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Objectives: Subgroups of children may benefit more from working memory training than others. In this study, we aimed to examine whether response to the Cogmed Working Memory Training program differed for children with low IQ and elevated attention-deficit/hyperactivity disorder, emotional and behavioral symptoms, special health care needs, or by sex., Methods: We used data from the Memory Maestros trial, a population-based randomized controlled trial of the Cogmed program delivered at school ( n = 226) compared to usual teaching ( n = 226) in grade 1 children (mean age 6.9 years; SD 0.4) with low working memory. Cogmed comprises 20 to 25 sessions of 45-minute duration over 5 to 7 weeks. Children completed subtests from the Automated Working Memory Assessment to measure change in working memory from baseline to 6 months postrandomization., Results: After training, improved working memory standard scores (>1 SD) from baseline to 6 months were observed for approximately one-third of the children, with more than half maintaining stable scores (within 1 SD). However, similar outcomes were observed for children receiving usual teaching. Differential effect of Cogmed versus usual teaching was evident for children with elevated hyperactivity and/or inattention, who were less likely to show improved visuospatial working memory, but not for other subgroups studied., Conclusions: Children with elevated hyperactivity and/or inattention were less likely to show clinically meaningful improvement after Cogmed; however, differential effects were not evident for children with low IQ and elevated emotional and behavioral symptoms, special health care needs, or by sex. More research is needed to determine if training can improve working memory and, if so, for whom., Competing Interests: POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose., (Copyright © 2020 by the American Academy of Pediatrics.)

Background: Chronically ill children are at increased risk of poor learning outcomes. Knowledge of the predictors of learning outcomes for this group of people is important to inform the development of education supports that stand the best chance of being effective. This study explored the child, family, and school risk and protective factors during the child's transition to elementary school (aged 6-7 years) that were associated with learning outcomes when children were aged 10-11 years for both children with and without a chronic illness., Methods: Data from the Longitudinal Study of Australian Children were used. Predictor variables were entered into separate multivariate regression models for children with and without a chronic illness., Results: The strongest predictors of learning outcomes were the child's approach to learning, a consistent parenting style, and family socioeconomic position and were common for both children with and without a chronic illness but strongest for children with a chronic illness., Conclusion: A child's approach to learning and a consistent parenting style during the period of the child's transition to elementary school are important and potentially modifiable factors that are predictive of academic performance in later childhood. These factors are particularly relevant for children with a chronic illness, their parents/caregivers, teachers both hospital and school based, and pediatricians and can be used to inform interventions., (© 2018 John Wiley & Sons Ltd.)

Background: Improving children's sleep could lead to significant benefits in several functional domains. Recent research in adults suggests that intensive, adaptive cognitive training may be beneficial in improving sleep, although there is limited understanding whether this approach yields similar results in children., Objective: To determine whether a working memory training program improved sleep latency, sleep problems, and sleep duration on school and nonschool nights and whether there was a differential effect of the timing of training during the school day on sleep outcomes., Design/methods: Design: Population-based randomised controlled trial., Setting: Forty-four schools in Melbourne, Australia., Participants: All Grade 1 children (mean age = 6.9 years, SD 0.4) underwent WM screening using two subtests from the Automated Working Memory Assessment. Children with low verbal and/or visuo-spatial WM scores relative to their peers ('low WM', ∼25%) were randomised to intervention or control arms., Intervention: 20 to 25 computerised 25-min training sessions were conducted using the CogMed program, over 5-7 weeks at school., Outcomes: Parent-reported child sleep characteristics (time, latency, duration and problem) at 6 months post randomisation., Results: A total of 452 (26.0%) of 1723 children screened (64.1% of approached) met trial eligibility criteria, with 226 in each study arm. Of intervention children, 91% completed the minimum 20 days of training. Retention was 90.5% at 6 months. Adjusted regressions showed that intervention children did not have better sleep latency, duration, bedtime consistency or less sleep problems., Conclusion: It does not appear that adaptive working memory training during the school day can be used as a novel approach to improve children's sleep attributes up to 6 months post-randomisation, regardless of the time of day training is delivered., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Objective: In a nationally representative sample of Australian children at ages 4 to 5, 6 to 7, 8 to 9, 10 to 11, and 12 to 13 years, we aim to examine the (1) prevalence of sleep problems in children with and without special health care needs (SHCN); (2) association of sleep problems with child behavior, health-related quality of life, learning and parent mental health outcomes; and (3) whether associations between sleep problems and outcomes among children with SHCN are larger in magnitude than among children without SHCN., Method: Biennial data from 5 waves of the Growing Up in Australia Study., Exposures: Child SHCN as defined by the Children Special Health Care Needs Screener and parent report of child sleep problem., Outcomes: Child: parent-reported health-related quality of life; parent-reported and teacher-reported behavior; nonverbal and verbal cognition and teacher-reported learning. Parent: self-report mental health., Analysis: Logistic and linear regression, adjusted for family socioeconomic position., Results: Children with SHCN were more likely to have sleep problems, odds ranging from 2.0 (95% confidence interval [CI], 1.6-2.5) at 4 to 5 years to 3.9 (95% CI, 3.0-5.2) at 8 to 9 years. Compared with children who had neither condition, those with either sleep problems or SHCN had similarly poor child and maternal outcomes. Children with both SHCN and sleep problems had the poorest outcomes at every age (all p < .001). Tests of interaction found sleep problems are more strongly associated with poorer behavior and health-related quality of life among children with SHCN than those without during the preschool and early school years., Conclusion: Sleep problems in children with SHCN are common and are associated with poorer child and maternal outcomes. These associations are stronger for poorer behavior and health-related quality of life among children with SHCN than those without during the preschool and early school years.

