Effects of condom social marketing on condom use in developing countries: a systematic review and meta-analysis, 1990–2010
Michael D Sweat a, Julie Denison b, Caitlin Kennedy c, Virginia Tedrow c & Kevin O'Reilly d
a. The Medical University of South Carolina, Department of Psychiatry and Behavioral Sciences, 67 President St Suite MC 406, Charleston, South Carolina 29425, United States of America (USA).
b. Family Health International, Durham, USA.
c. The Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
d. World Health Organization, Geneva, Switzerland.
Correspondence to Michael D Sweat (e-mail: firstname.lastname@example.org).
(Submitted: 03 August 2011 – Revised version received: 08 March 2012 – Accepted: 10 March 2012 – Published online: 29 May 2012.)
Bulletin of the World Health Organization 2012;90:613-622A. doi: 10.2471/BLT.11.094268
The social marketing of condoms began in earnest in developing countries in tandem with global family planning efforts and was dramatically expanded as an early response to the global pandemic of acquired immunodeficiency syndrome (AIDS). This brought about a coordinated effort to ensure a steady supply of quality condoms at the local level in developing countries as governments and donors injected considerable funds into large-scale condom social marketing programmes globally.1 A standardized theoretical and conceptual model of condom social marketing emerged over time, as depicted in Fig. 1. Ongoing professional market research is used to inform three main intervention components of condom social marketing: condom branding, the development of a commodity logistics system and a sustained marketing campaign.1–5 For all three components local adaptation and implementation are stressed. Condom brands are designed to be appealing and to reflect local cultural values, and multiple brands are established as needed to reach key segments of the market. The commodity logistics system is tailored to the local economy, with efforts made to ensure a steady supply of affordable quality condoms at existing sales venues. The commodity logistics system is also designed to track sales, warehouse supplies and ensure timely delivery of products. The marketing campaign uses professional marketing techniques based on market research and is updated regularly as the market changes. A key principle in such programmes is that condoms should be sold at an affordable price, except for free distribution to the truly destitute. On the supply side, condom branding and commodity logistics systems are designed to increase the availability of desirable and affordable quality condoms. On the demand side, the sustained marketing campaigns are designed to increase the desire for and use of condoms. The increased demand for condoms, coupled with enhanced condom availability, promotes condom sales and use, and this should ultimately reduce the transmission of human immunodeficiency virus (HIV) infection, sexually transmitted infections and unwanted pregnancies.
Fig. 1. Theoretical/conceptual model for condom social marketing
Ample evidence shows that condom social marketing programmes increase condom sales,6,7 which have often been cited as an indication that condom use is increasing, although the evidence points to a weak relationship between condom sales and use.7 It is important to the field of HIV prevention to understand how condom social marketing programmes influence condom use. Hence, we systematically examined the evidence on the relationship between condom social marketing campaigns and increases in condom use.
We began by defining condom social marketing as including interventions in which condoms were sold, a local brand name was developed for the condoms, and the condoms were marketed through a promotional campaign to increase sales. Studies were included if they: (i) were conducted in a developing country or emerging economy as defined by the World Bank8; (ii) evaluated a condom social marketing intervention as defined above; (iii) were a pre–post assessment or a controlled trial comparing a group exposed to an intervention with a control group exposed to none, to a less intensive form of the intervention, or to another intervention altogether; (iv) measured condom use behaviour; (v) were published between January 1990 and March 2010, and (vi) specifically sought to prevent HIV infection. Studies that compared more intensive with less intensive versions of the same intervention and those that measured outcomes across different levels of exposure to an intervention were included if they met all other criteria. Unpublished materials and conference abstracts were excluded from the review. In a separate process we also identified and coded background citations, studies with data on intervention costs, previous reviews and meta-analyses, and seminal reports addressing the theoretical or policy issues surrounding condom social marketing, regardless of their geographical focus. No materials published before 1990 were included, since earlier data would not have reflected the important developments that have occurred since then in HIV prevention.
