Bayesian change-point analysis reveals developmental change in a classic theory of mind task.

Although learning and development reflect changes situated in an individual brain, most discussions of behavioral change are based on the evidence of group averages. Our reliance on group-averaged data creates a dilemma. On the one hand, we need to use traditional inferential statistics. On the other hand, group averages are highly ambiguous when we need to understand change in the individual; the average pattern of change may characterize all, some, or none of the individuals in the group. Here we present a new method for statistically characterizing developmental change in each individual child we study. Using false-belief tasks, fifty-two children in two cohorts were repeatedly tested for varying lengths of time between 3 and 5 years of age. Using a novel Bayesian change point analysis, we determined both the presence and-just as importantly-the absence of change in individual longitudinal cumulative records. Whenever the analysis supports a change conclusion, it identifies in that child's record the most likely point at which change occurred. Results show striking variability in patterns of change and stability across individual children. We then group the individuals by their various patterns of change or no change. The resulting patterns provide scarce support for sudden changes in competence and shed new light on the concepts of "passing" and "failing" in developmental studies.

Staying self-regulated in the classroom: The role of children's executive functions and situational factors.

BACKGROUND: Self-regulation is crucial for children's learning and development. Several studies have explored children's inter-individual differences in self-regulation, but little is known about sources of intra-individual variation. AIMS: This study addressed the variability of children's self-regulation across typical classroom situations and how this might be associated with children's executive functions (EFs). SAMPLE: The study included 148 children (54.7% girls; Mage = 56.73 months). METHODS: Self-regulation was assessed with an observational measure in teacher-led and child-led activities within naturalistic classroom settings. Children's EFs were assessed with direct assessments at the start and end of the school year. RESULTS: Linear mixed-effect models showed that children demonstrated higher levels of self-regulation in child-led in comparison with teacher-led activities. Children with higher levels of EFs at the start of the school year showed less variation across teacher-led and child-led activities in comparison with children with lower levels of EFs. Regarding other aspects of the classroom context, neither the group size in which the activity took place nor which school subject it was focused on were associated with children's self-regulation. However, in teacher-led activities the type of interaction involved in the activity and the type of task influenced children's self-regulation. CONCLUSION: These results suggest that children who start school with higher levels of EFs are more able to adapt to different situations, highlighting the importance of fostering these skills in early childhood. In turn, children with lower levels of EFs may need additional support from teachers to remain self-regulated across different contexts.

Inhibitory control interacts with core knowledge in toddlers' manual search for an occluded object.

Core knowledge theories advocate the primacy of fundamental principles that constrain cognitive development from early infancy. However, there is concern that core knowledge of object properties does not constrain older preschoolers' reasoning during manual search. Here we address in detail both failure and success on two well-established search measures that require reasoning about solidity. We show that poor performance arises from an inability to engage the appropriate search strategy rather than a simple failure of core knowledge. Moreover, we demonstrate that successful search is positively correlated with inhibitory control. We believe that toddlers' manual search for an occluded object reflects a general capacity to deploy inhibition so that search behaviour can be guided by core knowledge.

A data mining and item response mixture modeling method to retrospectively measure Diagnostic and Statistical Manual of Mental Disorders-5 attention deficit hyperactivity disorder in the 1970 British Cohort Study.

OBJECTIVE: To facilitate future outcome studies, we aimed to develop a robust and replicable method for estimating a categorical and dimensional measure of Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) attention deficit hyperactivity disorder (ADHD) in the 1970 British Cohort Study (BCS70). METHOD: Following a data mining framework, we mapped DSM-5 ADHD symptoms to age 10 BCS70 data (N = 11,426) and derived a 16-item scale (α = 0.85). Mapping was validated by an expert panel. A categorical subgroup was derived (n = 594, 5.2%), and a zero-inflated item response theory (IRT) mixture model fitted to estimate a dimensional measure. RESULTS: Subgroup composition was comparable with other ADHD samples. Relative risk ratios (ADHD/not ADHD) included boys = 1.38, unemployed fathers = 2.07, below average reading = 2.58, and depressed parent = 3.73. Our estimated measures correlated with two derived reference scales: Strengths and Difficulties Questionnaire hyperactivity (r = 0.74) and a Rutter/Conners-based scale (r = 0.81), supporting construct validity. IRT model items (symptoms) had moderate to high discrimination (0.90-2.81) and provided maximum information at average to moderate theta levels of ADHD (0.5-1.75). CONCLUSION: We extended previous work to identify ADHD in BCS70, derived scales from existing data, modeled ADHD items with IRT, and adjusted for a zero-inflated distribution. Psychometric properties were promising, and this work will enable future studies of causal mechanisms in ADHD.