Importance: Working memory training may help children with attention and learning difficulties, but robust evidence from population-level randomized controlled clinical trials is lacking., Objective: To test whether a computerized adaptive working memory intervention program improves long-term academic outcomes of children 6 to 7 years of age with low working memory compared with usual classroom teaching., Design, Setting, and Participants: Population-based randomized controlled clinical trial of first graders from 44 schools in Melbourne, Australia, who underwent a verbal and visuospatial working memory screening. Children were classified as having low working memory if their scores were below the 15th percentile on either the Backward Digit Recall or Mister X subtest from the Automated Working Memory Assessment, or if their scores were below the 25th percentile on both. These children were randomly assigned by an independent statistician to either an intervention or a control arm using a concealed computerized random number sequence. Researchers were blinded to group assignment at time of screening. We conducted our trial from March 1, 2012, to February 1, 2015; our final analysis was on October 30, 2015. We used intention-to-treat analyses., Intervention: Cogmed working memory training, comprising 20 to 25 training sessions of 45 minutes' duration at school., Main Outcomes and Measures: Directly assessed (at 12 and 24 months) academic outcomes (reading, math, and spelling scores as primary outcomes) and working memory (also assessed at 6 months); parent-, teacher-, and child-reported behavioral and social-emotional functioning and quality of life; and intervention costs., Results: Of 1723 children screened (mean [SD] age, 6.9 [0.4] years), 226 were randomized to each arm (452 total), with 90% retention at 1 year and 88% retention at 2 years; 90.3% of children in the intervention arm completed at least 20 sessions. Of the 4 short-term and working memory outcomes, 1 outcome (visuospatial short-term memory) benefited the children at 6 months (effect size, 0.43 [95% CI, 0.25-0.62]) and 12 months (effect size, 0.49 [95% CI, 0.28-0.70]), but not at 24 months. There were no benefits to any other outcomes; in fact, the math scores of the children in the intervention arm were worse at 2 years (mean difference, -3.0 [95% CI, -5.4 to -0.7]; P = .01). Intervention costs were A$1035 per child., Conclusions and Relevance: Working memory screening of children 6 to 7 years of age is feasible, and an adaptive working memory training program may temporarily improve visuospatial short-term memory. Given the loss of classroom time, cost, and lack of lasting benefit, we cannot recommend population-based delivery of Cogmed within a screening paradigm., Trial Registration: anzctr.org.au Identifier: ACTRN12610000486022.

Objective: A significant proportion of school-aged children experience special health care needs (SCHN) and seek care from pediatricians with a wide range of condition types and severity levels. This study examines the learning pathways of children with established (already diagnosed at school entry) and emerging (teacher identified) SHCN from school entry through the elementary school years., Methods: The Longitudinal Study of Australian Children (LSAC) is a nationally representative clustered cross-sequential sample of 2 cohorts of Australian children which commenced in May 2004. Data were analyzed from the LSAC kindergarten cohort (n = 4,983), as well as a subsample of 720 children for whom teachers also completed the Australian Early Development Index checklist, a measure of early childhood development at school entry that includes SHCN., Results: Latent class analysis was utilized to establish 3 academic trajectories from 4-5 to 10-11 years: high (24.3%), average (49.8%), and low (23.6%). Descriptive statistics revealed a trend for both children with established and emerging SHCN to fall into weaker performing learning pathways. Multinomial logistic regression focusing on those children with emerging SHCN confirmed this pattern of results, even after adjustment for covariates (relative risk 3.06, 95% confidence interval 1.03-9.10). Children who additionally had low socioeconomic standing were particularly at risk., Conclusions: Even children with less complex SCHN are at risk for academic failure. Early identification, together with integrated health and educational support, may promote stronger pathways of educational attainment for these children. Achieving these better outcomes will require the involvement of both educational and health practitioners., (Copyright © 2015 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)

