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Am J Public Health. Author manuscript; available in PMC 2013 November 1.
Published in final edited form as:
PMCID: PMC3477958

Systematic Review and Meta-Analysis of Single-Session Behavioral Interventions to Prevent Sexually Transmitted Infections: Implications for Bundling Multiple STI/HIV Prevention Packages



Evidence based, single-session, behavioral interventions that can be used in public health settings are urgently needed for preventing the spread of HIV and other sexually transmitted infections (STI). Brief interventions are particularly promising given the relatively low burden they place on financially limited service providers.


To estimate the efficacy of single-session, behavioral interventions for STI prevention.

Data Sources

MEDLINE (PubMed), PsycINFO, CINAHL, ERIC, Proquest, all international sub-databases in the WHO's Global Health Library were searched through May 2011.

Study Selection

Data from 29 single-session interventions (20 studies; N = 52,465) with an STI outcome were coded and analyzed.


The odds of participants being infected with an STI in the intervention group were reduced by 35% (OR = .65, 95% CI=.55–.77) relative to control group participants. Interventions were compared to active controls and follow-up periods averaged 58 weeks. As such, single-session interventions lead to considerable benefit in terms of disease prevention and create minimal burden for both the patient and the provider.


Single-session interventions were most often implemented during routine health care services by clinic staff. Use of these procedures make these interventions a reasonable option for currently existing health care infrastructure. Brief and effective STI prevention interventions are a valuable tool for disease prevention and can be readily adapted to bolster the benefits of partially effective biomedical STI/HIV prevention technologies.


In order to deliver sexually transmitted infection (STI)/HIV prevention interventions during the course of routine clinical services, interventions must be succinct as well as effective. Interventions designed to reduce sexual risk behavior and STI/HIV have been tested in a variety of clinical and community settings. Although behavioral interventions have demonstrated significant reductions in risk behavior and have offered evidence for disease prevention, many consist of multiple steps and sessions,15 carry considerable patient burden, and require substantial resources.4 Of particular concern is the feasibility of implementing multiple-session behavioral interventions in conjunction with currently available health care services. These services continue to experience budget reductions which lead to staff shortages and limited means for retaining patients throughout the course of an extended intervention.6 Limited resources can render multiple-session interventions unusable or force service providers to substantially modify interventions.

In addition to the need for brief behavioral interventions in the public health sector, there is a growing demand for feasible behavioral interventions to use in combination with biomedical prevention technologies. To date, it is well recognized that no single prevention strategy including behavioral interventions, male circumcision, pre- and post-exposure prophylaxis, vaccines, and vaginal/anal microbicides will be completely effective in protecting against STI/HIV infection.714 Furthermore, the effectiveness of biomedical prevention technologies can be undermined by changes in risk behavior, such as risk compensation.15 Single-session, behavioral interventions can potentially add value to the protective effects of partially effective biomedical interventions. There is growing recognition of the need for bundling multiple partially effective prevention strategies to gain cumulative effects.16, 17 Behavioral risk-reduction interventions can play a critical role in comprehensive STI/HIV prevention packages, particularly when they are designed to fit within current health care services.18

We conducted a meta-analysis to examine the efficacy of single-session STI prevention interventions to determine if single-session, risk-reduction interventions achieve positive changes on disease outcomes. We focused on STI outcomes because they are clinically meaningful indicators of intervention efficacy. Moreover, we chose single-session interventions as they are most likely to be successfully implemented into existing services and meta-analyses have not, to date, focused on their effects. There are now sufficient numbers of trials with STI outcomes to determine whether single-session interventions can reduce incident disease relative to a standard-of-care. We also investigated moderators of STI outcomes to identify characteristics of single-session interventions that result in reduced incidences of disease. Finally, in a subset of studies that provided behavioral data related to sexual risk taking, we conducted an additional meta-analysis to determine if single-session interventions improve condom use.