Search and acquisition
Trained staff broadly searched the following databases: the National Library of Medicine’s Gateway (which includes Medline and AIDSline), PsycINFO, Sociological Abstracts, the Cumulative Index to Nursing and Allied Health Literature (CINAHL) and EMBASE. Staff then hand searched five HIV-related journals – AIDS Care, AIDS, AIDS and Behaviour, AIDS Education and Prevention and the Journal of AIDS – for any citation appearing to meet the inclusion criteria based on the title and abstract. Staff were given a preliminary list of search terms but were also free to explore search terms of their choice to increase the yield of relevant studies. The Boolean logic used for the database searches was as follows: (marketing OR sale OR sold); AND (condom* OR contraceptive*) AND (HIV or AIDS). Searchers were instructed to err on the side of including papers in the preliminary search, as references were later subjected to a more in-depth review. We also iteratively searched the references of those papers selected for inclusion until no new papers were identified. Finally, we carefully reviewed the references from previous review papers and meta-analyses for possible citations. References identified as potentially eligible were imported into a database for additional, separate screening of titles and abstracts by two senior staff members who then classified each citation as either: (i) accepted, in which case the paper was included in the meta-analysis; (ii) suitable as background material (included review papers and cost-effectiveness studies), used only to write the introduction and discussion (“qualitative”) sections of this paper but not included in the meta-analysis; or (iii) excluded. The citations screened by the two senior staff were then merged for comparison and differences were resolved through additional review and discussion. A list of citations for acquisition was thus generated, the citations were obtained, two independent coders screened the full citations and discordant results were resolved by a senior member of the team.
To extract data from each eligible citation the two independent coders used a highly detailed coding form covering 15 content areas: citation information; study inclusion criteria; study methods; study population characteristics; setting; sampling; study design; unit of analysis; rates of loss to follow-up; characteristics of the study arms or comparison groups; (11) characteristics of the intervention; questions specific to condom social marketing interventions, such as funder, charge for condom, condom sale venues, etc.; outcome measures; eligible outcomes, and additional information (e.g. costs, limitations, potential harms and community acceptance). We coded citations used as background (“qualitative” citations) less intensively; for these we only extracted data on study participants, setting, study design and key findings (as described in the original citation).
All outcome variables reported in a study were noted, but outcomes were only recorded in detail for studies with a pre–post or group comparison design. Such eligible outcomes were coded in a structured format that included: (i) the type of statistical analysis used; (ii) the effect size and base rate; (iii) the independent variable; (iv) catchments and/or follow-up times, (v) the confidence interval (CI) and/or P-value; (vi) the page number and table where the results were located, and (vii) any additional brief information felt to be important (e.g. unusual statistical analyses or inconsistencies found in the published paper). All eligible outcomes, whether presented in the aggregate or by subgroups, were coded. Project staff resolved discrepancies between coders, corrected data entry errors and identified differences between coders in the interpretation of study results. Senior staff resolved any remaining discrepancies in consultation with the principal investigator of this systematic review project (MDS) and other senior collaborators. We tried contacting authors when necessary to resolve differences. Data from all coding forms were double entered into EpiData version 3.1 (EpiData Association, Odense, Denmark) and later transferred to a statistical database using SPSS version 19 (SPSS Inc., Chicago, United States of America).
We applied various criteria to control for methodological rigour: (i) for prospective cohort studies, we checked for pre- and post-intervention analyses or for a control or comparison group; serial cross-sectional studies and “post” only analyses were not held to these requirements; (ii) for studies comparing an intervention group with a control group receiving no intervention or a less intensive one, we checked for stratification in cross-sectional analyses and pre–post analyses; (iii) we checked whether pre- and post-intervention outcomes were compared or whether only post-intervention outcomes were presented; (iv) in multi-arm studies, we checked for random assignment to intervention groups; (v) in all studies we checked for random selection of subjects for assessment as a measure to reduce enrolment bias; (vi) we verified assessment of attrition and checked for a minimum follow-up of 80% at each analysis point in cohort studies; (vii) in multi-arm studies, we checked for sociodemographic matching of intervention and control subjects to rule out significant baseline differences; and (viii) we checked for outcome matching of intervention and comparison groups, also to rule out significant baseline differences in outcome measures.9
We standardized the effect size estimates from study reports to the common metric of an OR, since all studies compared two groups and reported dichotomous outcomes. We used standard meta-analytic methods to derive standardized effect size estimates.10 We used the Comprehensive Meta-Analysis v.2.2 software package (Biostat, Englewood, USA) to conduct statistical analyses, and we sometimes hand-calculated effect sizes. All studies identified for this analysis reported effect sizes as the proportion of sexually active subjects who used, or did not use, a condom with various sexual partners. To test for the presence of heterogeneity across the studies included in the meta-analyses we used the Q statistic, a weighted sum of squared differences between individual effects and the pooled effect across studies.11 To assess the degree of heterogeneity between studies, we used the I2 statistic.
