Estimation of Dynamic Bivariate Correlation Using a Weighted Graph Algorithm.

Dynamic correlation is the correlation between two time series across time. Two approaches that currently exist in neuroscience literature for dynamic correlation estimation are the sliding window method and dynamic conditional correlation. In this paper, we first show the limitations of these two methods especially in the presence of extreme values. We present an alternate approach for dynamic correlation estimation based on a weighted graph and show using simulations and real data analyses the advantages of the new approach over the existing ones. We also provide some theoretical justifications and present a framework for quantifying uncertainty and testing hypotheses.

Factors influencing the performance of community health workers: A qualitative study of Anganwadi Workers from Bihar, India.

Globally, there remain significant knowledge and evidence gaps around how to support Community Health Worker (CHW) programmes to achieve high coverage and quality of interventions. India's Integrated Child Development Services scheme employs the largest CHW cadre in the world-Anganwadi Workers (AWWs). However, factors influencing the performance of these workers remain under researched. Lessons from it have potential to impact on other large scale global CHW programmes. A qualitative study of AWWs in the Indian state of Bihar was conducted to identify key drivers of performance in 2015. In-depth interviews were conducted with 30 AWWs; data was analysed using both inductive and deductive thematic analysis. The study adapted and contextualised existing frameworks on CHW performance, finding that factors affecting performance occur at the individual, community, programme and organisational levels, including factors not previously identified in the literature. Individual factors include initial financial motives and family support; programme factors include beneficiaries' and AWWs' service preferences and work environment; community factors include caste dynamics and community and seasonal migration; and organisational factors include corruption. The initial motives of the worker (the need to retain a job for family financial needs) and community expectations (for product-oriented services) ensure continued efforts even when her motivation is low. The main constraints to performance remain factors outside of her control, including limited availability of programme resources and challenging relationships shaped by caste dynamics, seasonal migration, and corruption. Programme efforts to improve performance (such as incentives, working conditions and supportive management) need to consider these complex, inter-related multiple determinants of performance. Our findings, including new factors, contribute to the global literature on factors affecting the performance of CHWs and have wide application.

Means, Motives and Opportunity: determinants of community health worker performance.

The performance of community health workers (CHWs) typically depends on the interaction between their motivation (their intent to achieve personal and organisational goals) and the constraints that they face in doing so. These constraints can be both at the individual level, for example, whether the worker has the skills and knowledge required to deliver on their job role, and the organisational level, for example, whether the worker is provided with the resources required to perform. Designing interventions to improve the performance of CHWs requires identifying the constraints to performance in a particular context. Existing frameworks on CHW performance tend to be derived empirically, identifying a broad range of intervention design and contextual factors that have been shown to influence CHW performance. These may not always be able to guide policy makers to identify the precise cause of a specific performance problem in a particular context and develop an appropriate policy response. This article presents a framework to help practitioners and researchers diagnose the constraints to performance of CHWs and guide programmatic and policy responses. The Means, Motives and Opportunity (MMO) framework has been adapted from the SaniFOAM framework used to identify the determinants of sanitation behaviours. It is based on three interdependent and interacting domains: means (whether an individual is capable of performing), motives (whether an individual wants to perform) and opportunity (whether the individual has the chance to perform). A wide range of data sources are expected to be used when applying the MMO framework, especially qualitative research that captures the perspectives and lived realities of CHWs and their communities. In this article, we demonstrate how the MMO framework can be applied to identify the constraints to CHW performance using the case study of Anganwadi Workers (village nutrition workers) in Bihar, India.