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Everyone has an opportunity to contribute to climate solutions. To help people engage with this opportunity, it is critical to understand how climate organizations and fundraisers can best communicate with people and win their financial support. In particular, fundraisers often rely on practical skills and anecdotal beliefs at the expense of scientific knowledge. Fundraisers could be motivated to achieve a substantial boost in funding for climate solutions, if there is evidence of the financial gains that science-based fundraising makes available. In this Perspective, we provide a preliminary foray into such evidence. We bring together findings from philanthropic research and climate psychology to identify what factors can help captivate donors. Then, through an experimental study of a charitable appeal for a climate charity, we show how putting these factors into practice may contribute toward an increase in donated money. This provides optimism that evidence-based fundraising can inspire donors to contribute much-needed resources toward climate solutions.

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Scientific publications are the building blocks of discovery and collaboration, but their impact is limited by the style in which they are traditionally written. Recently, many authors have called for a switch to an engaging, accessible writing style. Here, we experimentally test how readers respond to such a style. We hypothesized that scientific abstracts written in a more accessible style would improve readers' reported readability and confidence as well as their understanding, assessed using multiple-choice questions on the content. We created a series of scientific abstracts, corresponding to real publications on three scientific topics at four levels of difficulty-varying from the difficult, traditional style to an engaging, accessible style. We gave these abstracts to a team of readers consisting of 170 third-year undergraduate students. Then, we posed questions to measure the readers' readability, confidence, and understanding with the content. The scientific abstracts written in a more accessible style resulted in higher readability, understanding, and confidence. These findings demonstrate that rethinking the way we communicate our science may empower a more collaborative and diverse industry.

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Acute tolerance is a rapid decrease in the effect of alcohol relative to the blood alcohol concentration (BAC) occurring within the duration of a single dose of alcohol. It remains uncertain which cognitive domains are susceptible to acute tolerance, because findings vary between tasks used to measure the effect of alcohol. This study examined acute tolerance in subjective intoxication and in 2 cognitive domains: information processing, measured using the Inspection Time Task (ITT), and response inhibition, measured with the Sustained Attention to Response Task (SART). Forty participants were allocated to either an alcohol or placebo group. After baseline measures, the alcohol group were given an active dose to produce a peak BAC of 0.07%, whereas the placebo group received a placebo beverage. ITT and SART performance were measured at a BAC of 0.05% twice during the course of the dose, once when BAC was ascending and again when descending. The placebo group was tested at equivalent times. When BAC was ascending, the alcohol group showed increased ratings of subjective intoxication and impaired performance on the ITT. Consistent with an acute tolerance effect, ratings of subjective intoxication and impairment on the ITT in the alcohol group were lower when BAC was descending. Performance on the SART was not found to be affected by alcohol. The findings suggest information processing is a domain of behavior that shows acute tolerance to alcohol and that the subjective intoxication felt at a BAC of 0.05% can decrease substantially within the duration of a single dose. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

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Although the strength of the effect produced by alcohol is generally dose dependent, its effect on behavior cannot be reliably predicted by the dose alone because the dose effect has been shown to vary. Acute behavioral tolerance is a rapid decrease in the dose effect of alcohol, seen to occur within the duration of a single dose. Numerous research paradigms have been used to examine acute behavioral tolerance, across an array of different behavioral measures. We have reviewed studies that used a research paradigm appropriate to test for acute behavioral tolerance. The primary aim was to examine the different paradigms that have been used to identify what empirical evidence of the effect has been found. The additional aims were to identify domains of behavior in which acute tolerance has been shown to occur and ascertain which conditions have been shown to influence it. Findings of acute tolerance were prevalent. Seven different research paradigms were identified, and each found evidence of acute behavioral tolerance in at least 1 study. The effect was not uniform across all behavioral measures. Subjective measures reliably showed the effect, but objective measures of behavior were less reliable, providing evidence that particular aspects of task performance are more sensitive to acute tolerance than others. The dose effect of alcohol for behavioral measures is often shown to decrease within the duration of a single dose. Investigations into, and considerations of, the effects of alcohol on behavior need to consider temporal changes in the dose effect. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

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Although traditional assumptions tend to conceptualize stress as inherently dysfunctional, psychological theory suggests that it is not intrinsically maladaptive. Contemporary models emphasize that the stress response can be differentiated into both negative and positive aspects, known as distress and eustress. Research examining the differential effect of positive and negative stress on adolescent well-being is limited and has been hindered by a lack of appropriate measurement tools. The aim of the present study was to utilize the recently developed Adolescent Distress-Eustress Scale to provide a balanced understanding of the impact of stress on positive mental health, holistically considering the effect of both distress and eustress on adolescent well-being. One thousand eighty-one Australian adolescents (Mage = 15.14, 54.03% female) completed an online survey composed of the Adolescent Distress-Eustress Scale alongside measures of well-being, self-efficacy, psychological ill-being, physical activity, and daytime sleepiness. Conditional process analysis suggested that distress exerted no direct influence on well-being, with the observed negative relationship fully mediated by psychological and behavioural variables. Contrastingly, eustress was both directly related to increased well-being and exerted an indirect effect through relationships with mediating variables. These results demonstrate that stress can have profoundly positive consequences. Theoretical contributions, implications for practice, and perspectives for future research are discussed.