Selection of study endpoints
Most studies report multiple endpoint measures, and for this analysis we specifically sought to examine the impact of HIV-related condom social marketing programmes on condom use rates. Thus, we focused our analysis only on behaviours linked to condom use rather than on factors such as the intention to use a condom or attitudes towards condoms. Condom use behaviour was measured slightly differently both within and across studies, and several studies reported results with multiple measures of condom use that met our inclusion criteria. We thus established guidelines for prioritizing the measures to include in primary meta-analysis. We chose: (i) the measure of condom use during the most recent sexual act when other measures of condom use over a longer term were also reported in the citation; (ii) the measure of condom use with the last partner rather than all partners; (iii) measures of condom use among casual partners rather than regular partners; and finally, (iv) measures of condom use whose denominator included only sexually active participants were selected. Based on this selection process we defined our primary outcome for analysis as condom use during the most recent sexual encounter. The outcomes that satisfied these criteria and that were selected for the primary meta-analysis are described in Table 1.
We conducted an additional meta-analysis based on an average effect size for all condom use outcomes within a study meeting our inclusion criteria. Average within-study effect sizes were estimated by converting ORs to a standard Hedges’ g statistic, with associated standard errors (SEs) and sample sizes. Hedges’ g, standard errors and sample sizes were then averaged across measures within each study, and this composite effect size was used in our secondary meta-analysis. When available, adjusted effect sizes were used in the meta-analysis rather than unadjusted values. Given the limited number of studies and the large heterogeneity between intervention model, moderator analyses and multivariate meta-analysis could not be conducted. Thus, we are unable to examine how factors such as variations in programme implementation or type of target population affected intervention outcomes.
Fig. 2 is a flow diagram showing the study selection process and the reasons for excluding studies at various stages. Of an initial 656 citations, successive rounds of review yielded 11final citations4,12–21 and 6 studies12–17 for inclusion in the qualitative and the quantitative syntheses, respectively. Of the 11 studies in the qualitative synthesis, 5 were excluded from meta-analysis for the reasons shown in Fig. 2.4,18–21 In three studies ultimately included in the quantitative synthesis and meta-analysis,15–17 the authors analysed and reported the results separately by gender, and we treated each gender separately in meta-analysis with no double counting of results.
Fig. 2. Flow diagram of study selection for systematic review of the literature on condom social marketing and condom use
Studies, participants and interventions
Table 2 (available at: http://www.who.int/bulletin/volumes/90/8/11-094268) describes the characteristics of the six studies in the quantitative synthesis and their participants. All interventions were highly similar, perhaps because they were funded and operated by the same donor organization (Population Services International). All studies evaluated interventions that followed standard condom social marketing conventions, as depicted in Fig. 1, including condom branding based on pilot studies of acceptability, a commodity logistics system, and a sustained professional, media-based marketing campaign. One study was conducted in India among clients of female sex workers.13 The remaining five were conducted in sub-Saharan Africa. Three programmes targeted broad population groups12,16,17; the other two targeted urban youth15 and male miners.14 Of the four mixed gender studies, two had approximately equal numbers of males and females,12,15 another was approximately 75% female17 and the other did not report the sex distribution.16 Only three studies reported the age range of study subjects.13,15,17 Four used a serial cross-sectional design to compare outcomes before and after the intervention, with random selection of study participants.13–16 One study12 used a single cross-sectional design to compare provinces where condom social marketing programmes had operated for 18 months versus less than 6 months. One cross-sectional study examined condom use by measuring intervention exposure.17 In the South African study among male miners,14 baseline assessment sites differed from follow-up assessment sites, although the authors reported them as “similar”. Two studies were described as national in scope.12,14 The mass media were used extensively in all interventions, supplemented by community-based outreach efforts.
All studies randomly selected study participants for all assessments. Among serial cross-sectional studies, the average baseline sample size was 1723 (range: 928–2401) and the average follow-up assessment sample size was 1896 (range: 200–3370). The two cross-sectional studies had sample sizes of 541212 and 9803.17 In the four serial cross-sectional studies, follow-up ranged from 12 to 36 months, and the six studies were conducted between 1995 and 2008.
