Mark Hurlstone

Psychological research has offered valuable insights into how to combat misinformation. The studies conducted to date, however, have three limitations. First, pre-emptive (“prebunking”) and retroactive (“debunking”) interventions have mostly been examined in parallel, and thus it is unclear which of these two predominant approaches is more effective. Second, there has been a focus on misinformation that is explicitly false, but misinformation that uses literally true information to mislead is common in the real world. Finally, studies have relied mainly on questionnaire measures of reasoning, neglecting behavioural impacts of misinformation and interventions. To offer incremental progress towards addressing these three issues, we conducted an experiment (N = 735) involving misinformation on fair trade. We contrasted the effectiveness of prebunking versus debunking and the impacts of implied versus explicit misinformation, and incorporated novel measures assessing consumer behaviours (i.e., willingness-to-pay; information seeking; online misinformation promotion) in addition to standard questionnaire measures. In general, we found debunking to be more effective than prebunking, although both were able to reduce misinformation reliance. We also found that individuals tended to rely more on explicit than implied misinformation both with and without interventions.

Logan (2021) presented an impressive unification of serial order tasks including whole report, typing, and serial recall in the form of the context retrieval and updating (CRU) model. Despite the wide breadth of the model’s coverage, its reliance on encoding and retrieving context representations that consist of the previous items may prevent it from being able to address a number of critical benchmark findings in the serial order literature that have shaped and constrained existing theories. In this commentary, we highlight three major challenges that motivated the development of a rival class of models of serial order, namely positional models. These challenges include the mixed-list phonological similarity effect, the protrusion effect, and interposition errors in temporal grouping. Simulations indicated that CRU can address the mixed list phonological similarity effect if phonological confusions can occur during its output stage, suggesting that the serial position curves from this paradigm do not rule out models that rely on inter-item associations, as has been previously been suggested. The other two challenges are more consequential for the model’s representations, and simulations indicated the model was not able to provide a complete account of them. We highlight and discuss how revisions to CRU’s representations or retrieval mechanisms can address these phenomena and emphasize that a fruitful direction forward would be to either incorporate positional representations or approximate them with its existing representations.

We start with a brief review of evidence that verbal working memory (WM) involves a limited capacity phonological loop capable of retaining verbal sequences for a few seconds in immediate serial recall, vocabulary acquisition, speech production and language comprehension. The challenge of explaining how such a system handles information about serial order is discussed in the context of computational models of the immediate recall of unstructured sequences of words, letters, or digits, an extensively studied laboratory task for which there are many benchmark findings. Evaluating computational models against these benchmarks suggests a serial ordering mechanism in which items are simultaneously active before being selected for sequential output by a process of competitive queuing (CQ). Further evidence shows how this process may operate in the context of sequences that conform to various kinds of linguistic constraint. We conclude by suggesting that CQ is a promising theoretical mechanism for connecting and potentially unifying theories of WM and language processing more generally despite major differences in their scope and level of abstraction.

Research in social and cognitive sciences has used the Construal Level Theory (CLT) of psychological distance as a framework for understanding environmental challenges such as climate change. This primer reflects on the how psychological distance and construal can help to understand environmental challenges, from the perceptions and social construction of environmental issues as distant and abstract, to implications for decision-making and action towards long-term targets. We also reflect on areas where the theory and concept are less useful, when assuming that psychological distance and construal level can be easily reduced or altered to promote lasting changes to environmental action.

The COVID 19 pandemic has seen a surge of health misinformation, which has had serious consequences including direct harm and opportunity costs. We investigated (N = 678) the impact of such misinformation on hypothetical demand (i.e., willingness to pay) for an unproven treatment, and propensity to promote (i.e., like or share) misinformation online. This is a novel approach, as previous research has used mainly questionnaire based measures of reasoning. We also tested two interventions to counteract the misinformation, contrasting a tentative refutation based on materials used by health authorities with an enhanced refutation based on best practice recommendations. We found prior exposure to misinformation increased misinformation promotion (by 18%). Both tentative and enhanced refutations reduced demand (by 18% and 25%, respectively) as well as misinformation promotion (by 29% and 55%). The fact that enhanced refutations were more effective at curbing promotion of misinformation highlights the need for debunking interventions to follow current best practice guidelines.