We searched the following electronic databases (through May 2011): (a) MEDLINE (PubMed), PsycINFO, CINAHL, ERIC, Proquest, all international sub-databases in the WHO's Global Health Library (LILACS, SEARO, EMRO, WPRO, WHOLIS, and AFRO), (b) a database and document depository of STI/HIV-related interventions held by the Syntheses of HIV/AIDS Risk Reduction Project (SHARP), and (c) reference sections of obtained articles (databases included gray literature). No language or date restrictions were applied. We crossed the following key terms in our search: intervention, behavior, STI, STD, AIDS, HIV, brief, single session, one session, education, programme, and counseling. Search terms were truncated to increase sensitivity. Unpublished papers (e.g., dissertations) were included to avoid the file-drawer effect (i.e., stronger effects reported in published vs. unpublished studies).19 Studies were included in the sample if they satisfied the following criteria: (a) the intervention consisted of a single-session, (b) the study reported at least one STI outcome, (c) and the study reported a control arm (see Figure 1 for further details). Non-randomized controlled trials were included only when study designs were consistent with approaches set forth by Cochrane review procedures for non-randomized designs.20 Two independent reviewers conducted literature searches. Search results were compared and discrepancies were addressed. Next, three independent reviewers evaluated all literature results for determining inclusion. For this second step, the three independent reviewers overlapped search results and, again, any discrepancies between reviewers were addressed. We excluded interventions solely focused on standard HIV testing and counseling, as these interventions have been reviewed and analyzed. 21, 22 Search results yielded no studies focused exclusively on HIV positive persons.

Figure 1
Selection process for study inclusion.

We calculated individual effect sizes, odds ratio (OR), for STI. For this outcome, we used the most distal time point after the intervention- in some instances as long as two years- to serve as the index of STI acquisition. Therefore, we examined the most conservative data points. STI was established via medical records, STI surveillance, or self-report. Data for generating ORs were entered such that values below '1' indicated a reduction in STI for the intervention group relative to the control group. Consistent with meta-analytic convention, each intervention was treated as an individual study during analysis.23 Variables were created that represented either intervention or overall study characteristics in order to prevent double counting. Asymmetries suggestive of publication bias were analyzed through three different strategies: Trim and Fill, Begg's strategy, and Egger's test.2426 The analyses were conducted in Stata 11 with macros for meta-analysis.23, 27 Random-effects model with maximum likelihood variance estimation was used to obtain average STI effect size. Homogeneity (Q and I2) of the effect size was also examined.28 Sensitivity analyses were conducted to detect any possible outliers affecting the results. Study features were analyzed as possible effect modifiers. Moderator variables were entered into a series of weighted least squares bivariate regression models; fixed-effect assumptions were followed for moderator analyses.29 In a subset of studies that provided the behavioral data, we examined condom use as a secondary endpoint. For this analysis, we calculated individual effect sizes, i.e., standardized mean differences (d30), for condom use outcomes and used a random-effects model with maximum likelihood variance estimation. Most interventions reported only one STI and one condom use outcome; however, for studies reporting multiple outcomes, we calculated individual effect sizes and then averaged these calculations.


Two independent raters coded each study for sample characteristics and risks (e.g., ethnicity, gender, age), design and measurement specifics (e.g., length of session, methodological quality [adapted from31, see supplemental data], STI and behavioral outcomes), and format and content of control and intervention condition(s). Inter-rater reliability for categorical variables was calculated as Cohen’s kappa = .90.32 For continuous variables, we calculated the Spearman-Brown correlation value r = .98.33

In total, 52,465 participants from 29 single-session interventions (20 intervention trials3452) were included in the current review (Table 1). Demographic characteristics of participants varied across interventions, with 12 targeting females, 4 targeting males, and 13 targeting males and females. Studies included adolescents (k=6) and adults (k=23). Interventions included participants of varying races (k=18), while others focused specifically on African-Americans (k=8), Whites (k=1), Latinos (k=1), and Asians (k=1). For the total study sample, women comprised 37%, Whites 36%, African-Americans 29%, Hispanics 26%, Asians 1%, and other 8%. Average age was 29.5 years old. A majority of the studies were conducted in the US. The remainder of the studies were conducted in Mexico,49 Singapore,34 United Kingdom,41 Puerto Rico,46 and Malawi.52

Table 1
Single-session behavioral interventions with a STI outcome.

