Improving the Reporting of Health and Psychological Research

A growing body of empirical evidence has consistently demonstrated that much publically and privately funded research is reported in a way that makes it difficult for the findings to be included in evidence syntheses or used by researchers, clinicians, policy makers, and the public. Poorly reported studies thus represent a significant waste of scarce resources. Reporting guidelines are one strategy that has been increasingly used as a method to improve the completeness or usability of primary and secondary research across a broad range of disciplines including psychology. We present a synopsis of two studies investigating the impact of the Transparent Reporting of Evaluation with Nonrandomised Designs statement and factors that affect authors' and journal editors' use of it and other reporting guidelines. We also make recommendations for future guideline development or revisions based on our experiences, provide details of resources for psychologists, and make suggestions for future research and recommendations for improving the transparency of reporting of psychological research.     

Demonstrating and eliminating the aggregation effect in physical skill tasks

Confidence judgments can be elicited in multiple ways. One of these procedures is to provide confidence judgments regarding each of a number of cases (individual judgments). A second procedure is to provide confidence judgments about a set of items (an aggregate judgment). Much research has demonstrated an aggregation effect—that individual judgments are more confident than aggregate judgments—within the cognitive knowledge domain. However, this effect has not previously been investigated with physical performance skill tasks. In three experiments, participants gave individual and aggregate judgments regarding the number of successful tosses they would make in either a ring toss, ping‐pong toss, or basketball toss task. In keeping with the aggregation effect, individual judgments were more confident than were aggregate judgments of success. Additionally, we eliminated the aggregation effect in Experiments 2 and 3 by employing a case‐specific base rate manipulation. Consistent with previous research with cognitive tasks, these results suggest that individual confidence judgments for physical skill tasks are determined primarily by characteristics associated with the individual case to be judged, whereas aggregate confidence judgments are determined by a more general evaluation of one's ability in the domain. Copyright © 2009 John Wiley & Sons, Ltd.     

SOME THOUGHTS ABOUT THE REQUIREMENTS FOR REVIEWING BOOKS

Abstract: The quality of peer‐reviewed journals is vulnerable to the absence of declared standards for book reviews. Reviewers should agree to several simple rules before undertaking to review books and while writing them. Sensitivity to an author's aims is one requirement; familiarity with an author's previous and relevant publications is another. Critical judgment is always appropriate, but it can be set apart from an account of the ideas reviewed.     

Confirmatory reinforcement learning changes with age during adolescence

Understanding how learning changes during human development has been one of the long-standing objectives of developmental science. Recently, advances in computational biology have demonstrated that humans display a bias when learning to navigate novel environments through rewards and punishments: they learn more from outcomes that confirm their expectations than from outcomes that disconfirm them. Here, we ask whether confirmatory learning is stable across development, or whether it might be attenuated in developmental stages in which exploration is beneficial, such as in adolescence. In a reinforcement learning (RL) task, 77 participants aged 11–32 years (four men, mean age = 16.26) attempted to maximize monetary rewards by repeatedly sampling different pairs of novel options, which varied in their reward/punishment probabilities. Mixed-effect models showed an age-related increase in accuracy as long as learning contingencies remained stable across trials, but less so when they reversed halfway through the trials. Age was also associated with a greater tendency to stay with an option that had just delivered a reward, more than to switch away from an option that had just delivered a punishment. At the computational level, a confirmation model provided increasingly better fit with age. This model showed that age differences are captured by decreases in noise or exploration, rather than in the magnitude of the confirmation bias. These findings provide new insights into how learning changes during development and could help better tailor learning environments to people of different ages.

Research Highlights

• Reinforcement learning shows age-related improvement during adolescence, but more in stable learning environments compared with volatile learning environments.
• People tend to stay with an option after a win more than they shift from an option after a loss, and this asymmetry increases with age during adolescence.
• Computationally, these changes are captured by a developing confirmatory learning style, in which people learn more from outcomes that confirm rather than disconfirm their choices.
• Age-related differences in confirmatory learning are explained by decreases in stochasticity, rather than changes in the magnitude of the confirmation bias.