JAIDS Journal of Acquired Immune Deficiency Syndromes:
Effectiveness of Mass Media Interventions for HIV Prevention, 1986–2013: A Meta-analysis
LaCroix, Jessica M. MS*,†; Snyder, Leslie B. PhD‡; Huedo-Medina, Tania B. PhD†,§; Johnson, Blair T. PhD*,†
*Department of Psychology, University of Connecticut, Storrs, CT;
†Center for Health, Intervention, and Prevention, University of Connecticut, Storrs, CT;
‡Department of Communication, University of Connecticut, Storrs, CT and Center for Health Communication and Marketing, University of Connecticut, Storrs, CT;
§Department of Allied Health Sciences, University of Connecticut, Storrs, CT.
Correspondence to: Blair T. Johnson, PhD, Center for Health, Intervention, and Prevention, University of Connecticut, 2006 Hillside Road, Unit 1248, Storrs, CT 06269-1248 (e-mail: email@example.com).
Supported by the National Institute of Mental Health to B.T.J. (R01-MH58563) and J.M.L (T32-MH074387) and the Centers for Disease Control and Prevention to L.B.S. (P01-CD00237).
The authors have no conflicts of interest to disclose.
Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (www.jaids.com).
J.M.L. performed the literature search, coded studies, calculated effect sizes, contributed to study design, and led the analysis and writing. L.B.S. contributed to study design, supervision, analysis, and writing. T.B.H.-M. contributed to the analysis and writing. B.T.J. proposed the study, contributed to study design, supervision, analysis, and writing. J.M.L. had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
This is an open access article distributed under the terms of the Creative Commons Attribution-Noncommercial No Derivative 3.0 License, which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially.
Objectives: This meta-analysis was conducted to synthesize evaluations of mass media–delivered HIV prevention interventions, assess the effectiveness of interventions in improving condom use and HIV-related knowledge, and identify moderators of effectiveness.
Study Selection: We systematically searched electronic databases, relevant Web sites, related journals, and reference lists of previous reviews and included studies. Studies that quantitatively evaluated the effectiveness of mass media–delivered HIV prevention using pre-/post-campaign assessments, targeted the general population, reported outcomes of interest, and were available as of September 30, 2013 were eligible for inclusion.
Data Extraction and Synthesis: Raters coded report, intervention, and sample characteristics. The standardized mean difference, d, comparing pretest and posttest assessments was calculated for each study sample. Effect sizes were analyzed incorporating random-effects assumptions.
Results: Of the 433 obtained and screened reports, 54 reports containing evaluations of 72 interventions using 93 samples (N = 142,196) met the selection criteria and were included. Campaigns were associated with increases in condom use [d+ = 0.25, 95% confidence interval (CI) = 0.18 to 0.21], transmission knowledge (d+ = 0.30, 95% CI = 0.18 to 0.41), and prevention knowledge (d+ = 0.39, 95% CI = 0.25 to 0.52). Increases in condom use were larger for longer campaigns and in nations that scored lower on the human development index. Increases in transmission knowledge were larger to the extent that respondents reported greater campaign exposure, for more recent campaigns, and for nations that scored lower on the human development index.
Conclusions: Mass media interventions may be useful in reducing global HIV/AIDS disparities because of their reach and effectiveness.
Since the 1960s, mass media-delivered health interventions, also known as public communication campaigns or social marketing campaigns,1–3 have been an important strategy for many health behavior change topics, including heart disease, smoking, family planning, and HIV/AIDS prevention.4–9 Mass media–based interventions have been an integral part of HIV prevention since the mid-1980s, when many nations began sponsoring national campaigns,10 and community-based groups began developing local interventions. Using the mass media within an HIV prevention intervention provides such advantages as wide reach, standardization and repetition of messages, and the ability to use different content formats, including entertainment, news, and short advertisements or announcements. The international nature of the HIV prevention campaign literature allows for analysis of the differential impact of mass media–based interventions in different parts of the world.
With regard to HIV prevention campaigns, mass media channels can be used on their own (eg, television, newspapers, radio) or in combination with interpersonal sources of information (eg, outreach workers, peer educators). In addition, HIV prevention campaigns may incorporate condom pricing and distribution strategies,1,2 community organizing, or advocacy for policy change.11,12 The number of channels used in a campaign may predict the extent to which that campaign influences the target population; multichannel approaches are often seen as more effective than single channel interventions.5
Duration of HIV prevention campaigns may also predict campaign effects, although results from past research are conflicting. One meta-analysis suggested that US health promotion campaigns lasting a year or less were more effective than longer campaigns,8 whereas another review suggested that in developing countries, health promotion campaigns lasting 18 months or longer were more effective.13 It might be, for example, that in developing countries, mass media messages take a relatively long time to reach and to have an impact on the knowledge, attitudes, and behavior of a substantial portion of the target population, whereas the target population in developed countries may have more and faster media access.
