Melbourne School of Psychological Sciences - Research Publications
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ItemAttributions for extreme weather events: science and the people.(Springer Nature, 2022)Both climate scientists and non-scientists (laypeople) attribute extreme weather events to various influences. Laypeople's attributions for these events are important as these attributions likely influence their views and actions about climate change and extreme events. Research has examined laypeople's attribution scepticism about climate change in general; however, few climate scientists are familiar with the processes underpinning laypeople's attributions for individual extreme events. Understanding these lay attributions is important for scientists to communicate their findings to the public. Following a brief summary of the way climate scientists calculate attributions for extreme weather events, we focus on cognitive and motivational processes that underlie laypeople's attributions for specific events. These include a tendency to prefer single-cause rather than multiple-cause explanations, a discounting of whether possible causes covary with extreme events, a preference for sufficient causes over probabilities, applying prevailing causal narratives, and the influence of motivational factors. For climate scientists and communicators who wish to inform the public about the role of climate change in extreme weather events, these patterns suggest several strategies to explain scientists' attributions for these events and enhance public engagement with climate change. These strategies include showing more explicitly that extreme weather events reflect multiple causal influences, that climate change is a mechanism that covaries with these events and increases the probability and intensity of many of these events, that human emissions contributing to climate change are controllable, and that misleading communications about weather attributions reflect motivated interests rather than good evidence.
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ItemNo Preview AvailableProfiles of an Ideal Society: The Utopian Visions of Ordinary People(SAGE PUBLICATIONS INC, 2023)Throughout history, people have expressed the desire for an ideal society—a utopia. These imagined societies have motivated action for social change. Recent research has demonstrated this motivational effect among ordinary people in English-speaking countries, but we know little about the specific content of ordinary people’s utopian visions in different cultures. Here we report that a majority of samples from four countries—Australia, China, the United Kingdom, and the United States—converge on a small number of utopian visions: a Modern Green utopia, a Primitivist utopia, a Futurist utopia, and a Religious utopia. Although the prevalence of these utopia profiles differed across countries, there was a cross-cultural convergence in utopian visions. These shared visions may provide common ground for conversations about how to achieve a better future across cultural borders.
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ItemNo Preview AvailablePapers Please-Predictive Factors of National and International Attitudes Toward Immunity and Vaccination Passports: Online Representative Surveys(JMIR PUBLICATIONS, INC, 2022-07)BACKGROUND: In response to the COVID-19 pandemic, countries are introducing digital passports that allow citizens to return to normal activities if they were previously infected with (immunity passport) or vaccinated against (vaccination passport) SARS-CoV-2. To be effective, policy decision-makers must know whether these passports will be widely accepted by the public and under what conditions. This study focuses attention on immunity passports, as these may prove useful in countries both with and without an existing COVID-19 vaccination program; however, our general findings also extend to vaccination passports. OBJECTIVE: We aimed to assess attitudes toward the introduction of immunity passports in six countries, and determine what social, personal, and contextual factors predicted their support. METHODS: We collected 13,678 participants through online representative sampling across six countries-Australia, Japan, Taiwan, Germany, Spain, and the United Kingdom-during April to May of the 2020 COVID-19 pandemic, and assessed attitudes and support for the introduction of immunity passports. RESULTS: Immunity passport support was moderate to low, being the highest in Germany (775/1507 participants, 51.43%) and the United Kingdom (759/1484, 51.15%); followed by Taiwan (2841/5989, 47.44%), Australia (963/2086, 46.16%), and Spain (693/1491, 46.48%); and was the lowest in Japan (241/1081, 22.94%). Bayesian generalized linear mixed effects modeling was used to assess predictive factors for immunity passport support across countries. International results showed neoliberal worldviews (odds ratio [OR] 1.17, 95% CI 1.13-1.22), personal concern (OR 1.07, 95% CI 1.00-1.16), perceived virus severity (OR 1.07, 95% CI 1.01-1.14), the fairness of immunity passports (OR 2.51, 95% CI 2.36-2.66), liking immunity passports (OR 2.77, 95% CI 2.61-2.94), and a willingness to become infected to gain an immunity passport (OR 1.6, 95% CI 1.51-1.68) were all predictive factors of immunity passport support. By contrast, gender (woman; OR 0.9, 95% CI 0.82-0.98), immunity passport concern (OR 0.61, 95% CI 0.57-0.65), and risk of harm to society (OR 0.71, 95% CI 0.67-0.76) predicted a decrease in support for immunity passports. Minor differences in predictive factors were found between countries and results were modeled separately to provide national accounts of these data. CONCLUSIONS: Our research suggests that support for immunity passports is predicted by the personal benefits and societal risks they confer. These findings generalized across six countries and may also prove informative for the introduction of vaccination passports, helping policymakers to introduce effective COVID-19 passport policies in these six countries and around the world.
