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Epidemiology and Social

Effectiveness of HIV prevention for youth in sub-Saharan Africa: systematic review and meta-analysis of randomized and nonrandomized trials

Michielsen, Kristiena,b; Chersich, Matthew Fa,c; Luchters, Stanleya; De Koker, Petraa; Van Rossem, Ronanb; Temmerman, Marleena

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doi: 10.1097/QAD.0b013e3283384791
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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 [1]. 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 [2]. With few prevention technologies available, reducing sexual risk behaviours offers the best hope for preventing infection. Almost a decade ago, Merson et al.[3] 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 [6]. Others have focused on specific behaviours, for example condom use [7], 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

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.

Literature searches

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.

Data collection

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 [12]. 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).

Statistical analysis

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 [13]. 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 [14].


Study selection

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.

Fig. 1:
Flow diagram of studies selected for systematic review of HIV prevention in youth in sub-Saharan Africa. Adapted from Ref. [15].

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].

Table 1:
Characteristics of studies included in systematic review of HIV prevention interventions in youth in sub-Saharan Africa (per region and year of intervention).


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 [18], to intensive sexual health education over 3 years, combining teacher-peer activities in school, with community activities and provision of youth-friendly health services [19]. 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 [20].

Evaluation methods

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).

Condom use

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 [21]. 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 [25], one for males only [22] and one study [26] 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.

Table 2:
Effects of HIV prevention interventions on condom use among youth in sub-Saharan Africa.
Fig. 2:
Effects on condom at last sex in males.

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.[27] 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.

Fig. 3:
Effects on condom use in general in males.
Fig. 4:
Effects on condom use in randomized trials.

Of the studies reporting the intention to use a condom, one study had a positive effect on this outcome among the whole population [18] and one reported a positive effect in females [23,24]. The third study did not report a significant effect [28,29].

Sexual behaviour

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.[27] found a decrease in sexual activity for the whole population, whereas Shuey et al.[30] and Klepp et al.[31] found an increase. Overall, there is good evidence that interventions implemented to date do not increase sexual activity in youth (Table 3).

Table 3:
Effects of HIV prevention interventions on sexual behaviour among youth in sub-Saharan Africa.

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 [27]. 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 [32], 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) [27]. In three of five studies, interventions had a larger effect in males than females [19,21,27,35].

Biological outcomes

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 [20]. 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 [19]. 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).

Table 4:
Effects of HIV prevention interventions in youth in sub-Saharan Africa on HIV incidence, sexually transmitted infections and pregnancy.


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 –, 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.

(Limited) effectiveness

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 [20]). 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 [43]. 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 [27], less sexual intercourse in the past months [22] and higher intentions to use a condom [47]. 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.


