Effects of methylphenidate on executive functioning in attention-deficit/hyperactivity disorder across the lifespan:A meta-regression analysis

Attention-deficit/hyperactivity disorder (ADHD) in childhood and adulthood is often treated with the psychostimulant methylphenidate (MPH). However, it is unknown whether cognitive effects of MPH depend on age in individuals with ADHD, while animal studies have suggested age-related effects. In this meta-analysis, we first determined the effects of MPH on response inhibition, working memory and sustained attention, but our main goal was to examine whether these effects are moderated by age. A systematic literature search using PubMed, PsycINFO, Web of Science and MEDLINE for double-blind, placebo-controlled studies with MPH resulted in 25 studies on response inhibition (n = 775), 13 studies on working memory (n = 559) and 29 studies on sustained attention (n = 956) (mean age range 4.8–50.1 years). The effects of MPH on response inhibition [effect size (ES) = 0.40, p < 0.0001, 95% confidence interval (CI) 0.22–0.58], working memory (ES = 0.24, p = 0.053, 95% CI 0.00–0.48) and sustained attention (ES = 0.42, p < 0.0001, 95% CI 26–0.59) were small to moderate. No linear or quadratic age-dependencies were observed, indicating that effects of MPH on executive functions are independent of age in children and adults with ADHD. However, adolescent studies are lacking and needed to conclude a lack of an age-dependency across the lifespan

Raven’s Standard Progressive Matrices for Adolescents: A Case for a Shortened Version

Cognitive ability of adolescents is often measured using the Raven’s Standard Progressive Matrices (RSPM). However, the RSPM knows a long administration time which may be suboptimal, as time-on-task effects are known to increase fatigue, to lower motivation, and to worsen performance on cognitive tasks. Therefore, a shortened version for adolescents was developed recently. In the current preregistered study we investigated this shortened version in a sample of adolescents (N = 99) of average educational backgrounds. We tested whether the shortened RSPM is a valid alternative to the original RSPM, which proved to be the case, as we observed a moderate to high correlation between the two versions. Moreover, we tested version effects on fatigue, motivation and performance. Fatigue was lower and motivation was higher after completing the short compared to the original version, and performance was better in the short compared to the original version. However, additional analyses suggested that beneficial version effects on performance were not due to reduced time-on-task, but due to the short version containing less difficult items than the original version. Moreover, version related differences in performance were not related to version related differences in fatigue and motivation. We conclude that the shortened version of the RSPM is a valid alternative to the original version, and that the shortened version is beneficial in terms of fatigue and motivation, but that these beneficial effects on fatigue and motivation do not carry over to performance.</p

Quantitative or qualitative development in decision making?

A key question in the developmental sciences is whether developmental differences are quantitative or qualitative. For example, does age increase the speed in processing a task (quantitative differences) or does age affect the way a task is processed (qualitative differences)? Until now, findings in the domain of decision making have been based on the assumption that developmental differences are either quantitative or qualitative. In the current study, we took a different approach in which we tested whether development is best described as being quantitative or qualitative. We administered a judgment version and a choice version of a decision-making task to a developmental sample (njudgment = 109 and nchoice = 137; Mage = 12.5 years, age range = 9–18). The task, the so-called Gambling Machine Task, required decisions between two options characterized by constant gains and probabilistic losses; these characteristics were known beforehand and thus did not need to be learned from experience. Data were analyzed by comparing the fit of quantitative and qualitative latent variable models, so-called multiple indicator multiple cause (MIMIC) models. Results indicated that individual differences in both judgment and choice tasks were quantitative and pertained to individual differences in “consideration of gains,” that is, to what extent decisions were guided by gains. These differences were affected by age in the judgment version, but not in the choice version, of the task. We discuss implications for theories of decision making and discuss potential limitations and extensions. We also argue that the MIMIC approach is useful in other domains, for example, to test quantitative versus qualitative development of categorization, reasoning, math, and memory

How much do you want to learn? High-school students' willingness to invest effort in valenced feedback-learning tasks

High-school students decide in which tasks to invest their cognitive effort on a daily basis. At school, such decisions often relate to feedback-learning situations (e.g., whether or not to do homework exercises). To investigate how willing high-school students are to invest their cognitive effort in such situations, we administered in this preregistered study a feedback-learning task in combination with a cognitive effort-discounting task – a paradigm to quantify willingness to invest effort. We did so to a large sample (N = 195) from average educational backgrounds in an ecologically valid setting (a school class). We specifically tested whether high-school students discounted their effort in feedback-learning tasks, which proved to be the case, and whether this discounting was differentially affected by positive and negative feedback, which proved not to be the case. We also found that learning was unaffected by feedback valence, except that students learned better from positive than from negative feedback when high effort was required. These results imply that in a school setting, where feedback learning is common, high-school students are less willing to invest cognitive effort in more effortful tasks irrespective of feedback valence, and that positive feedback can aid learning when high effort is required. We provide several recommendations as to how our proposed combination of feedback learning and effort discounting could be used to understand and improve students' academic motivation. Educational relevance statement: High school students sometimes struggle with motivation for learning, at least partly because of low willingness to invest their effort. By investigating high-school students' willingness to invest effort for learning within an educational context, we aim to enhance understanding of this decision-making process in high-school students. Our results indicate that in a school setting, where feedback learning is common, high-school students are less willing to invest cognitive effort in more effortful tasks irrespective of whether they receive positive or negative feedback, but that positive feedback can aid learning when learning tasks require high effort. These results imply that positive feedback may reduce the costs of learning or increase its benefits for difficult tasks.</p

Uncertainty-driven regulation of learning and exploration in adolescents:A computational account

Healthy adults flexibly adapt their learning strategies to ongoing changes in uncertainty, a key feature of adaptive behaviour. However, the developmental trajectory of this ability is yet unknown, as developmental studies have not incorporated trial-to-trial variation in uncertainty in their analyses or models. To address this issue, we compared adolescents' and adults' trial-to-trial dynamics of uncertainty, learning rate, and exploration in two tasks that assess learning in noisy but otherwise stable environments. In an estimation task-which provides direct indices of trial-specific learning rate-both age groups reduced their learning rate over time, as self-reported uncertainty decreased. Accordingly, the estimation data in both groups was better explained by a Bayesian model with dynamic learning rate (Kalman filter) than by conventional reinforcement-learning models. Furthermore, adolescents' learning rates asymptoted at a higher level, reflecting an over-weighting of the most recent outcome, and the estimated Kalman-filter parameters suggested that this was due to an overestimation of environmental volatility. In a choice task, both age groups became more likely to choose the higher-valued option over time, but this increase in choice accuracy was smaller in the adolescents. In contrast to the estimation task, we found no evidence for a Bayesian expectation-updating process in the choice task, suggesting that estimation and choice tasks engage different learning processes. However, our modeling results of the choice task suggested that both age groups reduced their degree of exploration over time, and that the adolescents explored overall more than the adults. Finally, age-related differences in exploration parameters from fits to the choice data were mediated by participants' volatility parameter from fits to the estimation data. Together, these results suggest that adolescents overestimate the rate of environmental change, resulting in elevated learning rates and increased exploration, which may help understand developmental changes in learning and decision-making