Young people in developing countries are particularly vulnerable to HIV infection, other sexually transmitted infections (STI) and unintended pregnancy. This is due to a combination of experimental behaviour in adolescence, limited knowledge, poverty, and socio-cultural factors, including sex inequality . In sub-Saharan Africa, notwithstanding all efforts to prevent HIV infection among youth, an estimated 4.3% of women aged 15–24 years [95% confidence interval (CI) = 3.7–5.1] and 1.5% of young men (95% CI = 1.3–1.7) are infected with HIV . With few prevention technologies available, reducing sexual risk behaviours offers the best hope for preventing infection. Almost a decade ago, Merson et al. concluded a review on this topic by stating that there is a dearth of evaluated prevention interventions for young people. It is thus timely to take stock of available evidence, particularly in sub-Saharan Africa, where HIV transmission continues virtually unabated in many parts.
Previous reviews have assessed the impact of HIV prevention on youth in specific settings, such as schools [4,5], or with particular tools like mass media . Others have focused on specific behaviours, for example condom use , or on other geographic regions [3,8–11]. Given the narrow focus of these reviews, it is difficult to draw an overall picture of the effectiveness of prevention interventions among African youth.
We undertook a systematic review, and a meta-analysis when appropriate, to assess effectiveness of interventions to reduce sexual risk behaviours, and consequent HIV infection, among young people (10–25 years) in sub-Saharan Africa. To our knowledge, this is the first meta-analysis of the impact of behavioural interventions for youth in sub-Saharan Africa.
Study eligibility and extraction procedures were specified in a systematic review protocol. Only studies with a control group were included (randomized and parallel-group studies); however, since evaluations of mass media campaigns seldom have external control groups, we considered respondents with limited or no exposure to an intervention as a valid control group. Additionally, to be eligible, studies had to be published between January 1990 and December 2008; focus on the general population of young people (10–25 years) in sub-Saharan Africa; and report an evaluation of behavioural interventions aimed at preventing HIV transmission by reducing sexual risk taking. Studies among specific groups of youth (e.g. injecting drug users) were excluded.
Articles were sought in May 2009, without language restriction, in online databases Medline, ISI Web of Science and Ebscohost (all databases) using the search terms: (effectiveness or evaluation or impact or result) and (HIV or AIDS) and (prevention or education or ‘risk reduction’) and behaviour and (adolescent or youth or student or child) and Africa. To reduce publication bias, we searched websites of international organizations reputed for HIV prevention research (UNAIDS, UNESCO, World Health Organization, Population Services International) and Google Scholar. Reference lists of eligible articles and previous reviews were searched.
An electronic data extraction sheet was piloted by three investigators and refined accordingly thereafter. Data extraction was then done independently, in duplicate, by five investigators. Divergent findings were resolved through discussion between the pair of reviewers. Two authors were contacted and provided further information. Information was extracted on both early (first measure within 1 year of intervention) and late (last available measure) outcomes of interventions, when available. Data items extracted were first author, journal; year; country; study population; sample size; study population age; intervention type and duration; study design; and method of assigning intervention. For each outcome measure we extracted: free text description of outcome; outcome category; time outcome measured; group or sub-group; the outcome measure; and the univariate and multivariate measures, including confidence intervals. The proportion of participants with incomplete outcome data and the study design (randomization or parallel groups) were used to assess risk of bias and study quality in individual studies.
Study outcomes and subgroups
Three outcome categories were assessed. Firstly, condom use in its most frequent conceptualizations: use at last sex; use over a longer period of recall (measured as condom consistency and ever condom use); and intention to use condoms. This last subcategory, though not an actual behaviour, was included since it is a validated predictor of actual condom use . Secondly, we examined sexual activity of youth: primary abstinence; the proportion of sexually active youth; recent sexual intercourse; number of sexual partners; and multiple partnerships. Finally, biological outcomes were assessed, defined as incidence of HIV and other STIs, or pregnancy. Distal outcomes such as HIV knowledge, or beliefs about condom effectiveness were not assessed. Outcomes were extracted separately for prespecified subgroups (females, males, prestudy virgins and respondents with high exposure to the intervention).