1. United Nations Population Fund. Young people: the greatest hope for turning the tide. UNFPA:; 2008.
2. UNAIDS. Report on the global AIDS epidemic 2006. Geneva: UNAIDS; 2007.
3. Merson MH, Dayton JM, O'Reilly K. Effectiveness of HIV prevention interventions in developing countries. AIDS (Lond, Engl) 2000; 14(Suppl 2):S68–S84.
4. Gallant M, Maticka-Tyndale E. School-based HIV prevention programmes for African youth. Soc Sci Med 2004; 58:1337.
5. Paul-Ebhohimhen V, Poobalan A, van Teijlingen ER. A systematic review of school-based sexual health interventions to prevent STI/HIV in sub-Saharan Africa. BMC Public Health 2008.
6. Bertrand JT, Anhang R. The effectiveness of mass media in changing HIV/AIDS-related behaviour among young people in developing countries. World Health Organ Tech Rep Series 2007; 938:205–241.
7. Foss AM, Hossain M, Vickerman PT, Watts CH. A systematic review of published evidence on intervention impact on condom use in sub-Saharan Africa and Asia. Sex Transm Infect 2007; 83:510–516.
8. Speizer IS, Magnani RJ, Colvin CE. The effectiveness of adolescent reproductive health interventions in developing countries: a review of the evidence. J Adolesc Health 2003; 33:324–348.
9. Kirby DB, Obasi AI, Laris BA. The effectiveness of sex education and HIV education interventions in schools in developing countries. World Health Organ Tech Rep Series 2006; 938:103–150.
10. Magnussen L, Ehiri JE, Ejere HO, Jolly PE. Interventions to prevent HIV/AIDS among adolescents in less developed countries: are they effective? Int J Adolesc Med Health 2004; 16:303–323.
11. Kirby DB, Laris BA, Rolleri LA. Sex and HIV education programs: their impact on sexual behaviors of young people throughout the world. J Adolesc Health 2007; 40:206–217.
12. Albarracin D, Gillette J, Earl A, Glasman L, Durantini M, Ho MH. A test of major assumptions about behavior change: a comprehensive look at the effects of passive and active HIV-prevention interventions since the beginning of the epidemic. Psycholog Bull 2005; 131:856–897.
13. Higgins JP, Thomson SG. Quantifying heterogeneity in a meta-analysis. Stat Med 2002; 21:1539–1558.
14. Egger M, Davey SG, Schneider M, Minder C. Bias in meta-analysis detected by a simple,graphical test. BMJ 1997; 315:629–634.
15. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med 2009; 6:e1000100.
16. Brieger WR, Delano GE, Lane CG, Oladepo O, Oyediran KA. West African youth initiative: outcome of a reproductive health education program. J Adolesc Health 2001; 29:436–446.
17. Kuhn L, Steinberg M. Participation of the school community in AIDS education: an evaluation of a high school programme in South Africa. AIDS Care 1994; 6:161.
18. James S, Reddy PS, Ruiter R, Taylor M, Jinabhai CC, Van Empelen P, et al. The effects of a systematically developed photo-novella on knowledge, attitudes, communication and behavioural intentions with respect to sexually transmitted infections among secondary school learners in South Africa. Health Promot Int 2005; 20:157–165.
19. Ross DA, Changalucha J, Obasi AI, Todd J, Plummer ML, Cleophas-Mazige B, et al. Biological and behavioural impact of an adolescent sexual health intervention in Tanzania: a community-randomized trial. AIDS (Lond, Engl) 2007; 21:1943–1955.
20. Jewkes R, Nduna M, Levin J, Jama N, Dunkle K, Khuzwayo N, et al. A cluster randomized-controlled trial to determine the effectiveness of Stepping Stones in preventing HIV infections and promoting safer sexual behaviour amongst youth in the rural Eastern Cape, South Africa: trial design, methods and baseline findings. Trop Med Int Health 2006; 11:3–16.
21. Van Rossem R, Meekers D. An evaluation of the effectiveness of targeted social marketing to promote adolescent reproductive health in Guinea. PSI Research Division Working Paper No.23; 1999.
22. Maticka-Tyndale E, Wildish J, Gichuru M. Quasi-experimental evaluation of a national primary school HIV intervention in Kenya. Evaluat Program Plann 2007; 30:172–186.
23. Fitzgerald AM, Stanton BF, Terreri N, Shipena H, Li X, Kahihuata J, et al. Use of Western-based HIV risk-reduction interventions targeting adolescents in an African setting. J Adolesc Health 1999; 25:52–61.
24. Stanton B, Li X, Kahihuata J, Fitzgerald AM, Neumbo S, Kanduuombe G, et al. Increased protected sex and abstinence among Namibian youth following a HIV risk-reduction intervention: a randomized, longitudinal study. AIDS (Lond, Engl) 1998; 12:2473–2480.
25. Speizer IS, Tambashe BO, Tegang SP. An evaluation of the ‘Entre Nous Jeunes’ peer-educator program for adolescents in Cameroon. Stud Fam Plann 2001; 31:339–351.
26. Meekers D, Agha S, Klein M. The impact on condom use of the ‘100% Jeune’ social marketing program in Cameroon. J Adolesc Health 2005; 36:530.
27. Magnani R, MacIntyre K, Karim AM, Brown L, Hutchinson P. The impact of life skills education on adolescent sexual risk behaviors in KwaZulu-Natal, South Africa. J Adolesc Health 2005; 36:289–304.
