External Publications Using GUI Data

The increasing emphasis on inclusive education internationally has broadened the definition of special educational needs (SEN) and greatly affected national prevalence estimates. In line with these international trends, in Ireland the EPSEN Act (2004) defines SEN as any “restriction in the capacity of a person to participate in or benefit from education”. Taking this broad definition, this study draws on the first longitudinal study of children in Ireland, Growing Up in Ireland, to generate a new estimate of SEN prevalence among Irish nine-year-old children. The analysis combines detailed information, collected from parents and teachers, encompassing diverse types of SEN, including physical disabilities, speech impairments, learning disabilities and emotional/behavioural difficulties. In doing so, the study establishes a SEN prevalence rate of 25 per cent among children in the mid-primary years, a rate very much in line with recent research in other European contexts. Additionally, the study details the diversity of data collected on children and young people with SEN and disabilities across agencies and government departments, the potential value of this data and directions for improved learner databases.

Within categories of special educational needs, emotional and behavioural difficulties have received much attention in recent years, particularly in relation to their definition and identification by parents and teachers. This paper stems from previous research which highlights how children from disadvantaged backgrounds and those attending schools designated as socio-economically disadvantaged are significantly more likely than their peers to be identified as having a special educational need of a non-normative type such as emotional behavioural difficulty (EBD). Using data from the Growing Up in Ireland study, it examines whether the EBD identified by teachers or within certain schools is matched by the child’s own performance on an internationally validated emotional and mental health measure – the Piers–Harris. Findings show that overall self-reported social emotional well-being bears a strong relationship to the probability of being identified with an EBD. However, boys, children from economically inactive and one-parent households and children attending the most disadvantaged school contexts are more likely to be identified with having an EBD, even after taking into account their social background characteristics and their scoring on the Piers–Harris measure. These findings suggest that the subjective nature of EBD identification is resulting in a disproportionate number of these children being identified with EBD. The implications of this study are explored for existing disability/SEN classification systems, school-wide intervention models and the impact on individual students labelled as EBD. Overall, the findings pose searching questions about the validity of employing SEN classification systems in deciding eligibility and types of appropriate provision.

This article uses two longitudinal cohort studies (Growing Up in Ireland and the National Educational Panel Study) to examine how shadow education relates to academic performance in Ireland and Germany. Patterns of take-up of, and outcomes from, shadow education are found to reflect the particular country context—aimed at maintaining performance to avoid grade retention in Germany and preparing for a high-stakes upper secondary exam in Ireland. Participation enhances academic performance but only for students with lower levels of prior achievement. However, the relationship is not much stronger than with engagement in structured out-of-school activities. Thus, shadow education appears to be one of a number of strategies used by more privileged families to secure educational advantage.

Background:
Regulatory problems in infancy are associated with internalizing and externalizing symptom trajectories across childhood. It is unknown whether early screen media exposure exacerbates the association between infant regulatory problems and childhood internalizing and externalizing symptom trajectories.

Methods:
We studied 10,170 individuals from the Growing Up in Ireland ’08 cohort. Parents reported on their children’s regulatory problems at 9 months, screen media exposure at 3 years, and internalizing and externalizing symptoms at 3, 5, 7, and 9 years. Children were categorized based on their patterns of co-developing internalizing and externalizing symptoms using parallel process latent class growth analysis. Subsequently, multinominal logistic regression analyses were conducted to estimate whether screen media exposure (>1 hour or >2 hours) moderated the association between regulatory problems in infancy and co-developing internalizing and externalizing symptom classes across childhood.

Results:
There were four groups of children with distinct patterns of co-developing internalizing and externalizing symptoms: 1) low stable internalizing and low decreasing externalizing symptoms (N= 6236; 61.3%); 2) low stable internalizing and moderate stable externalizing symptoms (N= 2029; 20%); 3) moderate increasing internalizing and moderate decreasing externalizing symptoms (N= 1263; 12.4%); 4) moderate increasing internalizing and high increasing externalizing symptoms (N= 642; 6.3%). Presence of regulatory problems at 9 months and excessive screen media exposure at 3 years (particularly >2 hours) were independently associated with increased likelihood of all classes. Excessive screen media exposure at 3 years did not significantly moderate the association between regulatory problems at 9 months and internalizing and externalizing symptom trajectories.

