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Modelling Trajectories of Cool and Hot Executive Functions from Middle Childhood to Late Adolescence
No full textExecutive functions (EF) are cognitive abilities that allow for monitored, goal-, and future-oriented actions (Nigg, 2017). According to two complementary frameworks, EF are divided into cooler facets including inhibition and working-memory updating (Miyake et al., 2000), and hotter facets including decision-making (Zelazo & Carlson, 2012). Cool facets encompass more rational, situation-independent abilities that associate strongly with academic outcomes, whereas hot facets encompass more motivationally- and emotionally-driven, contextual abilities that associate strongly with social outcomes (Moriguchi & Phillips, 2023). These varying EF facets are thought to develop at different rates, with cool facets observed to improve in a slightly earlier and linear fashion up until adolescence (Laureys et al., 2022; Tervo-Clemmens et al., 2023) and hot EF facets observed to develop in a more heterogenous and non-linear fashion up until emerging adulthood (Cortes-Patino et al., 2017; Crone & van der Molen, 2004). In particular, hot EF and their development are thought to be influenced significantly by adolescence and the onset of puberty, leading to stagnating or compromised abilities during teenage years, before improving to adult-like levels (Performance Dip; Poon, 2018). Therefore, social and biological influences of gender are assumed, and may lead to variability in EF performance - particularly in hot EF which are more context-dependent than cool EF. Most approaches and studies of EF development typically identify a single trend of change, that is applicable to a large majority of individuals in a given sample. These approaches thereby run the risk of overseeing parallel trends of development that may apply to smaller but equally important minorities.
While a majority of variable-oriented studies focus on identifying average and generalizable patterns of EF development relevant to as many individuals as possible (e.g., Tervo-Clemmens et al., 2023), preliminary person-oriented studies suggest that there is more than one variable pattern of EF development observable across different individuals and subgroups of individuals cross-sectionally (e.g., Brandt et al., 2025; Chaku et al., 2022; Sasser et al., 2017). For example, Chaku et al., (2022) identified four latent profiles of varying combinations of cool EF facet performance in 9- to 10-year-olds including a large average-EF profile (characterized by average scores on inhibition, working memory, and cognitive flexibility), but also less prevalent low-EF and low-inhibition profiles (characterized by below-average performance on all cool facets or only inhibition, respectively). Profile membership was predicted by multiple variables, including gender and socio-economic status, suggesting that girls and children with a higher status belonged to the high-performance profiles more frequently. Such cross-sectional profiles demonstrate that cognitive performance is heterogenous and subject to many influences, even in typically developing and non-clinical samples. However, not many studies to date have observed EF development using such person-oriented approaches in longitudinal designs or with regards to hot EF.
The following preregistration describes a study which aims to use growth mixture modelling (GMM) across four timepoints (T1-T4) to investigate parallel longitudinal trends in EF development for two cool EF facets (inhibition, working-memory updating) and one hot EF facet (decision-making) from middle childhood to emerging adulthood (6 to 21 years). Each of the EF facets will be modelled separately. We assume to find more than one trajectory of development for each EF facet within a large, mostly typically developing cohort sample. The identified trajectories for each EF facet will be described and compared descriptively with the trajectories found for the other EF facets. Further, the GMMs will consider multiple covariates to test whether sociodemographic variables at T1 (binary sex, socio-economic status, family adversity) and initial T1 rates in the remaining EF facets associate with the identified EF trajectories (e.g., T1 inhibition and T1 working-memory updating entered as covariates for trajectories of decision-making). In doing so, we hope to uncover parallel developmental trends in EF abilities, while also setting the trajectories in relation to the other EF abilities at baseline, assuming partial dependence between EF during development. This perspective might demonstrate the importance of dissecting large samples and populations according to important parameters such as individual EF ability and EF change to gain more personalized and accurate insights on cognitive change across the lifespan
Emerging Adults' Use of AI Companions for Enhancing and Replacing Human Relationships: A Machine Learning Approach
No full textMaximising user acceptance of wastewater reuse through optimised socio-technical configurations: An experimental study in Bengaluru
No full textGas-operated patient ventilator: functionality and limitations — a bench study
No full textIn mass casualty events, military scenarios, and low- and middle-income countries (LMICs), resources for mechanical ventilation may be extremely limited. Gas-operated ventilators (GOVs), which require only a continuous oxygen source and no electricity or batteries, may represent a valuable option for invasive ventilation in such contexts.
However, current literature does not clearly define which patient profiles can be safely ventilated using these devices, nor the main physiological limitations associated with their use.
The aim of this study is therefore to characterize the functional properties and physiological limits of the most widely used gas-operated ventilator on the market by testing it on simulated patients
Scoping Review Protocol for "Reasonable Accommodation for Moral or Religious Objection in Pediatric Death by Neurologic Criteria"
No full textProtocol for "Reasonable Accommodation for Moral or
Religious Objection in Pediatric Death by Neurologic Criteria: A Scoping Review
The Effect of Carbohydrate Intake on Muscle Hypertrophy: A Systematic Review and Meta-Analysis
No full textEffect of Carbohydrate Intake on Muscle Hypertroph
Geospatial Census Data in R
No full textMaterials for a Data Bytes workshop on working with geospatial census data in