Vegetarian and sustainable food consumption behavior: Exploring the relation to explicit and implicit attitudes toward vegetarian foods and dispositional mindfulness

OBJECTIVES

This study investigates the relation between explicit and implicit attitude measures toward vegetarian and meat-based foods and sustainable, specifically vegetarian food consumption behavior. Moreover, attitude preferences and differences between the nutrition groups of vegetarians/ vegans and omnivores were examined. In addition, the possible relationships between specific facets of dispositional mindfulness and explicit and implicit attitudes and nutrition behavior measures were explored.

METHODS

This is a cross-sectional online study. Two hundred sixty-one participants completed a dispositional mindfulness questionnaire, explicit and implicit nutrition attitude measurements, and nutrition behavior assessments.

RESULTS

We found a strong correlation between explicit and implicit attitude measures. Both nutrition groups showed an implicit preference for vegetarian over meat-based foods. However, the group of vegetarians/ vegans explicitly preferred vegetarian foods and vegetarianism in almost all explicit attitude measures. In contrast, the findings in the group of omnivores were rather heterogeneous. Furthermore, the results showed that measures of explicit and implicit attitudes, together with two facets of dispositional mindfulness (Outer Awareness and Insight), predicted the vegetarian choice in the online supermarket scenario, indicating positive relationships, except for Insight.

CONCLUSION

Our findings suggest a correspondence of explicit and implicit attitudes toward vegetarian foods and highlight their role in vegetarian nutrition behavior. In addition, we underscore the potential role of dispositional mindfulness and mindfulness interventions in promoting vegetarian consumption behavior. As there are attitude differences in the nutrition groups, the primary target group for mindfulness interventions should be individuals following an omnivorous diet.

Mental health and socio-cognitive predictors of adherence to COVID-19 social distancing rules in adolescents in England

The COVID-19 pandemic prompted governments worldwide to introduce social distancing measures, including school closures and restrictions on in-person socialising. However, adherence to social distancing was challenging for many - particularly adolescents, for whom social interaction is crucial for development. The current study aimed to identify individual-level influences on adherence to social distancing in a longitudinal sample of adolescents aged 11-20 years in England, who took part in a randomised controlled trial. At baseline, 460 participants completed detailed pre-pandemic assessments, including mental health and well-being, altruism, delayed reward discounting, rejection sensitivity, prosociality and susceptibility to prosocial and anti-social influence. Of these, 205 participants reported their compliance with COVID-19 social distancing rules and attendance at social gatherings between June and August 2020. Bayesian ordinal regression models were used to predict adherence to social distancing from predictors, controlling for age at pandemic, gender, day of assessment, and intervention group. The results indicated that higher levels of prosociality, altruism and lower susceptibility to anti-social influence were associated with higher adherence to social distancing. Pre-pandemic levels of depression, anxiety, delayed reward discounting, rejection sensitivity, conduct problems and emotional awareness were not robustly related to the outcomes. These findings have implications for understanding how adolescents comply with public health guidelines, highlighting the role of social influence and peer norms.

Biased attention allocation in major depressive disorder: A replication and exploration of the potential effects of depression history

BACKGROUND

Increased attention allocation to negative-valenced information and decreased attention allocation to positive-valenced information have been implicated in the etiology and maintenance of depression. The Matrix task, a free-viewing eye-tracking attention assessment task, has shown corroborating results, coupled with adequate reliability. Yet, replication efforts are still needed. Therefore, we replicated a previously published study in depression, using the same task and attention measures. We also explored the potential added effect of depression history on attention allocation.

METHODS

Participants diagnosed with major depressive disorder (n = 65) and a matched control group of healthy participants (n = 37) freely viewed 60 different face matrices, each presented for six seconds and comprised of eight sad and eight happy faces. Attention allocation to corresponding areas of interest (AOIs) was compared, and the internal consistency of attention allocation measures was assessed. We then compared the attention allocation of participants amidst their first episode (n = 33) to that of participants with a recurrent depressive episode (n = 32).

RESULTS

A significant group-by-stimulus type (happy vs. sad faces) interaction emerged for total dwell time, replicating the findings of the original study. Groups differed on attention allocation to both the sad and happy faces. No findings emerged for first fixation measures. Internal consistency of the total dwell time measure was high. Depression history had no effect on attention allocation.

LIMITATIONS

Due to ethical constraints (delay of treatment), test-retest reliability was not assessed.

CONCLUSIONS

The Matrix task provides a reliable and replicable measure of attention allocation in MDD, showing no effects for depression history.

Reliability and validity of four cognitive interpretation bias measures in the context of social anxiety

People with social anxiety disorder tend to interpret ambiguous social information in a negative rather than positive manner. Such interpretation biases may cause and maintain anxiety symptoms. However, there is considerable variability in the observed effects across studies, with some not finding a relationship between interpretation biases and social anxiety. Poor psychometric properties of interpretation bias measures may explain such inconsistent findings. We evaluated the internal consistency, test-retest reliability, convergent validity, and concurrent validity of four interpretation bias measures, ranging from more implicit and automatic to more explicit and reflective: the probe scenario task, the recognition task, the scrambled sentences task, and the interpretation and judgmental bias questionnaire. Young adults (N = 94) completed interpretation bias measures in two sessions separated by one week. Psychometric properties were poor for the probe scenario and not acceptable for the recognition task. The reliability of the scrambled sentences task and the interpretation and judgmental bias questionnaire was good, and they correlated highly with social anxiety and each other, supporting their concurrent and convergent validity. However, there are methodological challenges that should be considered when measuring interpretation biases, even if psychometric indices suggest high measurement validity. We also discuss likely reasons for poor psychometric properties of some tasks and suggest potential solutions to improve the assessment of implicit and automatic biases in social anxiety in future research.

The Conscious Side of 'Subliminal' Linguistic Priming: A Systematic Review With Meta-Analysis and Reliability Analysis of Visibility Measures

Research on unconscious processing has been a valuable source of evidence in psycholinguistics for shedding light on the cognitive architecture of language. The automaticity of syntactic processing, in particular, has long been debated. One strategy to establish this automaticity involves detecting significant syntactic priming effects in tasks that limit conscious awareness of the stimuli. Criteria for assessing unconscious priming include the visibility (d') of masked words not differing significantly from zero and no positive correlation between visibility and priming. However, such outcomes could also arise for strictly methodological reasons, such as low statistical power in visibility tests or low reliability of dependent measures. In this study, we aimed to address these potential limitations. Through meta-analysis and Bayesian re-analysis, we find evidence of low statistical power and of participants having above-chance awareness of 'subliminal' words. Moreover, we conducted reliability analyses on a dataset from Berkovitch and Dehaene (2019), finding that low reliability in both syntactic priming and visibility tasks may better explain the absence of a significant correlation. Overall, these findings cast doubt on the validity of previous conclusions regarding the automaticity of syntactic processing based on masked priming effects. The results underscore the importance of revisiting the methods employed when exploring unconscious processing in future psycholinguistic research.

