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 PARTICIPANTSPopulation-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 MEASURESDirectly 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. RESULTSOf 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 RELEVANCEWorking 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.

BackgroundEvidence is required as to when and where to focus resources to achieve the greatest gains for children’s language development. Key to these decisions is the understanding of individual differences in children’s language trajectories and the predictors of those differences. To determine optimal timing we must understand if and when children’s relative language abilities become fixed. To determine where to focus effort we must identify mutable factors, that is those with the potential to be changed through interventions, which are associated with significant differences in children’s language scores and rate of progress.MethodsUniquely this study examined individual differences in language growth trajectories in a population sample of children between 4 and 7 years using the multilevel model for change. The influence of predictors, grouped with respect to their mutability and their proximity to the child (least-mutable, mutable-distal, mutable-proximal), were estimated.ResultsA significant degree of variability in rate of progress between 4 and 7 years was evident, much of which was systematically associated with mutable-proximal factors, that is, those factors with evidence that they are modifiable through interventions with the child or family, such as shared book reading, TV viewing and number of books in the home. Mutable-distal factors, such as family income, family literacy and neighbourhood disadvantage, hypothesised to be modifiable through social policy, were important predictors of language abilities at 4 years.ConclusionsPotential levers for language interventions lie in the child’s home learning environment from birth to age 4. However, the role of a family’s material and cultural capital must not be ignored, nor should the potential for growth into the school years. Early Years services should acknowledge the effects of multiple, cascading and cumulative risks and seek to promote child language development through the aggregation of marginal gains in the pre-school years and beyond.