Three previous systematic reviews have investigated the nature of mass media campaigns to combat HIV/AIDS. The first review reported characteristics for 41 campaigns published in peer-reviewed journals from 1986 to 1998.14 Of the 41 campaigns reviewed, 26 had a name or slogan, 28 reported rates of exposure, and only 7 used a controlled comparison group design. Of the studies reporting exposure, 50% of the audience was exposed to intervention messages, and televised campaigns had the highest rates of exposure. Building on the first review, a more recent publication systematically reviewed HIV/AIDS mass communication campaigns published in peer-reviewed journals between 1998 and 2007.15 Of the 34 new campaigns, 28 had a name or slogan, and 28 reported exposure, the mean of which was 77% of the audience. Although neither review was able to use meta-analytic techniques because of the lack of methodological rigor in intervention evaluations, Noar et al15 reported improvements in safer sex behavior and intention for 8 of the 10 campaigns that used quasi-experimental designs. A third review—focused exclusively on campaigns in developing countries—identified 24 articles published in peer-reviewed journals from 1990 to 2004.16 Half of the campaigns used television or radio and half used small media (eg, brochures, leaflets). The authors reported positive results for condom use and knowledge, but concluded that more research is needed to establish the magnitude of effects and identify which campaign elements contribute to success.
The purpose of the present meta-analysis was to expand on previous systematic reviews to examine the overall effectiveness of mass media–delivered HIV interventions and to identify predictors of changes in condom use and HIV-related knowledge. We define mass media–delivered interventions as those wherein the intervention message is delivered in a natural setting through a mass media channel to which individuals may or may not attend (eg, radio, television, newspaper, magazine, or mass distribution or mailing of printed materials). In addition to testing the role of campaign duration and number of channels, we also explored whether date of data collection, country of campaign, level of country development, and message and sample characteristics predicted effect size magnitude. This review is the first to analyze the results of mass media–delivered HIV interventions using meta-analytic techniques (ie, pooling effect sizes and analyzing possible moderator variables of effect size magnitude), and the first to attempt to locate and include unpublished reports. This study contributes to global public health by informing both HIV prevention work and interventions in general in terms of the effectiveness of mass media–delivered health interventions.
The current meta-analysis conformed with the standards implied by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines.17
Studies were included if they (1) had an HIV/AIDS prevention focus, (2) targeted youth or the general population, (3) evaluated a specific intervention delivered through an audio, visual, or printed mass media channel in a natural setting, (4) quantitatively evaluated the target population using a pre-/post-campaign design, (5) measured condom use and/or HIV/AIDS-related transmission or prevention knowledge, (6) reported sufficient information to calculate effect sizes, and (7) were available in English. Interventions that solely targeted high-risk groups (eg, injection drug users, commercial sex workers), used forced exposure to messages, only sampled individuals who had all been exposed to some campaign component, or used interpersonal communication supplemented by small media (eg, brochures delivered by outreach workers) were excluded.
Potentially relevant reports were located through (1) systematically searching PsycINFO, CINAHL Plus, Medline/PubMed, ProQuest Dissertations and Theses; (2) hand searching relevant Web sites (eg, Population Services International, MEASURE Evaluation), the Synthesis of HIV/AIDS Research Project's (SHARP) collection of sexual risk reduction interventions, relevant journals (eg, AIDS, AIDS and Behavior), the reference lists of previous reviews and included studies; and (3) personal communication with authors to locate additional reports (Fig. 1; see also Appendix A, Supplemental Digital Content, http://links.lww.com/QAI/A540, for details of the search and selection process). Each database was searched as far back in time as available. Two authors independently screened potentially relevant reports for eligibility; disagreement was resolved through discussion. Studies that fulfilled the search criteria and were available by September 30, 2013 were included.
Coding Study Characteristics
Trained raters coded characteristics describing the study reports (eg, publication status), interventions (eg, duration, number of channels, message branding), and evaluation samples (eg, age, gender, proportion sexually active). A subset of interventions (65%) was double coded to ensure coding accuracy; interrater reliability was high (mean r = 0.94, κ = 0.76, 92% agreement). All disagreements were resolved through discussion. In addition, interventions were matched by country and year of initial data collection to the corresponding Human Development Index (HDI), a measure of nation-level social and economic development that combines indices related to life expectancy, educational attainment, and income.18,19 HDI values range between 0 and 1, and countries are described as scoring high (HDI of 0.80–1.00), medium (HDI between 0.50 and 0.79), or low (HDI <0.50). In instances when HDI values were not available for the exact year of initial data collection, values from the closest year available were used.
Calculation and Analyses of Effect Sizes
To gauge the success of each mass media-delivered intervention, 2 independent researchers calculated the standardized mean difference, d, for each study sample, k, by subtracting the pre-campaign mean from the post-campaign mean and dividing by the pooled standard deviation.20 In the absence of mean values and standard deviations, other statistical information (eg, F-values) was used with the appropriate transformations.21,22 If the study reported dichotomous outcomes, we calculated an odds ratio and transformed it to d using the Cox transformation.23 Effect sizes were corrected for sample size bias. The primary outcome variable was condom use (eg, frequencies and proportions of protected sex). Secondary outcomes included HIV/AIDS transmission knowledge (eg, HIV is transmitted through unprotected intercourse) and HIV/AIDS prevention knowledge (eg, condoms prevent the sexual transmission of HIV). When multiple measures of the same outcome were reported, effects were averaged. Multiple effect sizes were calculated from individual studies when they had more than one intervention condition or when the outcomes were separated by sample characteristics (eg, gender). Effect size calculation disagreements were resolved through discussion. Positive effect sizes indicate more sexual risk reduction after the intervention compared with pre-campaign results (eg, increased condom use, decreased unprotected intercourse, improved HIV knowledge).