A multiverse assessment of the reliability of the self-matching task as a measurement of the self-prioritization effect

The self-matching task (SMT) is widely used to investigate the cognitive mechanisms underlying the self-prioritization effect (SPE), wherein performance is enhanced for self-associated stimuli compared to other-associated ones. Although the SMT robustly elicits the SPE, there is a lack of data quantifying the reliability of this paradigm. This is problematic, given the prevalence of the reliability paradox in cognitive tasks: many well-established cognitive tasks demonstrate relatively low reliability when used to evaluate individual differences, despite exhibiting replicable effects at the group level. To fill this gap, this preregistered study investigated the reliability of SPE derived from the SMT using a multiverse approach, combining all possible indicators and baselines reported in the literature. We first examined the robustness of 24 SPE measures across 42 datasets (N = 2250) using a meta-analytical approach. We then calculated the split-half reliability (r) and intraclass correlation coefficient (ICC2) for each SPE measure. Our findings revealed a robust group-level SPE across datasets. However, when evaluating individual differences, SPE indices derived from reaction time (RT) and efficiency exhibited relatively higher, compared to other SPE indices, but still unsatisfied split-half reliability (approximately 0.5). The reliability across multiple time points, as assessed by ICC2, RT, and efficiency, demonstrated moderate levels of test-retest reliability (close to 0.5). These findings revealed the presence of a reliability paradox in the context of SMT-based SPE assessment. We discussed the implications of how to enhance individual-level reliability using this paradigm for future study design.

Connecting the tots: Strong looking-pointing correlations in preschoolers' word learning and implications for continuity in language development

How does one assess developmental change when the measures themselves change with development? Most developmental studies of word learning use either looking (infants) or pointing (preschoolers and older). With little empirical evidence of the relationship between the two measures, developmental change is difficult to assess. This paper analyzes 914 pointing, looking children (451 female, varied ethnicities, 2.5-6.5 years, dates: 2009-2019) in 36 word- or sound-learning experiments with two-alternative test trials. Looking proportions and pointing accuracy correlated strongly (r = .7). Counter to the "looks first" hypothesis, looks were not sensitive to incipient knowledge that pointing missed: when pointing is at chance, looking proportions are also. Results suggest one possible path forward for assessing continuous developmental change. Methodological best practices are discussed.

Temporal binding: Task-dependent variations and reliability across experimental paradigms

Temporal binding refers to the subjective shortening of time between a cause and its effect compared with two unrelated events. The effect has been extensively explored over the past two decades and manifests across a robust range of paradigms, reflecting two distinct expressions of binding: (1) the subjective shortening of elapsed time between cause and effect and (2) the subjective attraction of cause and effect to each other. However, whether and how these binding expressions are related is still largely unknown. In this study, we report two experiments, employing four tasks (stimulus anticipation, Libet clock, interval estimation, and reproduction). We computed within and between session and task correlations across two (Experiment 1) and six (Experiment 2) sessions. Across both experiments, we successfully replicated temporal binding in temporal estimation, temporal reproduction, and the Libet clock, but not in stimulus anticipation. Good within-task and within-session reliability were observed, but reliability between sessions was poor. Correlation analyses revealed associations between binding effects measured via temporal estimation and temporal reproduction, underscoring task-dependent variations, in line with the suggestion that different temporal tasks tap into distinct facets of the temporal binding effect. This nuanced understanding contributes to refining experimental paradigms and advancing the comprehension of human temporal processing. The data, materials, and experiments from the present study are publicly available.

Which "working memory" are we talking about? Complex span tasks versus N-back

Psychologists and neuroscientists often use complex span tasks or the n-back to measure working memory capacity. At first glance, both tasks require many cognitive processes attributed to the construct, including the maintenance of information amidst interference. Nevertheless, evidence for their convergent validity is mixed. This poses consequences for the interpretation of working memory performance in cognitive neuroscience, developmental psychology, applied psychology, and executive functioning research. We recruited a large and diverse sample using a multisite approach (N = 1,272; community and university participants) and had them complete multiple working memory capacity, updating, and fluid intelligence tests. We found strong evidence for a dissociation between complex span and n-back tests, and more broadly, between working memory capacity and updating factors. Observed correlations between complex span and n-back performance were modest (r̄ = .25), and at the latent level, the two factors only shared 20% of their variance. Each explained unique variance in fluid intelligence, and each was more strongly related to fluid intelligence than to each other, with updating measures demonstrating stronger relations to fluid intelligence. These results were interpreted via the disengagement hypothesis. What distinguishes updating measures from working memory capacity measures is their relative emphasis on disengagement from outdated information; disengagement drives their strong relation with fluid intelligence because problem-solving requires generating hypotheses but also discarding those discovered to be false. We suggest that researchers who want to measure and draw conclusions about working memory capacity or updating should not use complex span tasks and the n-back interchangeably.

Individual differences in attention control: A meta-analysis and re-analysis of latent variable studies

A meta-analysis and re-analysis of prior latent variable studies was conducted in order to assess whether there is evidence for individual differences in broad attention control abilities. Data from 90 independent samples and over 23,000 participants suggested that most (84.4%) prior studies find evidence for a coherent attention control factor with average factor loadings of .51. This latent attention control factor was related to other cognitive ability factors including working memory, shifting, fluid intelligence, long-term memory, reading comprehension, and processing speed, as well as to self-reports of task-unrelated thoughts and task specific motivation. Further re-analyses and meta-analyses suggest that the results remained largely unchanged when considering various possible measurement issues. Examining the factor structure of attention control suggested evidence for sub-components of attention control (restraining, constraining and sustaining attention) which could be accounted for a by a higher-order factor. Additional re-analyses suggested that attention control represents a broad ability within models of cognitive abilities. Overall, these results provide evidence for attention control abilities as an important individual differences construct.

Advancing the reporting of pediatric EEG data: Tools for estimating reliability, effect size, and data quality metrics

EEG studies play a crucial role in enhancing our understanding of brain development across the lifespan. The increasing clinical and policy implications of EEG research underscore the importance of utilizing reliable EEG measures and increasing the reproducibility of EEG studies. However, important data characteristics like reliability, effect sizes, and data quality metrics are often underreported in pediatric EEG studies. This gap in reporting could stem from the lack of accessible computational tools for quantifying these metrics for EEG data. To help address the lack of reporting, we developed a toolbox that facilitates the estimation of internal consistency reliability, effect size, and standardized measurement error with user-friendly software that facilitates both computing and interpreting these measures. In addition, our tool provides subsampled reliability and effect size in increasing numbers of trials. These estimates offer insights into the number of trials needed for detecting significant effects and reliable measures, informing the minimum number of trial thresholds for the inclusion of participants in individual difference analyses and the optimal trial number for future study designs. Importantly, our toolbox is integrated into commonly used preprocessing pipelines to increase the estimation and reporting of data quality metrics in developmental neuroscience.

How to Produce, Identify, and Motivate Robust Psychological Science: A Roadmap and a Response to Vize et al

Some wish to mandate preregistration as a response to the replication crisis, while I and others caution that such mandates inadvertently cause harm and distract from more critical reforms. In this article, after briefly critiquing a recently published defense of preregistration mandates, I propose a three-part vision for cultivating a robust and cumulative psychological science. First, we must know how to produce robust rather than fragile findings. Key ingredients include sufficient sample sizes, valid measurement, and honesty/transparency. Second, we must know how to identify robust (and non-robust) findings. To this end, I reframe robustness checks broadly into four types: across analytic decisions, across measures, across samples, and across investigative teams. Third, we must be motivated to produce and care about robust science. This aim requires marshaling sociocultural forces to support, reward, and celebrate the production of robust findings, just as we once rewarded flashy but fragile findings. Critically, these sociocultural reinforcements must be tied as closely as possible to rigor and robustness themselves-rather than cosmetic indicators of rigor and robustness, as we have done in the past.

Latent Structure and Item Functioning of Self-Referent Encoding Task Word Stimuli in Preadolescent Youth

The Self-Referent Encoding Task (SRET) can be used to measure self-concept via endorsement of trait words, a robust metric associated with depression severity. Our study is the first to investigate the structural validity and item functioning of SRET endorsement scores using confirmatory factor analysis and item response theory. Community-dwelling preadolescent youth (N = 508; Mage = 12.39 years, SDage = .72) were shown a list of positive and negative trait adjectives and made binary ratings of whether words were self-descriptive. The SRET exhibited a two-factor structure, comprising positive and negative factors. Positive items were endorsed by most children and best estimated information about positive self-concepts below average levels of positivity. Conversely, negative items were unendorsed by most children and best estimated information about negative self-concepts above average levels of negativity. We identify standardized, psychometrically sound, and developmentally sensitive SRET items for assessing youth self-concept and its associations with depression risk.

