Defining quality in early childhood settings: Experiences from the field

“The successful education of the child during her/his years of schooling and the participation of that child in society as an adult, depends to a greater degree upon the foundation laid during the early years” (Evans, Myers and IIfled, 2000, p.7). Research indicates that learning is crucial to development whereby knowledge, skills, attitudes and values are developed. Research from disciplines such as physiology, nutrition, health, sociology, psychology and education provide evidence indicating that the early years are crucial in terms of developing intelligence, personality and social behaviour of children. If children are not provided opportunities to communicate, learn and develop they will not attain the optimal level of development and therefore will not thrive. It is therefore imperative that people working with young children understand the multifaceted aspects of children’s development within the context in which they grow, think and learn. Children spend a major part of their day in schools ‘learning’ and in interacting with other children and the adult/s (teacher/s). This implies that the role of the adult and significant others in the children’s life play a crucial role in providing opportunities for optimal development which include an emotionally safe and healthy environment, supportive interactions and relationships, stimulation and time. These are all important and integral aspects of quality in early childhood settings. Furthermore, research conducted in the area of early childhood in the UK and US indicate that the determinants of quality are a stimulating physical environment, staff knowledge and understanding of the curriculum, knowledge of how young children learn, adult skill in supporting children and helping parents to support children’s learning at home. (EPPE project, UK, 1999 to date). Katz, (1991) also indicates similar characteristics of quality. The quality standards that the Certificate in Education: Early Childhood Education Development (CE:ECED) programme at AKU-IED is based on the High/Scope quality determinants which include a stimulating physical environment, consistent 157 daily routines catering both to child-initiated and adult-initiated experiences, positive and sustained interactions between the adult and the child and positive relationships between other adults working with and for the children. This paper will present the findings that have emerged from our observations and work in a variety of early childhood settings as a part of the support we extend to the course participants of the CE:ECED programme and have been derived from our work over a period of four years (2001-2005). The data has been collected through systematic classroom observations including field notes, photographs, videos, children’s work and conferencing with teachers and children. Findings from the data reveal that teachers’ perception of their sense of efficacy and capabilities, their understanding of curriculum, prior knowledge of how young children think and develop, the school infrastructure, the parental partnerships, leadership and the administrative and academic organization are some of the major factors that effect quality of teaching and learning in early childhood settings. This paper will define quality in teaching and learning as have emerged from our findings

From knowing our needs to enacting change: findings from community consultations with indigenous communities in Bangladesh

Introduction: Indigenous peoples are among the most marginalized peoples in the world due to issues relating to well-being, political representation, and economic production. The research consortium Goals and Governance for Global Health (Go4Health) conducted a community consultation process among marginalized groups across the global South aimed at including their voices in the global discourse around health in the post-2015 development agenda. This paper presents findings from the consultations carried out among indigenous communities in Bangladesh. Methods: For this qualitative study, our research team consulted the Tripura and Mro communities in Bandarban district living in the isolated Chittagong Hill Tracts region. Community members, leaders, and key informants working in health service delivery were interviewed. Data was analyzed using thematic analysis. Findings: Our findings show that remoteness shapes the daily lives of the communities, and their lack of access to natural resources and basic services prevents them from following health promotion messages. The communities feel that their needs are impossible to secure in a politically indifferent and sometimes hostile environment. Conclusion: Communities are keen to participate and work with duty bearers in creating the conditions that will lead to their improved quality of life. Clear policies that recognize the status of indigenous peoples are necessary in the Bangladeshi context to allow for the development of services and infrastructure.publishedVersio

Understanding biological mechanisms underlying adverse birth outcomes in developing countries: Protocol for a prospective cohort (AMANHI bio-banking) study

