Understanding Australian Government Risk Communication Early in the COVID-19 Pandemic: Sociodemographics, Risk Attitudes and Media Consumption.

Effective risk communication is essential for government and health authorities to effectively manage public health during the Coronavirus disease (COVID-19) pandemic. Understanding the factors that influence people's perceptions of crisis-related risk messages is critical to identify gaps and inequalities in population risk communication. Using a longitudinal survey of a representative adult sample, we examined risk communication about COVID-19 during April-June 2020 in Australia across sociodemographic groups especially the at-risk groups, accounting for and exploring the effects of risk attitudes and media engagement. Our findings showed that individuals who were younger, more left-wing, more risk-tolerant, and had a current or a history of mental disorders perceived risk communication of the Australian Government to be lower quality. On the other hand, greater consumption of information from televisions was found to be associated with more positive attitudes toward government risk communication. Our results also revealed the importance of effective and high-quality risk communication in gaining the public endorsement of various public health directions. We discuss the implications of results in terms of the development of effective public communications that lead to health-protective behaviors and effectively scaffold public understanding of risk.

Measuring children's auditory statistical learning via serial recall.

Statistical learning (SL) has been a prominent focus of research in developmental and adult populations, guided by the assumption that it is a fundamental component of learning underlying higher-order cognition. In developmental populations, however, there have been recent concerns regarding the degree to which many current tasks reliably measure SL, particularly in younger children. In the current article, we present the results of two studies that measured auditory statistical learning (ASL) of linguistic stimuli in children aged 5-8 years. Children listened to 6 min of continuous syllables comprising four trisyllabic pseudowords. Following the familiarization phase, children completed (a) a two-alternative forced-choice task and (b) a serial recall task in which they repeated either target sequences embedded during familiarization or foils, manipulated for sequence length. Results showed that, although both measures consistently revealed learning at the group level, the recall task better captured learning across the full range of abilities and was more reliable at the individual level. We conclude that, as has also been demonstrated in adults, the method holds promise for future studies of individual differences in ASL of linguistic stimuli.

Caricaturing can improve facial expression recognition in low-resolution images and age-related macular degeneration.

Previous studies of age-related macular degeneration (AMD) report impaired facial expression recognition even with enlarged face images. Here, we test potential benefits of caricaturing (exaggerating how the expression's shape differs from neutral) as an image enhancement procedure targeted at mid- to high-level cortical vision. Experiment 1 provides proof-of-concept using normal vision observers shown blurred images as a partial simulation of AMD. Caricaturing significantly improved expression recognition (happy, sad, anger, disgust, fear, surprise) by ∼4%-5% across young adults and older adults (mean age 73 years); two different severities of blur; high, medium, and low intensity of the original expression; and all intermediate accuracy levels (impaired but still above chance). Experiment 2 tested AMD patients, running 19 eyes monocularly (from 12 patients, 67-94 years) covering a wide range of vision loss (acuities 6/7.5 to poorer than 6/360). With faces pre-enlarged, recognition approached ceiling and was only slightly worse than matched controls for high- and medium-intensity expressions. For low-intensity expressions, recognition of veridical expressions remained impaired and was significantly improved with caricaturing across all levels of vision loss by 5.8%. Overall, caricaturing benefits emerged when improvement was most needed, that is, when initial recognition of uncaricatured expressions was impaired.

Moderator effects differ on alternative effect-size measures.

This paper discusses largely ignored issues regarding moderation of effect-sizes. We show that, under commonly-occurring conditions, popular alternatives for effect-size measures in ANOVA and multiple regression are not moderated identically across independent samples. Effects may appear to be unmoderated according to one effect-size measure but not according to another, or may even be moderated in opposite directions. We identify the conditions under which differential effect-size moderation can occur, and show that they are commonplace. We then review techniques for detecting and dealing with differential moderation of alternative effect-size measures. Finally, we discuss implications for research practice, reporting, replication, and meta-analysis.

Can body temperature dysregulation explain the co-occurrence between overweight/obesity, sleep impairment, late-night eating, and a sedentary lifestyle?

