of sexual partners and rate of
unprotected sex acts decreased across the 12-month period of study
enrollment. Certain subgroups of women, however, exhibited different
growth curves. Data indicate that the HIV prevention counseling
associated with the trial was effective.
Conclusions: Counseling during the trial was effective. Different
types of counseling and messaging may be needed for different sub-
groups within a population. These ﬁndings also have implications for
required sample sizes for future HIV prevention trials where serocon-
version is the main outcome.
ONE OF THE CONCERNS raised regarding the introduction of any
new human immunodeﬁciency virus (HIV)-prevention measure is the
potential for risk disinhibition or sexual risk compensation.
Concerns center around the possibility that the availability of a
partially effective prevention technology will foster an overly
optimistic sense of protection among users and lead to increases in
other forms of risk behavior. This issue has been raised regarding
various HIV prevention efforts, including vaccines,
and vaginal microbicides.
Concerns over risk disinhibition are partially grounded in past
HIV and sexually transmitted infection-prevention studies. Wong
documented a decrease in condom use among Cameroonian
women participating in a clinical trial on the effectiveness of
nonoxynol-9 and results from hepatitis-B vaccine efﬁcacy trials in
the US indicated that placebo recipients were more likely to
become infected with hepatitis B after their ﬁnal injection.
studies point to the potential for risk disinhibition. However, risk
reduction counseling in HIV-prevention trials has also been shown
to be effective and have a positive effect on reducing sexual
risk. Bartholow and colleagues showed a general decline in HIV
risk behavior among gay male participants in an HIV vaccine
a ﬁnding corroborated qualitatively by Guest et
These ﬁndings are, at least partially, consistent with other
clinical studies in which HIV/STI risk behavior declined sig-
niﬁcantly from baseline.
The oral tenofovir, PrEP, HIV-prevention trial, in particular, has
stimulated much international discussion.
Media from various
countries reported concerns that the trials lacked adequate HIV
prevention counseling for participants and that sexual risk behav-
ior would increase as a result of trial participation.
argued that the tenofovir disoproxil fumarate (TDF) trial partici-
pants—who were primarily sex workers—would feel protected
and use condoms less often, or have sex with more clients.
This article directly addresses these concerns and presents sexual
behavior data from the Tenofovir HIV prevention trial in Ghana.
Materials and Methods
The oral tenofovir trial was a randomized, double-blind,
placebo-controlled study conducted between June 2004 and
March 2006 in Tema, Ghana; Douala, Cameroon; and Ibadan,
The data presented here are from the Ghana site only, due
to premature study closures in the other sites.
The Ghanaian portion
of the study was approved by the Ghana Health Service Ethical
Review Committee, Accra, Ghana and the Protection of Human
Subjects Committee, Family Health International, USA.
The trials were designed to test the safety and efﬁcacy for
prevention of HIV acquisition of a 300 mg daily oral dose of TDF.
At the Ghana site 400 women were enrolled into the trial over a 6
month period and data from 361 participants were analyzed. Eli-
gibility criteria for the study included being HIV-antibody nega-
tive, 18- to 35-years old, not being pregnant or breastfeeding, not
desiring pregnancy during 12 months of study participation, and
having an average of 3 or more coital acts per week and 4 or more
sexual partners per month. All participants completed written
informed consent at enrollment.
The contents of this publication do not necessarily reﬂect the views or
policies of or imply endorsement by the ﬁnancial supporter.
Supported by the Bill and Melinda Gates Foundation (Oral Tenofovir for
HIV Prevention, grant 19789).
Correspondence: Greg Guest, PhD, Family Health International, PO Box
13950, Research Triangle Park, NC 27709. E-mail: email@example.com.
Received for publication August 22, 2007 and accepted May 25, 2008.
From the Divisions of *Behavioral and Biomedical Research,
and †Biostatistics, Family Health International, North Carolina;
‡Department of Sociology, University of Ghana, Legon;
and §Ghana Health Service, Ministry of Health, Ghana
Sexually Transmitted Diseases, December 2008, Vol. 35, No. 12, p.1002–1008
Copyright © 2008, American Sexually Transmitted Diseases Association
All rights reserved.
