Search

Objective:Scant evidence exists indicating how governments in African countries consider the economic vulnerability of their populations when instituting initial social control policies. This study examined possible clusters of financial resilience among African countries and how these clusters predicted the length of social control policies. Method:We harmonized country-level financial resilience data from the World Bank 2019 Global Findex database, data on COVID-19 cases from the Africa Centres for Disease Control and Prevention, and social control data from government press releases. We used multivariate cluster analysis and geographically weighted regression to assess the level of savings, domestic remittance, self-employment, wages, emergency funds, and agricultural income—all predictors of financial resilience. Results:We found two profiles of financial resilience: 41% of countries were financially resilient, and 59% were not. We also found that financial resilience profiles predicted longer durations of initial social control policies but in varying directions and degrees depending on the country. Conclusion:The study sheds light on the heterogeneity of financial resilience among African countries and extends our knowledge of financial resilience vis-a-vis pandemic responses. Social protection programs must be developed and implemented to help populations cope during and after the pandemic.

This study focuses on trends in STEM performanceand inclusiveness. We examine performance trajectories in STEM subjects, the predictive role of social support and psychological well-being of students, and variations across student gender and school locality (rural vs urban). We used three waves of data from 135 junior high school students in Ghana. Multilevel growth curve modeling was used to assess the trajectories and the socio-environmental predictors of STEM performance, and posthoc power calculation was used to confirm the adequacy of the sample size. Results show that overall, students’ STEM performance improves over time. Minimal gender differences exist but depend on the subject area and evolve with time. We observed a nuanced “urban advantage,” with rural students starting well but declining over time. Among various indicators of social support and psychological well-being, teacher support was the strongest positive predictor of STEM performance. The study highlights the need to focus on the structural and cultural impediments to STEM education at the lower levels of education in order not to risk excluding marginalized groups early in the education system. Further, STEM interventions may do well to incorporate long-term measures to sustain girls’ interest, motivation, and efforts in STEM.

Researchers globally are testing the potential of economic empowerment interventions such as financial guidance, education savings accounts, and asset transfer to promote educational well-being. Yet limited evidence exists of these interventions’ quality and effectiveness in improving educational well-being outcomes such as school enrollment and academic achievement. This systematic review evaluates these interventions’ methodological strengths and weaknesses, describes common intervention components and outcomes measured, and assesses intervention effectiveness. Overall, 15 studies from Sub-Saharan Africa, North and Central America, Southeast Asia, and Europe were included in this review (age: 5–19 years). Over half of the intervention studies scored at/above the median (high rigor). Notable strengths include using experimental study designs, articulation of theoretical framework, longer follow-up periods, transparency about dropout/attrition rates, and the conduct of parallel intervention replications across multiple schools. Methodological weaknesses included not stating quality control measures and not reporting measurement validity and reliability. Overall, most interventions effectively improved educational well-being. Interventions were most effective at improving academic attendance/participation, performance, and achievement, and less effective in educational enrollment. As education is a key modifiable determinant of well-being, interventionists have a great opportunity to develop and implement tailored economic empowerment interventions to promote educational well-being.

Objective:This article is an exposition of the joint-modeling approach to testing intervention effects through the harmonization of longitudinal and time-to-event data. We demonstrate the advantages of the joint-modeling approach over the classical approach of separately analyzing these types of outcome data. Method:We used a subset of 150 participants from the Illinois Birth through Three Title IV-E Waiver intervention study, which collected longitudinal Devereux Early Childhood Assessment for Infants and Toddlers (DECA-I/T) scores and time-to-permanence data for up to 3 years. We ran and contrasted three competing models: Cox proportional hazard, linear mixed-effects, and joint modeling. Results:If analyzed separately, the DECA-I/T scores are highly nonsignificantly related to time to permanence (p=.929). However, when analyzed jointly, the significance level drops 88 percentage points, from .929 to .105. Because of its efficiency in addressing information loss when longitudinal and survival data are incorporated together, the joint model properly accounts for outcome-dependent missingness. Conclusion:This article highlights the utility of joint modeling in randomized longitudinal intervention studies by demonstrating its ability to preserve information from both longitudinal and time-to-event data, produce unbiased estimates, and retain higher statistical power than the traditional approach.

