29 research outputs found
Recent intimate partner violence as a prenatal predictor of maternal depression in the first year postpartum among Latinas
The study aims to determine if recent intimate partner violence (IPV) is a prenatal risk factor for postpartum depression (PPD) among pregnant Latinas seeking prenatal care. A prospective observational study followed Latinas from pregnancy through 13 months postpartum. Prenatal predictors of PPD included depression, recent IPV exposure, remote IPV exposure, non-IPV trauma history, poverty, low social support, acculturation, high parity, and low education. Postpartum depression was measured at 3, 7, and 13 months after birth with the Beck's Depression Inventory—Fast Screen. Strength of association was evaluated using bivariate and multivariable odds ratio analysis. Subjects were predominantly low income, monolingual Spanish, and foreign-born, with mean age of 27.7. Recent IPV, prenatal depression, non-IPV trauma, and low social support were associated with greater likelihood of PPD in bivariate analyses. Recent IPV and prenatal depression continued to show significant association with PPD in multivariate analyses, with greater odds of PPD associated with recent IPV than with prenatal depression (adjusted OR = 5.38, p < 0.0001 for recent IPV and adjusted OR = 3.48, p< 0.0001 for prenatal depression). Recent IPV exposure is a strong, independent prenatal predictor of PPD among Latinas. Screening and referral for both IPV and PPD during pregnancy may help reduce postpartum mental health morbidity among Latinas
Prevalence and risk of mental disorders in the perinatal period among migrant women: a systematic review and meta-analysis
Empirical study on the maintainability of Web applications: Model-driven Engineering vs Code-centric
Model-driven Engineering (MDE) approaches are often acknowledged to improve the maintainability of the resulting applications. However, there is a scarcity of empirical evidence that backs their claimed benefits and limitations with respect to code-centric approaches. The purpose of this paper is to compare the performance and satisfaction of junior software maintainers while executing maintainability tasks on Web applications with two different development approaches, one being OOH4RIA, a model-driven approach, and the other being a code-centric approach based on Visual Studio .NET and the Agile Unified Process. We have conducted a quasi-experiment with 27 graduated students from the University of Alicante. They were randomly divided into two groups, and each group was assigned to a different Web application on which they performed a set of maintainability tasks. The results show that maintaining Web applications with OOH4RIA clearly improves the performance of subjects. It also tips the satisfaction balance in favor of OOH4RIA, although not significantly. Model-driven development methods seem to improve both the developers’ objective performance and subjective opinions on ease of use of the method. This notwithstanding, further experimentation is needed to be able to generalize the results to different populations, methods, languages and tools, different domains and different application sizes.This paper has been co-supported by the DLSI, the Spanish Ministry of Education, and the University of Alicante under contracts TIN2010-15789 (SONRIA) and GRE10-23 (DISEMRIA)