Mark Hurlstone

Avoiding dangerous climate change requires ambitious emissions reduction. Scientists agree on this, but policy-makers and citizens do not. This discrepancy can be partly attributed to faulty mental models, which cause individuals to misunderstand the carbon dioxide (CO2) system. For example, in the Climate Stabilization Task (hereafter, ‘CST’) (Sterman & Booth-Sweeney, 2007), individuals systematically underestimate the emissions reduction required to stabilize atmospheric CO2 levels, which may lead them to endorse ineffective ‘wait-and-see’ climate policies. Thus far, interventions to correct faulty mental models in the CST have failed to produce robust improvements in decision-making. Here, in the first study to test a group-based intervention, we found that success rates on the CST markedly increased after participants deliberated with peers in a group discussion. The group discussion served to invalidate the faulty reasoning strategies used by some individual group members, thus increasing the proportion of group members who possessed the correct mental model of the CO2 system. Our findings suggest that policy-making and public education would benefit from group-based practices.

Any mature field of research in psychology – such as short-term/working memory – is characterized by a wealth of empirical findings. It is currently unrealistic to expect a theory to explain them all; theorists must satisfice with explaining a subset of findings. The aim of the present article is to make the choice of that subset less arbitrary and idiosyncratic than is current practice. We propose criteria for identifying benchmark findings that every theory in a field should be able to explain: Benchmarks should be reproducible, generalize across materials and methodological variations, and be theoretically informative. We propose a set of benchmarks for theories and computational models of short-term and working memory. The benchmarks are described in as theory-neutral a way as possible, so that they can serve as empirical common ground for competing theoretical approaches. Benchmarks are rated on three levels according to their priority for explanation. Selection and ratings of the benchmarks is based on consensus among the authors, who jointly represent a broad range of theoretical perspectives on working memory, and they are supported by a survey among other experts on working memory. The article is accompanied by a web page providing an open forum for discussion; a site for submitting proposals for new benchmarks; and a repository for reference data sets for each benchmark.

Objective: We tested a novel intervention for reducing demand for ineffective health remedies. The intervention aimed to empower participants to overcome the illusion of causality, which otherwise drives erroneous perceptions regarding remedy efficacy. Design: A laboratory experiment adopted a between-participants design with six conditions that varied the amount of information available to participants (N = 245). The control condition received a basic refutation of multivitamin efficacy, whereas the principal intervention condition received a full contingency table specifying the number of people reporting a benefit vs. no benefit from both the product and placebo, plus an alternate causal explanation for inefficacy over placebo. Main outcome measures: We measured participants’ willingness to pay (WTP) for multivitamin products using two incentivized experimental auctions. General attitudes towards health supplements were assessed as a moderator of WTP. We tested generalization using ratings of the importance of clinical-trial results for making future health purchases. Results: Our principal intervention significantly reduced participants’ WTP for multivitamins (by 23%) and increased their recognition of the importance of clinical-trial results. Conclusion: We found evidence that communicating a simplified full- contingency table and an alternate causal explanation may help reduce demand for ineffective health remedies by countering the illusion of causality.

Temporal grouping effects in verbal and spatial serial recall suggest that the representation of serial order in verbal and spatial short-term memory (STM) incorporates positional information. However, not all effects of grouping are created equal in the verbal and spatial domains. Although grouping a sequence of verbal items engenders an increase in between-group transpositions that maintain their within-group position, grouping a sequence of spatial items does not engender an increase in these so-called interposition errors. Here I present experimental and computational modeling evidence which suggests that positional information is represented in subtly different ways in verbal and spatial STM. Specifically, the findings indicate that in verbal STM, groups are coded for their position in a sequence and items are coded for their position in a group. By contrast, in spatial STM groups are coded for their position in a sequence, but items are coded for their position in a sequence, rather than in a group. Findings support the notion that positional information in verbal and spatial STM is represented by modality-specific mechanisms rather than a domain-general system.

Current research shows that emotions can motivate climate engagement and action, but precisely how has received scant attention. We propose that strong emotional responses to climate change result from perceiving one’s “objects of care” as threatened by climate change, which motivates caring about climate change itself, and in turn predicts behaviour. In two studies, we find that climate scientists (N = 44) experience greater emotional intensity about climate change than do students (N = 94) and the general population (N = 205), and that patterns of emotional responses explain differences in support for climate change policy. Scientists tied their emotional responses to concern about consequences of climate change to future generations and the planet, as well as personal identities associated with responsibility to act. Our findings suggest that “objects of care” that link people to climate change may be crucial to understanding why some people feel more strongly about the issue than others, and how emotions can prompt action.