Test-retest reliability of behavioral and computational measures of advice taking under volatility

The development of computational models for studying mental disorders is on the rise. However, their psychometric properties remain understudied, posing a risk of undermining their use in empirical research and clinical translation. Here we investigated test-retest reliability (with a 2-week interval) of a computational assay probing advice-taking under volatility with a Hierarchical Gaussian Filter (HGF) model. In a sample of 39 healthy participants, we found the computational measures to have largely poor reliability (intra-class correlation coefficient or ICC < 0.5), on par with the behavioral measures of task performance. Further analysis revealed that reliability was substantially impacted by intrinsic measurement noise (indicated by parameter recovery analysis) and to a smaller extent by practice effects. However, a large portion of within-subject variance remained unexplained and may be attributable to state-like fluctuations. Despite the poor test-retest reliability, we found the assay to have face validity at the group level. Overall, our work highlights that the different sources of variance affecting test-retest reliability need to be studied in greater detail. A better understanding of these sources would facilitate the design of more psychometrically sound assays, which would improve the quality of future research and increase the probability of clinical translation.

Revisiting the role of computational neuroimaging in the era of integrative neuroscience

Computational models have become integral to human neuroimaging research, providing both mechanistic insights and predictive tools for human cognition and behavior. However, concerns persist regarding the ecological validity of lab-based neuroimaging studies and whether their spatiotemporal resolution is not sufficient for capturing neural dynamics. This review aims to re-examine the utility of computational neuroimaging, particularly in light of the growing prominence of alternative neuroscientific methods and the growing emphasis on more naturalistic behaviors and paradigms. Specifically, we will explore how computational modeling can both enhance the analysis of high-dimensional imaging datasets and, conversely, how neuroimaging, in conjunction with other data modalities, can inform computational models through the lens of neurobiological plausibility. Collectively, this evidence suggests that neuroimaging remains critical for human neuroscience research, and when enhanced by computational models, imaging can serve an important role in bridging levels of analysis and understanding. We conclude by proposing key directions for future research, emphasizing the development of standardized paradigms and the integrative use of computational modeling across neuroimaging techniques.

Advances in meta-analysis: A unifying modelling framework with measurement error correction

In psychological studies, multivariate outcomes measured on the same individuals are often encountered. Effects originating from these outcomes are consequently dependent. Multivariate meta-analysis examines the relationships of multivariate outcomes by estimating the mean effects and their variance-covariance matrices from series of primary studies. In this paper we discuss a unified modelling framework for multivariate meta-analysis that also incorporates measurement error corrections. We focus on two types of effect sizes, standardized mean differences (d) and correlations (r), that are common in psychological studies. Using generalized least squares estimation, we outline estimated mean vectors and variance-covariance matrices for d and r that are corrected for measurement error. Given the burgeoning research involving multivariate outcomes, and the largely overlooked ramifications of measurement error, we advocate addressing measurement error while conducting multivariate meta-analysis to enhance the replicability of psychological research.

Reaction-time task reliability is more accurately computed with permutation-based split-half correlations than with Cronbach's alpha

While it has become standard practice to report the reliability of self-report scales, it remains uncommon to do the same for experimental paradigms. To facilitate this practice, we review old and new ways to compute reliability in reaction-time tasks, and we compare their accuracy using a simulation study. Highly inaccurate and negatively biased reliability estimates are obtained through the common practice of averaging sets of trials and submitting them to Cronbach's alpha. Much more accurate reliability estimates are obtained using split-half reliability methods, especially by computing many random split-half correlations and aggregating them in a metric known as permutation-based split-half reliability. Through reanalysis of existing data and comparison of reliability values reported in the literature, we confirm that Cronbach's alpha also tends to be lower than split-half reliability in real data. We further establish a set of practices to maximize the accuracy of the permutation-based split-half reliability coefficient through simulations. We find that its accuracy is improved by ensuring each split-half dataset contains an approximately equal number of trials for each stimulus, by correcting the averaged correlation for test length using a modified variant of the Spearman-Brown formula, and by computing a sufficient number of split-half correlations: around 5,400 are needed to obtain a stable estimate for median-based double-difference scores computed from 30 participants and 256 trials. To conclude, we review the available software for computing this coefficient.

Comparing methods for assessing the reliability of health care quality measures

Quality measurement plays an increasing role in U.S. health care. Measures inform quality improvement efforts, public reporting of variations in quality of care across providers and hospitals, and high-stakes financial decisions. To be meaningful in these contexts, measures should be reliable and not heavily impacted by chance variations in sampling or measurement. Several different methods are used in practice by measure developers and endorsers to evaluate reliability; however, there is uncertainty and debate over differences between these methods and their interpretations. We review methods currently used in practice, pointing out differences that can lead to disparate reliability estimates. We compare estimates from 14 different methods in the case of two sets of mental health quality measures within a large health system. We find that estimates can differ substantially and that these discrepancies widen when sample size is reduced.

Openness to experience predicts eye movement behavior during scene viewing

Individuals' abilities to perform goal-directed spatial deployments of attention are distinguishable from their broader preferences for how they use spatial attention when circumstances do not compel a specific deployment strategy. Although these preferences are likely to play a major role in how we interact with the visual world during daily life, they remain relatively understudied. This exploratory study investigated two key questions about these preferences: firstly, are individuals consistent in their preferences for how they deploy their spatial attention when making shifts of attention versus adopting an attentional breadth? Secondly, which other factors are associated with these preferences? Across two experiments, we measured how participants preferred to deploy both attentional breadth (using an adapted Navon task) and eye movements (using a free-viewing task). We also measured participants' working memory capacities (Experiment 1), and their personalities and world beliefs (Experiment 2). In both experiments, there were consistent individual differences in preference for attentional breadth and eye movement characteristics, but these two kinds of preference were unrelated to each other. Working memory capacity was not linked to these preferences. Conversely, the personality trait of Openness to Experience robustly predicted two aspects of eye movement behavior preference, such that higher levels of Openness predicted smaller saccades and shorter scan paths. This suggests that personality dimensions may predict preferences for more absorbed engagement with visual information. However, it appears that individuals' preferences for shifts of attention during scene viewing do not necessarily relate to the breadth of attention they choose to adopt.

The Ambiguous Cue Task: Measurement reliability of an experimental paradigm for the assessment of interpretation bias and associations with mental health

Interpretation biases in the processing of ambiguous affective information are assumed to play an important role in the onset and maintenance of emotional disorders. Reports of low reliability for experimental measures of cognitive biases have called into question previous findings on the association of these measures with markers of mental health and demonstrated the need to systematically evaluate measurement reliability for measures of cognitive biases. We evaluated reliability and correlations with self-report measures of mental health for interpretation bias scores derived from the Ambiguous Cue Task (ACT), an experimental paradigm for the assessment of approach-avoidance behavior towards ambiguous affective stimuli. For a non-clinical sample, the measurement of an interpretation bias with the ACT showed high internal consistency (rSB = .91 - .96, N = 354) and acceptable 2-week test-retest correlations (rPearson = .61 - .65, n = 109). Correlations between the ACT interpretation bias scores and mental health-related self-report measures of personality and well-being were generally small (r ≤ |.11|) and statistically not significant when correcting for multiple comparisons. These findings suggest that in non-clinical populations, individual differences in the interpretation of ambiguous affective information as assessed with the ACT do not show a clear association with self-report markers of mental health. However, in allowing for a highly reliable measurement of interpretation bias, the ACT provides a valuable tool for studies considering potentially small effect sizes in non-clinical populations by studying bigger samples as well as for work on clinical populations, for which potentially greater effects can be expected.