PURPOSE: Overweight/obesity, sleep disturbance, night eating, and a sedentary lifestyle are common co-occurring problems. There is a tendency for them to co-occur together more often than they occur alone. In some cases, there is clarity as to the time course and evolution of the phenomena. However, specific mechanism(s) that are proposed to explain a single co-occurrence cannot fully explain the more generalized tendency to develop concurrent symptoms and/or disorders after developing one of the phenomena. Nor is there a clinical theory with any utility in explaining the development of co-occurring symptoms, disorders and behaviour and the mechanism(s) by which they occur. Thus, we propose a specific mechanism-dysregulation of core body temperature (CBT) that interferes with sleep onset-to explain the development of the concurrences. METHODS: A detailed review of the literature related to CBT and the phenomena that can alter CBT or are altered by CBT is provided. RESULTS: Overweight/obesity, sleep disturbance and certain behaviour (e.g. late-night eating, sedentarism) were linked to elevated CBT, especially an elevated nocturnal CBT. A number of existing therapies including drugs (e.g. antidepressants), behavioural therapies (e.g. sleep restriction therapy) and bright light therapy can also reduce CBT. CONCLUSIONS: An elevation in nocturnal CBT that interferes with sleep onset can parsimoniously explain the development and perpetuation of common co-occurring symptoms, disorders and behaviour including overweight/obesity, sleep disturbance, late-night eating, and sedentarism. Nonetheless, a significant correlation between CBT and the above symptoms, disorders and behaviour does not necessarily imply causation. Thus, statistical and methodological issues of relevance to this enquiry are discussed including the likely presence of autocorrelation. LEVEL OF EVIDENCE: Level V, narrative review.

Reasoned Decision Making Without Math? Adaptability and Robustness in Response to Surprise.

Many real-world planning and decision problems are far too uncertain, too variable, and too complicated to support realistic mathematical models. Nonetheless, we explain the usefulness, in these situations, of qualitative insights from mathematical decision theory. We demonstrate the integration of info-gap robustness in decision problems in which surprise and ignorance are predominant and where personal and collective psychological factors are critical. We present practical guidelines for employing adaptable-choice strategies as a proxy for robustness against uncertainty. These guidelines include being prepared for more surprises than we intuitively expect, retaining sufficiently many options to avoid premature closure and conflicts among preferences, and prioritizing outcomes that are steerable, whose consequences are observable, and that do not entail sunk costs, resource depletion, or high transition costs. We illustrate these concepts and guidelines with the example of the medical management of the 2003 SARS outbreak in Vietnam.

School Refusal Behaviors: The Roles of Adolescent and Parental Factors.

School refusal behaviors in adolescents have deleterious immediate and long-term consequences and are associated with mental ill-health such as anxiety and depression. Understanding factors that place youth at higher risk of school refusal behavior may assist in developing effective management approaches. We investigated parental and adolescent factors that may be associated with school refusal behaviors by specifically focusing on the role of parental and adolescent emotion dysregulation, their anxiety and depression, and parental rearing style. First, we hypothesized that adolescents with school refusal behaviors, as well as their parents, will report higher levels of emotion dysregulation, anxiety, and depression compared to their counterparts without school refusal behaviors. Furthermore, we hypothesized that multivariate models testing the role of parental and child factors concurrently will show that parental (emotion dysregulation, anxiety and depression, and rearing styles) and adolescent (emotion dysregulation, anxiety, and depression) factors are associated with school refusal behaviors. One hundred and six adolescents aged 12 to 18 years and their parents completed an online questionnaire measuring both parental and adolescent emotion dysregulation, anxiety, depression, parental rearing styles, and adolescents' school refusal behaviors. Adolescents with school refusal behaviors reported greater anxiety and depression, with their parents showing greater emotion dysregulation. Multivariate analyses showed that parental emotion dysregulation and adolescent age were associated with school refusal behaviors independently. Future management for school refusal behaviors should consider age-tailored approaches by incorporating training for parental emotion regulation skills.

The receiver operating characteristic area under the curve (or mean ridit) as an effect size.

