Overcoming Methodological Challenges in Evaluating Health Communication Campaigns
Evidence from Rural Bangladesh
Datos Bibliográficos
| ID | 10797331 |
|---|---|
| Autores | David K Guilkey (University of North Carolina at Chapel Hill, autor de correspondencia), Paul Hutchinson (0000-0002-5435-7799), Paul L Hutchinson |
| Año | 2011 |
| Volumen | 42 |
| Número | 2 |
| Páginas | 93-106 |
| Fecha de publicación | 2011-06-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Studies in Family Planning (JOURNAL) |
| Identificadores de la revista | ISSN: 0039-3665 • E-ISSN: 1728-4465 |
| Editorial | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/j.1728-4465.2011.00269.x |
| PMID | 21834411 |
| OpenAlex | W2104512479 |
| Idioma | EN |
| Citas recibidas | 4 |
| Referencias citadas | 28 |
In this study, we examine the effectiveness of the Smiling Sun multimedia health communication campaign in encouraging women to use family health services in rural Bangladesh. We control for endogenous program placement and address the potential endogeneity of self‐reported campaign exposure in health‐behavior equations by estimating a set of exposure, contraceptive‐use, and antenatal‐care equations by full information maximum likelihood (FIML). We find that evaluation methods that do not take into account these nonrandom characteristics of communication and program exposure may produce underestimates of program benefits. Relative to the exposure effect of 3.7 percentage points in the simple model of contraceptive use, the exposure effect in the FIML model is a larger 5.5 percentage points, corresponding to as many as 40,000 additional contraceptive users. We conclude that evaluations of health communication campaigns would benefit from methods such as estimation by FIML that address nonrandom exposure and program targeting
Behavior change communication · Developing country · Econometrics · Economic growth · Economics · Endogeneity · Environmental health · Estimation · Health services · Population · Program evaluation · Set (abstract data type · Statistics · Computer Science · Global Maternal and Child Health · Mathematics · Media Influence and Politics · Medicine · Poverty, Education, and Child Welfare
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| Obras citantes distintas | 4 |
|---|---|
| Citas por año | 0,31 |
| Intervalo de citas | 2013 - 2021 (9) |
| Velocidad de citación | historical |
| Altamente citado | No |
| Tipos de cita | Neutras: 4 |