The livelihood impacts of cash transfers in sub-Saharan Africa: beneficiary perspectives from six countries

Cash transfers (CTs) are a social protection mechanism to reduce the poorest households’ vulnerability to shocks and build human capital by smoothing consumption and sustaining expenditure on education and social welfare. Our study examines whether and how CTs go beyond welfare objectives to promote livelihoods. Presenting a cross-case analysis using original qualitative data on beneficiary perspectives from six African countries - Kenya, Ethiopia, Malawi, Lesotho, Zimbabwe and Ghana – we explore CT livelihood impacts within household economies and social networks, paying attention to gender issues. We find that a small but predictable flow of cash improves strategic livelihood choices and stimulates productive investments, including through positive effects on beneficiary entry into risk-sharing arrangements and networks for economic collaboration. Levels of household vulnerability and labour constraint nevertheless significantly mediate the ability of CTs to consolidate present livelihood outcomes. The varying availability of economic opportunities and effective programme implementation also shape livelihood impact. Incorporating beneficiary perspectives brings to the fore the multi-dimensionality of CT effects on experiences of poverty and deprivation, including gender dynamics and intangibles such as dignity and respect; they add powerful realism to the influence of the CT on both immediate survival and livelihood choices. Beyond this, they confirm wider knowledge on productive impact and bring nuance to the conditions under which, and mechanisms by which beneficiaries’ use CTs to build productive capability and assets and to make strategic livelihood choices

Generating demand for and use of evaluation evidence in government health ministries: Lessons from a pilot programme in Uganda and Zambia

Background The Demand-Driven Evaluations for Decisions (3DE) programme was piloted in Zambia and Uganda in 2012-2015. It aimed to answer evaluative questions raised by policymakers in Ministries of Health, rapidly and with limited resources. The aim of our evaluation was to assess whether the 3DE model was successful in supporting and increasing evidence-based policymaking, building capacity and changing behaviour of Ministry staff. Methods Using mixed methods, we compared the ex-ante theory of change with what had happened in practice, why and with what results (intended and unintended), including a qualitative assessment of 3DE's contribution. Data sources included a structured quality assessment of the five impact evaluations produced, 46 key informant interviews at national and international levels, structured extraction from 170 programme documents, a wider literature review of relevant topics, and a political economy analysis conducted in Zambia. Results We found that 3DE had a very limited contribution to changing evidence-based policymaking, capacity and behaviour in both countries as a result of having a number of aspirations not all compatible with one another. Co-developing evaluation questions was more time-consuming than anticipated, Ministry evidence needs did not fit neatly into questions suitable for impact evaluations and constricted timeframes for undertaking trials did not necessarily produce the most effective results and value for money. The evaluation recommended a focusing of objectives and a more strategic approach to strengthening evaluative demand and capacity. Conclusions Lessons emerge that are likely to apply in other low- and middle-income settings, such as the importance of supporting evaluative thinking and capacity within wider institutions, of understanding the political economy of evidence use and its uptake, and of allowing for some flexibility in terms of programme targets. Fixating on one type of evidence is unhelpful in the context of institutions like ministries of health, which require a wide range of evidence to plan and deliver programmes. In addition, having success tied to indicators, such as number of 'policy decisions made', provides potentially perverse incentives and neglects arguably more important aspects such as incremental programmatic adjustments and improved implementation.sch_iih15 [86]pub4897pu

Differences in the functional brain architecture of sustained attention and working memory in youth and adults

Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9- to 11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM model predicted WM performance both across and within children—and captured individual differences in later recognition memory—but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed 2 network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in each age group differently. Thus, functional connectivity (FC) predicts SA and WM in youth, with networks predicting WM performance differing more between youths and adults than those predicting SA

Semantic content outweighs low-level saliency in determining children's and adults' fixation of movies

To make sense of the visual world, we need to move our eyes to focus regions of interest on the high-resolution fovea. Eye movements, therefore, give us a way to infer mechanisms of visual processing and attention allocation. Here, we examined age-related differences in visual processing by recording eye movements from 37 children (aged 6–14 years) and 10 adults while viewing three 5-min dynamic video clips taken from child-friendly movies. The data were analyzed in two complementary ways: (a) gaze based and (b) content based. First, similarity of scanpaths within and across age groups was examined using three different measures of variance (dispersion, clusters, and distance from center). Second, content-based models of fixation were compared to determine which of these provided the best account of our dynamic data. We found that the variance in eye movements decreased as a function of age, suggesting common attentional orienting. Comparison of the different models revealed that a model that relies on faces generally performed better than the other models tested, even for the youngest age group (<10 years). However, the best predictor of a given participant’s eye movements was the average of all other participants’ eye movements both within the same age group and in different age groups. These findings have implications for understanding how children attend to visual information and highlight similarities in viewing strategies across development