Consistency within change: Evaluating the psychometric properties of a widely used predictive-inference task

Rapid adaptation to sudden changes in the environment is a hallmark of flexible human behaviour. Many computational, neuroimaging, and even clinical investigations studying this cognitive process have relied on a behavioural paradigm known as the predictive-inference task. However, the psychometric quality of this task has never been examined, leaving unanswered whether it is indeed suited to capture behavioural variation on a within- and between-subject level. Using a large-scale test-retest design (T1: N = 330; T2: N = 219), we assessed the internal (internal consistency) and temporal (test-retest reliability) stability of the task's most used measures. We show that the main measures capturing flexible belief and behavioural adaptation yield good internal consistency and overall satisfying test-retest reliability. However, some more complex markers of flexible behaviour show lower psychometric quality. Our findings have implications for the large corpus of previous studies using this task and provide clear guidance as to which measures should and should not be used in future studies.

Developing and Validating of the Family Coping Scale for Patients with Chronic Heart Failure

Background

: Family coping, as an essential part of family management of patients with chronic heart failure (CHF), is an important component of CHF interventions, affecting the health of patients, family members, and the whole family. It is necessary to understand the current situation of family coping in patients with CHF to facilitate the development of family interventions for patients with CHF. This study aims to develop and validate a tool for assessing the family coping scale for patients with CHF.

Methods

The semi-structured interviews, expert consensus meetings, expert consultations, and item analysis were used to develop the initial scale. We employed classical test theory and exploratory factor analysis to scrutinize and refine the items in the scale. To validate the scale, we used confirmatory factor analysis to assess structural validity. We assessed internal consistency, and split-half reliability to ensure the scale's robustness and accuracy.

Results

The FCS-CHF consisted of 24 items, including six dimensions: strategies for better management of CHF, psychological coping, substantial support by family members, emergency coping, overall heart failure awareness, and patients' health behavior. The results of confirmatory factor analysis showed that the scale fitted the data with well construct validity. The results of the confirmatory factor analysis for the overall goodness of fit indices for the fitted model were found to be acceptable for the scale. The scale demonstrates good reliability and validity, meeting the requirements of psychometrics.

Conclusions

The FCS-CHF developed in this study is considered reliable and valid, which can measure family coping in patients with CHF and provide a basis for developing family coping enhancement strategies.

A meta-analysis on the relationship between subjective cognitive failures as measured by the cognitive failures questionnaire (CFQ) and objective performance on executive function tasks

The Cognitive Failures Questionnaire (CFQ) has been widely used as a measure of subjective cognitive function in everyday life for decades. However, the evidence on how it relates to objective performance on executive function tasks is mixed. One possible reason for these mixed results is that the CFQ has selective relationships with some aspects of executive function and not others. Here, therefore, we classified tasks according to an influential framework of executive functions-switching, updating, inhibition, and we also considered the Sustained Attention to Response Task (SART) as a category because it was custom designed to gauge cognitive failures. We synthesized a large body of available evidence and performed four Bayesian meta-analyses on the relationship between CFQ scores and objective performance on executive function tasks in these four categories. Results suggested that CFQ scores were associated with objective performance on SART (18 effect sizes, μ = -.19, BF10 = 18.03, i.e., 18.03 times more evidence of a relationship versus no relationship), updating working memory (49 effect sizes, μ = -.06, BF10 = 17.80), and inhibition tasks (41 effect sizes, μ = -.07, BF10 = 15.40), whereas there was not definitive evidence regarding switching (34 effect sizes, μ = -.06, BF10 = .50, i.e., two times greater evidence for no relationship). This suggests that subjective cognitive function can predict objective performance on at least some executive function tasks. We discuss methodological and theoretical factors that constrain the maximum observable correlation and consider the relative insights that subjective measures versus task performance provide.

Neuroticism is Associated With Greater Affective Variability at High Levels of Momentary Affective Well-Being, but With Lower Affective Variability at Low Levels of Momentary Affective Well-Being

OBJECTIVE

Research challenged the notion that neuroticism correlates with affective variability, suggesting that it may result from statistical artifacts due to the non-normal distribution of negative affect. We aim to advance this line of research by (a) introducing affect balance as a normally distributed measure of affective well-being and (b) examining current affect balance as a moderator of the relationship between neuroticism and affect balance variability.

METHOD

We meta-analyzed the results of 14 ambulatory assessment datasets (N = 2389 participants, N = 174,423 observations).

RESULTS

We found that while the associations between the mean and affective variability were large for negative affect, they were much smaller for affect balance. Moreover, the association between neuroticism and variability in negative affect was very small, yet medium-sized for affect balance. Importantly, the latter association depended on current affect levels: Participants high relative to low in neuroticism showed stronger subsequent fluctuations in affect balance when currently feeling better than usual, but weaker subsequent fluctuations in (and thus more persistent) affect balance when currently feeling worse than usual.

CONCLUSION

Increased variability should not be seen as a bad sign but may be a sign that an affective system is changing, which may be adaptive or maladaptive for an individual, depending on the initial state of the system.

On the reliability of value-modulated attentional capture: An online replication and multiverse analysis

Stimuli predicting rewards are more likely to capture attention, even when they are not relevant to our current goals. Individual differences in value-modulated attentional capture (VMAC) have been associated with various psychopathological conditions in the scientific literature. However, the claim that this attentional bias can predict individual differences requires further exploration of the psychometric properties of the most common experimental paradigms. The current study replicated the VMAC effect in a large online sample (N = 182) and investigated the internal consistency, with a design that allowed us to measure the effect during learning (rewarded phase) and after acquisition, once feedback was omitted (unrewarded phase). Through the rewarded phase there was gradual increase of the VMAC effect, which did not decline significantly throughout the unrewarded phase. Furthermore, we conducted a reliability multiverse analysis for 288 different data preprocessing specifications across both phases. Specifications including more blocks in the analysis led to better reliability estimates in both phases, while specifications that removed more outliers also improved reliability, suggesting that specifications with more, but less noisy, trials led to better reliability estimates. Nevertheless, in most instances, especially those considering fewer blocks of trials, reliability estimates fell below the minimum recommended thresholds for research on individual differences. Given the present results, we encourage researchers working on VMAC to take into account reliability when designing studies aimed at capturing individual differences and provide recommendations to improve methodological practices.

Temporal stability of Bayesian belief updating in perceptual decision-making

Bayesian inference suggests that perception is inferred from a weighted integration of prior contextual beliefs with current sensory evidence (likelihood) about the world around us. The perceived precision or uncertainty associated with prior and likelihood information is used to guide perceptual decision-making, such that more weight is placed on the source of information with greater precision. This provides a framework for understanding a spectrum of clinical transdiagnostic symptoms associated with aberrant perception, as well as individual differences in the general population. While behavioral paradigms are commonly used to characterize individual differences in perception as a stable characteristic, measurement reliability in these behavioral tasks is rarely assessed. To remedy this gap, we empirically evaluate the reliability of a perceptual decision-making task that quantifies individual differences in Bayesian belief updating in terms of the relative precision weighting afforded to prior and likelihood information (i.e., sensory weight). We analyzed data from participants (n = 37) who performed this task twice. We found that the precision afforded to prior and likelihood information showed high internal consistency and good test-retest reliability (ICC = 0.73, 95% CI [0.53, 0.85]) when averaged across participants, as well as at the individual level using hierarchical modeling. Our results provide support for the assumption that Bayesian belief updating operates as a stable characteristic in perceptual decision-making. We discuss the utility and applicability of reliable perceptual decision-making paradigms as a measure of individual differences in the general population, as well as a diagnostic tool in psychiatric research.

