| Literature DB >> 15676068 |
Dominique Meekers1, Stephen Rahaim.
Abstract
BACKGROUND: Over the past two decades, social marketing programs have become an important element of the national family planning and HIV prevention strategy in several developing countries. As yet, there has not been any comprehensive empirical assessment to determine which of several social marketing models is most effective for a given socio-economic context. Such an assessment is urgently needed to inform the design of future social marketing programs, and to avoid that programs are designed using an ineffective model.Entities:
Mesh:
Year: 2005 PMID: 15676068 PMCID: PMC548279 DOI: 10.1186/1471-2458-5-10
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Distribution of Years of Social Marketing Program Experience by Management Structure and by Socio-Economic Context
| Distribution of Program Years | ||||
| % NGO Affiliate | % Local Organizations | % Commercial Partnership | No. of Program Years | |
| Population Size | ||||
| <10 Million | 76.3% | 17.1% | 6.6% | 211 |
| 10–25 Million | 62.7% | 24.0% | 13.3% | 150 |
| 25+ Million | 72.5% | 9.0% | 18.5% | 189 |
| Urban Population | ||||
| <25% | 86.1% | 13.9% | 0.0% | 101 |
| 25–49% | 80.8% | 7.7% | 11.5% | 260 |
| 50+% | 47.0% | 31.0% | 22.0% | 168 |
| GNI per capita | ||||
| <$1000 | 97.0% | 3.0% | 0.0% | 132 |
| $1000–3000 | 68.2% | 18.6% | 13.2% | 258 |
| $3000+ | 52.3% | 24.5% | 23.2% | 151 |
| Phone mainlines per 1,000 | ||||
| <5 | 87.1% | 11.8% | 1.1% | 178 |
| 5–30 | 73.4% | 9.2% | 17.4% | 184 |
| 30+ | 53.8% | 27.4% | 18.8% | 186 |
| Television sets per 1,000 | ||||
| <20 | 88.2% | 10.1% | 1.8% | 169 |
| 20–100 | 70.9% | 18.7% | 10.4% | 182 |
| 100+ | 48.5% | 23.3% | 28.2% | 163 |
| Time Period | ||||
| 1986–93 | 56.4% | 25.4% | 18.3% | 126 |
| 1994–97 | 66.2% | 18.5% | 15.3% | 216 |
| 1998–01 | 85.9% | 8.0% | 6.1% | 213 |
| Region | ||||
| Eastern Europe | 100.0% | 0.0% | 0.0% | 16 |
| Africa | 89.7% | 7.7% | 2.6% | 273 |
| Asia | 64.2% | 17.5% | 18.3% | 137 |
| Latin America | 42.9% | 41.9% | 15.2% | 105 |
| Mid. East/N. Afr. | 13.6% | 0.0% | 86.4% | 22 |
| Total | 71.5% | 16.0% | 12.4% | 555 |
Effect of Socio-Economic Context on Condom Sales and CYP Among Social Marketing Programs Managed Through an NGO Affiliate (Random-Effects Regression GLS Coefficients)
| Per Capita Condom Sales | OC Sales | |
| Markets Two or More Products | .159*** | .017 |
| Program Maturity | ||
| 1–3 (ref) | ||
| 4–6 | .181*** | .001 |
| 7+ | .348*** | .003 |
| Time Period | ||
| <1994 (ref) | ||
| 1995–2001 | .143** | .004 |
| Population (in 10 millions) | -.006*** | -.000* |
| Percent Urban | -.002 | -.000 |
| Per Capita Gross National Income | -.003 | .007 |
| Phone mainlines per 1,000 | -.001 | -.000 |
| Constant | .260*** | (dropped) |
| R Square | .236 | .082 |
| Number of Program-Years | 374 | 90 |
| Number of Countries Included | 58 | 26 |
*** p < .01; ** p < .05; * p < .10
Effect of Socio-Economic Context on Condom Sales and CYP Among Social Marketing Programs Managed Through the Manufacturer's Model (Random-Effects Regression GLS Coefficients)
| Per Capita Condom Sales | OC Sales | |
| Markets Two or More Products | .078 | -.015* |
| Program Maturity | ||
| 1–3 (ref) | ||
| 4–6 | -.018 | .003 |
| 7+ | -.069 | .007 |
| Time Period | ||
| <1994 (ref) | ||
| 1995–2001 | .099 | .007 |
| Population (in 10 millions) | -.012*** | -.002 |
| Percent Urban | .001 | -.000 |
| Per Capita Gross National Income | -.111** | .015** |
| Phone mainlines per 1,000 | .001** | -.000 |
| Constant | .278** | .030 |
| R Square | .384 | .185 |
| Number of Program-Years | 54 | 55 |
| Number of Countries Included | 9 | 12 |
*** p < .01; ** p < .05; * p < .10
Effect of Socio-Economic Context on Condom Sales and CYP Among Social Marketing Programs Managed Through Local Organizations (Random-Effects Regression GLS Coefficients)
| Per Capita Condom Sales | OC Sales | |
| Markets Two or More Products | .075 | -.012 |
| Program Maturity | ||
| 1–3 (ref) | ||
| 4–6 | .158 | .022* |
| 7+ | .181 | .028** |
| Time Period | ||
| <1994 (ref) | ||
| 1995–2002 | .138 | -.010 |
| Population (in millions) | .036** | .008** |
| Percent Urban | -.012*** | .001 |
| Per Capita Gross National Income | .006 | .028*** |
| Phone mainlines per 1,000 | .001 | -.001*** |
| Constant | .436** | -.021 |
| R Square | .309 | .401 |
| Number of Program-Years | 80 | 63 |
| Number of Countries Included | 17 | 12 |
*** p < .01; ** p < .05; * p < .10