Conclusions:
Both regulatory problems in infancy and screen media exposure >2 hours in early childhood are early risk factors for the development of internalizing and externalizing symptoms. However, the association between infant regulatory problems and childhood internalizing and externalizing symptoms appears to operate independently of excessive screen media exposure. Clinicians should be aware of, and treat, regulatory problems in infancy to prevent chronic patterns of self-regulatory problems across childhood. Further, they should discuss and advocate for family media plans with parents to help decrease the long-term negative effects on internalizing and externalizing symptoms.

Introduction
Despite a growing body of research on associations between adolescent digital use and well-being, few studies have investigated these associations a) longitudinally and b) across socioeconomic status. The present study uses high-quality longitudinal data to examine how digital engagement shapes socioemotional and educational outcomes from early to late adolescence across socioeconomic status (SES).

Methods
Participants are 7685 individuals (49.0% female) from the 1998 birth cohort of the longitudinal Growing Up In Ireland (GUI) survey. The survey was administered to Irish parents and children between 2007 and 2016 (at ages 9, 13, and 17/18). Fixed-effects regression modeling was used to establish associations between digital engagement and socioemotional and educational outcomes. Further Fixed-Effects models were analyzed separately by SES, to assess how associations between digital use and adolescent outcomes differ by socioeconomic groups.

Results
Results show that digital screen time increases markedly from early to late adolescence, but to a higher extent among low-SES versus high-SES groups. Heavy levels of digital screen time (i.e., 3+ hours daily) are associated with declines in well-being, particularly for external and prosocial functioning, while engagement in learning-oriented digital activities and gaming is associated with better adolescent outcomes. Yet, low-SES adolescents are globally more harmed than high-SES adolescents by their digital engagement, and high-SES adolescents benefit more from moderate levels of digital use and from engaging in learning-oriented digital activities.

Conclusions
This study suggests that digital engagement is associated with socioeconomic inequalities in adolescents’ socioemotional well-being and, to a lesser extent, educational outcomes.

Background
There is growing concern around youth mental health. A population health approach to improve mental health must address, among other issues, economic insecurity, access to housing and education, harm reduction from substance use. As a universal public health intervention, increasing physical activity at a population level may have an important role in our approach. The aim of this study was to examine the longitudinal association between physical activity patterns between childhood and early adolescence and emotional-behavioural difficulties in later adolescence.

Methods
This study was based on data from the ′98 Child cohort of the Growing Up in Ireland Study. Participants were categorized according to physical activity levels at ages 9 and 13. Emotional-behavioural difficulties at age 17 were measured using the parent-reported Strengths and Difficulties Questionnaire. Logistic regression was used to examine the association between physical activity and emotional-behavioural outcomes.

Results
Among 4618 participants included in the regression model, those categorized as Inactive (n=1607) or Reducer (n=1662) were more than twice as likely to have emotional-behavioural difficulties at age 17 compared with those who were Active [adjusted odds ratio (AOR) 2.1, 95% CI 1.46–3.01, P<0.001; AOR 1.93, 95% CI 1.34–2.76, P<0.001, respectively]. Among those with emotional-behavioural difficulties at baseline (n=525), those categorized as Active had 2.3-fold reduced odds for emotional-behavioural problems at age 17 compared with those who were Inactive (AOR 0.43, 95% CI 0.23–0.78, P=0.006).

Conclusions
Increasing physical activity among adolescents is a safe and sustainable public health intervention associated with improved mental health.

The first 1000 days of life are a period of unique sensitivity and plasticity during which critical cognitive abilities are formed. Routine developmental screening tools aim to identify infants who would benefit from early intervention. While these tools have been validated for detecting children with more severe neurodevelopmental disorders, their ability to identify the larger proportion with below average cognitive function has not been sufficiently explored. The aim of this study was to examine the validity of the Ages and Stages Questionnaire (ASQ), for identifying children with later below average cognitive function.