All trials provided biological outcomes; most trials reported an aggregate measure of multiple incident STI which included HIV (k=19). Other trials reported specifically on Neisseria gonorrhea, Chlamydia trachomatis, and/or Trichomoniasis (k=10). STI outcomes were gathered through medical records (k=23, chart-abstraction and lab results), disease surveillance systems (k=3), self-report (k=2), and a combination of medical records/surveillance (k=1). There were no asymmetries in effect sizes (Begg’s Test, z = .39, p = .68, Egger’s test, t = −2.31, p = .03). Trim-and-fill technique identified no added or omitted studies that were necessary to normalize the distribution and suggested no bias. Sensitivity analyses revealed no study variations significantly affecting results. Specifically, we conducted four additional sets of analyses to test the effects of each of the following studies on overall STI effect size: (1) the study with the largest N51, (2) the study with the largest effect size52, (3) studies with self-reported data35, 45, and (4) studies with non-randomized controlled designs34, 50, 52 (one employed a controlled cohort study design and two trials used a controlled before-and-after study design with attention to match). Overall, STI effect size remained significant even with the removal of these studies.

Summary of intervention characteristics

The reviewed interventions varied considerably in their design, session duration, and components. Although most of the intervention trials used two-arm randomized designs, some tested multiple interventions against control conditions. Intervention formats included one-on-one counseling conducted face-to-face, computer delivered counseling, small group workshops, and videotapes/DVDs. Single-session interventions ranged from 1540–25042 minutes in duration, averaging 79 minutes. The average length of time between intervention and follow-up was 58 weeks.

We coded session content using descriptions in the published articles as well as in manuals and session outlines when available. Common intervention components included didactic education, personalized feedback, communication skills building, safer sex discussions, eroticizing safer sex, activities to alter perceived social norms, and condom skills training using role-playing risk scenarios. Although most of the interventions integrated multiple active components, their brief duration typically required emphasizing a particular component as a major feature of the intervention. The most frequently used intervention elements were educational and skills building strategies. Twenty one interventions reported these components as major themes in the intervention.34, 3638, 4143, 47, 48, 51, 52 A smaller number of interventions (k=5)38, 44, 49, 50 employed motivational interviewing as their general framework. Trials often used a risk education counseling session as a control condition, although many trials compared the experimental intervention to treatment as usual.

Overall intervention effects on sexually transmitted infections

On the whole, interventions succeeded in reducing incidence of STI. The weighted mean risk reduction, expressed in OR metric, was .65 (95% CI: .55–.77; Table 1, Figure 2). The effect sizes exhibited heterogeneity (I2=70, 95%CI=59.42, 80.68, Q=99.99); however, there were no trials for which the control group exhibited a significant reduction in STI relative to the intervention group. Furthermore, 28 out of the 29 controls were considered active, meaning that control group participants received some form of risk reduction counseling. Thus, findings regarding disease related reductions resulting from single-session interventions occurred even in the context of incorporating relatively stringent controls.

Figure 2
Forest plot of STI incidence effect sizes ordered by magnitude expressed in OR metric.

Of particular note are the STI reduction outcomes observed among female sex workers in Mexico,49 adolescents in the northeastern US 42, 43, and STI patients in Malawi.52 These studies demonstrate feasibility under varying scenarios and risk groups. Moreover, Warner et al.51 -the study with the largest number of participants-found that a 23-minute video intervention reduced STI outcomes for intervention participants more so than for standard-care participants. This study demonstrates the efficacy of an intervention engendering minimal burden, yet resulting in clinically meaningful outcomes.

Moderating factors related to STI reduction efficacy

Analyses examined how various intervention components and sample characteristics may affect STI effect size results (Table 2). Interventions achieved greater efficacy when (a) conducted with non-White participants, (b) conducted with all African-American participants, (c) they were of longer duration, (d) they were evaluated at intervals nearer to the intervention, (e) compared to wait list and relevant content (versus standard-care) control groups, and (f) conducted at the individual and group level (versus media delivery). In no instances did the control group result in fewer incidences of STI than the intervention group. Finally, age, gender, risk group, publication year, methodological quality, and time matched intervention and control groups did not significantly moderate overall STI effect size.

Table 2
STI incidence effect sizes as a function of study characteristics.