28. Agha S, Van Rossem R. Impact of a school-based peer sexual health intervention on normative beliefs, risk perceptions, and sexual behavior of Zambian adolescents. J Adolesc Health 2004; 34:441–452.
29. Agha S. An evaluation of the effectiveness of a peer sexual health intervention among secondary-school students in Zambia. AIDS Educ Prev 2002; 14:269–281.
30. Shuey DA, Babishangire BB, Omiat S, Bagarukayo H. Increased sexual abstinence among in-school adolescents as a result of school health education in Soroti district, Uganda. Health Educ Res 1999; 14.
31. Klepp KI, Ndeki SS, Seha AM, Hannan P, Lyimo BA, Msuya MH, et al. AIDS education for primary school children in Tanzania: an evaluation study. AIDS 1994; 8:1157–1162.
32. Kim Young Mi. Promoting sexual responsibility among young people in Zimbabwe. Int Fam Plan Perspect 2001; 27:11–19.
33. Underwood C, Hachonda H, Serlemitsos E, Bharath-Kumar U. Reducing the risk of HIV transmission among adolescents in Zambia: psychosocial and behavioral correlates of viewing a risk-reduction media campaign. J Adolesc Health 2006; 38:55e1–55e13.
34. James S, Reddy P, Ruiter RAC, McCauley A, van den Borne B. The impact of an HIV and AIDS life skills program on secondary school students in Kwazulu-Natal, South Africa. AIDS Educ Prev 2006; 18:281–294.
35. Van Rossem R, Meekers D. An evaluation of the effectiveness of targeted social marketing to promote adolescent and young adult reproductive health in Cameroon. AIDS Educ Prev 2000; 15:383–404.
36. Magnussen L, Ehiri JE, Jolly PE. Interventions to prevent HIV/AIDS among adolescents in less developed countries: are they effective? Int J Adolesc Med Health 2004; 16:303–323.
37. Gallant M, Maticka-Tyndale E. School-based HIV prevention programmes for African youth. Soc Sci Med 2004; 58:1337–1351.
38. Johnson BT, Carey MP, Marsh KL, Levin KD, Scott-Sheldon LA. Interventions to Reduce Sexual Risk for the Human Immunodeficiency Virus in Adolescents, 1985–2000: a research synthesis. Arch Pediatrics Adolesc Med 2003; 157:381–388.
39. Bertrand JT, Anhang R. The effectiveness of mass media in changing HIV/AIDS-related behaviour among young people in developing countries. World Health Organ Tech Rep Series 2006; 938:205–241.
40. Klepp KI, Ndeki SS, Leshabari MT, Hann PJ, Yimo BA. AIDS education in Tanzania: promoting risk reduction among primary school children. Am J Public Health 1997; 12:12.
41. Okonofua FE, Coplan P, Collins S, Oronsaye F, Ogunsakin D, Ogonor JT, et al. Impact of an intervention to improve treatment-seeking behavior and prevent sexually transmitted diseases among Nigerian youth. Int J Infect Dis 2003; 7:61–73.
42. Visser MJ. Life skills training as HIV/AIDS preventive strategy in secondary schools: evaluation of a large-scale implementation process. SAHARA 2005; 2:203–216.
43. Bronfenbrenner U. The ecology of human development: experiments by nature and design. Cambridge, MA: Harvard University Press; 1979.
44. Türmen. Gender and HIV/AIDS. Int J Gynecol Obstetrics 2003; 82:411–418.
45. Lear. Sexual communication in the age of AIDS: the construction of risk and trust among young adults. Soc Sci Med 1995; 41:1311–1323.
46. Plautz A, Meekers D, Neukom J. The impact of the Madagascar TOP Réseau Social Marketing Program on sexual behavior and use of reproductive health services: PSI Research Division. Working Paper No. 57; 2003.
47. Karnell AP, Cupp PK, Zimmerman RS, Feist-Price S, Bennie T. Efficacy of an American alcohol and HIV prevention curriculum adapted for use in South Africa: results of a pilot study in five township schools. AIDS Educ Prev 2006; 18:295–310.
48. Kinsman J, Nakiyingi J, Kamali A, Carpenter L, Quigley M, Pool R, et al. Evaluation of a comprehensive school-based AIDS education programme in rural Masaka, Uganda. Health Educ Res 2001; 16:85–100.
49. Erulkar AS, Ettyang LIA, Onoka C, Nyagah FK, Muyonga A. Behavior change evaluation of a culturally consistent reproductive health program for young Kenyans. Int Fam Plan Perspect 2004; 30:58–67.
50. Harvey B, Stuart J, Swan T. Evaluation of a drama-in-education programme to increase AIDS awareness in South African high schools: a randomized community intervention trial. Intl J STD AIDS 2000; 11:105–111.
    51. Meekers D. The effectiveness of targeted social marketing to promote adolescent reproductive health: the case of Soweto, South Africa. Population Services International: Working Paper, No 16; 1998.
      52. Visser MJ. HIV/AIDS prevention through peer education and support in secondary schools in South Africa. J Soc Aspects HIV/AIDS 2007; 4:678–694.
        53. Fawole IO, Asuzu MC, Oduntan SO, Brieger WR. A school-based AIDS education programme for secondary school students in Nigeria: a review of effectiveness. Health Educ Res 1999; 14:675–683.

        adolescent; Africa South of the Sahara; evaluation studies; HIV prevention; intervention studies; meta-analysis; sexual behaviour

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