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Methodological considerations in using the Network Scale Up (NSU) for the estimation of risky behaviors of particular age-gender groups: An example in the case of intentional abortion

BACKGROUND: Network Scale Up (NSU) is a promising tool for size estimation of sensitive issues. In this study we investigated the important methodological considerations to employ this method for estimating behaviors, such as abortion, which happens in a particular age-gender group. METHODS: We recr...

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Detalles Bibliográficos
Autores principales: Zamanian, Maryam, Zolala, Farzaneh, Haghdoost, Ali Akbar, Haji-Maghsoudi, Saeide, Heydari, Zeynab, Baneshi, Mohammad Reza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6559635/
https://www.ncbi.nlm.nih.gov/pubmed/31185067
http://dx.doi.org/10.1371/journal.pone.0217481
Descripción
Sumario:BACKGROUND: Network Scale Up (NSU) is a promising tool for size estimation of sensitive issues. In this study we investigated the important methodological considerations to employ this method for estimating behaviors, such as abortion, which happens in a particular age-gender group. METHODS: We recruited 1250 males and 1250 females aged 18 to 50. Abortion rate was calculated through direct question and NSU methodology. The NSU was applied on three sub-samples (male, female and aggregate). Integrating replies to 25 reference groups, we estimated the network size (C) of respondents and its age-gender structure. To calculate the part of network that is subject to abortion, we compared two approaches: proportional and data based. The Visibility Factor (VF) was calculated through 222 females who had abortion. Direct estimate was considered as gold standard. RESULTS: Using C’s derived from proportional method, the Relative Bias (RB) in the male and female samples was 33% and 84%. Applying the data-based C’s, the RB in the gender-specific and aggregate samples was 5% and 2%. CONCLUSION: The proportional method overestimates the prevalence. The data-based method to calculate the C is superior. The determination of the age-sex distribution of the network and the specific VF is essential.