Intervention effects on condom use outcomes

Overall, single-session behavioral interventions demonstrated a pattern of positive effects on sexual risk, including reductions in number of unprotected sex acts and increases in condom use (k = 20; Figure 3). Efficacy expressed in the d metric was .22 (95%CI=.06–.37, I2 =82, 95%CI=73.98–88.19, Q=108.38). This effect size can be interpreted as a small but significant effect of improved condom use among intervention group participants compared to control group participants. Heterogeneity was present; however, no study exhibited a significant reversal such that its treatment group had less condom use than the control. Most studies demonstrated reductions in sexual risk taking among intervention participants relative to controls (i.e. 38, 40, 4244, 48, 49, 52). Of the remaining studies, all reported sexual risk reduction at follow-ups at similar rates between groups; i.e., participants in all arms of the trials reported less sexual risk taking (i.e.,34, 35, 39, 41, 45). Although not included in the condom use meta-analysis, Neumann et al.,46 reported greater condom acquisition (redemption of study provided condom coupons at local stores) among intervention participants compared to control participants post intervention (p<.05).

Figure 3
Forest plot of condom use effect sizes ordered by magnitude expressed in d metric.


The current meta-analysis is the first to focus on single-session, behavioral interventions to reduce incidence of STI. Findings demonstrate that single-session interventions can have a substantial impact on clinically meaningful outcomes across a wide array of sample and intervention characteristics. The documented reduction in STI among intervention group participants rivals the effects observed among biomedical technologies for disease prevention.810, 53 Investing in single-session interventions and delivering them during routine health services is practical and efficient. Doing so offers potential cost savings when taking into consideration the expense of treating patients infected with STI. Reductions in STI are also consistent with improvements observed in condom use. This result suggests that interventions targeting reductions in sexual risk taking have an impact on clinically meaningful outcomes.

Additional findings warrant further investigation. We observed multiple moderators affecting the efficacy of the intervention on preventing STI. The strength of the interventions varied based on demographic information and suggested that interventions with ethnic minorities were most effective at reducing STI. In regards to long-term findings, we did observe a decline in efficacy as time between intervention and follow-up increased. The effects of behavioral and biomedical interventions generally require adherence to regimens or plans and are prone to dilute over time. It is possible that single-session interventions delivered during routine care would result in patients being exposed to their content repeatedly. This practice may in effect act as a booster and improve long-term efficacy.

Adapting single-session interventions for bundling multiple HIV prevention packages

Single-session interventions can help improve the issue of partial efficacy, risk compensation and non-adherence found in new and emerging biomedical HIV prevention technologies. Mathematical modeling studies consistently show that combinations of HIV prevention interventions are required to reverse HIV epidemics.54, 55 Models that evaluate HIV treatment for prevention demonstrate that even fairly small increases in transmission risk behaviors can reduce the protective benefits of lowered risk of transmission.55, 56 For example, it is now established that male circumcision reduces HIV transmission risks by as much as 55%,57 microbicides 39%,9 and pre-exposure prophylaxis 44%.8 It is possible that single-session interventions could boost the disease reduction observed for these biomedical forms of prevention. Furthermore, single-session interventions could also serve to mitigate the effects of risk compensation58 and product non-adherence.8, 9 In fact, non-adherence in pre-exposure prophylaxis HIV prevention trials has been documented as a critical factor affecting efficacy.10 In summary, single-session, behavioral interventions have established efficacy among at-risk populations, can directly address risk taking and can potentially increase the beneficial effects of biomedical HIV prevention technologies.

Single-session behavioral interventions versus multi-session behavioral interventions and biomedical prevention technologies

In order to establish a frame of reference for the results of the current study, we conducted a non-systematic review to identify STI or HIV outcomes in (a) other meta-analyses that consisted of multi-session behavioral interventions5968 and (b) biomedical HIV/STI prevention trials810, 14, 6971 (i.e., male circumcision, PrEP, microbicide, vaccine, diaphragm, and herpes simplex virus treatment). Using OR to compare these studies to the current study's biomedical outcome, we found that single-session interventions rivaled the effects of both multi-session behavioral interventions and biomedical prevention trials (see supplemental data). However, further analyses that account for heterogeneity, length of trial, settings, etc., are needed to precisely compare interventions and should be the focus of future research.

