GROWING UP IN IRELAND. Cohort '08 (Infant Cohort). Design, Instrumentation and Procedures for Cohort ’08 of Growing Up in Ireland at 9 Years Old (Wave 5)

Growing Up in Ireland is the national longitudinal cohort study of children that commenced in 2006. The study has followed two groups of Irish children: Cohort ’98 (so-called because most of them were born in 1998; formerly called the ‘Child Cohort’); and Cohort ’08 (most of whom were born a decade later in 2008; formerly called the ‘Infant Cohort’). The primary aim of the study is to provide a strong evidence base to improve the understanding of children’s and young people’s health and development across a range of domains. This information is used to inform government policy in relation to children, yong people and their families

Growing Up in Ireland: Key findings from the special COVID-19 survey of Cohorts ’98 and ‘08. ESRI Growing Up in Ireland March 2021.

In a new short report released today, the ESRI and Trinity College Dublin launch the results of a special survey of COVID-19 experiences for children and young adults participating in Growing Up in Ireland. These first insights highlight the extent of changes to everyday life as a result of the pandemic and point to likely inequalities in impact

Growing Up in Ireland: Growing up and developing as an adult: A review of the literature on selected topics pertaining to cohort ’98 at age 20 years. ESRI Report December 2020.

The goal of this report is to provide research information on selected potential research questions using data collected in interviews with 20-year-olds and their parents. At the time of writing, fieldwork was under way, so the topics of the survey were known but not the outcome of the interviews. The research questions address the central outcomes of the Growing Up in Ireland study that contribute to building developmental trajectories from childhood to adulthood: socio-emotional well-being; educational and cognitive development; physical health and growth. Three potential research questions are outlined under each outcome and provide a short supporting review of the national and international literature, followed by a description of the measures in Growing Up in Ireland useful in exploring the topic. While there is a wide array of possible research questions with a dataset such as this, the selected topics are those that offer new potential given the measures at this particular wave and/or are particularly salient to this phase of the life-course

Design, instrumentation and procedures for Cohort ‘08 of Growing Up in Ireland at 9 years old (Wave 5).

Growing Up in Ireland is the national longitudinal cohort study of children that commenced in 2006. The study has followed two groups of Irish children: Cohort ’98 (so-called because most of them were born in 1998; formerly called the ‘Child Cohort’); and Cohort ’08 (most of whom were born a decade later in 2008; formerly called the ‘Infant Cohort’). The primary aim of the study is to provide a strong evidence base to improve the understanding of children’s and young people’s health and development across a range of domains. This information is used to inform government policy in relation to children, young people and their families. This report gives details of the data collection and research methods used. The study covers a broad range of child outcomes with a view to documenting how well children and young people in Ireland are developing. In so doing, it can facilitate comparison with findings from similar studies of children in other countries, as well as establishing typical patterns for children in Ireland. Being longitudinal in nature, the study also addresses developmental trajectories over time and explores the factors that most affect those trajectories and the life chances of children in Ireland today. By providing comprehensive data on a representative national sample of Irish children, the study informs and contributes to the setting of responsive policies and the design of services for children and their families

Growing Up in Ireland: The lives of 9-year-olds of cohort '08. ESRI Growing up in Ireland June 2021.

This report provides a descriptive analysis of the findings from detailed interviews conducted between June 2017 and April 2018 with 8,032 9-year-olds and their families from Cohort ’08 (formerly known as the Infant Cohort) of the Growing Up in Ireland study. These families were first interviewed when the Study Child was 9 months old (September 2008 to March 2009) and followed up at 3 years of age (January-August 2011) and 5 years of age (March-September 2013). An inter-wave postal survey was conducted when the cohort was 7/8 years of age (March-October 2016). Responses at 9 years of age represented 72 per cent of the original sample interviewed at Wave 1. The data have been re-weighted to account for differential response across different groups. Capturing experiences and outcomes in middle childhood is crucial as peers become more important in children’s lives and they take a more active role in shaping the nature of their play and activities. Middle childhood is also an important period for developing social and cognitive skills and for children’s emerging self-concept. Behaviours at this stage, including physical activity and diet, may have longer-term consequences for physical health and well-being

Growing Up in Ireland. National Longitudinal Study of Children. Report 6 2018

This report provides a descriptive analysis of the findings from detailed interviews with 13-year-olds and their parents in the Growing Up in Ireland study. The purpose of the report is to present a broad, comprehensive overview of the lives of the Child Cohort at age 13 and to describe how they are faring in important areas of their lives. Preliminary key findings from data collected at age 13 were published in November 2012. This report explores data from this wave of data collection in more detail and expands on the issues covered in those key findings. In the current report, findings are explored on a longitudinal basis, allowing insights into developmental trajectories for the cohort since the age of nine years. Exploration into interactions between multiple factors on the lives of young people are also presented, a type of analysis that was not possible in previous cross-sectional reports