Objectives: The AMANHI study aims to seek for biomarkers as predictors of important pregnancy-related outcomes, and establish a biobank in developing countries for future research as new methods and technologies become available.Methods: AMANHI is using harmonised protocols to enrol 3000 women in early pregnancies (8-19 weeks of gestation) for population-based follow-up in pregnancy up to 42 days postpartum in Bangladesh, Pakistan and Tanzania, with collection taking place between August 2014 and June 2016. Urine pregnancy tests will be used to confirm reported or suspected pregnancies for screening ultrasound by trained sonographers to accurately date the pregnancy. Trained study field workers will collect very detailed phenotypic and epidemiological data from the pregnant woman and her family at scheduled home visits during pregnancy (enrolment, 24-28 weeks, 32-36 weeks & 38+ weeks) and postpartum (days 0-6 or 42-60). Trained phlebotomists will collect maternal and umbilical blood samples, centrifuge and obtain aliquots of serum, plasma and the buffy coat for storage. They will also measure HbA1C and collect a dried spot sample of whole blood. Maternal urine samples will also be collected and stored, alongside placenta, umbilical cord tissue and membrane samples, which will both be frozen and prepared for histology examination. Maternal and newborn stool (for microbiota) as well as paternal and newborn saliva samples (for DNA extraction) will also be collected. All samples will be stored at -80°C in the biobank in each of the three sites. These samples will be linked to numerous epidemiological and phenotypic data with unique study identification numbers.Importance of the study: AMANHI biobank proves that biobanking is feasible to implement in LMICs, but recognises that biobank creation is only the first step in addressing current global challenges

Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks

Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques

Burden of severe maternal morbidity and association with adverse birth outcomes in sub-Saharan Africa and south Asia: protocol for a prospective cohort study

Objectives The AMANHI morbidity study aims to quantify and describe severe maternal morbidities and assess their associations with adverse maternal, fetal and newborn outcomes in predominantly rural areas of nine sites in eight South Asian and sub-Saharan African countries. Methods AMANHI takes advantage of on-going population-based cohort studies covering approximately 2 million women of reproductive age with 1- to 3-monthly pregnancy surveillance to enrol pregnant women. Morbidity information is collected at five follow-up home visits - three during the antenatal period at 24-28 weeks, 32-36 weeks and 37+ weeks of pregnancy and two during the postpartum period at 1-6 days and after 42-60 days after birth. Structured- questionnaires are used to collect self-reported maternal morbidities including hemorrhage, hypertensive disorders, infections, difficulty in labor and obstetric fistula, as well as care-seeking for these morbidities and outcomes for mothers and babies. Additionally, structured questionnaires are used to interview birth attendants who attended women's deliveries. All protocols were harmonised across the sites including training, implementation and operationalising definitions for maternal morbidities. Importance of the AMANHI morbidity study Availability of reliable data to synthesize evidence for policy direction, interventions and programmes, remains a crucial step for prioritization and ensuring equitable delivery of maternal health interventions especially in high burden areas. AMANHI is one of the first large harmonized population- based cohort studies being conducted in several rural centres in South Asia and sub-Saharan Africa, and is expected to make substantial contributions to global knowledge on maternal morbidity burden and its implications

Development and validation of a simplified algorithm for neonatal gestational age assessment - protocol for the Alliance for Maternal Newborn Health Improvement (AMANHI) prospective cohort study.

OBJECTIVE: The objective of the Alliance for Maternal and Newborn Health Improvement (AMANHI) gestational age study is to develop and validate a programmatically feasible and simple approach to accurately assess gestational age of babies after they are born. The study will provide accurate, population-based rates of preterm birth in different settings and quantify the risks of neonatal mortality and morbidity by gestational age and birth weight in five South Asian and sub-Saharan African sites. METHODS: This study used on-going population-based cohort studies to recruit pregnant women early in pregnancy (<20 weeks) for a dating ultrasound scan. Implementation is harmonised across sites in Ghana, Tanzania, Zambia, Bangladesh and Pakistan with uniform protocols and standard operating procedures. Women whose pregnancies are confirmed to be between 8 to 19 completed weeks of gestation are enrolled into the study. These women are followed up to collect socio-demographic and morbidity data during the pregnancy. When they deliver, trained research assistants visit women within 72 hours to assess the baby for gestational maturity. They assess for neuromuscular and physical characteristics selected from the Ballard and Dubowitz maturation assessment scales. They also measure newborn anthropometry and assess feeding maturity of the babies. Computer machine learning techniques will be used to identify the most parsimonious group of signs that correctly predict gestational age compared to the early ultrasound date (the gold standard). This gestational age will be used to categorize babies into term, late preterm and early preterm groups. Further, the ultrasound-based gestational age will be used to calculate population-based rates of preterm birth. IMPORTANCE OF THE STUDY: The AMANHI gestational age study will make substantial contribution to improve identification of preterm babies by frontline health workers in low- and middle- income countries using simple evaluations. The study will provide accurate preterm birth estimates. This new information will be crucial to planning and delivery of interventions for improving preterm birth outcomes, particularly in South Asia and sub-Saharan Africa