The study population (n=8260) is formed from two national cohort studies, the Growing Up in Ireland (GUI) Infant cohort (n=7,444) and the Cork BASELINE cohort (n=816). The ASQ was completed at 8 months and 24-27 months respectively. Cognitive assessments were performed at age 5. Those scoring <1 standard deviation (SD) below the mean were categorised as below average cognitive function. Applying the currently used onward referral criterion (one fail in any domain) the sensitivity, specificity, positive and negative predictive values of the 8- and 24-27- month ASQ for detecting children with later below average cognitive function were calculated.

In the GUI cohort n=905 participants (12.5%) had scores <1SD below the mean on the Picture Similarities Scale. In the BASELINE cohort n=101 participants (13.4%) had an IQ <1SD below the cohort mean. Applying the currently used onward referral criterion (failing in any one domain in the ASQ), the sensitivity of the 8-month ASQ for detecting children scoring <1SD below the mean on the Picture Similarities Scale at age 5 was 16.4% (95% CI 14.0-19.0). The specificity was 92.0% (95% CI 91.3-92.6), with a positive predictive value (PPV) of 22.6% (95% CI 19.5-26.0) and a negative predictive value (NPV) of 88.5% (95% CI 87.7%-89.2%).

In the BASELINE cohort n=468 participants completed the 24-month ASQ and n=316 the 27-month ASQ. Applying the same onward referral criterion to the 24- and 27- month ASQ combined, the sensitivity for detecting those with an IQ <1SD below the cohort mean was 20.8% (95% CI 13.6-30.2) and the specificity was 91.1% (95% CI 88.6-93.2).

The ASQ has a low sensitivity for identifying children with below average cognitive function at age 5. The findings of this study suggest that if we are to intervene early in the developmental trajectory for children with below average cognitive function alternative methods of identifying high risk infants are needed.

Children with below average cognitive function represent a substantial yet under-researched population for whom academic and social demands, which increase in complexity year by year, pose significant challenge. Effects on emotional-behavioural development (EBD) are not well understood. The aim of this study was to compare trajectories of EBD for children with and without below average cognitive function. The underlying hypothesis was that trajectories of EBD would differ between groups, with divergence occurring as children are subject to increasingly complex cognitive demands.

Participants consist of 7,000 children and caregivers who completed the Growing Up in Ireland survey at age 3,5 and 9 years. Cognitive function was measured at age 3 using the Picture Similarities Scale. A t-score 1-2 standard deviations below the mean was categorised as below average cognitive function (n=767), and scores above this categorised as average cognitive function (n=6418). EBD was measured using the Strengths and Difficulties Questionnaire (SDQ) at age 3,5 and 9. Repeated measures ANOVA was used to examine the difference between the overall group means across the repeated measures of SDQ, the SDQ change over time, and the interaction between cognitive group and change over time. Further analysis of trajectories was performed using latent growth curve analysis.

Compared to those with average cognitive function, a significantly higher proportion of children with below average function were male (61.8% v 38.2%, χ2 (1, N=7134) = 42.07 p<0.001), born to a single parent family (22.4% v 14.7%, χ2 (1, N=7134) = 23.15 p<0.001), and had a parent who smoked (35.6% v 25.8%, χ2 (1, N=7134) = 33.23 p<0.001). Children with below average cognitive function had significantly higher mean total SDQ scores at all ages. Repeated measures ANOVA demonstrated a significant group-by-time interaction effect (F(2,7182)=4.649, p=0.010). The mean difference (MD) in SDQ between cognitive groups increased over time (MD Age 3:0.87, 95% confidence interval (CI) 0.53-1.21, Age 9 MD:1.49,95% CI 1.08-1.91). For those with average or above cognitive function the overall SDQ decreased between age 3-9 (MD: -0.49 95% CI -0.65—0.33). This decrease was not seen for those with below average function, who had a non-statistically significant increase in SDQ between age 3-9.