Women were recruited from the port city of Tema using out-
reach workers. They were tested for HIV at their screening visit,
their enrollment visit, and each subsequent monthly visit. They
also received pre–post-test and HIV prevention counseling at all of
Eligible women were randomized into 1 of 2 arms—placebo pill
or TDF pill—and were counseled to take 1 pill every day. All
participants received HIV risk-reduction counseling, male con-
doms, and treatment for STIs at monthly clinic visits. Women were
counseled at each visit to use male condoms to prevent pregnancy,
HIV, and STIs. At each monthly follow-up visit, participants also
received free male condoms.
All participants were administered a structured questionnaire at
enrollment and at each of the monthly visits. The primary 2 risk
outcomes from this questionnaire that were used for this analysis
were the number of different male sexual partners they had in the
past 30 days and the proportion of unprotected coital acts in the
past 7 days. The proportion of unprotected coital acts variable was
calculated by dividing the participants’ numeric responses for 1
item (In the last 7 days, how many times did you have vaginal
sex?) by a second item (In the last 7 days, how many times did you
use a condom for vaginal sex?). The value derived from this
procedure was subtracted from 1.0. A subsample of women were
also asked, in separate in-depth interviews, open-ended questions
(after their 6-month visit) about changes in sexual behavior.
Of the 361 participants, 151 (42%) completed all twelve follow
up visits. To account for potential biases from loss to follow-up we
conducted an attrition analysis, comparing baseline risk indicators
between women who completed varying numbers of follow up
visits. We compared women who discontinued the trial before their
fourth visit (n ⫽ 48) with those who completed 4 or more visits
(n ⫽ 313). We also compared participants who discontinued
before their seventh visit (n ⫽ 82), and those who completed 7 or
more visits (n ⫽ 279). Finally, we compared women who com-
pleted all 12 visits (n ⫽ 151) with those who completed less than
12 visits (n ⫽ 210). Using Chi-square and t tests, we compared
these groups on 4 risk indicators reported at the screening visit:
history of an sexually transmitted disease, condom use at last sex,
number of different sexual partners in the past 30 days, and the
condom use ratio in the past 30 days.
To measure participants’ sexual behavior over time, we ﬁrst
conducted an exploratory analysis using pairwise tests to examine
whether signiﬁcant differences existed between any 2 time points.
We then performed growth curve analyses (GCA)
by a 2-step
analysis procedure to estimate the trend of each outcome variable
(number of partners and proportion of unprotected sex acts) over
time adjusted with participants’ characteristics.
GCA models were ﬁrst used to examine each of the baseline
covariates and time data (visit) to test whether demographic char-
acteristics inﬂuenced change for either outcome. Demographic
variables included age, education, previous STI diagnosis, previ-
ous pregnancy, presently living with partner, condom use during
last coital act, previous contraceptive use, and previous practice of
anal sex and previous practice of oral sex. Any variable that had a
P-value of less than 0.1 was included as a covariate to control for
that effect in the later multivariable linear and curvilinear GCA.
A series of random effects models were evaluated to assess
changes in each risk behavior over time, at both individual and
aggregate levels. Each model contained time and 1 of the covari-
ates identiﬁed as signiﬁcant in the bivariate analysis. The multi-
TABLE 1. Baseline Demographic Characteristics of Participants in the Oral Tenofovir HIV-Prevention Trial (n ⫽ 361)
Number of Men in One Month Proportion of Unprotected Sex
Extreme Quartile Remaining 75% Extreme Quartile Remaining 75%
18–23 194 (53.7%) 43 (55.8%) 151 (53.2%) 47 (60.3%) 147 (51.9%)
24–34 167 (46.3%) 34 (44.2%) 133 (46.8%) 31 (39.7%) 136 (48.1%)
0–8 y 182 (50.4%) 42 (54.5%) 140 (49.3%) 34 (43.6%) 148 (52.3%)
⬎9 y 179 (49.6%) 35 (45.5%) 144 (50.7%) 44 (56.4%) 135 (47.7%)
Previously diagnosed with STI
Yes 158 (43.8%) 37 (48.1%) 121 (42.6%) 32 (41%) 126 (44.5%)