Several authors have recommended adopting the receiver operator characteristic (ROC) area under the curve (AUC) or mean ridit as an effect size, arguing that it measures an important and interpretable type of effect that conventional effect-size measures do not. It is base-rate insensitive, robust to outliers, and invariant under order-preserving transformations. However, applications have been limited to group comparisons, and usually just two groups, in line with the popular interpretation of the AUC as measuring the probability that a randomly chosen case from one group will score higher on the dependent variable than a randomly chosen case from another group. This tutorial article shows that the AUC can be used as an effect size for both categorical and continuous predictors in a wide variety of general linear models, whose dependent variables may be ordinal, interval, or ratio level. Thus, the AUC is a general effect-size measure. Demonstrations in this article include linear regression, ordinal logistic regression, gamma regression, and beta regression. The online supplemental materials to this tutorial provide a survey of currently available software resources in R for the AUC and ridits, along with the code and access to the data used in the examples. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Compositional data analysis tutorial.

This article presents techniques for dealing with a form of dependency in data arising when numerical data sum to a constant for individual cases, that is, "compositional" or "ipsative" data. Examples are percentages that sum to 100, and hours in a day that sum to 24. Ipsative scales fell out of fashion in psychology during the 1960s and 1970s due to a lack of methods for analyzing them. However, ipsative scales have merits, and compositional data commonly occur in psychological research. Moreover, as we demonstrate, sometimes converting data to a compositional form yields insights not otherwise accessible. Fortunately, there are sound methods for analyzing compositional data. We seek to enable researchers to analyze compositional data by presenting appropriate techniques and illustrating their application to real data. First, we elaborate the technical details of compositional data and discuss both established and new approaches to their analysis. We then present applications of these methods to real social science data-sets (data and code using R are available in a supplementary document). We conclude with a discussion of the state of the art in compositional data analysis and remaining unsolved problems. A brief guide to available software resources is provided in the first section of the supplementary document. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Psychological Benefits of an Uncertain World: Hope and Optimism in the Face of Existential Threat.

We examine how prior mental health predicts hopes and how hopes predict subsequent mental health, testing hypotheses in a longitudinal study with an Australian nation-wide adult sample regarding mental health consequences of the COVID-19 outbreak during its initial stage. Quota sampling was used to select a sample representative of the adult Australian population in terms of age groups, gender, and geographical location. Mental health measures were selected to include those with the best psychometric properties. Hypotheses were tested using generalized linear models with random intercepts, with the type of GLM determined by the nature of the dependent variable. Greater anxiety, depression, distress, and loneliness predict less hope, but impaired quality of life and stress positively predict hopes of gaining new skills. Distress and loneliness predict hopes for social connectedness and an improved society, suggesting that predictors of hope depend on what is hoped for. These findings suggest the need for more nuanced theories of hope. Greater hopes for societal improvement predict lower anxiety, depression, distress, and impaired quality of life, but greater hopes for skills and better mental health predict higher levels of these covariates. Moreover, when relevant prior psychological states are more intense, the impact of hope state declines. These findings indicate that the consequences of hope are heterogeneous, and suggest a possible explanation for the seemingly inconsistent therapeutic effectiveness of raising hope.

Risk tolerance and changes in coronavirus disease (COVID) related health behaviors: A longitudinal study.

OBJECTIVE: The present study examined behavioral responses during the coronavirus disease 2019 (COVID-19) pandemic and the role of dispositional risk tolerance in the Australian context. METHOD: The study involved a six-wave longitudinal investigation with a nationally representative sample of Australians (N = 1,296). Dispositional risk tolerance was measured at Wave 1 and participants' anxiety level and self-report implementation of 10 COVID actions was assessed in each wave. Autoregressive multinomial regression models were estimated to assess the unique contribution of risk tolerance to the longitudinal change of participants' implementation of COVID actions. RESULTS: The results revealed a high implementation rate for protective actions when Australia had a peak in the severity of the COVID-19 pandemic and subsequently declined with the easing threat of the pandemic. Individuals' dispositional risk tolerance significantly predicted transition to, and endorsement of, protective actions. Participants who had low risk tolerance were more likely to remain at the state of implementing COVID-19 measures than being in, or transitioning to, other states. CONCLUSIONS: The findings suggest that when encouraging protective actions, governments and public authorities should acknowledge variability in the community in responding to risk and consider measures in addition to risk messaging to encourage protective actions among individuals with a high level of risk tolerance. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Exploiting test structure: case series, case-control comparison, and dissociation.