Detailed descriptions of the interventions evaluated were limited in the source citations. However, the general social marketing strategy was very similar across studies, as mentioned before, with some differences only in the communication channels used. Peer education was reported in five study interventions12,14–17; interpersonal communication supporting condom use was reported in the sixth.14 Radio advertisements were used in five interventions12,14–17 and television ads in three.12,15,17
Overall study quality was low (Table 3). There were no randomized controlled trials. None of the six studies followed individual subjects prospectively; instead they conducted serial cross-sectional surveys. Only three studies had a control or comparison group. No study randomly assigned participants to intervention arms; for studies on condom social marketing interventions, a group randomized trial would have been needed. All studies randomly selected participants for assessments. In the three studies with a comparison group, study arms differed sociodemographically at baseline. Of the three studies with a pre-post intervention design that included a comparison group, only one reported equivalent baseline rates of condom use across study arms.
Table 4 shows the results of the primary meta-analysis for the outcome of interest: condom use during the most recent sexual encounter. In three studies, results were reported separately by gender, and we replicated this in the meta-analysis. This yielded nine discrete effect size estimates, five of which showed statistically significant effects of condom social marketing on condom use. ORs across the four significant effect size estimates, for the comparison of those exposed versus those not exposed to a social marketing intervention, ranged from 1.10 to 6.21. The random-effects pooled OR for all studies was 2.01. The Q statistic, a significant 553.87, indicated the presence of heterogeneity across studies.
Table 5 presents the results of the meta-analysis using a composite measure of condom use. Interestingly, differences across the two meta-analyses were minimal, with a random effects pooled OR of 2.10. In addition, the same four ORs were statistically significant, whether a single or an average outcome was used. The Q statistic, 645.4, was statistically significant and showed heterogeneity across studies. The study by Agha12 only reported on condom use during the most recent sexual encounter, and we used this outcome in this analysis. When we ran a separate analysis without the Agha12 study, the pooled OR was 1.96.
Table 6 presents the results of all meta-analyses, including several subanalyses. When results were stratified by gender, the odds of having used a condom during the most recent sexual encounter were 1.69 higher for males and 2.18 higher for females who had been exposed to condom social marketing than among males and females who had not. Similarly, the odds of using condoms overall were 2.00 times higher for exposed males and 1.88 times higher for exposed females. The test for heterogeneity remained significant within each gender stratum.
Because studies reported on condom use with different partner types, we conducted an additional meta-analysis with studies that reported on condom use during the most recent sexual encounter with a non-regular/casual partner (including female sex workers).12,13,15 The odds of having used a condom during the most recent sexual encounter with a casual partner, for males and females combined, was 3.45 times higher among those who had been exposed to condom social marketing interventions than among those who had not. The intervention effects remained significant when the outcome was restricted to males only (OR = 2.56). This analysis was the only one for which the Q statistic, 1.84, was not statistically significant.
An analysis for females only could not be conducted because only one of the studies included in the overall meta-analysis reported on condom use during the most recent sexual encounter with a non-regular partner among females.15 We also performed meta-analysis of the results from studies that focused on the general population by excluding studies conducted among specific high-risk populations, such as miners14 and clients of female sex workers.13 When the four remaining studies were meta-analysed, the odds of having used a condom during the most recent sexual encounter for males and females combined was 2.0 times higher than among the unexposed. When the meta-analysis was restricted to males, the odds were 1.69 higher. A separate analysis for females was not conducted because all studies that included female participants were performed in the general population and are thus included in the analyses for females only. For overall condom use, the OR among studies of the general population, for males and females combined, was 2.01; the OR for males only was 1.78. The results of meta-analyses stratified by population type were similar to those of the overall meta-analysis, which included all studies.
Given the global scale and scope of condom social marketing as an intervention for the prevention of HIV infection, we were surprised to find only six studies meeting our minimal inclusion criteria that were suitable for meta-analysis. Five of these studies were conducted in sub-Saharan Africa, which makes the results difficult to generalize to other settings. Further, these six studies generally lacked methodological rigour. There were no randomized trials or cohort studies. Only one of the studies had a high degree of equivalence across comparison groups in the baseline rate of condom use.16 We also had to eliminate one study from analysis due to the large and statistically significant baseline differences in condom use across study groups.22 The limited number of studies, lack of methodological rigour and lack of more recent studies render it difficult to definitively determine whether current implementation of condom social marketing is likely to increase condom use across developing countries. Despite these methodological weaknesses, the meta-analysis revealed that participants exposed to condom social marketing had twice the odds of reporting condom use when compared with either baseline rates or comparison groups.