Analyses were conducted following random-effects assumptions using published macros24 in Stata 11.2 (StataCorp, College Station, TX).25 The homogeneity statistic index, I2, its corresponding 95% confidence intervals (CIs), and the inference test of homogeneity Q were calculated to determine the extent to which study outcomes were consistent; heterogeneity is inferred when CIs do not include zero.26–28 Asymmetries in distribution of the different effect size outcomes, which can suggest reporting bias, were examined with Begg technique, trim and fill, and Egger technique.29–31 The relation between sample, methodological, or campaign characteristics and the magnitude of the effects were examined using a modified weighted least squares regression analysis with weights equivalent to the inverse of the sample and population variance. The moving constant technique was used to estimate mean effect sizes (d+) and CIs for specific moderator values of interest.32
Report, Intervention, and Sample Characteristics
In total, 433 reports were obtained and screened; 54 reports containing evaluations of 72 separate interventions met the selection criteria and were included.33–86 Interventions were evaluated at pre-/post-campaign using a total of 93 separate sample comparisons drawn from the target populations. Table 1 presents descriptive characteristics of the individual reports (k = 54), interventions (k = 72; see Table S1, Supplemental Digital Content, http://links.lww.com/QAI/A540, for additional characteristics), and samples (k = 93; eg, results were split by gender). Reports were published between 1986 and 2010 (mean = 1999), were retrieved primarily from journals (69%) or organization Web sites (28%), and most studies were conducted in Africa (50%) or Asia (17%). Interventions were generally conducted nationally (49%) or based in individual communities (43%). Many campaigns pretested message content before campaign launch (39%), and 45% were theory based. Of the 72 interventions, 15% used only 1 channel, and of these, 4 used small media, 3 used radio, 3 used newspapers or magazines, and 1 used television. All other campaigns (83%) used 2 or more channels including signage (72%), radio (70%), television (57%), educational literature (51%), newspapers or magazines (33%), and promotional materials (21%). Overall, 47% of the interventions included an interpersonal component. Most interventions focused on condom promotion (76%), and more than a third used an entertainment–education strategy (39%). Most campaigns had an identifying logo, slogan, or brand (57%), and 42% included condom distribution. The median intervention duration was approximately 8 months, though duration varied widely.
TABLE 1-a Descriptiv...Image Tools
All reports (k = 54) evaluated interventions using pre- vs. post-campaign designs; 2 reports evaluated multiple campaigns,39,43 5 reports evaluated campaigns at multiple sites,36,44,51,72,80 and 2 reports47,53 evaluated campaigns in intervention and comparison areas wherein the comparison areas were exposed to specific campaign elements and were coded separately. Only 8 reports provided results for a no-exposure comparison group at pre- and post-campaign.36,55,59,72,77,80,82,86 The 72 interventions were evaluated using a total of 96 samples; median sample size was about 600 participants. Among the individual samples, the mean proportion female was 0.48, mean proportion married was 0.39, mean proportion sexually active was 0.69, mean age was 24.25 years, and mean campaign exposure was 59%.
TABLE 1-b Descriptiv...Image Tools
Overall Efficacy of the Interventions
Overall, analyses indicate significant increases in condom use (d+ = 0.25, 95% CI = 0.18 to 0.21, k = 57; Fig. 2) and significant improvements in HIV-related transmission knowledge (d+ = 0.30, 95% CI = 0.18 to 0.41, k = 47) and prevention knowledge (d+ = 0.39, 95% CI = 0.25 to 0.52, k = 65) following mass media interventions compared with pre-campaign assessments. Nonetheless, the hypothesis of homogeneity was rejected for each outcome; the effects on each of these dimensions were characterized by large heterogeneity (I2 > 91, Ps < 0.001; see Table S2, Supplemental Digital Content, http://links.lww.com/QAI/A540), necessitating the use of a priori determined effect modifiers to explain the variation in study effects. For published articles, trim-and-fill results showed asymmetries for prevention knowledge, suggesting publication bias, but Begg test results and Egger test results were nonsignificant for asymmetries on all 3 outcomes (see Table S2).
Several dimensions were related to the magnitude of effect sizes gauging condom use (Table 2). Greater increases in condom use occurred following interventions conducted in African nations, in countries with lower HDI scores (Fig. 3), following longer campaigns, when message content was reportedly matched to the target audience, and when refusal rates were low. Condom use also increased to the extent that campaigns increased knowledge of transmission (β = 0.56, P = 0.009, k =16) and prevention (β = 0.30, P = 0.03, k = 41).