No 203 (56.2%) 40 (51.9%) 163 (57.4%) 46 (59%) 157 (55.5%)
Yes 258 (71.5%) 59 (76.6%) 199 (70.1%) 64 (82.1%) 89 (31.4%)
No 103 (28.3%) 18 (23.4%) 85 (29.9%) 14 (17.9%) 194 (68.6%)
Presently living with partner
Yes 35 (9.7%) 5 (6.5%) 30 (10.6%) 10 (12.8%) 258 (91.2%)
No 326 (90.3%) 72 (93.5%) 254 (89.4%) 68 (87.2%) 25 (8.8%)
Condom use during last sex
Yes 147 (40.7%) 32 (41.6%) 115 (40.5%) 19 (24.4%) 128 (45.2%)
No 214 (59.3%) 45 (58.4%) 169 (59.5%) 59 (75.6%) 155 (54.8%)
Previous contraceptive use
Yes 160 (44.3%) 40 (51.9%) 120 (42.3%) 31 (39.7%) 129 (54.4%)
No 201 (55.7%) 37 (48.1%) 164 (57.7%) 47 (60.3%) 154 (45.6%)
Previously practiced anal sex
Yes 64 (17.7%) 7 (9.1%) 57 (20.1%) 11 (14.1%) 53 (18.7%)
No 297 (82.3%) 70 (90.9%) 227 (79.9%) 67 (85.9%) 230 (81.3%)
Previously practiced oral sex
Yes 148 (41%) 29 (37.7%) 119 (41.9%) 37 (47.4%) 111 (39.2%)
No 213 (59%) 48 (62.3%) 165 (58.1%) 41 (52.6%) 172 (60.8%)
No. 12 1003CHANGES IN SEXUAL RISK BEHAVIOR
variable analysis also included all 2-fold interactions with time. A
ﬁnal model containing all main effects that entered into the mul-
tivariable model plus any signiﬁcant interaction terms was ﬁt to the
data. Owing to the high degree of variability between the respon-
dents’ reported number of sexual partners and unprotected acts, we
further categorized study participants into 2 groups: an extreme
quartile, exemplifying the riskiest and most variable behavior
(across visits), and the remaining 75% for each outcome variable.
A sensitivity analysis was then carried out to examine whether
either group was driving the observed change.
In addition to reporting P-values from the ﬁnal multivariable
model for each outcome, pairwise tests of all time-points were
evaluated as well, to determine whether signiﬁcant differences
existed between any 2 time points. All testing was 2-sided and all
P-values ⬍0.05 were considered signiﬁcant. Statistical analyses
were carried out in SAS v9.1, using Proc GLIMMIX.
For the qualitative component, a sample of 24 women was
systematically selected from the entire clinical trial population. For
each of the 6 enrollment months, 6 women were randomly selected
from the pool of clinical trial participants for each month. For each
of these groups, outreach workers recruited 4 of the 6 possible
participants based on their availability. A total of 26 women were
approached and 2 refused. Qualitative interviewers were not asso-
ciated with the clinical trial.
A semistructured open-ended instrument was used to interview
participants. All interviews were recorded on audio tapes, trans-
lated into English, and transcribed verbatim by ﬁeld staff in
accordance with a transcription protocol.
development followed a standardized process.
As per this itera-
tive process, themes were identiﬁed from the transcript content by
2 researchers who reached agreement on the deﬁnition of each
theme. Code (theme) frequencies were generated in AnSWR.
this analysis, theme frequencies were generated only for themes
that emerged in response to 2 open-ended questions and subse-
1. Has participating in the TDF study affected your condom
use? If so, please explain.
How do you feel about these changes?
What do you think are the reasons for these changes?
2. Has participating in the TDF study affected the number of
sexual partners you have?
How do you feel about these changes?
What do you think are the reasons for these changes?
The demographic characteristics of the clinical trial participants
at enrollment are presented below in Table 1. The mean age and
level of education for participants was 23.7 and 7.1 year, respec-
tively. For our analysis, age and education were dichotomized
based on their medians.
A small percentage of women (9.7%) reported living with a
partner at enrollment. Less than 45% of the women reported
previous use of contraceptives (including condoms), or using con-
doms during their last sexual act. More than 70% of participants
had been pregnant previously and about 44% reported ever having
been diagnosed with an STI. Close to half of the sample (41%)
Number of Men Past 30 Days
Fig. 1. Number of male partners per month during trial.
1004 Sexually Transmitted Diseases
December 2008GUEST ET AL.
reported ever performing oral sex on humans. Far fewer (17.7%)
reported ever having practiced anal sex.