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We assessed the suitability of six applied tests of cognitive functioning to provide a single marker for dose-related alcohol intoxication. Numerous studies have demonstrated that alcohol has a deleterious effect on specific areas of cognitive processing but few have compared the effects of alcohol across a wide range of different cognitive processes. Adult participants (N = 56, 32 males, 24 females aged 18-45 years) were randomized to control or alcohol treatments within a mixed design experiment involving multiple-dosages at approximately one hour intervals (attained mean blood alcohol concentrations (BACs) of 0.00, 0.048, 0.082 and 0.10%), employing a battery of six psychometric tests; the Useful Field of View test (UFOV; processing speed together with directed attention); the Self-Ordered Pointing Task (SOPT; working memory); Inspection Time (IT; speed of processing independent from motor responding); the Traveling Salesperson Problem (TSP; strategic optimization); the Sustained Attention to Response Task (SART; vigilance, response inhibition and psychomotor function); and the Trail-Making Test (TMT; cognitive flexibility and psychomotor function). Results demonstrated that impairment is not uniform across different domains of cognitive processing and that both the size of the alcohol effect and the magnitude of effect change across different dose levels are quantitatively different for different cognitive processes. Only IT met the criteria for a marker for wide-spread application: reliable dose-related decline in a basic process as a function of rising BAC level and easy to use non-invasive task properties.

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The "wisdom of the crowd" phenomenon refers to the finding that the aggregate of a set of proposed solutions from a group of individuals performs better than the majority of individual solutions. Most often, wisdom of the crowd effects have been investigated for problems that require single numerical estimates. We investigate whether the effect can also be observed for problems where the answer requires the coordination of multiple pieces of information. We focus on combinatorial problems such as the planar Euclidean traveling salesperson problem, minimum spanning tree problem, and a spanning tree memory task. We develop aggregation methods that combine common solution fragments into a global solution and demonstrate that these aggregate solutions outperform the majority of individual solutions. These case studies suggest that the wisdom of the crowd phenomenon might be broadly applicable to problem-solving and decision-making situations that go beyond the estimation of single numbers.

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Inductive generalization, where people go beyond the data provided, is a basic cognitive capability, and it underpins theoretical accounts of learning, categorization, and decision making. To complete the inductive leap needed for generalization, people must make a key ''sampling'' assumption about how the available data were generated. Previous models have considered two extreme possibilities, known as strong and weak sampling. In strong sampling, data are assumed to have been deliberately generated as positive examples of a concept, whereas in weak sampling, data are assumed to have been generated without any restrictions. We develop a more general account of sampling that allows for an intermediate mixture of these two extremes, and we test its usefulness. In two experiments, we show that most people complete simple one-dimensional generalization tasks in a way that is consistent with their believing in some mixture of strong and weak sampling, but that there are large individual differences in the relative emphasis different people give to each type of sampling. We also show experimentally that the relative emphasis of the mixture is influenced by the structure of the available information. We discuss the psychological meaning of mixing strong and weak sampling, and possible extensions of our modeling approach to richer problems of inductive generalization.

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A contrast category effect on categorization occurs when the decision to apply a category term to an entity not only involves a comparison between the entity and the target category but is also influenced by a comparison of the entity with 1 or more alternative categories from the same domain as the target. Establishing a contrast category effect on categorization in natural language categories has proven to be laborious, especially when the categories concerned are natural kinds situated at the superordinate level of abstraction. We conducted 3 studies with these categories to look for an influence on categorization of both similarity to the target category and similarity to a contrast category. The results are analyzed with a probabilistic threshold model that assumes categorization decisions arise from the placement of threshold criteria by individual categorizers along a single scale that holds the experimental stimuli. The stimuli's positions along the scale are shown to be influenced by similarity to both target and contrast. These findings suggest that the prevalence of contrast category effects on categorization might have been underestimated. Additional analyses demonstrate how the proposed model can be employed in future studies to systematically investigate the origins of contrast category effects on categorization.