Generating demand for and use of evaluation evidence in government health ministries: lessons from a pilot programme in Uganda and Zambia

Abstract Background The Demand-Driven Evaluations for Decisions (3DE) programme was piloted in Zambia and Uganda in 2012–2015. It aimed to answer evaluative questions raised by policymakers in Ministries of Health, rapidly and with limited resources. The aim of our evaluation was to assess whether the 3DE model was successful in supporting and increasing evidence-based policymaking, building capacity and changing behaviour of Ministry staff. Methods Using mixed methods, we compared the ex-ante theory of change with what had happened in practice, why and with what results (intended and unintended), including a qualitative assessment of 3DE’s contribution. Data sources included a structured quality assessment of the five impact evaluations produced, 46 key informant interviews at national and international levels, structured extraction from 170 programme documents, a wider literature review of relevant topics, and a political economy analysis conducted in Zambia. Results We found that 3DE had a very limited contribution to changing evidence-based policymaking, capacity and behaviour in both countries as a result of having a number of aspirations not all compatible with one another. Co-developing evaluation questions was more time-consuming than anticipated, Ministry evidence needs did not fit neatly into questions suitable for impact evaluations and constricted timeframes for undertaking trials did not necessarily produce the most effective results and value for money. The evaluation recommended a focusing of objectives and a more strategic approach to strengthening evaluative demand and capacity. Conclusions Lessons emerge that are likely to apply in other low- and middle-income settings, such as the importance of supporting evaluative thinking and capacity within wider institutions, of understanding the political economy of evidence use and its uptake, and of allowing for some flexibility in terms of programme targets. Fixating on one type of evidence is unhelpful in the context of institutions like ministries of health, which require a wide range of evidence to plan and deliver programmes. In addition, having success tied to indicators, such as number of ‘policy decisions made’, provides potentially perverse incentives and neglects arguably more important aspects such as incremental programmatic adjustments and improved implementation

Getting the most out of participatory impact assessment: reflections from a multi-country cash transfer impact assessment

Mixed methods approaches are widely used in impact evaluations, but all too often a ‘methodological gap’ emerges between broad, large-scale surveys and in depth, small-scale qualitative investigation that can be difficult to bridge. In this CDI Practice Paper by Jeremy Holland, Ramlatu Attah, Valentina Barca, Clare O’Brien, Simon Brook, Eleanor Fisher and Andrew Kardan, we reflect on a multi-country impact assessment of cash transfer programmes in sub-Saharan Africa. Within a broader mixed methods suite of research modules we discuss specifically the design of a qualitative module that used participatory methods to integrate quantitative and qualitative data and analysis. We conclude that future impact assessment designs can utilise this self standing ‘within‑module’ participatory research approach to move beyond an impact assessment norm of often poorly integrated large-scale quantitative surveys and in-depth qualitative investigation

Additional file 1: of Generating demand for and use of evaluation evidence in government health ministries: lessons from a pilot programme in Uganda and Zambia

Extended theory of change. (PDF 471 kb

Functional brain connectivity predicts sleep duration in youth and adults

Sleep is critical to a variety of cognitive functions and insufficient sleep can have negative consequences for mood and behavior across the lifespan. An important open question is how sleep duration is related to functional brain organization which may in turn impact cognition. To characterize the functional brain networks related to sleep across youth and young adulthood, we analyzed data from the publicly available Human Connectome Project (HCP) dataset, which includes n-back task-based and resting-state fMRI data from adults aged 22–35 years (task n = 896; rest n = 898). We applied connectome-based predictive modeling (CPM) to predict participants' mean sleep duration from their functional connectivity patterns. Models trained and tested using 10-fold cross-validation predicted self-reported average sleep duration for the past month from n-back task and resting-state connectivity patterns. We replicated this finding in data from the 2-year follow-up study session of the Adolescent Brain Cognitive Development (ABCD) Study, which also includes n-back task and resting-state fMRI for adolescents aged 11–12 years (task n = 786; rest n = 1274) as well as Fitbit data reflecting average sleep duration per night over an average duration of 23.97 days. CPMs trained and tested with 10-fold cross-validation again predicted sleep duration from n-back task and resting-state functional connectivity patterns. Furthermore, demonstrating that predictive models are robust across independent datasets, CPMs trained on rest data from the HCP sample successfully generalized to predict sleep duration in the ABCD Study sample and vice versa. Thus, common resting-state functional brain connectivity patterns reflect sleep duration in youth and young adults