Information about foregone rewards impedes dynamic decision-making in older adults

“Making an informed decision” implies that more information leads to better decisions, yet it may be the case that additional information biases decisions in a systematic and sometimes detrimental manner. In the present study, we examined the effect of additional information on older adults’ decision-making using a task for which available rewards were dependent on the participant’s recent pattern of choices. The optimal strategy was to forego the immediately rewarding option in favor of the option that yielded larger delayed reward. We found that providing information about true foregone rewards – the reward that would have been received had the participant chosen the other option – significantly reduced older adults’ decision-making performance. However, false foregone rewards – foregone rewards manufactured to make the long-term option appear more immediately rewarding – led older adults to perform at a level equal to younger adults. We conclude that providing information about foregone rewards biases older adults toward immediate rewards at a greater rate than younger adults, leading to poorer older adult performance when immediate rewards and long-term rewards conflict, but intact performance when immediate rewards and long-term rewards appear to align.     

Verbal facilitation effects instead of verbal overshadowing in face memory of 4- to 6-year olds

Research on eye witness memory in older children and adults revealed that verbally describing unfamiliar faces impairs later recognition of these faces, known as the “verbal overshadowing effect”. The aim of this study was to investigate whether a verbal overshadowing effect occurs in 4- to 6-year olds, too, and whether visualization (i.e., drawing the seen face) might elicit a visual overshadowing effect. Instead of a verbal overshadowing effect, a verbal facilitation effect was revealed with verbal intelligence being a significant predictor for recognition accuracy in the verbalization group but not in the control group. No effect of visualization was observed on recognition accuracy. Potential explanations for the results are discussed.     

Moral Worth and Doing the Right Thing by Accident

Kantian conceptions of moral worth are thought to enjoy an advantage over their rivals in virtue of accommodating two plausible intuitions—that the praiseworthiness of an action is never accidental, and that how an agent might have acted in other circumstances does not determine the moral worth of her actual conduct. In this paper, I argue that neither the Kantian nor her rivals can adequately accommodate both intuitions, in as much as non-accidentality presupposes counterfactual robustness. If we are to adequately accommodate both claims, then we must reconsider the kind of non-accidentality that really matters to moral worth. I propose that the kind of non-accidentality worth caring about requires only that the agent who does what is right acts competently from morally relevant concerns. Under this account, both the Kantian and (some of) her rivals can ensure that the praiseworthiness of an action is never accidental without counting the behaviour of non-actual agents as being relevant to assessments of moral worth.     

Decoding emotions in expressive music performances: A multi-lab replication and extension study

With over 560 citations reported on Google Scholar by April 2018, a publication by Juslin and Gabrielsson (1996) presented evidence supporting performers’ abilities to communicate, with high accuracy, their intended emotional expressions in music to listeners. Though there have been related studies published on this topic, there has yet to be a direct replication of this paper. A replication is warranted given the paper’s influence in the field and the implications of its results. The present experiment joins the recent replication effort by producing a five-lab replication using the original methodology. Expressive performances of seven emotions (e.g. happy, sad, angry, etc.) by professional musicians were recorded using the same three melodies from the original study. Participants (N?=?319) were presented with recordings and rated how well each emotion matched the emotional quality using a 0–10 scale. The same instruments from the original study (i.e. violin, voice, and flute) were used, with the addition of piano. In an effort to increase the accessibility of the experiment and allow for a more ecologically-valid environment, the recordings were presented using an internet-based survey platform. As an extension to the original study, this experiment investigated how musicality, emotional intelligence, and emotional contagion might explain individual differences in the decoding process. Results found overall high decoding accuracy (57%) when using emotion ratings aggregated for the sample of participants, similar to the method of analysis from the original study. However, when decoding accuracy was scored for each participant individually the average accuracy was much lower (31%). Unlike in the original study, the voice was found to be the most expressive instrument. Generalised Linear Mixed Effects Regression modelling revealed that musical training and emotional engagement with music positively influences emotion decoding accuracy.     

Influence of in utero exposure to maternal depression and natural disaster-related stress on infant temperament at 6 months: The children of Superstorm Sandy

This study examined the effects of in utero exposure to maternal depression and Superstorm Sandy, a hurricane that hit metropolitan New York in 2012, on infant temperament at 6 months. Temperament was assessed using the Infant Behavior Questionnaire-Revised. Maternal depression was measured by the Edinburgh Postnatal Depression Scale. The main effects and the interaction of maternal depression and Sandy exposure on infant temperament were examined using a multivariable generalized linear model. Results show that prenatal maternal depression was associated with lower emotion regulation and greater distress. Stratification and interaction analyses suggested that the adverse effects of prenatal maternal depression on problematic temperament were amplified by in utero Sandy exposure. This study underscores the importance of providing prenatal screening and treatment for maternal depression during pregnancy while also identifying high-risk families who may have suffered from disaster-related traumas to provide necessary services. As the frequency of natural disasters may increase due to climate change, it is important to understand the consequences of in utero stress on child development and to formulate plans for early identification.     

Gender Differences in Reactions to Mental Illness Labeling: The Role of Agency and Communion

Numerous individual characteristics influence responses to receiving a mental health diagnosis, including gender. This study sought to determine how gender influences reactions to being labeled as depressed or not depressed, which were categorized as falling into themes of communion or agency. Using the themes developed by Niedzwienska (2003), 168 college students’ responses to depression labels were coded as a part of a laboratory experiment. The results indicate that the expected sex differences do exist, but multivariate analyses indicate that the choice of communal themes was influenced by sex but the use of agency themes was not influenced by sex.     

Machine learning in suicide science: Applications and ethics

For decades, our ability to predict suicide has remained at near‐chance levels. Machine learning has recently emerged as a promising tool for advancing suicide science, particularly in the domain of suicide prediction. The present review provides an introduction to machine learning and its potential application to open questions in suicide research. Although only a few studies have implemented machine learning for suicide prediction, results to date indicate considerable improvement in accuracy and positive predictive value. Potential barriers to algorithm integration into clinical practice are discussed, as well as attendant ethical issues. Overall, machine learning approaches hold promise for accurate, scalable, and effective suicide risk detection; however, many critical questions and issues remain unexplored.