Transmission and Prevention Knowledge
Increases in HIV/AIDS transmission and prevention knowledge were largest in Asian nations. Improvement in transmission knowledge was greater to the extent that the nation had a lower HDI and a larger proportion of the sample reported exposure to the campaign. Increases in prevention knowledge were larger following longer campaigns. Interventions that reportedly included demonstrations of condom use did not significantly improve prevention knowledge compared with interventions that did not report condom demonstrations. No other coded report characteristics (eg, publication status), campaign characteristics (eg, number of communication channels, message branding, reported theoretical background, condom distribution) or sample characteristics (eg, age, gender, proportion sexually active, pre-campaign rate of condom use) were significant predictors of effect size magnitude for any outcome of interest.
Results from the current meta-analysis of 54 reports evaluating 72 interventions demonstrated that mass media-delivered interventions increase condom use and improve transmission and prevention knowledge. To the best that we know, our meta-analysis is the first to examine published and unpublished mass media reports across the world. Average effect sizes in this study were of small to medium magnitude (0.25–0.39; Table 1); yet, results were marked by heterogeneity, and several study characteristics moderated intervention efficacy.
First, as previous meta-analytic work related to HIV prevention has demonstrated, this meta-analysis supports the conclusion that interventions achieve better results where the need is greatest,87–89 as demonstrated by the linkage between HDI and outcome measures (Table 2). Investing resources into areas of the world with lower social and economic development seems to yield greater returns than investing resources into those with greater development. In contrast, the CI results in Table 2 and in Figure 3 that include the value of 0 suggest that mass media interventions failed, on average, in relatively developed nations. The differential impact between nations scoring higher and lower on the HDI may be because of reduced “media clutter” in less developed nations, and differences in incidence rates and perceived risk.
Second, longer campaign duration related to increased condom use; the CI results in Table 2 suggest that mass media interventions failed, on average, in short duration campaigns. With regard to knowledge, the longer the campaign duration, the more prevention knowledge increased, and the higher the proportion of the sample that was exposed to intervention messages, the more transmission knowledge increased. Effect size magnitude did not vary because of age or gender. Increases in HIV/AIDS-related knowledge were also positively related to increased condom use. More recent campaigns demonstrated greater increases in transmission knowledge, but contrary to previous findings, we found no significant linkage between exposure and year of publication.15 Although the moderator for amount of exposure did not achieve formal significance levels, the CI results in Table 2 suggest that mass media interventions failed, on average, for those who had little exposure to the intervention, a pattern that appeared for condom use and the 2 knowledge dimensions.
Because most interventions included in this meta-analysis used multiple communication channels, it was impossible to tease apart the effects of different channels used in the interventions. Interventions often use as many communication channels as they can afford, consistent with studies that show reach and impact increasing as numbers of media and interpersonal channels increase.1,4,5 We found no evidence that number of channels was related to greater impact in the present meta-analysis. Unfortunately, studies tend to show the combined impact of all channels and messages; the way in which the media are used within an intervention may differ, and it would inform future interventions to know which types of media approaches work under what conditions.
Previous reviews of mass media–delivered interventions to prevent HIV/AIDS have addressed the variability in research design, methodology, and reporting of intervention development, content, and delivery.14–16 The most persistent hurdle in determining the efficacy of mass media campaigns is the lack of available comparison groups in the evaluation of these interventions; only 8 of the 72 interventions included in the present meta-analysis provided valid comparison group data. Because of the inability to reliably control access to mass media, it may be both difficult and costly to use true or quasi-experimental designs. As a result, many campaign evaluations compare pre- and post-campaign data or compare individuals who were or were not exposed to the campaign. Both of these evaluation methods have limitations. The former does not allow for direct attribution of changes in knowledge or behavior to the campaign message alone, although it is notable that in the current investigation, campaigns were more successful to the extent that more respondents reported exposure. Additional factors unrelated to a specific campaign, such as the social or political climate, public policy changes, current events, and the presence of multiple campaigns in a targeted area can influence HIV/AIDS-related knowledge and sexual risk behaviors, making it impossible to isolate intervention effects. Evaluations based solely on exposure are also limited in that exposure to mass media may be related to individual characteristics such as income, gender, relationship status, and age.90,91
As with other reviews, the results of the present meta-analysis are limited by the available studies and reflect the empirical state of the field. The intervention literature in general would benefit tremendously from the public availability of more quantitative evaluations (ie, using pre-campaign comparison groups or quasi-experimental designs), described in greater detail (eg, specifying media channels used). In cases where reporting space is limited, researchers can provide additional information regarding campaign details as online supplements to publications, provide references to more descriptive papers, or invite readers who desire additional information to contact them directly. It would also be beneficial to the literature to have studies include cost information to facilitate cost-effectiveness analyses. Additional information would allow for more nuanced theorizing about what sorts of mass media interventions may work best in different contexts.
Another limitation of the present study is that our database generally focused on short-term effects of the interventions, when media effects are most likely to be at their peak. In media research, effects tend to dissipate over time,92,93 and analysis of the rate of decay of HIV media interventions is best addressed in a meta-analysis designed to examine such effects. Still, intensive interpersonal HIV prevention strategies have been shown to have larger effects at extended periods (1–3 years) compared with briefer interpersonal interventions.94 Finally, the present article does not explore other aspects of campaign content and message design, and although campaigns from more than 30 countries were included, we limited our search to reports available in English.