Single-session STI prevention interventions and the teachable moment

One mechanism that may play an important role in determining the efficacy of brief, single-session interventions is their delivery among populations at-risk for HIV/STI, or during a teachable moment.72 Health behavior interventions often take advantage of periods of heightened awareness and increased perceived vulnerability to enhance health promotion outcomes. The teachable moment has been critically important in interventions for smoking cessation, treatment for alcoholism, cardiovascular risk reduction, and cancer prevention, where significant changes in lifestyle are demanded to ward off life-threatening conditions. It is likely that bundled HIV prevention measures will target persons at-risk for HIV/STI; therefore, we must capitalize on the teachable moment. For example, the openness to behavior change that can occur following a diagnosis may explain at least some of the observed effects in single-session interventions with clinic patients. Receiving an STI diagnosis is itself a potent motivator for many people to change their sexual risk behaviors; therefore, this time period is an important window of opportunity for intervention.


Findings from the current study should be considered in light of their limitations. This synthesis included single-session interventions that measured STI by aggregating across new STIs including HIV. We are unable to speak to differences and similarities in the efficacy of single-session interventions for preventing individual STIs because insufficient studies reported results separately for STIs. We were unable to identify any single-session interventions powered on using HIV as an outcome. Likewise, condom use was reported differently by studies (e.g., numbers of unprotected acts, percentages of unprotected acts, event-level condom use); therefore, reported risk may vary across studies. Similarly, some studies did not report on behavioral outcomes, therefore, we were unable to include all studies in our analysis investigating condom use. Our results also do not speak to the critical active ingredients that are necessary to motivate protective behavior or reduce risky behavior, thereby decreasing STI. The most common approach emphasized education and skills building, but there were insufficient numbers of studies to determine if use of these elements is associated with the greatest risk reduction. Moreover, the definition of standard-of-care appears to vary greatly across studies. Many studies cited treatment and prevention guidelines as their basis for constructing the control conditions; however, there was clearly variability in what the control condition provided. Implementation level and age group were two moderating variables determined post hoc, and therefore these two analyses are prone to bias.20 In some cases, the unit of analysis did not match the unit of assignment; this limitation should be the focus of future studies. Furthermore, results demonstrated heterogeneity of tested interventions. The presence of heterogeneity creates limitations when making conclusive statements regarding meta-analytic findings. However, we used random effects models to address heterogeneity7375 and we conducted moderator analyses to account for variability in study results.

In order to create a comparison across other meta-analytic results and biological studies, we completed statistical approximations and transformations from the standardized mean difference, proportion of risk, and risk ratios to odds ratio. As a result of these procedures, some small deviations are possible relative to completing these procedures with raw data.76


Single-session risk reduction interventions are effective in reducing incident STI. On the whole, brief interventions require considerably less services, resources and attendance motivation from participants when compared to multi-session interventions and they result in disease prevention. The low cost of single-session interventions offers high public health utility, as well as their potential to achieve wide spread coverage. Moreover, brief interventions appear to succeed in behavior change as well as, or even better than longer interventions. This finding is consistent with the results of a recent meta-synthesis of health promotion meta-analyses 77 and a meta-analysis for behavioral interventions for STI prevention among African-American females64.

The promise of single-session interventions rests mainly their ability to reach large numbers of people in populations at greatest risk for STI. Single-session interventions can readily fit into existing services. Attaching interventions to routine care eliminates the need for additional infrastructure and staffing. Single-session behavioral interventions require capitalizing on teachable moments while condensing effective intervention elements. Focused behavioral interventions will prove necessary for the success of many biomedical prevention technologies. Given their potential for reducing high risk behaviors in clinical and community settings, effective single session interventions should be made more available. Particularly in resource constrained settings, these interventions may be the most viable option for behavioral change interventions. Future areas of research should focus on establishing the potential benefit of biomedical technology when combined with single session interventions.


United States Public Health Service grants R01MH058563, K18AI094581, R01MH094230, R01MH074371, and R01AA017399 supported this research directly or indirectly. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Public Health Service.


Contributor Statement: LAE contributed to search and review, wrote manuscript and contributed to analysis, TBHM conducted analyses, SCK contributed to search, review, writing and analysis, JAP conducted search and review, MJS conducted data analysis, MW conducted search and review, BTJ contributed to search and review, ARP conducted search and review.

Human Participant Protection:

Study procedures were exempt from institutional review board.


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