Data were analysed using Stata, version 10 (StataCorp, College Station, Texas, USA). For each outcome category, we examined point estimates and 95% CIs of exposure-outcome pairs and displayed these in forest plots. In many instances the ratio and 95% CI was derived from frequencies or proportions reported by authors. Heterogeneity was examined using the I2 statistic, describing the percentage of total variation across studies due to heterogeneity other than chance . I2 values 50–75% were interpreted as indicating moderate heterogeneity and greater than 75% as pronounced between-study variability. Exposure-outcome pairs from different studies were combined using a random-effects model if heterogeneity was low or moderate, and assuming that all effect estimates approximated the same measure and could therefore be combined. Summary statistics of dichotomous outcomes are presented as relative risks (RRs). If heterogeneity was pronounced, we examined potential explanations in stratified analyses, notably by study design. Subgroup analyses explored whether summary effects varied according to characteristics such as sex. Funnel plots asymmetry was used to detect small study biases .
The search identified 758 articles, with 160 duplicates (Fig. 1). Assessment of title and/or abstract excluded a further 527 articles that did not meet inclusion criteria. After assessing full text of the remaining articles, 37 were excluded (10 did not target youth, 14 did not report an intervention to reduce sexual risk behaviour and 13 had no control group). In total, 31 articles met inclusion criteria, reporting on 28 interventions.
Overview of intervention characteristics
Southern Africa accounts for 15 studies (10 in South Africa), six were in Western Africa, four in Eastern Africa and three in Central Africa. Sample sizes varied between 226 and 9219 with a median of 1297 and a total of 50 990 participants (Table 1). Average age of study participants ranged from 13.6 to 19.1 years (mean age 16.7 years). Females (n = 24 583) and males (n = 23 932) were equally represented; two studies did not specify sex [16,17].
Most interventions were set in schools (12 in secondary, 3 in primary, and 1 in both primary and secondary schools). Four interventions combined school and community-level activities, whereas eight were only community-based. The majority were in urban areas (15) or in a combination of urban and rural settings (10). Duration of intervention ranged from an hour-long reading of an illustration book , to intensive sexual health education over 3 years, combining teacher-peer activities in school, with community activities and provision of youth-friendly health services . The median duration of the interventions prior to evaluation of outcomes was 1 year [interquartile range (IQR) = 7 weeks to 2 years]. Seventeen contained elements of peer education, of which five relied solely on peer workers. In 12 interventions teachers were included and they were responsible for delivering all components of the intervention in six studies. Seven used media to transfer messages. In total, 12 interventions used one technique to reach youth, whereas the other 16 interventions combined several methods. The most recent intervention took place in 2003–2004 .
Of the 28 studies, 11 were randomized trials (eight randomized schools, two communities and one student); five had a prepost design controlling for exposure level, and 12 used a parallel-group design, comparing intervention group(s) with control group(s). Fifteen studies used a repeat cross-sectional design, whereas 13 were cohort studies, in which between 64.7 and 96.2% of participants were retained (median = 76.5%). Including the prespecified subgroups, 217 outcome measures were extracted: 88 early (within 1 year of intervention) and 129 late outcomes (more than 1 year after the end of the intervention).
Overall, there was marked variability in the magnitude and direction of outcome measures of condom use at last sex, which was the commonest outcome reported (Table 2). In subgroup analysis, effects on condom use at last sex were larger in males than in females in all studies excepting one . In meta-analysis, condom use at last sex was 1.46 times higher among males in the intervention group than control males (95% CI = 1.31–1.64) with little heterogeneity in these effect measures (I2 = 16.5%, P = 0.30; Fig. 2). The heterogeneity in the female effect measures was marked (I2 = 66.7%, P = 0.001) and therefore no summary measure was calculated. Little effect was noted on condom use at last sex among preintervention virgins in the two studies which assessed this [22–24]. Of the three studies assessing the impact on highly exposed youth, one reported an increase in condom use at last sex for the whole population , one for males only  and one study  did not report an effect. The interventions that reported a significant effect on condom use at last sex were very diverse: four took place in schools, three in communities and two both in schools and in communities. One intervention took place in a rural area, four in urban area and three both in rural and urban areas. Peer educations played a role in six interventions, of which only one solely relied on peer education, two were led by teachers and one by health workers.