Capturing individual differences in sentence processing: How reliable is the self-paced reading task?

Advances in research on language processing have originally come from group-level comparisons, but there is now a growing interest in individual differences. To investigate individual differences, tasks that have shown robust group-level differences are often used with the implicit assumption that they will also be reliable when used as an individual differences measure. Here, we examined whether one of the primary tasks used in psycholinguistic research on language processing, the self-paced reading task, can reliably measure individual differences in relative clause processing. We replicated the well-established effects of relative clauses at the group level, with object relative clauses being more difficult to process than subject relative clauses. However, when using difference scores, the reliability of the size of the relative clause effect was close to zero because the self-paced reading times for the different relative clause types were highly correlated within individuals. Nonetheless, we found that the self-paced reading task can be used to reliably capture individual differences in overall reading speed as well as key sentence regions when the two types of relative clause sentences are considered separately. Our results indicate that both the reliability and validity of different sentence regions need to be assessed to determine whether and when self-paced reading can be used to examine individual differences in language processing.

Individual differences in visual search: A systematic review of the link between visual search performance and traits or abilities

Visual search (VS) comprises a class of tasks that we typically perform several times during a day and requires intentionally scanning (with or without moving the eyes) the environment for a specific target (be it an object or a feature) among distractor stimuli. Experimental research in lab-based or real-world settings has offered insight into its underlying neurocognitive mechanisms from a nomothetic point of view. A lesser-known but rapidly growing body of quasi-experimental and correlational research has explored the link between individual differences and VS performance. This combines different research traditions and covers a wide range of individual differences in studies deploying a vast array of VS tasks. As such, it is a challenge to determine whether any associations highlighted in single studies are robust when considering the wider literature. However, clarifying such relationships systematically and comprehensively would help build more accurate models of VS, and it would highlight promising directions for future research. This systematic review provides an up to date and comprehensive synthesis of the existing literature investigating associations between common indices of performance in VS tasks and measures of individual differences mapped onto four categories of cognitive abilities (short-term working memory, fluid reasoning, visual processing and processing speed) and seven categories of traits (Big Five traits, trait anxiety and autistic traits). Consistent associations for both traits (in particular, conscientiousness, autistic traits and trait anxiety - the latter limited to emotional stimuli) and cognitive abilities (particularly visual processing) were identified. Overall, however, informativeness of future studies would benefit from checking and reporting the reliability of all measurement tools, applying multiplicity correction, using complementary techniques, study preregistration and testing why, rather than only if, a robust relation between certain individual differences and VS performance exists.

Test-retest reliability of reinforcement learning parameters

It has recently been suggested that parameter estimates of computational models can be used to understand individual differences at the process level. One area of research in which this approach, called computational phenotyping, has taken hold is computational psychiatry. One requirement for successful computational phenotyping is that behavior and parameters are stable over time. Surprisingly, the test-retest reliability of behavior and model parameters remains unknown for most experimental tasks and models. The present study seeks to close this gap by investigating the test-retest reliability of canonical reinforcement learning models in the context of two often-used learning paradigms: a two-armed bandit and a reversal learning task. We tested independent cohorts for the two tasks (N = 69 and N = 47) via an online testing platform with a between-test interval of five weeks. Whereas reliability was high for personality and cognitive measures (with ICCs ranging from .67 to .93), it was generally poor for the parameter estimates of the reinforcement learning models (with ICCs ranging from .02 to .52 for the bandit task and from .01 to .71 for the reversal learning task). Given that simulations indicated that our procedures could detect high test-retest reliability, this suggests that a significant proportion of the variability must be ascribed to the participants themselves. In support of that hypothesis, we show that mood (stress and happiness) can partly explain within-participant variability. Taken together, these results are critical for current practices in computational phenotyping and suggest that individual variability should be taken into account in the future development of the field.

Split-sample reliability estimation in health care quality measurement: Once is not enough

OBJECTIVE

To examine the sensitivity of split-sample reliability estimates to the random split of the data and propose alternative methods for improving the stability of the split-sample method.

DATA SOURCES AND STUDY SETTING

Data were simulated to reflect a variety of real-world quality measure distributions and scenarios. There is no date range to report as the data are simulated.

STUDY DESIGN

Simulation studies of split-sample reliability estimation were conducted under varying practical scenarios.

DATA COLLECTION/EXTRACTION METHODS

All data were simulated using functions in R.

PRINCIPAL FINDINGS

Single split-sample reliability estimates can be very dependent on the random split of the data, especially in low sample size and low variability settings. Averaging split-sample estimates over many splits of the data can yield a more stable reliability estimate.

CONCLUSIONS

Measure developers and evaluators using the split-sample reliability method should average a series of reliability estimates calculated from many resamples of the data without replacement to obtain a more stable reliability estimate.

Towards implementation of cognitive bias modification in mental health care: State of the science, best practices, and ways forward

Cognitive bias modification (CBM) has evolved from an experimental method testing cognitive mechanisms of psychopathology to a promising tool for accessible digital mental health care. While we are still discovering the conditions under which clinically relevant effects occur, the dire need for accessible, effective, and low-cost mental health tools underscores the need for implementation where such tools are available. Providing our expert opinion as Association for Cognitive Bias Modification members, we first discuss the readiness of different CBM approaches for clinical implementation, then discuss key considerations with regard to implementation. Evidence is robust for approach bias modification as an adjunctive intervention for alcohol use disorders and interpretation bias modification as a stand-alone intervention for anxiety disorders. Theoretical predictions regarding the mechanisms by which bias and symptom change occur await further testing. We propose that CBM interventions with demonstrated efficacy should be provided to the targeted populations. To facilitate this, we set a research agenda based on implementation frameworks, which includes feasibility and acceptability testing, co-creation with end-users, and collaboration with industry partners.

Evaluating the efficacy of cranial electrotherapy stimulation in mitigating anxiety-induced cognitive deficits

Cranial electrotherapy stimulation (CES) is a form of non-invasive brain stimulation (NIBS) that has demonstrated potential to modulate neural activity in a manner that may be conducive to improved cognitive performance. While other forms of NIBS, such as transcranial direct current stimulation (tDCS), have received attention in the field as potential acute cognitive enhancers, CES remains relatively unexplored. The current study aimed to assess the efficacy of CES in improving acute cognitive performance under normal experimental conditions, as well as during sessions of induced situational anxiety (threat of shock or ToS). To study this question, participants completed a cognitive battery assessing processing speed and distinct aspects of executive functioning (working memory, inhibition, and task switching) in two separate sessions in which they received active and sham CES. Participants were randomly assigned to between subject groups of either situational anxiety (ToS) or control condition (no ToS). We predicted that active CES would improve performance on assessments of executive functioning (working memory, inhibition, and task switching) relative to sham CES under ToS. We did not find any significant effects of ToS, CES, or an interaction between ToS and CES for any measures of executive functioning or processing speed. These findings suggest that a single dose of CES does not enhance executive functioning or processing speed under normal conditions or during ToS.