Past meta-analyses of HIV prevention literature have focused almost exclusively on trials evaluating relatively intensive strategies that demand interpersonal interaction, often in small-group sessions that continue over a series of weeks or months.94–98 The current studies, in contrast, use media that often are brief, and only sometimes include interpersonal communication in clinics or with outreach workers. Despite the differences in channels between the current and previous meta-analyses, the effects on behavior change are similar in magnitude—small to medium, depending on moderating factors. Despite their modest size in absolute terms, for statewide or national media interventions the scope of their impact is quite large in absolute terms. Media campaigns are a means of “going to scale”—taking an intervention to large numbers of people.22
In summary, the present results provide strong testimony to the power that mass media campaigns can have for people living in nations most at need for HIV prevention and other health promotion interventions. Results also suggest that such campaigns generally lack effectiveness in relatively developed countries, where the need for health promotion is generally lessened except in particular locales.
1. Andreasen A. Marketing Social Change: Changing Behavior to Promote Health, Social Development, and the Environment. San Francisco, CA: Jossey-Bass; 1995.
2. Kotler P, Lee N. Social Marketing: Influencing Behaviors for Good. Thousand Oaks, CA: Sage; 2008.
3. Atkin CK, Freimuth VS. Formative evaluation research in campaign design. In: Rice RE, Atkin CK, eds. Public Communication Campaigns. 3rd ed. Thousand Oaks, CA: Sage; 2001:125–145.
4. Rogers EM. Diffusion of Innovations. 5th ed. New York, NY: Free Press; 2003.
5. Piotrow PT, Kincaid DL, Rimon JG III, et al.. Health Communication: Lessons from Family Planning and Reproductive Health. Westport, CT: Praeger; 1997.
6. National Cancer Institute. The Role of the Media in Promoting and Preventing Tobacco Use. Available at: http://cancercontrol.cancer.gov/Brp/tcrb/monographs/19/m19_complete.pdf
. Bethesda, MD: U.S. Department of Health & Human Services, National Institutes of Health, National Cancer Institute. Tobacco Control Monograph No. 19. NIH Pub. No 07–6242. Published June 2008.
7. Shea S, Basch CE. A review of five major community-based cardiovascular disease prevention programs. Part II: Intervention strategies, evaluation methods, and results. Am J Health Promot. 1990;4:279–287.
8. Snyder LB, Hamilton MA. Meta-analysis of U.S. health campaign effects on behavior: emphasize enforcement, exposure, and new information, and beware the secular trend. In: Hornik RC, ed. Public Health Communication: Evidence for Behavior Change. Hillsdale, NJ: Lawrence Erlbaum Associates; 2002:357–383.
9. Snyder LB, Hamilton MA, Mitchell EW, et al.. A meta-analysis of the effect of mediated health communication campaigns on behavior change in the United States. J Health Comm. 2004;9(suppl l):71–96.
10. Wellings K. Evaluating AIDS public education in Europe: a cross-national comparison. In: Hornik RC, ed. Public Health Communication: Evidence for Behavior Change. Hillsdale, NJ: Lawrence Erlbaum Associates; 2002:131–146.
11. Ross JA, Mauldin WP. Family planning programs: efforts and results, 1972-1994. Stud Fam Plann. 1996;27:137–147.
12. Snyder LB. Development communication campaigns. In: Mody B, ed. International and Development Communication: A 21st-Century Perspective. Thousand Oaks, CA: Sage; 2003:167–188.
13. Hornik R, Contreras-Budge E, McDivitt J, et al.. Communication for child survival: evaluation of “Healthcom” projects in ten countries. 1992. Unpublished manuscript. USAID Contract No. DPE-5984-Z-00-9018-00.
14. Myhre SL, Flora JA. HIV/AIDS communication campaigns: progress and prospects. J Health Comm. 2000;5(suppl l):29–45.
15. Noar SM, Palmgreen P, Chabot M, et al.. A 10-year systematic review of HIV/AIDS mass communication campaigns: have we made progress? J Health Comm. 2009;14:15–42.
16. Bertrand JT, O’Reilly K, Denison J, et al.. Systematic review of the effectiveness of mass communication programs to change HIV/AIDS-related behaviors in developing countries. Heath Educ Res. 2006;21:567–597.
17. Moher D, Liberati A, Tetzlaff J, et al.. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2002;6:e1000097.
18. World Bank. World Development Indicators 2007 [CD-rom]. Washington, DC; World Bank; 2007.
19. United Nations Development Programme. Statistics of the Human Development Report. New York, NY: Oxford University Press; 2008.
20. Hedges LV. Distribution theory for Glass's estimator of effect size and related estimators. J Educ Stat. 1981;6:107–128.
21. Lipsey MW, Wilson DB. Practical Meta-analysis. Thousand Oaks, CA: Sage; 2001.
22. Huedo-Medina TB, Johnson BT. Estimating the Standardized Mean Difference Effect Size and its Variance from Different Data Sources [Spreadsheet]. Storrs, CT: Authors; 2011.
23. Sanchez-Meca J, Marin-Martinez F, Chacon-Moscoso S. Effect-size indices for dichotomized outcomes in meta-analysis. Psychol Methods. 2003;8:448–467.