Effects of the interventions on condom use in general (ever use of condom or consistent condom use) was detected in males with the overall RR = 1.32 (95% CI = 1.25–1.40), with findings consistent across the studies (I2 = 0.0%) (Fig. 3). As the study by Magnani et al. had a major influence on the overall summary measure, analysis was repeated excluding this study; findings were similar (RR = 1.28, 95% CI = 1.16–1.42). Again, among females, there was substantial heterogeneity in the findings of this outcome (I2 = 75.4%, P < 0.001), as among the whole population (I2 = 57.2%, P = 0.03). To examine the pronounced heterogeneity on condom use in general measured in the whole population, we stratified analysis by study design (Fig. 4). There was little heterogeneity among five randomized trials with this outcome (I2 = 33.3%, P = 0.19), with the overall RR = 1.28 (95% CI = 1.13–1.45). The trial which reported that condom use about halved in the interventions compared to controls (RR = 0.52, 95% CI = 0.22–1.24) asked about ever condom use with a regular partner and reported considerable differences between baseline socio-demographic characteristics in the intervention and control arms.
Of the studies reporting the intention to use a condom, one study had a positive effect on this outcome among the whole population  and one reported a positive effect in females [23,24]. The third study did not report a significant effect [28,29].
The most common measure for sexual activity was ever having had sex. Eleven studies reported this outcome, of which 10 provided estimates disaggregated by sex. Magnani et al. found a decrease in sexual activity for the whole population, whereas Shuey et al. and Klepp et al. found an increase. Overall, there is good evidence that interventions implemented to date do not increase sexual activity in youth (Table 3).
The three studies that reported on abstinence [27,32,33] are included in the ‘ever sex’ column of Table 2: two resulted in an increase in abstinence [32,33], one in a reduction . Recent sexual activity, operationalized as having had sexual intercourse in the past months, was measured by seven studies. Only one study found a reduction in recent sexual activity , whereas three found an increase [29,30,34].
Nine studies presented information about the effects of interventions on multiple partners, five disaggregated by sex. There was pronounced heterogeneity, but little evidence of an increase in multiple partners (only detected in 1 of 21 reported outcomes) . In three of five studies, interventions had a larger effect in males than females [19,21,27,35].
HSV-2 incidence was lower in the intervention group in a cluster-randomized trial in South Africa [RR = 0.67 (0.47–0.96)], assessing the effects of 13 3-h sessions of participatory learning . No effects, however, were detected on HIV or pregnancy incidence. Similarly, no effect was noted on HIV or pregnancy incidence in a Tanzania trial with randomized communities . However, among female participants, the prevalence of N. gonorrhoea was higher in the intervention arm, though this difference was of borderline significance. Meta-analysis of HIV incidence data in these two trials showed an overall RR of 0.91 (95% CI = 0.66–1.26; I2 = 0.0%) (Table 4).
Paucity and low quality of evaluations
Surprisingly little information was available on youth interventions in sub-Saharan Africa: only 28 studies were identified with as few as two studies collecting biological endpoints, and many studies had suboptimal study designs. This is particularly concerning given the extent of the vulnerability to HIV infection faced by the 125 million young people in sub-Saharan Africa, and the presence of numerous HIV-prevention initiatives and funding opportunities in this region. The paucity of high-quality studies confirms findings of previous reviews on this topic [8,11,36,37]. Field experiences of the authors of this study, however, indicate that considerably more interventions are implemented, but are generally not designed for robust evaluation, or evaluation data are not analysed and disseminated.
There were very few commonalities in study design and interventions tested, perhaps suggesting that there is little consensus on the optimal approach to these interventions and that few studies have built upon previous knowledge in a linear fashion. In addition, no two studies used the same methods of analysing or reporting data, and outcome indicators very markedly diverse. Oftentimes odds ratios and CIs were not provided, and multivariate analysis was not universal. There should be more studies that use a strong evaluation design and measure biological outcomes. Moreover, evaluators should provide more transparency in their multivariable analysis and reporting.