Children with below average cognitive function experience higher and worsening mean SDQ scores throughout childhood. A scalable method of early identification of children at risk for below average cognitive function should be a research priority for public health, enabling early intervention for cognitive and adaptive outcomes.

Background
There are no early, accurate, scalable methods for identifying infants at high risk of poor cognitive outcomes in childhood. We aim to develop an explainable predictive model, using machine learning and population-based cohort data, for this purpose.

Methods
Data were from 8858 participants in the Growing Up in Ireland cohort, a nationally representative study of infants and their primary caregivers (PCGs). Maternal, infant, and socioeconomic characteristics were collected at 9-months and cognitive ability measured at age 5 years. Data preprocessing, synthetic minority oversampling, and feature selection were performed prior to training a variety of machine learning models using ten-fold cross validated grid search to tune hyperparameters. Final models were tested on an unseen test set.

Results
A random forest (RF) model containing 15 participant-reported features in the first year of infant life, achieved an area under the receiver operating characteristic curve (AUROC) of 0.77 for predicting low cognitive ability at age 5. This model could detect 72% of infants with low cognitive ability, with a specificity of 66%.

Conclusions
Model performance would need to be improved before consideration as a population-level screening tool. However, this is a first step towards early, individual, risk stratification to allow targeted childhood screening.

Impact
• This study is among the first to investigate whether machine learning methods can be used at a population-level to predict which infants are at high risk of low cognitive ability in childhood.
• A random forest model using 15 features which could be easily collected in the perinatal period achieved an AUROC of 0.77 for predicting low cognitive ability.
• Improved predictive performance would be required to implement this model at a population level but this may be a first step towards early, individual, risk stratification.

Background
Parental incarceration (PI) is associated with adverse developmental outcomes for children affected. However, research in this area often reports conflicting results with few studies following children across time in non-U.S. populations. Additionally, more research is called for using multi-informant perspectives rather than relying on adult reports of child outcomes alone.

Methods
This study used data from the first two waves of a nationally representative cohort study of 8,568 children aged 9 years and followed up at age 13 living in the Republic of Ireland (2007–2012). Propensity score matching was used to match children who had experienced PI by the age of nine to children who had not experienced PI by sociodemographics and experience of other stressful events. Mental health, as measured by self-concept (Piers-Harris II) and externalizing and internalizing difficulties (strength and difficulties questionnaire), was compared across both groups.

Results
Fifty of the 8,568 children (weighted percentage 0.9%) reported experiencing PI by the age of nine. These children came from more socially disadvantaged homes and were more likely to have experienced other potentially stressful life events. In comparison to a matched sample of children not affected by PI, children affected by PI reported higher levels of anxiety at age nine. Longitudinal analysis indicated these children affected by PI also reported lower levels of happiness at age 13 with higher levels of emotional difficulties reported by their primary caregiver.

Conclusions
Children of incarcerated parents face a greater array of life challenges. PI had an association with child-reported levels of anxiety at age nine. PI also had a medium-term association on caregiver assessments of emotional difficulties of children affected as well child-reported levels of happiness over time.

Previous research has suggested that the children of teenage parents are at a high risk of developing both internalising and externalising behaviour disorders. The current study aimed to explore pathways through which children of teenage mothers show more externalising and internalising psychopathology than their peers whose parents were older. The present study used data from the first wave of the ‘Growing Up in Ireland’ 9-year-old cohort and employed structural equation modelling to assess the explanatory value of a model informed by previous research findings. Goodness-of-fit indices indicated that many aspects of the familial environment of Irish teenage families did indeed place children at a substantial risk of problematic developmental outcomes. In particular, the results implicated the influential power of economic stability and familial conflict on the well-being of teenage families and related child outcomes, results similar to those reported in international studies.

Keywords: teenage mothers in Ireland, economic stability, externalising problems, internalising problems

Aims
This study aims to replicate Przybylski and Weinstein (Psychol Sci 28(2):204–215, 2017), using a large population cohort to examine the validity of the proposed Goldilocks Hypothesis, which states that moderate digital media engagement may be beneficial and that both high and low usage may have a negative relationship with mental wellbeing.