Comparisons were done between groups of women who discon-
tinued the clinical trial at different points in time. The only
signiﬁcant difference between the groups outlined above was
found in the condom use ratio. Women who completed all 12 visits
had signiﬁcantly higher rates of condom use at screening. All other
comparisons generated nonsigniﬁcant ﬁndings, suggesting that no
systematic bias resulted from loss-to-follow-up during the clinical
Number of Sexual Partners
The overall trend of change in number of partners over time
(Fig. 1) was a curvilinear (quadratic) trend. Controlling for age,
previous contraceptive use, and previous pregnancy (variables
found to be signiﬁcant bivariate predictors) we tested nonsigniﬁ-
cant general linear (P ⫽ 0.14) and curvilinear (P ⫽ 0.94) changes
Chi-squared and t tests indicated that women whose mean
scores and individual standard deviations for the overall number of
partners placed them in the riskiest quartile (n ⫽ 78) reported
engaging in less anal sex than the remaining 75% (P ⬍0.05; Table
2). Trend lines were plotted and reviewed for the 2 subgroups and
reﬂected dissimilar trends (Fig. 1). The extreme group had sub-
stantially higher overall averages than the remaining 75%. Testing
this relationship using GCA, we found a statistically signiﬁcant
difference in the change of these 2 groups. The extreme group
decreased their number of partners when compared with the re-
maining 75% (P ⬍0.01). Separate adjusted linear and curvilinear
GCA models were then tested for each subgroup. In these 2
separate subanalyses neither the trend for the extreme quartile nor
for the remaining 75% revealed a signiﬁcant change in the number
of men per month. These results suggest that the statistical signif-
icance found in the overall group was driven by the juxtaposition
of these 2 groups.
Despite slight increases in the reported rate of unprotected sex
acts at visits 2, 3, and 5, the general trend across all visits revealed
Percentage of Unprotected Sex Acts
Fig. 2. Rate of unprotected sex during trial.
TABLE 2. Sexual Behavior Change During the Trial: Most
Frequently Expressed Themes from In-depth Interviews (n ⫽ 24)*
Increased condom use 18 75.0
Trial counseling affected sexual
No more sex without condoms 13 54.2
Had more sexual partners 12 50.0
Had fewer sexual partners 7 29.2
Increased access to condoms 6 25.0
No change in behavior 4 16.7
Learned how to use condoms 4 16.7
Can negotiate condom use
*Frequencies refer to the number of unique respondents, out of a
possible 24, who expressed a given theme in the context of ques-
tions that asked speciﬁcally about changes in behavior and possible
reasons for any changes mentioned.
No. 12 1005CHANGES IN SEXUAL RISK BEHAVIOR
that participants reported decreases in unprotected sex as the study
continued (Fig. 2). Unadjusted pairwise analysis showed no sig-
niﬁcant differences between any 2 consecutive visit points. How-
ever, in the pairwise comparisons from baseline to follow-up,
visits 4 and 6 to 12 all showed signiﬁcantly lower rates of unpro-
tected sex [visit 4 (P ⫽ 0.04), 6 (P ⫽ 0.04), 7 (P ⬍0.01), 8 (P
⬍0.01), 9 (P ⫽ 0.02), 10 (P ⬍0.01), 11 (P ⬍0.01), and 12 (P
⬍0.01)]. Reported increases in unprotected sex at visits 2, 3, and
5 were not statistically different from baseline. Controlling for
condom use at last sex and previous pregnancy, GCA revealed a
nonsigniﬁcant linear change (P ⫽ 0.16) and a nonsigniﬁcant
quadratic trend over time (P ⫽ 0.98).
In our subgroup analysis for this variable, an unadjusted GCA
curvilinear comparison between the riskiest quartile (n ⫽ 78) and the
remaining 75% (n ⫽ 283) revealed higher rates of reported condom
use by the riskier quartile across the duration of the study. Women in
the riskier quartile were also less likely to have been pregnant before
enrolling (P ⬍0.05), and more likely to report having used a condom
during their last sexual encounter at screening (P ⬍0.01).
For women in the riskier quartile the rate of unprotected acts
decreased from 22.2% to 10.5%, a highly signiﬁcant curvilinear
change (P ⬍ 0.001). In the remaining 75%, the mean change in
unprotected sex decreased less dramatically from the baseline rate
of 3.7% to the ﬁnal rate of 1.5%, a signiﬁcant linear change over
time (P ⬍0.001). When tested, we found that the rates of change
were signiﬁcantly different for the 2 groups of women (P ⬍0.001).
The extreme group exhibited a greater decrease in unprotected
acts. This could reﬂect a regression towards the mean, but given
that all groups showed similar overall trends, we cannot assume
that convergence over a longer period of time would occur.