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ItemHigh Acceptance of COVID-19 Tracing Technologies in Taiwan: A Nationally Representative Survey Analysis(MDPI, 2022-03)Taiwan has been a world leader in controlling the spread of SARS-CoV-2 during the COVID-19 pandemic. Recently, the Taiwan Government launched its COVID-19 tracing app, 'Taiwan Social Distancing App'; however, the effectiveness of this tracing app depends on its acceptance and uptake among the general population. We measured the acceptance of three hypothetical tracing technologies (telecommunication network tracing, a government app, and the Apple and Google Bluetooth exposure notification system) in four nationally representative Taiwanese samples. Using Bayesian methods, we found a high acceptance of all three tracking technologies, with acceptance increasing with the inclusion of additional privacy measures. Modeling revealed that acceptance increased with the perceived technology benefits, trust in the providers' intent, data security and privacy measures, the level of ongoing control, and one's level of education. Acceptance decreased with data sensitivity perceptions and a perceived low policy compliance by others among the general public. We consider the policy implications of these results for Taiwan during the COVID-19 pandemic and in the future.
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ItemImagining better societies: A social psychological framework for the study of utopian thinking and collective action(Wiley, 2020-01-01)We present an integrative theoretical model that specifies social psychological mechanisms by which utopian thinking, which activates the social imagination, may enhance collective action intentions oriented toward social change and human progress. The model synthesizes complementary insights from interdisciplinary research programs on utopianism, hope, construal level, and system justification to identify mechanisms by which imagining better societies: (a) increases social hope, (b) yields an abstract mindset that bridges the psychological distance between the status quo (“here and now”) and a better possible future, (c) decreases system justification motivation, and (d) promotes social justice-oriented forms of collective action.
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ItemGeneral and specific graphic health warning labels reduce willingness to consume sugar-sweetened beverages(ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2021-06-01)Sugar-sweetened beverage (SSB) consumption is associated with obesity and other severe negative health consequences. The present study examined the effectiveness of two types of health warning labels (HWLs) in modulating dietary choices for SSBs: specific HWLs, presenting health consequences associated with consuming SSBs, and general HWLs, presenting health consequences of an unhealthy diet and obesity. While electroencephalography (EEG) was recorded, 63 participants completed a computer-based task in which they were first randomly allocated to view either SBB-specific, general, or non-warning control HWLs. They then viewed images of a range of SSB products, varying on perceived healthiness and tastiness, and rated their willingness to consume (WTC) each one. Linear mixed-effect model analyses revealed that general and specific HWLs both decreased WTC SSBs perceived as tasty, compared to the control condition. For general HWLs, this effect was reduced for SSBs perceived to be healthy, suggesting that specific HWLs may be more effective at reducing SSB consumption. The EEG data showed that SSBs considered unhealthy elicited greater N1 amplitudes, and tasty SSBs elicited greater late positive potential (LPP) amplitudes, possibly reflecting attentional allocation and craving responses, respectively. However, no strong differences between HWL types were found. Taken together, the results suggest that graphic HWLs, both general and specific, have the potential to reduce SSB consumption, but they do not strongly modulate craving-related neural responses to SSBs.