GROWING UP IN IRELAND. COHORT ’08 (Infant Cohort). Report on the Pilot for Wave Five of the Cohort ’08 Survey (at 9 Years of Age)

This report summarises the experience of the pilot fieldwork with the Growing Up in Ireland Cohort ’08 (formerly the Infant Cohort) at 9 years of age. This wave represents the fifth survey for this cohort who were first interviewed at age 9 months – and subsequently surveyed at 3, 5 and 7/8 years. It is also the first time that the younger cohort has reached an age where there was also data collection for Cohort ’98 (formerly the Child Cohort). The report is intended to inform data-users of the role played by the pilot process in informing the final instrumentation and procedures for the main phase of data collection

Deprescribing in multi-morbid older people with polypharmacy: agreement between STOPPFrail explicit criteria and gold standard deprescribing using 100 standardized clinical cases

Purpose: Older people with advanced frailty are among the highest consumers of medications. When life expectancy is limited, some of these medications are likely to be inappropriate. The aim of this study was to compare STOPPFrail, a concise, easy-to-use, deprescribing tool based on explicit criteria, with gold standard, systematic geriatrician-led deprescribing. Methods: One hundred standardized clinical cases involving 1024 medications were prepared. Clinical cases were based on anonymized hospitalized patients aged ≥ 65 years, with advanced frailty (Clinical Frailty Scale ≥ 6), receiving ≥ 5 regular medications, who were selected from a recent observational study. Level of agreement between deprescribing methods was measured by Cohen’s kappa coefficient. Sensitivity and positive predictive value of STOPPFrail-guided deprescribing relative to gold standard deprescribing was also measured. Results: Overall, 524 medications (51.2%) of medications prescribed to this frail, elderly cohort were potentially inappropriate by gold standard criteria. STOPPFrail-guided deprescribing led to the identification of 70.2% of the potentially inappropriate medications. Cohen’s kappa was 0.60 (95% confidence interval 0.55–0.65; p < 0.001) indicating moderate agreement between STOPPFrail-guided and gold standard deprescribing. The positive predictive value of STOPPFrail was 89.3% indicating that the great majority of deprescribing decisions aligned with gold standard care. Conclusions: STOPPFrail removes an important barrier to deprescribing by explicitly highlighting circumstances where commonly used medications can be safely deprescribed in older people with advanced frailty. Our results suggest that in multi-morbid older patients with advanced frailty, the use of STOPPFrail criteria to address inappropriate polypharmacy may be reasonable alternative to specialist medication review

Predicting 1‐year mortality in older hospitalized patients: external validation of the HOMR Model

Objectives: Accurate prognostic information can enable patients and physicians to make better healthcare decisions. The Hospital‐patient One‐year Mortality Risk (HOMR) model accurately predicted mortality risk (concordance [C] statistic = .92) in adult hospitalized patients in a recent study in North America. We evaluated the performance of the HOMR model in a population of older inpatients in a large teaching hospital in Ireland. Design: Retrospective cohort study. Setting: Acute hospital. Participants: Patients aged 65 years or older cared for by inpatient geriatric medicine services from January 1, 2013, to March 6, 2015 (n = 1654). After excluding those who died during the index hospitalization (n = 206) and those with missing data (n = 39), the analytical sample included 1409 patients. Measurements: Administrative data and information abstracted from hospital discharge reports were used to determine covariate values for each patient. One‐year mortality was determined from the hospital information system, local registries, or by contacting the patient's general practitioner. The linear predictor for each patient was calculated, and performance of the model was evaluated in terms of its overall performance, discrimination, and calibration. Recalibrated and revised models were also estimated and evaluated. Results: One‐year mortality rate after hospital discharge in this patient cohort was 18.6%. The unadjusted HOMR model had good discrimination (C statistic = .78; 95% confidence interval = .76‐.81) but was poorly calibrated and consistently overestimated mortality prediction. The model's performance was modestly improved by recalibration and revision (optimism corrected C statistic = .8). Conclusion: The superior discriminative performance of the HOMR model reported previously was substantially attenuated in its application to our cohort of older hospitalized patients, who represent a specific subset of the original derivation cohort. Updating methods improved its performance in our cohort, but further validation, refinement, and clinical impact studies are required before use in routine clinical practice