Table 2 presents the frequencies for the most common content-
driven themes related to changes in sexual behavior. From this
table and the larger thematic analysis that was conducted, we
developed a provisional model of the effect of counseling on HIV
risk behavior. This model is presented in the narrative below.
Verbatim quotes from in-depth interview participants are provided
in Table 3 for each of the postulated causal pathways described in
the narrative. Note that the model represents the maximum vari-
ability of potential pathways within the qualitative data (i.e., in
TABLE 3. Effect of Counseling on HIV Risk Behavior: Causal Pathways and Illustrative Quotes
Pathway Illustrative Quote
#1. Knowledge of HIV-negative
status provided motivation for
Whenever he 关a client兴 asked me to have sex without a condom, I did it because of money,
but after I enrolled, I told him ‘No,’ I was not going to do it without a
condom...because I had done the test and I knew I was okay. – P#4
#2. Trial counseling increased HIV
awareness and knowledge
When I enrolled, they exposed a lot of things to me: the effects of the disease 关HIV兴 on the
affected person and his family . . . hence my decision to use condoms. – P#15
#3. Trial counseling led to an
increased perception of risk for
Because even though there was news about HIV everywhere, I didn’t really pay attention to
it; but since I enrolled, I listen carefully...andbecause of the way you people do the
counseling, I have now realized that the disease is real. – P#23
#4. Trial counseling increased
reported condom use
Before I enrolled I wasn’t using condom, but after having gone through counseling I always
use condom. – P#23
#5. Access to condoms increased
due to trial participation
When I go out I don’t think of how to get condoms because I always have some ...Ijust
ﬁll my bag with it. It is good I joined this study of which I get as much condoms as I
want for my outing. – P#16
#6. Trial-supplied condoms
perceived to be of higher quality
than condoms on the market
If the condoms were not made available to us, we would be purchasing them from the
drug store and those ones are of poor quality, unlike the ones we collect from this place
关trial clinic兴, which are of a better quality. – P#7
#7. Study participation (counseling)
improved condom self-efﬁcacy
Before I joined the study, I was reluctant to use condoms…because any time I used it, it
burst, but I was taught how to wear it and ever since I have not had the problem of
bursting again. – P#5
#8. Counseling resulted in a
decrease in number of sexual
Because of the education we receive here, the number 关of partners兴 has decreased a little. – P#7
#9. Increased risk perception of HIV
reduced number of sexual partners
Int: What do you attribute the reduction in the number of partners?
P: I am scared of the disease that’s why there are fewer of them now. – P#10
#10. Knowledge of HIV-negative
status decreased number of
Whenever he 关a client兴 asked me to have sex without a condom, I did it because of money,
but after I enrolled, I told him ‘No,’ I was not going to do it without a
condom...because I had done the test and I knew I was okay, so he left me for a long
time. – P#4
#11. Knowledge of HIV-negative
status increased number of
Whenever a man visited me...Igave them the books they 关study staff兴 gave to me . . . so
that made them love me the more because they themselves were afraid of their
status...sowhen they got to know that I have done the test, and had passed,
automatically they felt secure. There are some who just come to visit me, but after they
read the books and know that I am clean, they decide to do business with me. – P#4
#12. Condom insistence facilitated an
increase in number of sexual
Int: Why has it 关the number of partners兴 increased?
P: Because they 关clients兴 also like the condom I use so they always prefer the person who
insists on condom use to the person who wants to have sex raw. – P21
#13. Perceived protection from
condom use facilitated increase
in number of partners
关number of partners has increased兴 . . . because of the condom, I am not afraid, I can have
sex with as many men as I want. – P12
#14. Increased condom use
decreased number of sexual
I used to have a lot of sexual partners but ever since I joined the study and started using
condoms the number of my sexual partners has reduced because most of them don’t
want to use condoms. When I ask them to use condom, they turn away. – P#18
1006 Sexually Transmitted Diseases
December 2008GUEST ET AL.
some cases only 1 participant expressed a given pathway). The
number of participants exemplifying an individual pathway varied
The counseling provided during the trial was perceived by the
majority of participants to affect their risk behavior in a positive
(protective) direction (Table 2). For some women, getting tested
for HIV in the trial and ﬁnding out they were HIV-negative (a
requirement of the study) gave them added motivation to use
condoms (path #1, Table 3). In a similar fashion, counseling made
some participants more health conscious in general, increasing
their knowledge and awareness of HIV/AIDS (#2). Related to the
above, the counseling also increased participants’ risk perception
of contracting HIV (#3).