24. Harbord RM, Higgins JPT. Meta-regression in Stata. Stata J. 2008;8:493–519.
25. Stata Statistical Software: Release 11.2. [Computer Program]. College Station, TX: StataCorp LP; 2010.
26. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21:1539–1558.
27. Huedo-Medina TB, Sanchez-Meca J, Marin-Martinez F, et al.. Assessing heterogeneity in meta-analysis: Q statistic or I2 index? Psychol Methods. 2006;11:193–206.
28. Higgins JP, Thompson SG, Deeks JJ, et al.. Measuring inconsistency in meta-analyses. Br Med J. 2003;327:557–560.
29. Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994;50:1088–1101.
30. Duval S, Tweedie R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics. 2000;56:455–463.
31. Egger M, Davey Smith G, Schneider M, et al.. Bias in meta-analysis detected by a simple, graphical test. Br Med J. 1997;315:629–634.
32. Johnson BT, Huedo-Medina TB. Depicting estimates using the intercept in meta-regression models: the moving constant technique. Res Synth Methods. 2011;2:204–220.
34. Alstead M, Campsmith M, Halley CS, Hartfield K, Goldbaum G, Wood RW. Developing, implementing, and evaluating a condom promotion program targeting sexually active adolescents. AIDS Educ Prev. 1999;11:497–512.
35. American Refugee Committee (ARC) International. Post-Intervention Survey Report: HIV/AIDS/STI Knowledge, Attitudes and Practice (KAP) Survey Among Commercial Sex Workers, Military and Youth in Port Loko, Sierra Leone. Refugee Studies Centre. Available at: http://www.rhrc.org/resources/ARCSLPostInterventionSurvey.pdf
. Published August 2003.
36. Askew I, Chege J, Njue C, Radeny S. A multi-sectoral approach to providing reproductive health information and services to young people in western Kenya: Kenya adolescent reproductive health project. Population Council In-house Project No: 5800 13042. USAID Cooperative Agreement No: HRN-A-00-98-00012-00. Available at: http://www.popcouncil.org/pdfs/frontiers/FR_FinalReports/Kenya_KARP%20Adol.pdf
. Published June 2004.
37. Brown J. Evaluation of the impact of the protector condom campaign in Malawi. Social Marketing for Change (SOMARC) Occasional Paper No. 19. Available at: http://pubs.futuresgroup.com/sop19iht.pdf
. Published May 1994.
38. Caron SL, Davis CM, Wynn RL, Roberts LW. “America responds to AIDS,” but did college students? Differences between March, 1987, and September, 1988. AIDS Educ Prev. 1992;4:18–28.
39. de Vroome EMM, Paalman MEM, Sandfort TGM. AIDS in the Netherlands: The effects of several years of campaigning. Int J STD AIDS. 1990;1:268–275.
40. Duff D, Muthuswamy N, Singhal A. Quantitative report #2: A pre-post sentinel site survey in Bihar, India assessing the effects of Taru. In: Singhal A, Witte K, Muthuswamy N, Duff D, et al., eds. Effects of Taru, a Radio Soap Opera, on Audiences in India: A Quantitative and Qualitative Analysis. Athens, OH: Ohio University, School of Communication Studies. Consolidated report submitted to Population Communications International. Available at: http://utminers.utep.edu/asinghal/technical%20reports/TARU-CONSOLIDATED-Report.pdf
. Published January 2004.
41. Elkins D, Maticka-Tyndale E, Kuyyakanond T, Kiewying M, Anusornteerakul S, Chantapreeda N, et al.. Evaluation of HIV/AIDS education initiatives among women in northeastern Thai villages. Southeast Asian J Trop Med Pub Health. 1996;27:430–442.
42. Elkins D, Maticka-Tyndale E, Kuyyakanond T, Miller P, Haswell-Elkins M. Toward reducing the spread of HIV in northeastern Thai villages: Evaluation of a village-based intervention. AIDS Educ Prev. 1997;9:49–69.
43. Great Britain Department of Health and Social Security. AIDS: Monitoring Response to the Public Education Campaign February 1986-February 1987. London, United Kingdom: Her Majesty's Stationary Office; 1987.
44. Hattori MG, Richter K, Greene J. Trust, caution, and condom use with regular partners: an evaluation of the trusted partner campaign targeting youth in four countries. Soc Market Quart. 2010;16:18–48.
46. Keating J, Meekers D, Adewuyi A. Assessing effects of a media campaign on HIV/AIDS awareness and prevention in Nigeria: results from the VISION Project. BMC Pub Health. 2006;6:123.
47. Kim YM, Kols A, Nyakauru R, Marangwanda C, Chibatamoto P. Promoting sexual responsibility among young people in Zimbabwe. Int Fam Plan Perspec. 2001;27:11–19.
48. Lehmann P, Hausser D, Somini B, Gutzwiller F. Campaign against AIDS in Switzerland: evaluation of a nationwide educational programme. Brit Med J. 1987;295:1118–1120.
49. Manafa OU, Ahmed OA, Omotola BD. Post-intervention survey on the knowledge, attitudes, beliefs and practices of people in Lagos State, Nigeria about HIV/AIDS. World Health Pop. 2006;8:35–45.