Methods
Using the GUI98 cohort, we used separate weekday and weekend time-based categorical variables indicating time spent online, playing video games, watching TV/films as well as a frequency variable indicating multiscreening, and their associations with SDQ internalizing and externalizing symptoms using linear and quadratic regression parameters. We followed procedures for confounder adjustments outlined in Przybylski and Weinstein (Psychol Sci 28(2):204–215, 2017).

Results
As hypothesized by the Goldilocks Hypothesis, time spent online watching TV/films at the weekend and multiscreening all had curvilinear relationships with internalizing and externalizing symptoms with significantly higher symptoms for no time as well as for higher exposures. internalizing and externalizing symptoms increased with time spent playing video games.

Conclusions
This brief report supports the Goldilocks Hypothesis, that suggests that moderate use of digital technology is not intrinsically harmful and may instead be beneficial, even necessary in a world becoming ever more increasingly reliant on digital media (Przybylski and Weinstein in Psychol Sci 28(2):204–215, 2017).

Objectives
To assess the impact of digital media usage on psychiatric symptoms in an adolescent population utilizing a longitudinal cohort design.

Methods
Using two waves of the GUI child cohort, age 13 (N = 7527) and age 17/18 (N = 6126), we used latent class analysis (LCA) to create latent groups centred around self-reported time spent online, and the self-reported behaviours children engaged with online. At both waves, the 4 class latent model suited best. We used the different symptoms scales of the Strengths and Difficulties Questionnaires (SDQ), self-reported, at age 17 as our outcome variable. Using linear regression analysis, we then examined the associations between our latent class model and psychiatric symptoms, using moderate usage as our reference group, with adjustments being made for baseline psychiatric symptoms, maternal education and pre-diagnosed mental disorder.

Results
For females, placement in the high usage group at 13 was associated with increased internalizing symptoms, whereas placement in the high usage group at 17 was associated with an increase in all symptoms. For males, placement in the high usage group at 17 was associated with increased emotional symptoms, and placement in the “low usage & behaviour engagement”group, a group showing low reported time online and low engagement in our measured online behaviours at 17, was associated with an increase in all symptoms. Finally for both sexes, placement in the “moderate usage, entertainment only” group at age 13, (a group reporting no school-based online engagement), was associated with increases in all symptoms except emotional symptoms.

Conclusion
High digital media usage is associated with increased psychiatric symptoms in both males and females, with moderate usage associated with positive effects on symptoms compared to both our high usage, and low usage groups.

Keywords
Digital engagement, Psychiatric symptoms, Internet usage, Latent class analysis

Objective
This study aims to examine the associations between prenatal exposure to maternal smoking, birth weight and persistent offspring psychiatric symptoms. Additionally, we aim to examine whether the relationship between prenatal maternal smoking and persistent offspring psychiatric symptoms is mediated by offspring birth weight.

Methods
This study used the Growing Up in Ireland (GUI) longitudinal cohort. The GUI is a nationally representative longitudinal study of children which consisted of three data collection waves, at ages 9, 13, and 17 years. Logistic regression analysis was used to examine associations between prenatal tobacco exposure, and offspring psychiatric symptoms. Linear regression was used to examine associations between prenatal tobacco exposure and offspring birth weight. We conducted a mediation analysis examining potential etiological pathways linking maternal smoking during pregnancy, offspring birth weight, and later offspring psychiatric symptoms. All analyses were adjusted for confounders including household income, maternal level of education, and family psychiatric history. Additionally, examination of birth weight and subsequent psychiatric symptoms also was controlled for prematurity.

Results
We found that the association between prenatal tobacco exposure and later psychiatric symptoms is mediated by birth weight.

Conclusions
This work provides further evidence that maternal smoking during pregnancy is an important modifiable lifestyle factor that has an impact not just on the physical health of offspring but also their mental wellbeing. Supporting women with structured smoking cessation programs at the earliest stages of pregnancy should be a public health priority.