Most neuropsychological tests consist of multiple items, and a subject's test score is the sum of the item scores. The test results for each subject thus comprise multiple data-points, and any data-set with test results from more than one subject has at least a two-level structure, with the test item as the first level and the subject as the second level. This structure may be exploited to yield more nuanced statistical analyses than those that treat each subject's test score as a single data-point. Exploiting this structure allows us to take into account the effect of test length and dispersion on score variance and may enhance statistical power. Focusing on tests for which the score can be regarded as a binomial random variable, and using the binomial general linear model, we describe appropriate statistical methods for exploiting test structure in analysing a case series, comparing a case with a control sample, and testing for dissociation. These methods also allow multiple predictors, both categorical and continuous, to be taken into account, thereby enhancing the capacity of researchers to test hypotheses in a case series and to investigate other explanatory factors, in addition to case-control status.

Cause or symptom? A longitudinal test of bidirectional relationships between emotion regulation strategies and mental health symptoms.

Previous work has generally conceptualized emotion regulation as contributing to mental health outcomes, and not vice versa. The present study challenges this assumption by using a prospective design to investigate the directionality of underlying relationships between emotion regulation and mental health in the context of a major population-level stressor. We surveyed a large nationally representative sample of adults (18-91 years, N = 704) at three 1-month intervals across the acute lockdown phase of the COVID-19 pandemic in Australia, using standardized measures of depression and anxiety symptoms. At each time point, we also measured the use of two emotion regulation strategies-cognitive reappraisal and emotional suppression-previously associated with adaptive and maladaptive mental health outcomes, respectively. We found cognitive reappraisal was unrelated to mental health symptoms. In contrast, greater emotional suppression was robustly associated with higher symptom levels for both depression and anxiety. Longitudinal analyses revealed this association reflected bidirectional relationships. Higher symptoms of depression and anxiety each predicted greater subsequent use of emotional suppression, and greater use of emotional suppression predicted higher subsequent symptoms. This bidirectionality suggests emotional suppression is both symptomatic and predictive of psychological distress. The lack of a relationship for cognitive reappraisal is discussed with respect to the pandemic context and evidence that high stress might reduce people's ability to use this strategy effectively. Given the strong emphasis on reappraisal in clinical practice, there is a critical need to understand for whom, what and when this strategy is helpful. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Beyond risk and ambiguity: deciding under ignorance.

In this study, we examined the neural basis of decision making under different types of uncertainty that involve missing information: ambiguity (vague probabilities) and sample space ignorance (SSI; unknown outcomes). fMRI revealed that these two different types of uncertainty recruit distinct neural substrates: Ambiguity recruits the left insula, whereas SSI recruits the anterior cingulate cortex, bilateral inferior parietal cortex, and the lateral orbitofrontal cortex. The finding of unique activations for different types of uncertainty may not necessarily be predicted within the reductive approach of modern theories of decision making under uncertainty, because these theories purport that humans reduce more complicated uncertain environments to subjectively formed less complicated ones (i.e., SSI to ambiguity). The predictions of the reductive view held only for ambiguity-averse individuals and not for ambiguity-tolerant individuals. Consequently, theories of decision making under uncertainty should include individual tolerance for missing information and how these individual differences modulate the neural systems engaged during decision making. Supplemental materials for this article may be downloaded from http://cabn.psychonomic-journals.org/content/supplemental.

Impact of uncertainty and ambiguous outcome phrasing on moral decision-making.

The literature has shown that different types of moral dilemmas elicit discrepant decision patterns. The present research investigated the role of uncertainty in contributing to these decision patterns. Two studies were conducted to examine participants' choices in commonly used dilemmas. Study 1 showed that participants' perceived outcome probabilities were significantly associated with their moral choices, and that these associations were independent from the dilemma type. Study 2 revealed that participants had significantly less preference for killing the individual when the outcome probabilities were stated using the modal verb 'will' than when they were stated using the numerical phrasing of '100%'. Our findings illustrate a discord between experimenter and participant in the interpretation of task instructions.

Corrigendum: The Effect of COVID-19 on Mental Health and Wellbeing in a Representative Sample of Australian Adults.