50. Martínez-Donate AP, Zellner JA, Sanudo F, et al.. Hombres Sanos: evaluation of a social marketing campaign for heterosexually identified Latino men who have sex with men and women. Am J Pub Health. 2010;100:2532–2540.
51. McCombie S, Hornik R. Evaluation of a Workplace-Based Peer Education Program Designed to Prevent AIDS in Uganda. Final report. Working Paper No. 1011. USAID Contract No. DPE 5972-Z-00-7070-00. University Park, PA: University of Pennsylvania, Annenberg School for Communication, Center for International, Health and Development Communication. Published April 1992.
52. McCombie S, Hornik RC, Anarfi JK. Effects of a mass media campaign to prevent AIDS among young people in Ghana. In: Hornik RC, ed. Public Health Communication: Evidence for Behavior Change. Hillsdale, NJ: Lawrence Erlbaum Associates; 2002.
54. Meekers D. Going underground and going after women: trends in sexual risk behaviour among gold miners in South Africa. Int J STD AIDS. 2000;11:21–26.
55. Meekers D. The effectiveness of targeted social marketing to promote adolescent reproductive health: the case of Soweto, South Africa. J HIV/AIDS Prev Educ Adolesc Children. 2000;3:73–92.
56. Merritt AP, Kincaid DL, Lujan M, Varela L. Mass media AIDS prevention campaign in Lima, Peru. Paper presented at: The 117th Annual Meeting of the American Public Health Association; 1997; Chicago, IL.
57. Milleliri JM, Krentel A, Rey JL. Sensitisation about condom use in Gabon (1999): evaluation of the impact of a comic book. Sante. 2003;13:253–264.
58. Mills S, Campbell MJ, Waters WE. Public knowledge of AIDS and the DHSS advertisement campaign. Brit Med J. 1986;293:1089–1090.
59. Pauw J, Ferrie J, Villegas RR, Martinez JM, Gorter A, Egger M. A controlled HIV/AIDS-related health education programme in Managua, Nicaragua. AIDS. 1996;10:537–544.
60. Plautz A, Meekers D. The Reach and Impact of the PSI Adolescent Reproductive Health Program in Butare Province, Rwanda. Washington, DC: Population Services International Research Division Working Paper No. 56. Available at: http://paa2004.princeton.edu/papers/41247
. Published 2003.
61. Plautz A, Meekers D. Evaluation of the reach and impact of the 100% Jeune youth social marketing program in Cameroon: findings from three cross-sectional surveys. Reprod Health. 2007;4:1.
62. 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. Washington, DC: Population Services International Research Division Working Paper No. 57. Published 2003.
63. Rigby K, Brown M, Anagnostou P, Ross MW, Rosser BRS. Shock tactics to counter AIDS: the Australian experience. Psychol Health. 1989;3:145–159.
64. Rimal RN, Creel AH. Applying social marketing principles to understand the effects of the Radio Diaries program in reducing HIV/AIDS stigma in Malawi. Health Mark Q. 2008;25:119–146.
65. Sherr L. An evaluation of the UK government health education campaign on AIDS. Psychol Health. 1987;1:61–72.
66. Sikkema KL, Kelly JA, Winett RA, et al.. Outcomes of a randomized community-level HIV prevention intervention for women living in 18 low-income housing developments. Am J Public Health. 2000;90:57–63.
67. Singer E, Rogers TF, Glassman MB. Public opinion about AIDS before and after the 1988 U.S. Government public information campaign. Public Opin Quart. 1991;55:161–179.
68. Sood S, Singh PK, Sarwal R. Reaching the underserved: measuring the impact of a community media intervention, Uttar Pradesh, India. Int Q Community Health Educ. 2004;23:117–138.
69. Sood S, Shefner-Rogers CL, Sengupta M. The impact of a mass media campaign on HIV/AIDS knowledge and behavior change in North India: results from a longitudinal study. Asian J Commun. 2006;16:231–250.
70. Tambashe BO, Speizer IS, Amouzou A, Djangone AMR. Evaluation of the PSAMO “Roulez Protege” mass media campaign in Burkina Faso. AIDS Educ Prev. 2003;15:33–48.
71. Thompson ME, Harutyunyan TL. Impact of a community-based integrated management of childhood illnesses (IMCI) programme in Gegharkunik, Armenia. Health Policy Plan. 2009;24:101–107.
72. Tian L, Songyuan T, Cao W, Zhang K, Li V, Detels R. Evaluation of a web-based intervention for improving HIV/AIDS knowledge in rural Yunnan, China. AIDS. 2007;21(Suppl 8):S137–S142.
73. Trykker H, Kalumba K, Hamming A, Eberhard M. Changes in public knowledge and awareness of AIDS in Zambia. AIDS. 1992;6:1408–1409.
74. Tweedie I. Evaluation of the “We Are All At Risk” HIV/AIDS Prevention Campaign in Ghana, 1994–1995: Key Findings. Baltimore, MD: Johns Hopkins Bloomberg School of Public Health, Center for Communication Programs; 1999.