Negative affective priming: Reliability and associations with depression symptoms in three samples

The negative affective priming (NAP) task is a behavioral measure of inhibition of emotional stimuli. Previous studies using the NAP task have found that individuals with depression show reduced inhibition of negative stimuli, suggesting that inhibition biases may play a role in the etiology and maintenance of depression. However, the psychometric properties of the NAP task have not been evaluated or reported. In the present study, we report data on the association between NAP task performance and depression symptoms in three independent samples, and we evaluate the internal consistency and test-retest reliability of the NAP effect indices. The NAP effect for both negative and positive target words had poor internal consistency in all three samples, as well as poor 2-week (Study 2) and 6-month (Study 3) test-retest reliability. The internal consistency and test-retest reliability of response times (RT) for the individual trial types were moderate to high, as were the intercorrelations between trial types. This pattern of results indicates that overall RT is reliable but variance in RTs for the different trial types in the NAP task is indistinguishable from variance in overall RT. Depression symptom severity was not associated with the NAP effect for negative or positive target words in any of the samples, which could be due to the poor reliability of the NAP effect. Based on these findings, we do not recommend that researchers use the NAP task as a measure of individual differences in the inhibition of emotional stimuli.

Reliability of variability and complexity measures for task and task-free BOLD fMRI

Brain activity continuously fluctuates over time, even if the brain is in controlled (e.g., experimentally induced) states. Recent years have seen an increasing interest in understanding the complexity of these temporal variations, for example with respect to developmental changes in brain function or between-person differences in healthy and clinical populations. However, the psychometric reliability of brain signal variability and complexity measures-which is an important precondition for robust individual differences as well as longitudinal research-is not yet sufficiently studied. We examined reliability (split-half correlations) and test-retest correlations for task-free (resting-state) BOLD fMRI as well as split-half correlations for seven functional task data sets from the Human Connectome Project to evaluate their reliability. We observed good to excellent split-half reliability for temporal variability measures derived from rest and task fMRI activation time series (standard deviation, mean absolute successive difference, mean squared successive difference), and moderate test-retest correlations for the same variability measures under rest conditions. Brain signal complexity estimates (several entropy and dimensionality measures) showed moderate to good reliabilities under both, rest and task activation conditions. We calculated the same measures also for time-resolved (dynamic) functional connectivity time series and observed moderate to good reliabilities for variability measures, but poor reliabilities for complexity measures derived from functional connectivity time series. Global (i.e., mean across cortical regions) measures tended to show higher reliability than region-specific variability or complexity estimates. Larger subcortical regions showed similar reliability as cortical regions, but small regions showed lower reliability, especially for complexity measures. Lastly, we also show that reliability scores are only minorly dependent on differences in scan length and replicate our results across different parcellation and denoising strategies. These results suggest that the variability and complexity of BOLD activation time series are robust measures well-suited for individual differences research. Temporal variability of global functional connectivity over time provides an important novel approach to robustly quantifying the dynamics of brain function. PRACTITIONER POINTS: Variability and complexity measures of BOLD activation show good split-half reliability and moderate test-retest reliability. Measures of variability of global functional connectivity over time can robustly quantify neural dynamics. Length of fMRI data has only a minor effect on reliability.

Is it really a neuromyth? A meta-analysis of the learning styles matching hypothesis

Learning styles have been a contentious topic in education for years. The purpose of this study was to conduct a meta-analysis of the effects of matching instruction to modality learning styles compared to unmatched instruction on learning outcomes. A systematic search of the research findings yielded 21 eligible studies with 101 effect sizes and 1,712 participants for the meta-analysis. Based on robust variance estimation, there was an overall benefit of matching instruction to learning styles, g = 0.31, SE = 0.12, 95% CI = [0.05, 0.57], p = 0.02. However, only 26% of learning outcome measures indicated matched instruction benefits for at least two styles, indicating a crossover interaction supportive of the matching hypothesis. In total, 12 studies without sufficient statistical details for the meta-analysis were also examined for an indication of a crossover effect; 25% of these studies had findings indicative of a crossover interaction. Given the time and financial expenses of implementation coupled with low study quality, the benefits of matching instruction to learning styles are interpreted as too small and too infrequent to warrant widespread adoption.

A measure of reliability convergence to select and optimize cognitive tasks for individual differences research

Surging interest in individual differences has faced setbacks in light of recent replication crises in psychology, for example in brain-wide association studies exploring brain-behavior correlations. A crucial component of replicability for individual differences studies, which is often assumed but not directly tested, is the reliability of the measures we use. Here, we evaluate the reliability of different cognitive tasks on a dataset with over 250 participants, who each completed a multi-day task battery. We show how reliability improves as a function of number of trials, and describe the convergence of the reliability curves for the different tasks, allowing us to score tasks according to their suitability for studies of individual differences. We further show the effect on reliability of measuring over multiple time points, with tasks assessing different cognitive domains being differentially affected. Data collected over more than one session may be required to achieve trait-like stability.

A proof-of-concept study testing the factor structure of the Stop Signal Task: overlap with substance use and mental health symptoms

Background: Research utilizing experimental tasks usually does not report estimates of internal reliability of measurement. However, modern measurement theories conceptualize reliability as sample dependent indicating that reliability should be empirically demonstrated in the samples used to make inferences.Objectives: Test whether confirmatory factor analytic (CFA) estimates of reliability can be applied to a commonly used task measuring response inhibition (the Stop Signal Task) to predict substance use (alcohol and cannabis) and mental health symptoms.Methods: Thirty-seven participants between the ages of 18-20 (72% female; 16% Asian, 3% Native American, 11% Black or African American, 59% White; 32% Latino/a/x) were recruited via social media advertisement and attended a laboratory visit. The Stop Signal Reaction Time (SSRT) was calculated as the outcome for three experimental blocks and used as indicators in a CFA.Results: CFA suggests the task yields reliable scores; factor loadings were statistically significant (p < .05) and substantial (standardized loadings ranged from .74 to .94). However, reliability increased across experimental blocks and error was non-trivial (ranging from 50% to 12% of the variance). The inhibition factor predicted higher maximum number of drinks consumed (β = .37, p < .05), higher frequency of cannabis use (β = .39, p < .05), and more cannabis use occasions within using days (β = .40, p < .05), as well as facets of mental health (anxious/depression, attention, and anxiety problems; all p's < .05).Conclusion: Results support the utility of CFA to test for reliability of measurement, with the ability to inhibit dominant responses serving as a transdiagnostic correlate of substance use and mental health problems.

Decoupling the Conflicting Evaluative Meanings in Automatically Activated Race-Based Associations

Implicit measures of attitudes have classically focused on the association between a social group and generalized valence, but debate exists surrounding how these associations arise and what they can tell us about beliefs and attitudes. Here, we suggest that representations of oppression, which relate positively to implicitly measured prejudice but negatively to explicitly measured prejudice, can serve to decrease the predictive validity of implicit measures through statistical suppression. We had participants complete a Black-White implicit association test (IAT) and an IAT measuring representations of oppression, and find that oppression-related representations statistically suppress the relation between IAT scores and explicit attitudes, such that accounting for these representations increases the total amount of variance explained by implicit measures. We discuss the implications of this work both for practical matters around use of the IAT and for theoretical debates on the conceptualization of valence in implicit attitudes.

Individual differences in emotion-induced blindness: Are they reliable and what do they measure?

The emotion-induced-blindness (EIB) paradigm has been extensively used to investigate attentional biases to emotionally salient stimuli. However, the low reliability of EIB scores (the difference in performance between the neutral and emotionally salient condition) limits the effectiveness of the paradigm for investigating individual differences. Here, across two studies, we investigated whether we could improve the reliability of EIB scores. In Experiment 1, we introduced a mid-intensity emotionally salient stimuli condition, with the goal of obtaining a wider range of EIB magnitudes to promote reliability. In Experiment 2, we sought to reduce the attentional oddball effect, so we created a modified EIB paradigm by removing the filler images. Neither of these approaches improved the reliability of the EIB scores. Reliability for the high- and mid-intensity EIB difference scores were low, while reliability of the scores for absolute performance (neutral, high-, and mid-intensity) were high and the scores were also highly correlated, even though overall performance in the emotionally salient conditions were significantly worse than in the neutral conditions. Given these results, we can conclude that while emotionally salient stimuli impair performance in the EIB task compared with the neutral condition, the strong correlation between the emotionally salient and neutral conditions means that while EIB can be used to investigate individual differences in attentional control, it is not selective to individual differences in attentional biases to emotionally salient stimuli.