The trial counseling was perceived by the majority of partici-
pants to increase their condom use (e.g., #2, #4). More speciﬁcally,
the counseling gave women greater access (free and unlimited
supply) to condoms (#5) that participants, and in some cases their
clients, perceived to be of higher quality than other condoms (#6).
Women also learned how to better negotiate condom use with
clients and how to use condoms properly, thereby improving their
condom self-efﬁcacy (#7).
The most common theme expressed in the text analyzed was
increased condom use (Table 2). In sum, women reported that know-
ing their HIV-negative status, combined with increased knowledge
and risk perception regarding HIV, made them more likely to use
condoms with clients and (in a few cases) regular partners. Better condom
efﬁcacy (i.e., better knowledge and skills for effectively using condoms)
and greater access to condoms also increased condom use.
Counseling also had an effect on the number of sexual partners
women had. Some participants suggested that the education from
the counseling and enhanced HIV risk perception led to a decrease
in the number of partners (#8, #9, respectively). Even the simple
knowledge of an HIV-negative status could indirectly result in a
reduction in the number of sexual partners (#10). Trial participa-
tion, however, could also facilitate an increase in number of sexual
partners. In a few cases, women reported that having a conﬁrmed
HIV-negative status (and being associated with the trial in general)
made them more attractive to their male clients who perceived them
to be disease-free (#11). Some women capitalized on this situation
and reported an increase in their number of sexual partners.
Number of sexual partners was also inﬂuenced in both direc-
tions by the reported increase in condom use. In some instances,
women reported that clients perceived a woman who insists on
condom use as safer, and therefore, more desirable (#12). In other
situations, women took on more clients because they themselves
felt a sense of protection afforded by the condom (#13). Some
women took advantage of this perception of enhanced desirability
and accepted more partners. Conversely, some clients simply did
not want to use condoms, resulting in an overall reduction in
number of partners for some women (#14).
One of the main conclusions that can be drawn from our study
is that, overall, being in an HIV prevention study does not neces-
sarily lead to risk disinhibition. In fact, in the TDF study risk
behavior, on average, decreased over the course of the trial. These
ﬁndings are congruent with other studies showing similar re-
duction of risk in clinical trials.
Results further conﬁrm that
consistent counseling and associated condom provision can be
effective risk reduction strategies and, in this trial, were likely the
main reason behind the largely positive behavioral changes observed.
Participants clearly ascribed their changes in behavior to various
aspects of the counseling provided throughout the trial.
These ﬁndings have implications for required sample sizes for
future HIV prevention trials where seroconversion is the main
outcome. Indeed, the HIV incidence for the TDF study in Ghana
was much lower than predicted (based on existing epidemiologic
data), and, combined with the closure of the other 2 study sites,
rendered the efﬁcacy data statistically inconclusive.
questions about how and where future effectiveness trials should
be conducted for PrEP, vaccines, and vaginal microbicides. The
notion that HIV prevention trials can be conducted more efﬁciently
in high incidence populations needs to be reconsidered in a more
nuanced way. For example, if high incidence is reﬂective of
individual-level factors such as condom skills and condom access
then participation in a prevention trial is likely to have a signiﬁcant
impact on incidence. Alternatively, if high incidence is reﬂective
of structural barriers to risk reduction, such as gender power
dynamics and economic vulnerability, then trial participation will
probably have less of a direct effect.
Results from the growth curve analysis showed signiﬁcant dif-
ferences between women in the riskiest quartile and the remaining
75% of the trial participants in terms of changes in risk behavior
across the trial. Our subanalysis also showed that although the
“risky” group of women had more sexual partners they were less
likely to engage in other types of risk behavior such as anal sex.
They also tended to use condoms more often, suggesting they were
engaging in risk management based on the context of the sexual
activity. These ﬁndings, and the fact that not all risk behaviors cluster
together, warrant further investigation, as they have implications for
how counseling or other interventions are developed. The data suggest
that a one-size-ﬁts-all model of prevention messaging and delivery
may not be the most effective for this population.
The other implication of the ﬁndings presented is that counseling
may have a differential effect on groups with unique risk proﬁles.
More research is needed to better understand these differences and to
describe the intricate relationship between counseling, risk perception,
individual characteristics, and risk behavior, both within and outside
of the clinical trial context.
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