Background: Adequate sleep optimizes children's learning and behavior. However, the natural history and impact of sleep problems during school transition is unknown., Objectives: To determine (1) the natural history of sleep problems over the 2-year period spanning school entry and (2) associations of children's health-related quality of life, language, behavior, learning, and cognition at ages 6.5 to 7.5 years with (a) timing and (b) severity of sleep problems., Methods: Data were drawn from the Longitudinal Study of Australian Children. Children were aged 4 to 5 years at wave 1 and 6 to 7 years at wave 2. Parent-reported predictors included (1) timing (none, persistent, resolved, incident) of moderate/severe sleep problems over the 2 waves and (2) severity (none, mild, moderate/severe) of sleep problems at wave 2. Outcomes included parent-reported health-related quality of life and language, parent- and teacher-reported behavior, teacher-reported learning, and directly assessed nonverbal (matrix reasoning) and verbal (receptive vocabulary) cognition. Linear regression, adjusted for child age, gender, and social demographic variables, was used to quantify associations of outcomes with sleep-problem timing and severity., Results: Sleep data were available at both waves for 4460 (89.5%) children, of whom 22.6% (17.0% mild, 5.7% moderate/severe) had sleep problems at wave 2. From wave 1, 2.9% persisted and 2.8% developed a moderate/severe problem, whereas 10.1% resolved. Compared with no sleep problems, persistent and incident sleep problems predicted poorest health-related quality of life, behavior, language, and learning scores, whereas resolving problems showed intermediate outcomes. These outcomes also showed a dose-response relationship with severity at wave 2, with effect sizes for moderate/severe sleep problems ranging from -0.25 to -1.04 SDs. Cognitive outcomes were unaffected., Conclusions: Sleep problems during school transition are common and associated with poorer child outcomes. Randomized, controlled trials could determine if population-based sleep interventions can reduce the prevalence and impact of sleep problems.

Objectives: Children's additional health and developmental needs are often first identified by teachers when they begin school. This study estimates the Grade 3 literacy and numeracy outcomes of children with teacher‐identified additional needs emerging in the first year of school, including the added burden conferred by socioeconomic disadvantage. Methods: Population linked data (n = 42,619) were analysed from the Australian Early Development Census, which include teacher reports on children's health and development at school entry, and the National Assessment Program–Literacy and Numeracy, a direct assessment of reading and numeracy skills at Grade 3. Linear regression analyses were used to estimate associations between emerging needs and learning outcomes, adjusted for sociodemographic characteristics. The combined effect of emerging needs and low maternal education (an indicator of socioeconomic disadvantage) on academic outcomes was examined by estimating the relative excess risk due to interaction (RERI). Results: Emerging health and developmental needs at school entry were associated with lower reading (b = −26.86, 95% CI = −29.19, −24.52) and numeracy (b = −24.39, 95% CI = −26.43, −22.35) outcomes at Grade 3. The combined effect of emerging needs and socioeconomic disadvantage was greater than expected when their individual effects are summed (RERI = 0.38, 95% CI 0.22, 0.55 for reading and RERI = 0.27, 95% CI 0.10, 0.43 for numeracy). Conclusion: In the current study, emerging health and developmental needs identified by teachers at the outset of schooling were associated with poorer literacy and numeracy skills at Grade 3, and family socioeconomic disadvantage appeared to further amplify this effect. Meeting the needs of these children will require timely and coordinated supports across the health and education systems, particularly for those children who are also disadvantaged. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study is to use national Australian time-diary data to examine both (1) cross-sectionally and (2) longitudinally whether being late versus early to sleep or wake is associated with poorer child behavior, quality of life, learning, cognition and weight status, and parental mental health.Methods: Design/setting: Data from the first three waves of the Longitudinal Study of Australian Children were taken.Participants: A national representative sample of 4983 4-5-year-olds, recruited in 2004 from the Australian Medicare database and followed up biennially, was taken; 3631 had analyzable sleep information and a concurrent measure of health and well-being for at least one wave.Measures: Exposure: Parents completed 24-h child time-use diaries for one week and one weekend day at each wave. Using median splits, sleep timing was categorized into early-to-sleep/early-to-wake (EE), early-to-sleep/late-to-wake (EL), late-to-sleep/early-to-wake (LE), and late-to-sleep/late-to-wake (LL) at each wave.Outcomes: The outcomes included parent-reported child behavior, health-related quality of life, maternal/paternal mental health, teacher-reported child language, literacy, mathematical thinking, and approach to learning. The study assessed child body mass index and girth.Results: (1) Using EE as the comparator, linear regression analyses revealed that being late-to-sleep was associated with poorer child quality of life from 6 to 9 years and maternal mental health at 6-7 years. There was inconsistent or no evidence for associations between sleep timing and all other outcomes. (2) Using the count of the number of times (waves) at which a child was categorized as late-to-sleep (range 0-3), longitudinal analyses demonstrated that there was a cumulative effect of late-to-sleep profiles on poorer child and maternal outcomes at the child age of 8-9 years.Conclusions: Examined cross-sectionally, sleep timing is a driver of children's quality of life and maternal depression. Examined longitudinally, there appears to be cumulative and adverse relationships between late-to-sleep profiles and poorer child and maternal outcomes at the child age of 8-9 years. Understanding how other parameters - such as scheduling consistency, sleep efficiency and hygiene - are also related to child and parent outcomes will help health professionals better target sleep management advice to families. [ABSTRACT FROM AUTHOR]