Individual differences in the use of top-down versus bottom-up cues to resolve phonetic ambiguity

How listeners weight a wide variety of information to interpret ambiguities in the speech signal is a question of interest in speech perception, particularly when understanding how listeners process speech in the context of phrases or sentences. Dominant views of cue use for language comprehension posit that listeners integrate multiple sources of information to interpret ambiguities in the speech signal. Here, we study how semantic context, sentence rate, and vowel length all influence identification of word-final stops. We find that while at the group level all sources of information appear to influence how listeners interpret ambiguities in speech, at the level of the individual listener, we observe systematic differences in cue reliance, such that some individual listeners favor certain cues (e.g., speech rate and vowel length) to the exclusion of others (e.g., semantic context). While listeners exhibit a range of cue preferences, across participants we find a negative relationship between individuals' weighting of semantic and acoustic-phonetic (sentence rate, vowel length) cues. Additionally, we find that these weightings are stable within individuals over a period of 1 month. Taken as a whole, these findings suggest that theories of cue integration and speech processing may fail to capture the rich individual differences that exist between listeners, which could arise due to mechanistic differences between individuals in speech perception.

Don't SNARC me now! Intraindividual variability of cognitive phenomena - Insights from the Ironman paradigm

Two implicit generalizations are often made from group-level studies in cognitive experimental psychology and their common statistical analysis in the general linear model: (1) Group-level phenomena are assumed to be present in every participant with variations between participants being often treated as random error in data analyses; (2) phenomena are assumed to be stable over time. In this preregistered study, we investigated the validity of these generalizations in the commonly used parity judgment task. In the proposed Ironman paradigm, the intraindividual presence and stability of three popular numerical cognition effects were tested in 10 participants on 30 days: the SNARC (Spatial-Numerical Association of Response Codes, i.e., faster left-/right-sided responses to small/large magnitude numbers, respectively; Dehaene, Bossini, & Giraux, 1993), MARC (Linguistic Markedness of Response Codes; i.e., faster left-/right-sided responses to odd/even numbers, respectively; Nuerk, Iversen, & Willmes, 2004), and Odd (i.e., faster responses to even numbers; Hines, 1990) effects. We replicated the group-level effects; however, they were reliably present in only four to five (SNARC), six (MARC) or five (Odd) of 10 participants. Fluctuations seemed unsystematic, although the SNARC effect decreased over time along with reaction times. No correlation between the SNARC and MARC effects and sleep duration, tiredness, daytime, and consumption of stimulants were detected in most participants. These results challenge the frequent generalizations from group-level phenomena to individual participants and from single sessions to typical behavior. The innovative Ironman paradigm combined with bootstrap analyses permits unique insights into the intraindividual presence and stability of cognitive phenomena.

The effect of an odd-one-out visual search task on attentional bias, body size adaptation, and body dissatisfaction

Body image disturbance is a both a risk factor for, and a symptom of, many eating disorders and refers to the misperception of and dissatisfaction with one's own body. Women with high body dissatisfaction have been shown to direct more attention to low body mass index (BMI) bodies, which results in the overestimation of body size via body size adaptation. Therefore, attention may have a causal role in body image disturbance. We conducted a novel training visual search task with 142 young adult women who we trained to attend to either high or low BMI bodies. We assessed the effects of this training on attention to bodies of different sizes, body size adaptation, and body dissatisfaction. Women trained to attend to low BMI bodies decreased their perceptions of a 'normal' body size via adaptation from pre- to post-training (p < 0.001); however, women trained to attend to high BMI bodies showed no change in their perception of a 'normal' body size. We found no lasting effects of the training on attention to body size or body dissatisfaction; however, our visual search task showed poor internal consistency as a measure of attention. These findings indicate that attention to low BMI bodies may exacerbate body image disturbance in women. However, more reliable measures of attentional are required to confirm this finding.

Revisiting representativeness heuristic classic paradigms: Replication and extensions of nine experiments in Kahneman and Tversky (1972)

Kahneman and Tversky showed that when people make probability judgements, they tend to ignore relevant statistical information (e.g., sample size) and instead rely on a representativeness heuristic, whereby subjective probabilities are influenced by the degree to which a target is perceived as similar to (representative of) a typical example of the relevant population, class or category. Their article has become a cornerstone in many lines of research and has been used to account for various biases in judgement and decision-making. Despite the impact this article has had on theory and practice, there have been no direct replications. In a pre-registered experiment (N = 623; Amazon MTurk on CloudResearch), we conducted a replication and extensions of nine problems from Kahneman and Tversky's 1972 article. We successfully replicated eight out of the nine problems. We extended the replication by examining the consistency of heuristic responses across problems and by examining decision style as a predictor of participants' use of the representativeness heuristic. Materials, data, and code are available on: https://osf.io/nhqc4/.

Sleep-related attentional bias in insomnia: The mediating role of arousal

BACKGROUND AND OBJECTIVES

Characterize the nature of attentional biases toward nocturnal and diurnal sleep-related stimuli in individuals with insomnia disorder. We investigated the contributing role of sleep-related attentional biases in insomnia severity and whether their effects on insomnia severity were mediated by arousal and valence levels of the presented stimuli.

METHODS

Sixty-four individuals with insomnia disorder and 70 controls completed two Posner spatial cueing tasks including both nocturnal (alarm clocks) and diurnal (fatigue) pictorial stimuli associated with neutral cues. Arousal and valence of the sleep-related stimuli were assessed using a 5-point Likert type scale.

RESULTS

Attention biases characterized by difficulty disengaging from and increased avoidance for daytime fatigue, and by difficulty disengaging from alarm clocks were observed in individuals with insomnia disorder compared to controls. On the whole sample, difficulty to disengage from diurnal and nocturnal sleep-related stimuli were related mostly to higher arousal rating of sleep-related stimuli and insomnia severity. Higher arousal rating for sleep-related stimuli mediates the relationship between difficulty disengaging and insomnia severity.

LIMITATIONS

The cross-sectional nature of the study.

CONCLUSIONS

We provide first initial evidence for an attentional bias characterized by on one side, avoidance for diurnal sleep-related stimuli and on other side, disengagement for both diurnal and nocturnal sleep-related stimuli in patients with insomnia. Disengagement difficulties for both diurnal and nocturnal sleep-related stimuli indirectly affected insomnia severity through arousal elicited by these stimuli. It appears important to develop and apply attentional bias modification training therapeutic interventions that can effectively reduce sleep-related arousal and attentional biases.

On the (un)reliability of common behavioral and electrophysiological measures from the stop signal task: Measures of inhibition lack stability over time

Response inhibition, the intentional stopping of planned or initiated actions, is often considered a key facet of control, impulsivity, and self-regulation. The stop signal task is argued to be the purest inhibition task we have, and it is thus central to much work investigating the role of inhibition in areas like development and psychopathology. Most of this work quantifies stopping behavior by calculating the stop signal reaction time as a measure of individual stopping latency. Individual difference studies aiming to investigate why and how stopping latencies differ between people often do this under the assumption that the stop signal reaction time indexes a stable, dispositional trait. However, empirical support for this assumption is lacking, as common measures of inhibition and control tend to show low test-retest reliability and thus appear unstable over time. The reasons for this could be methodological, where low stability is driven by measurement noise, or substantive, where low stability is driven by a larger influence of state-like and situational factors. To investigate this, we characterized the split-half and test-retest reliability of a range of common behavioral and electrophysiological measures derived from the stop signal task. Across three independent studies, different measurement modalities, and a systematic review of the literature, we found a pattern of low temporal stability for inhibition measures and higher stability for measures of manifest behavior and non-inhibitory processing. This pattern could not be explained by measurement noise and low internal consistency. Consequently, response inhibition appears to have mostly state-like and situational determinants, and there is little support for the validity of conceptualizing common inhibition measures as reflecting stable traits.