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Abstract categories present with graded structure. The extent to which feature commonality between exemplars and category provides a satisfying account of this graded structure varies from one abstract category to the other (Hampton, 1981). We investigate whether the incorporation of features that exemplars share with external categories yields an improved account of abstract categories' graded structures. In doing so, we follow the suggestion that abstract categories are relational in nature (Goldstone, 1996; Wiemer-Hastings & Xu, 2005). The generalized polymorphous concept model, which incorporates both types of features, is found to improve the account of typicality and category membership in three of seven studied abstract categories. These three categories are found to be the most abstract, suggesting that it is appropriate to think of abstract categories as varying along a continuum of abstractness/interrelatedness rather than as a distinct type of category altogether.

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Many real-world categories contain graded structure: certain category members are rated as more typical or representative of the category than others. Research has shown that this graded structure can be well predicted by the degree of commonality across the feature sets of category members. We demonstrate that two prominent feature-based models of graded structure, the family resemblance (Rosch & Mervis, 1975) and polymorphous concept models (Hampton, 1979), can be generalized via the contrast model (Tversky, 1977) to include both common and distinctive feature information, and apply the models to the prediction of typicality in 11 semantic categories. The results indicate that both types of feature information play a role in the prediction of typicality, with common features weighted more heavily for within-category predictions, and distinctive features weighted more heavily for contrast-category predictions. The same pattern of results was found in additional analyses employing rated goodness and exemplar generation frequency. It is suggested that these findings provide insight into the processes underlying category formation and representation.

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Spatial models are employed to represent conceptual data in a wide range of fields within psychological research. In order to generate spatial models, it is necessary to first obtain empirical similarity data. A number of methods are available for collecting these data, but little effort has been made to compare their relative utility. In this article, we compare directly rated and five feature-based similarity data types in regard to their ability to be adequately represented by a spatial model (representational goodness of fit), and the ability of the representations to predict three external empirical variables (predictive validity). The results indicate that the representational goodness of fit of the feature-based similarities is noticeably superior to the directly rated similarities, and that the predictions of representations derived from common feature similarity data are substantially more likely than the predictions of all of the alternative representations. It is suggested that these findings are highly relevant to researchers employing spatial models to represent conceptual data, given that direct pairwise ratings have generally been considered the "gold standard" means of obtaining empirical similarities.

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Features are at the core of many empirical and modeling endeavors in the study of semantic concepts. This article is concerned with the delineation of features that are important in natural language concepts and the use of these features in the study of semantic concept representation. The results of a feature generation task in which the exemplars and labels of 15 semantic categories served as cues are described. The importance of the generated features was assessed by tallying the frequency with which they were generated and by obtaining judgments of their relevance. The generated attributes also featured in extensive exemplar by feature applicability matrices covering the 15 different categories, as well as two large semantic domains (that of animals and artifacts). For all exemplars of the 15 semantic categories, typicality ratings, goodness ratings, goodness rank order, generation frequency, exemplar associative strength, category associative strength, estimated age of acquisition, word frequency, familiarity ratings, imageability ratings, and pairwise similarity ratings are described as well. By making these data easily available to other researchers in the field, we hope to provide ample opportunities for continued investigations into the nature of semantic concept representation. These data may be downloaded from the Psychonomic Society's Archive of Norms, Stimuli, and Data, www.psychonomic.org/archive.

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Numerous models of symmetry perception have been proposed in recent years. Unfortunately, it is difficult to assess the relative utility of these models as little effort has been made to directly compare them. This paper outlines a new model of symmetry perception based upon the relational structure revealed by Voronoi tessellation. The model has been developed in response to evidence suggesting that the human visual system is generating a Voronoi-like representation at an early stage in processing. Bayesian model selection is employed to compare the performance of the Voronoi model to that of five previously published models across six empirical datasets. The results indicate that the Voronoi model provides a more likely account of the data than the five alternative models.

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We study human decision making in a simple forced-choice task that manipulates the frequency and accuracy of available information. Empirically, we find that people make decisions consistent with the advice provided, but that their subjective confidence in their decisions shows 2 interesting properties. First, people's confidence does not depend solely on the accuracy of the advice. Rather, confidence seems to be influenced by both the frequency and accuracy of the advice. Second, people are less confident in their guessed decisions when they have to make relatively more of them. Theoretically, we develop and evaluate a type of sequential sampling process model-known as a self-regulating accumulator-that accounts for both decision making and confidence. The model captures the regularities in people's behavior with interpretable parameter values, and we show its ability to fit the data is not due to excessive model complexity. Using the model, we draw conclusions about some properties of human reasoning under uncertainty.