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ItemDecoding explicit and implicit representations of health and taste attributes of foods in the human brain(PERGAMON-ELSEVIER SCIENCE LTD, 2021-11-12)Obesity has become a significant problem word-wide and is strongly linked to poor food choices. Even in healthy individuals, taste perceptions often drive dietary decisions more strongly than healthiness. This study tested whether health and taste representations can be directly decoded from brain activity, both when explicitly considered, and when implicitly processed for decision-making. We used multivariate support vector regression for event-related potentials (as measured by the electroencephalogram) to estimate a regression model predicting ratings of tastiness and healthiness for each participant, based on their neural activity occurring in the first second of food cue processing. In Experiment 1, 37 healthy participants viewed images of various foods and explicitly rated their tastiness and healthiness. In Experiment 2, 89 healthy participants completed a similar rating task, followed by an additional experimental phase, in which they indicated their desire to consume snack foods with no explicit instruction to consider tastiness or healthiness. In Experiment 1 both attributes could be decoded, with taste information being available earlier than health. In Experiment 2, both dimensions were also decodable, and their significant decoding preceded the decoding of decisions (i.e., desire to consume the food). However, in Experiment 2, health representations were decodable earlier than taste representations. These results suggest that health information is activated in the brain during the early stages of dietary decisions, which is promising for designing obesity interventions aimed at quickly activating health awareness.
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ItemA New Opinion Polarization Index Developed by Integrating Expert Judgments(FRONTIERS MEDIA SA, 2021-10-13)Opinion polarization is increasingly becoming an issue in today's society, producing both unrest at the societal level, and conflict within small scale communications between people of opposite opinion. Often, opinion polarization is conceptualized as the direct opposite of agreement and consequently operationalized as an index of dispersion. However, in doing so, researchers fail to account for the bimodality that is characteristic of a polarized opinion distribution. A valid measurement of opinion polarization would enable us to predict when, and on what issues conflict may arise. The current study is aimed at developing and validating a new index of opinion polarization. The weights of this index were derived from utilizing the knowledge of 58 international experts on polarization through an expert survey. The resulting Opinion Polarization Index predicted expert polarization scores in opinion distributions better than common measures of polarization, such as the standard deviation, Van der Eijk's polarization measure and Esteban and Ray's polarization index. We reflect on the use of expert ratings for the development of measurements in this case, and more in general.
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ItemA Polarized Discourse: Effects of Opinion Differentiation and Structural Differentiation on Communication(SAGE PUBLICATIONS INC, 2022-07)In Western societies, many polarized debates extend beyond the area of opinions, having consequences for social structures within society. Such segmentation of society into opinion-based groups may hinder communication, making it difficult to reconcile viewpoints across group boundaries. In three representative samples from Australia and the Netherlands (N = 1,206), we examine whether perceived polarization predicts the quality (harmony, comfort, and experience of negative emotions) and quantity (avoidance of the issue) of communication with others in the community. We distinguish between perceived opinion differentiation (i.e., the extent to which opinions in society are divided) and perceived structural differentiation (i.e., the extent to which society fissions into subgroups). Results show that although opinion differentiation positively predicts the discussion of societal issues, the belief that these opinions reflect a deeper societal divide predicts negative communication expectations and intentions. We discuss how polarization perceptions may reinforce communicative behaviors that catalyze actual polarization processes.
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ItemExplainable models for forecasting the emergence of political instability(PUBLIC LIBRARY SCIENCE, 2021-07-29)Building on previous research on the use of macroeconomic factors for conflict prediction and using data on political instability provided by the Political Instability Task Force, this article proposes two minimal forecasting models of political instability optimised to have the greatest possible predictive power for one-year and two-year event horizons, while still making predictions that are fully explainable. Both models employ logistic regression and use just three predictors: polity code (a measure of government type), infant mortality, and years of stability (i.e., years since the last instability event). These models make predictions for 176 countries on a country-year basis and achieve AUPRC's of 0.108 and 0.115 for the one-year and two-year models respectively. They use public data with ongoing availability so are readily reproducible. They use Monte Carlo simulations to construct confidence intervals for their predictions and are validated by testing their predictions for a set of reference years separate from the set of reference years used to train them. This validation shows that the models are not overfitted but suggests that some of the previous models in the literature may have been. The models developed in this article are able to explain their predictions by showing, for a given prediction, which predictors were the most influential and by using counterfactuals to show how the predictions would have been altered had these predictors taken different values. These models are compared to models created by lasso regression and it is shown that they have at least as good predictive power but that their predictions can be more readily explained. Because policy makers are more likely to be influenced by models whose predictions can explained, the more interpretable a model is the more likely it is to influence policy.