The overall effect of condom social marketing on condom use was moderate (OR approximately 2). In addition, when the effect of the intervention was examined by gender and type of sexual partner, the results remained nearly the same. Larger effects were seen for condom use with casual partners. In analyses by gender we found only minor differences in intervention effectiveness. In addition, when studies of special risk groups (sex workers or miners) were removed from the analysis, the intervention effect changed very little.
Over time social marketing of condoms can result in substantial changes in condom use in the general population. The follow-up time frame for these six studies ranged from only 1 to 2 years. It is possible that if this effect were cumulative over a much longer period, a sustained programme could substantially increase the use of condoms. Cleland and Ali, in an interesting study of long-term trends in condom use among African women, examined data across a host of surveys conducted in 18 African countries between 1993 and 2001.23 They found that over these eight years the median proportion of women who used condoms to prevent pregnancy rose substantially, from 5.3% to 18.8%. However, the median annual increase in condom use was only 1.4%. The authors attribute these changes to sustained condom promotion associated with reproductive health campaigns, and they note that short-term evaluations can obscure the long-term cumulative benefits of such intervention programmes. If the same is true for condom social marketing, the results presented herein speak to the need to evaluate systems that track changes in behavioural outcomes over the duration of these interventions. Moreover, having more information on how condom social marketing differentially affects uptake by partner type would be valuable. Without such longer-term follow up of behavioural impacts by partner type it is difficult to accurately assess programme success. Basic ongoing behavioural sentinel surveillance would be relatively affordable, and the methods for conducting such evaluations have been well defined and tested.24,25
The limitations of this synthesis and meta-analysis include the potential for publication bias, self-reporting bias, and an inability to identify some aspects of the interventions originally studied. In our overall synthesis project examining a variety of interventions for the prevention of HIV infection, of which this review is a part, we also purposively focused on developing countries, which represent a neglected area of research and are uniquely different from wealthy countries socially, politically and economically. Furthermore, the most severe national epidemics of HIV infection have occurred in developing countries. Publication bias may have also affected this analysis, since studies with negative findings are seldom published,26 although other studies have not found systematic publication bias27 and this is an area of some controversy. After initially attempting to cull data from unpublished sources, we found that the quality of data identified was always below that required by our inclusion criteria. We also found that conference abstracts often reported results that differed substantially from the reports on the same study that appeared later in the peer-reviewed literature. Such unpublished reports also tended to lack the requisite level of detail on the intervention and results. Self-reporting bias and social desirability bias may have also been present. Finally, many of the published reports also failed to fully describe the interventions tested or to report on important aspects of the study findings and study populations. We did not always succeed in contacting authors to obtain missing data, and new studies have emerged since 2010. One final limitation is the heterogeneity in the study results. While this is a concern, a positive association between condom social marketing and condom use was found in all studies, albeit not always statistically significant.
There is evidence that condom social marketing can increase condom use, although such evidence comes from studies lacking sufficient rigour. Community-randomized controlled trials of condom social marketing would provide much stronger evidence, but they are expensive, so large-scale condom social marketing programmes are supported by little evidence. More studies in subpopulations would also be valuable to the field. Our meta-analyses did show a positive and statistically significant effect of condom social marketing on increasing condom use, and all individual studies showed trends for a positive effect. Although the effect size across studies was moderate, the cumulative effect of condom social marketing could be substantial in longer-term evaluations. It is regrettable that with so many resources being devoted to condom social marketing for so long that there is not a larger evidence base available, especially in light of the debates over the relative benefits of abstinence versus condom use. We also recognize that in many cases the groups working diligently to provide and promote low cost quality condoms in developing country settings have not been given the resources to fully evaluate their programmes. We strongly encourage more, and more robust, research and evaluation of the efficacy of condom social marketing programmes.
We wish to thank the following individuals for their help throughout the various stages of our systematic review project: Samantha Dovey, Jewel Gausman, Jennifer Gonyea, Andrea Ippel, Ruxy Kambarami, Erica Layer, Elizabeth McCarthy, Amy Medley, Devaki Nambiar, Amolo Okero, Alexandria Smith and Alicen Spaulding.
This research was supported by the World Health Organization, Department of HIV/AIDS; the US National Institute of Mental Health, grant number 1R01MH090173; and the Horizons Program. The Horizons Program was funded by The US Agency for International Development under the terms of HRN-A-00–97–00012–00.
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