75. Underwood C, Serlemitsos E, Chabwela P, Bharath U, Hachonda H. Impact of the Heart Campaign: Findings From the 2003 Survey of Zambian Youth. Baltimore, MD: Johns Hopkins Bloomberg School of Public Health, Center for Communication Programs; 2004.
76. 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;38:55.e1–55.e13.
77. Van Rossem R, Meekers D. An Evaluation of the Effectiveness of Targeted Social Marketing to Promote Adolescent and Reproductive Health in Guinea. Washington, DC: Population Services International Research Division Working Paper No. 23. Available at: http://www.psi.org/sites/default/files/publication_files/WP23.pdf
. Published 1999.
78. 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;12:383–404.
79. Vaughan PW, Regis A, St. Catherine E. Effects of an entertainment-education radio soap opera on family planning and HIV prevention in St. Lucia. Int Fam Plan Perspectives. 2000;26:148–157.
80. Vaughan PW, Rogers EM, Singhal A, Swalehe RM. Entertainment-education and HIV/AIDS prevention: a field experiment in Tanzania. J Health Comm. 2000;5:81–100.
81. Vernon R, Ojeda G, Murad R. Incorporating AIDS prevention activities into a family planning organization in Columbia. Stud Family Plan. 1990;21:335–343.
82. Weir S, Figueroa JP, Byfield L, et al.. A Randomized Controlled Trial to Investigate Impact of Site-Based Safer Sex Programs in Kingston, Jamaica: Trial Design, Methods, and Results. MEASURE Evaluation Report No. TR-09-64. USAID Cooperative Agreement No. GPO-A-00-03-00003-00. Chapel Hill, NC: Carolina Population Center. Available at: http://www.cpc.unc.edu/measure/publications/tr-09-65
. Published October 2009.
83. Wober JM. Informing the British public about AIDS. Health Educ Res. 1988;3:19–24.
84. Xiangyang T, Lan Z, Xueping M, Tao Z, Yuzhen S, Jagusztyn M. Beijing health promoting universities: practice and evaluation. Health Promot Int. 2003;18:107–113.
85. Yoder H, Chirwa. Evaluating the program effects of a radio drama about AIDS in Zambia. Stud Family Plan. 1996;27:188–203.
86. Zimmerman RS, Palmgreen PM, Noar SM, Lustria MLA, Lu HY, HoroseWithinki ML. Effects of a televised two-city safer sex mass media campaign targeting high-sensation-seeking and impulsive-decision-making young adults. Health Educ Behav. 2007;34:810–826.
87. Huedo-Medina TB, Boynton MH, LaCroix JM, et al.. Efficacy of HIV prevention intervention in Latin American and Caribbean Nations, 1995–2008: a meta-analysis. AIDS Behav. 2010;14:1237–1244.
88. LaCroix JM, Pellowski JA, Lennon CA, et al.. Behavioural interventions to reduce sexual risk for HIV in heterosexual couples: a meta-analysis. Sex Transm Infect. 2013;89:620–627.
89. Tan JY, Huedo-Medina TB, Warren MR, et al.. A meta-analysis of the efficacy of HIV/AIDS prevention interventions in Asia, 1995–2009. Soc Sci Med. 2012;75:676–687.
90. Sood S, Sengupta M. More is more! the dose-effect relationship between HIV/AIDS-related mass media exposure and HIV/AIDS knowledge and behavior outcomes. Paper presented at the annual meeting of the International Communication Association; May 27-31, 2004; New Orleans, LA.
91. Mizuno Y, Kennedy M, Weeks-Norton K, et al.. An examination of adolescents who were and were not exposed to “Teens Stopping AIDS”: reaching the hard-to-reach. J Health Comm. 2002;7:197–203.
92. Broadbent S. Spending Advertising Money: An Introduction to Media Planning, Media Buying and the Uses of Media Research. 3rd ed. London, United Kingdom: Business Books; 1979.
93. Watt JH, Mazza M, Snyder L. Agenda setting effects of television news coverage and the effects decay curve. Commun Res. 1993;20:408–435.
94. Johnson BT, Scott-Sheldon LA, LaCroix JM, et al.. Behavioral interventions for African-Americans to reduce sexual risk of HIV: a meta-analysis of randomized controlled trials. J Acquir Immune Defic Syndr. 2009;51:492–501.
95. Albarracín D, Gillette J, Earl A, et al.. A test of assumptions about behavior change: a comprehensive look at HIV prevention interventions since the beginning of the epidemic. Psychol Bull. 2005;131:856–897.
96. Johnson BT, Scott-Sheldon LAJ, Carey MP. Meta-synthesis of health behavior change meta-analyses? Am J Public Health. 2010;100:2193–2198.
97. Johnson BT, Carey MP, Marsh KL, et al.. Interventions to reduce sexual risk for the Human Immunodeficiency Virus in adolescents, 1985-2000: a research synthesis. Arch Pediatr Adolesc Med. 2011;165:77–84.
98. Noar SM. Behavioral interventions to reduce HIV-related sexual risk behavior: review and synthesis of meta-analytic evidence. AIDS Behav. 2008;12:335–353.
HIV/AIDS; global health; mass media; health promotion; sexual health
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