The same outcomes are often operationalized in slightly different ways. Several attempts have been made to standardize indicators and make them easily available online (e.g. by the Centre for HIV Identification, Prevention and Treatment Services – http://chipts.ucla.edu/assessment/index.asp), which has not yet translated into widespread and systematic use of these indicators. The development of standardized methods and indicators does not guarantee the use thereof, and therefore organizations and evaluators should be informed and sensitized on the importance of using standardized indicators and scales.
It is encouraging to note that taken together the evidence indicates that sex education and condom promotion activities among youth does not increase sexual activity, nor promote risky sexual behaviour. However, we could not observe large positive changes either. Youth did not significantly reduce sexual activity, and condom use at last sex only increased notably among males. Only one study reported a positive impact on a biological outcome (HSV-2 ). This finding corresponds with other reviews, who find significant changes in knowledge and attitudes, but a small degree of risk reduction [5,7,8,36,38,39].
Studies ascribed the limited impact of interventions to poor implementation of the intervention [22,27,31,40–42]. Several authors explicitly reported a reluctance of teachers and health professionals to discuss condom use with youth [22,31,41]. Resource constraints and general disorganization in schools often hampered implementation of the planned activities, such that time assigned for the scheduled activities was often curtailed or cancelled altogether [27,42]. Since interventions which reported implementation barriers did not generally have fewer positive outcomes, it is possible that other studies also experienced implementation difficulties, but did not report them.
Limited effectiveness might also stem from flaws in the assumptions underlying HIV risk reduction interventions. Although the interventions varied markedly in the setting and delivery strategies they adopted, they predominantly focused on HIV/AIDS as a means of changing sexual risk behaviour. However, the existence of a direct causal link between sexual behaviour and HIV infection does not mean that the converse is true. From an ecological perspective, HIV/AIDS is only one factor among a great number of interacting factors which operate on different levels to influence sexual behaviour . Seen from an ecological viewpoint, it is quite logical that interventions focusing on knowledge or attitudes to HIV/AIDS can only result in relatively small changes in sexual behaviour.
Differences by subgroups
Several indicators showed a larger impact on males than females (condom use at last sex, ever had sex, and number of partners). This might suggest that women still experience marked difficulties in negotiating condom use or assuming full control over their sexual activity [44,45]. Also, several evaluations drew a distinction between moderate and high exposure to the intervention, reporting more impact among the highly exposed group [22,26,32–34,46]. In order to increase programme effectiveness, it is crucial to analyse the determinants of the level of intervention exposure, and how to optimally reach underexposed groups. Furthermore, differences in impact according to sexual history were present in several evaluations: participants who were virgins at the time of exposure to the intervention reported higher rates of abstinence after the intervention , less sexual intercourse in the past months  and higher intentions to use a condom . This highlights the importance of HIV prevention interventions for children and early adolescents.
Though no publication bias was detected with funnel plots, it is highly likely that organizations will generally be less likely to publish negative or neutral results, especially regarding subgroups. However, it is also possible that those research groups who do publish their findings are more conscious of the importance of rigorous evaluation and publication, and therefore perhaps more cognisant of the importance of meticulous intervention development and implementation. All but two studies relied exclusively on self-reported data on sexual behaviour, which is subject to several biases and unsupported by biological outcomes. We selected behavioural interventions to reduce HIV/STI infections, whereas other interventions also may have an impact on sexual behaviour among young people, such as interventions to reduce alcohol or drug use.
There remains a stark mismatch between the burden of HIV in youth and efforts to conceptualize putative interventions and subject them to trial conditions with robust endpoints. The effectiveness of HIV-prevention interventions on sexual behaviour overall, to date, however, appears relatively small and perhaps confined to particular subgroups such as males. More attention is required to comprehend difficulties with implementation, differences in response to interventions by sex, determinants of exposure to interventions and promoting the inclusion of factors other than HIV which determine sexual behaviour.
Sources of support: K.M. was funded by the Research Foundation Flanders (FWO) Belgium.
Description of the role of each of the authors in the study: K.M.: initiation of the study, literature search, data extraction, writing.
M.F.C.: data extraction, statistical analysis, support in writing.
S.L.: data extraction, support in statistical analysis and writing.
P.deK.: data extraction, support in writing.
R.vanR.: data extraction, support in writing.
M.T.: promoter of the study, support in writing.
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