[This corrects the article DOI: 10.3389/fpsyt.2020.579985.].

The Effect of COVID-19 on Mental Health and Wellbeing in a Representative Sample of Australian Adults.

There is minimal knowledge about the impact of large-scale epidemics on community mental health, particularly during the acute phase. This gap in knowledge means we are critically ill-equipped to support communities as they face the unprecedented COVID-19 pandemic. This study aimed to provide data urgently needed to inform government policy and resource allocation now and in other future crises. The study was the first to survey a representative sample from the Australian population at the early acute phase of the COVID-19 pandemic. Depression, anxiety, and psychological wellbeing were measured with well-validated scales (PHQ-9, GAD-7, WHO-5). Using linear regression, we tested for associations between mental health and exposure to COVID-19, impacts of COVID-19 on work and social functioning, and socio-demographic factors. Depression and anxiety symptoms were substantively elevated relative to usual population data, including for individuals with no existing mental health diagnosis. Exposure to COVID-19 had minimal association with mental health outcomes. Recent exposure to the Australian bushfires was also unrelated to depression and anxiety, although bushfire smoke exposure correlated with reduced psychological wellbeing. In contrast, pandemic-induced impairments in work and social functioning were strongly associated with elevated depression and anxiety symptoms, as well as decreased psychological wellbeing. Financial distress due to the pandemic, rather than job loss per se, was also a key correlate of poorer mental health. These findings suggest that minimizing disruption to work and social functioning, and increasing access to mental health services in the community, are important policy goals to minimize pandemic-related impacts on mental health and wellbeing. Innovative and creative strategies are needed to meet these community needs while continuing to enact vital public health strategies to control the spread of COVID-19.

Ambiguity and Conflict Aversion When Uncertainty Is in the Outcomes.

We argue that the way ambiguity has been operationalized throughout the literature on ambiguity effects has an important limitation, insofar as ambiguity in outcomes has been neglected. We report two studies where judges do encounter ambiguity in the sampled outcomes and find evidence that ambiguity aversion is not less than when judges are given a range of outcomes without reference to ambiguous outcomes themselves. This result holds regardless of whether people are presented with a sample all at once or sample outcomes sequentially. Our experiments also investigate the effects of conflicting information about outcomes, finding that conflict aversion also does not decrease. Moreover, ambiguity and conflict aversion do not seem to arise as a consequence of judges ignoring uncertain outcomes and thereby treating outcome sets as reduced samples of unambiguous (or unconflicting) information. Instead, ambiguity and conflict aversion are partly explained by more pessimistic outcome forecasts by judges. This pessimism, in turn, may be due to the judges' uncertainty about how the chance of a desirable outcome from an ambiguous or conflictive alternative compares with an equivalent risky alternative. Both studies used hypothetical scenarios, and no incentives were provided for participants' decisions.

Perceived time slows during fleeting fun or fear.

Previous psychophysical studies at durations greater than 1000 ms have confirmed the anecdotal reports of an increase in the perceived duration of both positively and negatively valenced emotive stimuli; however, the results of studies at durations less than 1000 ms have been inconsistent. This study further investigated the effect of valence on the perception of durations less than 1000 ms. We used both positively and negatively valenced stimuli in order to compare their effects on the distortion of duration, and we tested multiple data points within the sub-one-second range. We found an increase in the perceived duration of both positively and negatively valenced emotional stimuli at all data points. This is consistent with studies at durations longer than 1000 ms and also with models of temporal processing. We also confirmed that Weber fractions, within the range tested, followed the generalized form of Weber's law.

CDF-quantile distributions for modelling random variables on the unit interval.

This paper introduces a two-parameter family of distributions for modelling random variables on the (0,1) interval by applying the cumulative distribution function of one 'parent' distribution to the quantile function of another. Family members have explicit probability density functions, cumulative distribution functions and quantiles in a location parameter and a dispersion parameter. They capture a wide variety of shapes that the beta and Kumaraswamy distributions cannot. They are amenable to likelihood inference, and enable a wide variety of quantile regression models, with predictors for both the location and dispersion parameters. We demonstrate their applicability to psychological research problems and their utility in modelling real data.