Selecting life course frameworks to guide and communicate large new cohort studies: Generation Victoria (GenV) case study

Creating the conditions for robust early language development for all-Part 1: Evidence-informed child language surveillance in the early years

BACKGROUND

The emergence of language in the early years is a major developmental accomplishment that underpins learning, enables social interaction and, later, is an indicator of well-being. Learning language is an effortless process for most, but can be challenging for others. There is a need to act early. First, because there are several social, environmental and family factors known to influence how language develops during the critical early years. Second, there is a robust association between a child's socio-economic circumstances and language outcomes. Put simply, children living in less advantaged circumstance have poorer language outcomes, which are apparent very early and persist across the lifespan. Third, children with demonstrated weaknesses in language learning in early childhood have poorer educational, employment, mental health and quality-of-life outcomes across the lifespan. Acting early to counter these impacts is important; however, there are several well-documented challenges in accurately identifying in the early years children who are at later risk of developmental language disorder (DLD) and to deliver prevention and intervention programmes to scale. This is critical because many services do not currently reach those who need them most; as many as 50% of children in need may not be receiving support.

AIM

To determine whether an improved surveillance system, based on best evidence, could be developed for the early years.

METHODS & PROCEDURES

We summarised findings from longitudinal, population or community studies that: (1) adopted bioecological models, (2) repeatedly measured language (including the early years) and (3) adopted similar methodologies, to identify factors that influence language outcomes.

MAIN CONTRIBUTION

The evidence confirmed that language development is not always stable but is characterized by distinct trajectories and each has distinguishing social, environmental features. Children in the change or fluctuating groups tend to live in less advantageous circumstances that may not always support and enable language development. Risk factors tend to cluster and accumulate across the early years and beyond, thereby markedly increasing the likelihood of poorer language outcomes later in life.

CONCLUSIONS & IMPLICATIONS

In this the first of two papers, designed to be read together, we integrate research on the social determinants of child language and propose they be embedded into surveillance models. This has the potential to reach more children and those living in disadvantaged circumstances. In the accompanying paper we combine this information with evidence-informed early prevention/intervention approaches and propose the design and implementation of an early language public health framework.

WHAT THIS PAPER ADDS

What is already known on the subject There are several well-documented challenges in accurately identifying in the early years children who are at later risk of DLD and reaching those most in need of language support. What this study adds to existing knowledge A combination of child, family and environmental determinants, collectively and cumulatively, play out over time and dramatically increase the risk of later language problems, in particular those children living in disadvantaged circumstances. We propose an improved surveillance system that incorporates these determinants be developed and that this be part of a whole of system approach to child language in the early years. What are the potential or actual clinical implications of this work? Clinicians intuitively act to prioritize children with multiple features or risks; however, they can only do so for those who present or are identified to be at risk. Given many children with language problems are not being reached by many early language services, it is reasonable to ask if this knowledge can be integrated to improve reach. Or is a different surveillance model required?

Synthesizing Core Outcome Sets for outcomes research in cohort studies: a systematic review

BACKGROUND

Life course studies are designed to "collect once, use multiple times" for observational and, increasingly, interventional research. Core Outcome Sets (COS) are minimum sets developed for clinical trials by multi-stakeholder consensus methodologies. We aimed to synthesize published COS that might guide outcomes selection for early life cohorts with an interventional focus.

METHODS

We searched PubMed, Medline, COMET, and CROWN for COS published before January 2021 relevant to four life stages (pregnancy, newborns, children <8 years, and parents (adults aged 18-50 years)). We synthesized core outcomes into overarching constructs.

RESULTS

From 46 COS we synthesized 414 core outcomes into 118 constructs. "Quality of life", "adverse events", "medication use", "hospitalization", and "mortality" were consistent across all stages. For pregnancy, common constructs included "preterm birth", "delivery mode", "pre-eclampsia", "gestational weight gain", "gestational diabetes", and "hemorrhage"; for newborns, "birthweight", "small for gestational age", "neurological damage", and "morbidity" and "infection/sepsis"; for pediatrics, "pain", "gastrointestinal morbidity", "growth/weight", "breastfeeding", "feeding problems", "hearing", "neurodevelopmental morbidity", and "social development"; and for adults, "disease burden", "mental health", "neurological function/stroke", and "cardiovascular health/morbidity".

CONCLUSION

This COS synthesis generated outcome constructs that are of high value to stakeholders (participants, health providers, services), relevant to life course research, and could position cohorts for trial capabilities.

IMPACT

We synthesized existing Core Outcome Sets as a transparent methodology that could prioritize outcomes for lifecourse cohorts with an interventional focus. "Quality of life", "adverse events", "medication use", "hospitalization", and "mortality" are important outcomes across pregnancy, newborns, childhood, and early-to-mid-adulthood (the age range relevant to parents). Other common outcomes (such as "birthweight", "cognitive function/ability", "psychological health") are also highly relevant to lifecourse research. This synthesis could assist new early life cohorts to pre-select outcomes that are of high value to stakeholders (participants, health providers, services), are relevant to lifecourse research, and could position them for future trials and interventional capability.

Enhancing Value and Uptake for Whole-Population Cohorts of Children and Parents: Methods to Integrate Registries into the Generation Victoria Cohort

Health registries are critical to understanding, benchmarking and improving quality of care for specific diseases and conditions, but face hurdles including funding, bias towards clinical rather than population samples, lack of pre-morbid and outcomes data, and absent cross-registry harmonisation and coordination. Children are particularly under-represented in registry research. This paper lays out novel principles, methods and governance to integrate diverse registries within or alongside a planned children's mega-cohort to rapidly generate translatable evidence. GenV (Generation Victoria) will approach for recruitment parents of all newborns (estimated 150,000) over two years from mid-2021 in the state of Victoria (population 6.5 million), Australia. Its sample size and population denominator mean it will contain almost all children with uncommon or co-morbid conditions as they emerge over time. By design, it will include linked datasets, biosamples (including from pregnancy), phenotypes and participant-reported measures, all of which will span pre-morbid to long-term outcomes. We provide a vignette of a planned new registry for high-risk pregnancies to illustrate the possibilities. To our knowledge, this is the first paper to describe such a methodology designed prospectively to enhance both the clinical relevance of a large multipurpose cohort and the value and inclusivity of registries in a population.