A latent class analysis of attitudes concerning the acceptability of intimate partner violence in rural Senegal
Tóm tắt
Research concerning the causes and consequences of intimate partner violence (IPV), particularly in less developed areas of the world, has become prominent in the last two decades. Although a number of potential causal factors have been investigated the current consensus is that attitudes toward IPV on the individual level, likely representing perceptions of normative behavior, and the normative acceptability of IPV on the aggregate level likely play key roles. Measurement of both is generally approached through either binary indicators of acceptability of any type of IPV or additive composite indexes of multiple indicators. Both strategies imply untested assumptions which potentially have important implications for both research into the causes and consequences of IPV as well as interventions aimed to reduce its prevalence. Using survey data from rural Senegal collected in 2014, this analysis estimates latent class measurement models of attitudes concerning the acceptability of IPV. We investigate the dimensional structure of IPV ideation and test the parallel indicator assumption implicit in common measurement strategies, as well as structural and measurement invariance between men and women. We find that a two-class model of the acceptability of IPV in which the conditional probability of class membership is allowed to vary between the sexes is preferred for both men and women. Though the assumption of structural invariance between men and women is supported, measurement invariance and the assumption of parallel indicators (or equivalence of indicators used) are not. Measurement strategies conventionally used to operationalize the acceptability of IPV, key to modeling perceptions of norms around IPV, are a poor fit to the data used here. Research concerning the measurement characteristics of IPV acceptability is a precondition for adequate investigation of its causes and consequences, as well as for intervention efforts aimed at reducing or eliminating IPV.
Tài liệu tham khảo
García-Moreno C, Amin A. The sustainable development goals, violence and women’s and children’s health. Bulletin of the World Health Organization. 2016;94:396–7.
García-Moreno C, Zimmerman C, Morris-Gehring A, Heise L, Amin A, Abrahams N, et al. Addressing violence against women: a call to action. Lancet. 2015;385:1685–95.
Devries KM, Mak JYT, García-Moreno C, Petzold M, Child JC, Falder G, et al. The Global Prevalence of Intimate Partner Violence Against Women. Science. 2013;340:1527–8.
World Health Organization. Global and Regional Estimates of Violence Against Women: Prevalence and Health Effects of Intimate Partner Violence and Non-partner Sexual Violence. World Health Organization; 2013.
Abramsky T, Watts CH, Garcia-Moreno C, Devries K, Kiss L, Ellsberg M, et al. What factors are associated with recent intimate partner violence? Findings from the WHO multi-country study on women’s health and domestic violence. BMC Public Health. 2011;11:109.
Arango DJ, Morton M, Gennari F, Kiplesund S, Ellsberg M. Interventions to prevent or reduce violence against women and girls: a systematic review of reviews. The World Bank; 2014. http://documents.worldbank.org/curated/en/700731468149970518/Interventions-to-prevent-or-reduce-violence-against-women-and-girls-a-systematic-review-of-reviews. Accessed 28 Sep 2016.
Hindin MJ, Kishor S, Ansara DL. Intimate partner violence among couples in 10 DHS countries: predictors and health outcomes; 2008.
Heise L. What works to prevent partner violence? An evidence overview. 2011. http://strive.lshtm.ac.uk/resources/what-works-prevent-partner-violence-evidence-overview. Accessed 28 Sep 2016.
Bott S, Morrison A, Ellsberg M. Preventing and Responding to Gender-based Violence inmiddle and low-income countries: a global review and analysis. Washington, DC: World Bank Publications; 2005.
Hossain M, Zimmerman C, Kiss L, Abramsky T, Kone D, Bakayoko-Topolska M, et al. Working with men to prevent intimate partner violence in a conflict-affected setting: a pilot cluster randomized controlled trial in rural Côte d’Ivoire. BMC Public Health. 2014;14:1.
Jewkes R, Flood M, Lang J. From work with men and boys to changes of social norms and reduction of inequities in gender relations: a conceptual shift in prevention of violence against women and girls. Lancet. 2015;385:1580–9.
McCleary-Sills J. Jordanian social norms and the risk of intimate partner violence and limited reproductive agency. J Int Womens Studies. 2013;14:12–29.
Michau L, Horn J, Bank A, Dutt M, Zimmerman C. Prevention of violence against women and girls: lessons from practice. Lancet. 2015;385:1672–84.
Pierotti RS. Increasing rejection of intimate partner violence evidence of global cultural diffusion. Am Sociol Rev. 2013;78:240–65.
Hayes BE, Boyd KA. Influence of individual- and national-level factors on attitudes toward intimate partner violence. Sociol Perspect. 2017;60:685–701.
Okenwa-Emegwa L, Lawoko S, Jansson B. Attitudes Toward Physical Intimate Partner Violence Against Women in Nigeria. SAGE Open. 2016;6:2158244016667993..
Tsai AC, Kakuhikire B, Perkins JM, Vořechovská D, McDonough AQ, Ogburn EL, et al. Measuring personal beliefs and perceived norms about intimate partner violence: population-based survey experiment in rural Uganda. PLoS Med. 2017;14:e1002303.
Uthman OA, Lawoko S, Moradi T. Factors associated with attitudes towards intimate partner violence against women: a comparative analysis of 17 sub-Saharan countries. BMC Int Health Human Rights. 2009;9:14.
Speizer IS. Intimate partner violence attitudes and experience among women and men in Uganda. J Interpersonal Violence. 2010;25:1224–41.
Heise L, Kotsadam A. Cross-national and multilevel correlates of partner violence: an analysis of data from population-based surveys. Lancet Global Health. 2015;3:e332–40.
Kishor S, Subaiya L. Understanding women’s empowerment: a comparative analysis of demographic and health surveys (DHS) data. Macro International: Calverton, Maryland, USA; 2008. http://dhsprogram.com/pubs/pdf/CR20/CR20.pdf.
Hagenaars JA. Categorical longitudinal data log-linear panel, trend. Newbury Park, California: Sage Publications; 1990.
Goodman LA. Latent class analysis: the empirical study of latent types, latent variables, and latent structures. Appl Latent Class Analysis. 2002. https://doi.org/10.1017/CBO9780511499531.002.
Delaunay V, Douillot L, Rytina S, Boujija Y, Bignami S, Gning SB, et al. The Niakhar social networks and health project. MeX. 2019. https://doi.org/https://doi.org/10.1016/j.mex.2019.05.037.
Delaunay V. La situation démographique dans l’Observatoire de Niakhar : 1963-2014. Dakar: IRD; 2017. http://www.documentation.ird.fr/hor/fdi:010071521.
Enders CK, Bandalos DL. The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Struct Equ Model Multidiscip J. 2001;8:430–57.
Linda K. Muthén, Bengt O. Muthen. Mplus User’s Guide. 7th edition. Los Angeles: Muthén & Muthén; 1998.
Nylund KL, Asparouhov T, Muthén BO. Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct Equ Model Multidiscip J. 2007;14:535–69.