Objective:Intervention evaluation typically follows a frequentist paradigm: New analyses are conducted for each subsequent study, and findings are then used to improve policy practice. This approach largely ignores data from prior studies, leading to information loss and incomplete or inaccurate conclusions. Unlike the frequentist paradigm, the Bayesian paradigm uses formative data (as priors), which can be updated with the summative data, thus building on existing evidence about an intervention’s effectiveness. Method:This article uses data from the Safe Families for Children randomized controlled trial to illustrate how the Bayesian paradigm incorporates prior evidence at the formative phase with data at the summative phase to provide a more comprehensive analysis. This approach is consistent with the scientific principle of evidence building. We compare the merits of each paradigm on two evaluation criteria: (a) p-values from a chi-square test, and (b) the probability that the intervention is superior to the comparison group on three outcome variables (protective custody, deflection from foster care, and whether repeat victimization occurred). Results:The Bayesian paradigm consistently outperformed the frequentist paradigm. Conclusion:The Bayesian paradigm is superior to the frequentist paradigm in demonstrating the effectiveness of an intervention, as evidenced by smaller p-values and a higher probability that the intervention group outperformed the comparison group.

Objective:This article introduces Bayesian spatial–temporal modeling for social and health science research. We use the World Bank’s World Development Indicatorsdata on youth unemployment and HIV risk in Africa to illustrate the utility of the Bayesian paradigm in modeling space–time changes in outcomes. Method:Data on adolescents and young adults were collected in 36 African countries from 1991 to 2014. We examined associations between HIV risk and youth unemployment rates using 16 Bayesian Poisson models incorporating spatial and temporal autocorrelations. Results:The best fit to the data was the model with spatially uncorrelated heterogeneity, temporally correlated random-walk autocorrelation, and spatial–temporal interaction. HIV risk factors are spatially uncorrelated across 36 countries but temporally correlated (i.e., country and time interaction) over the data collection period. The relationship between HIV risk and unemployment rate is statistically nonsignificant because of large spatial–temporal variations. Conclusions:This article demonstrates the capacity of Bayesian modeling to incorporate spatial (neighborhood) and temporal (historical) information to reflect not only the influences of space and time but also their interactions on the phenomenon of interest. The Bayesian framework holds great promise for improving the dynamic targeting of interventions and strategies to achieve desired outcomes.

Samburu pastoralists often express the belief that formal education may be an alternative route out of poverty for poor pastoralists. The roles of parental wealth, livestock inheritance, and education in household wealth and income are investigated for two communities. Parental wealth and primary education, but not amount of livestock inherited, are positively associated with household wealth. Educational attainment is not statistically significantly associated with income. While livestock inheritance does not translate directly into greater wealth, there are structural advantages to membership in a wealthier family. The trade-off between investments in inheritance and herd growth versus formal education is discussed.

This study investigates current practices and attitudes regarding livestock inheritance and education. There is evidence that investments in education may in some cases replace traditional forms of livestock inheritance, re flecting current perceptions of the relative values of pastoralism and forms of employment for which formal education is required. This trend suggests that a long-standing and critical mechanism for intergenerational transmission of wealth is changing.

Student-directed projects are increasingly becoming a common phenomenon inschools of social work across the United States. Students acquire a great learningexperience from these projects, which sharpen their skills in leadership,innovation, and practice. Social work practitioners who go through such aprocess emerge having acquired knowledge beyond what is offered in the classroom.In this article we present a case study of 5 African graduate students whoengaged in innovative efforts to implement a social development interventionin Uganda. The discussion includes ways to support students who embark onstudent-directed projects in schools of social work.