Comparing Self-Report vs. Performance Measures of Attentional Control and Efficiency

Background: The Attention Control Scale (ATTC) is a widely used self-report measure of attentional control capacities. However, research questions whether it accurately substitutes for objective attention control tasks. This study investigated ATTC's correlation with the Attention Network Test (ANT) across alerting, orienting, and executive control networks. We also used the Inverse Efficiency Score (IES) as an additional factor to check ATTC using ANT. Methods: We administered 143 participants who completed the ATTC questionnaire and ANT behavioral test assessing network efficiencies. Results: The results showed non-significant ATTC-ANT correlations across all networks. In an additional analysis, while the ATTC demonstrated factorial validity, subjective control was disconnected from actual attention regulation efficiency. A small male advantage emerged for executive control. Conclusions: Dissociations likely stem from attention complexity and method variances rather than overlap. The findings do not support the ATTC as a stand-alone proxy for performance-based measurement. Multifaceted assessments are essential for comprehensively capturing attentional control.

Opposite perceptual biases in analogous auditory and visual tasks are unique to consonant-vowel strings and are unlikely a consequence of repetition

Despite wide reporting of a right ear (RE) advantage on dichotic listening tasks and a right visual field (RVF) advantage on visual half-field tasks, we know very little about the relationship between these perceptual biases. Previous studies that have investigated perceptual asymmetries for analogous auditory and visual consonant-vowel tasks have indicated a serendipitous finding: a RE advantage and a left visual field (LVF) advantage with poor cross-modal correlations. In this study, we examined the possibility that this LVF advantage for visual processing of consonant-vowel strings may be a consequence of repetition by examining perceptual biases in analogous auditory and visual tasks for both consonant-vowel strings and words. We replicated opposite perceptual biases for consonant-vowel strings (RE and LVF advantages). This did not extend to word stimuli where we found RE and RVF advantages. Furthermore, these perceptual biases did not differ across the three experimental blocks. Thus, we can firmly conclude that this LVF advantage is unique to consonant-vowel strings and is not a consequence of the repetition of a relatively limited number of stimuli. Finally, a test of covariances indicated no cross-modal relationships between laterality indices suggesting that perceptual biases are dissociable within individuals and cluster on mode of presentation.

Chronotype, Time of Day, and Children's Cognitive Performance in Remote Neuropsychological Assessment

Research on the influence of chronotype and time of day (TOD) on cognitive performance, especially in children, is limited. We explored potential interactive effects, hypothesizing that performance differs when comparing preferred vs. non-preferred TOD. In total, 76 morning-type (MT = 37) or evening-type (ET = 39) children from the third and fourth grades (48.7% girls; M age = 8.05; SD age = 0.51), identified through the Children Chronotype Questionnaire, completed two 30-min neuropsychological assessment sessions via videoconference on the first (9:00) or last hour (16:00) of the school day. The protocol included neuropsychological tests targeting memory, language, and attention/executive domains. The results revealed an interactive effect of medium size between chronotype and TOD on a Rapid Alternating Stimulus (Naming) Task. MT and ET performed faster in asynchrony conditions (morning for ET; afternoon for MT). Additionally, ET outperformed MT in a Backward Digit Span Task, irrespective of TOD. TOD also influenced performance on an Alternating Verbal Fluency Task, with both MT and ET children performing better in the morning. These results underscore the importance of chronotype and TOD in children's cognitive performance, particularly in working memory and verbal fluency. Children assessed during non-preferred TOD exhibited better performance on some cognitive tasks, challenging the assumption that optimal times always yield superior results.

Measuring the Reliability of a Gamified Stroop Task: Quantitative Experiment

BACKGROUND

Few gamified cognitive tasks are subjected to rigorous examination of psychometric properties, despite their use in experimental and clinical settings. Even small manipulations to cognitive tasks require extensive research to understand their effects.

OBJECTIVE

This study aims to investigate how game elements can affect the reliability of scores on a Stroop task. We specifically investigated performance consistency within and across sessions.

METHODS

We created 2 versions of the Stroop task, with and without game elements, and then tested each task with participants at 2 time points. The gamified task used points and feedback as game elements. In this paper, we report on the reliability of the gamified Stroop task in terms of internal consistency and test-retest reliability, compared with the control task. We used a permutation approach to evaluate internal consistency. For test-retest reliability, we calculated the Pearson correlation and intraclass correlation coefficients between each time point. We also descriptively compared the reliability of scores on a trial-by-trial basis, considering the different trial types.

RESULTS

At the first time point, the Stroop effect was reduced in the game condition, indicating an increase in performance. Participants in the game condition had faster reaction times (P=.005) and lower error rates (P=.04) than those in the basic task condition. Furthermore, the game condition led to higher measures of internal consistency at both time points for reaction times and error rates, which indicates a more consistent response pattern. For reaction time in the basic task condition, at time 1, rSpearman-Brown=0.78, 95% CI 0.64-0.89. At time 2, rSpearman-Brown=0.64, 95% CI 0.40-0.81. For reaction time, in the game condition, at time 1, rSpearman-Brown=0.83, 95% CI 0.71-0.91. At time 2, rSpearman-Brown=0.76, 95% CI 0.60-0.88. Similarly, for error rates in the basic task condition, at time 1, rSpearman-Brown=0.76, 95% CI 0.62-0.87. At time 2, rSpearman-Brown=0.74, 95% CI 0.58-0.86. For error rates in the game condition, at time 1, rSpearman-Brown=0.76, 95% CI 0.62-0.87. At time 2, rSpearman-Brown=0.74, 95% CI 0.58-0.86. Test-retest reliability analysis revealed a distinctive performance pattern depending on the trial type, which may be reflective of motivational differences between task versions. In short, especially in the incongruent trials where cognitive conflict occurs, performance in the game condition reaches peak consistency after 100 trials, whereas performance consistency drops after 50 trials for the basic version and only catches up to the game after 250 trials.

CONCLUSIONS

Even subtle gamification can impact task performance albeit not only in terms of a direct difference in performance between conditions. People playing the game reach peak performance sooner, and their performance is more consistent within and across sessions. We advocate for a closer examination of the impact of game elements on performance.

Attentional biases to signals of negative information: Reliable measurement across three anxiety domains

Cognitive models propose that individuals with elevated vulnerability to experiencing negative emotion are characterised by biased attentional responding to negative information. Typically, methods of examining these biases have measured attention to pictures of emotional scenes, emotional faces, or rewarding or feared objects. Though these approaches have repeatedly yielded evidence of anxiety-linked biases, their measurement reliability is suggested to be poor. Recent research has shown that attentional responding to cues signalling negative information can be measured with greater reliability. However, whether such biases are associated with emotion vulnerability remains to be demonstrated. The present study conducted three experiments that recruited participants who varied in trait and state anxiety (N = 134), social anxiety (N = 122), or spider fear (N = 131) to complete an assessment of selective attention to cues signalling emotionally congruent negative information. Analyses demonstrated that anxiety and fear were associated with biased attentional responding to cues signalling negative information, and that such biases could be measured with acceptable reliability (rsplit-half = .69-.81). Implications for research on the relation between emotion and attention are discussed.