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Although academic procrastination is prevalent, few interventions targeting it have been rigorously tested. We propose a novel approach to developing effective classroom interventions for academic procrastination, based on the ideas that changing complex behaviors requires a holistic, multipronged approach and that intervention research must embrace objective measures of procrastination behavior. We illustrate what such intervention efforts may look like by deriving some easily implementable techniques from a simple process model of self-control, which characterizes procrastination as a goal-management failure resulting from a need to repair negative emotion triggered by impending academic tasks.

This paper presents novel datasets providing numerical representations of ICD-10-CM codes by generating description embeddings using a large language model followed by a dimension reduction via autoencoder. The embeddings serve as informative input features for machine learning models by capturing relationships among categories and preserving inherent context information. The model generating the data was validated in two ways. First, the dimension reduction was validated using an autoencoder, and secondly, a supervised model was created to estimate the ICD-10-CM hierarchical categories. Results show that the dimension of the data can be reduced to as few as 10 dimensions while maintaining the ability to reproduce the original embeddings, with the fidelity decreasing as the reduced-dimension representation decreases. Multiple compression levels are provided, allowing users to choose as per their requirements. The readily available datasets of ICD-10-CM codes are anticipated to be highly valuable for researchers in biomedical informatics, enabling more advanced analyses in the field. This approach has the potential to significantly improve the utility of ICD-10-CM codes in the biomedical domain.

Background: Recent advances in developing “tumor agnostic” oncology therapies have identified molecular targets that define patient subpopulations in a manner that supersedes conventional criteria for cancer classification. These successes have produced effective targeted therapies that are administered to patients regardless of their tumor histology. Trials have evolved as well with master protocol designs. By blending translational and clinical science, basket trials in particular are well-suited to investigate and develop targeted therapies among multiple cancer histologies. However, basket trials intrinsically involve more complex design decisions, including issues of multiple testing across baskets, and guidance for investigators is needed. Methods: The sensitivity of the multisource exchangeability model to prior specification under differing degrees of response heterogeneity is explored through simulation. Then, a multisource exchangeability model design that incorporates control of the false-discovery rate is presented and a simulation study compares the operating characteristics to a design where the family-wise error rate is controlled and to the frequentist approach of treating the baskets as independent. Simulations are based on the original design of a real-world clinical trial, the SUMMIT trial, which investigated Neratinib treatment for a variety of solid tumors. The methods studied here are specific to single-arm phase II trials with binary outcomes. Results: Values of prior probability of exchangeability in the multisource exchangeability model between 0.1 and 0.3 provide the best trade-offs between gain in precision and bias, especially when per-basket sample size is below 30. Application of these calibration results to a re-analysis of the SUMMIT trial showed that the breast basket exceeded the null response rate with posterior probability of 0.999 while having low posterior probability of exchangeability with all other baskets. Simulations based on the design of the SUMMIT trial revealed that there is meaningful improvement in power even in baskets with small sample size when the false-discovery rate is controlled as opposed to the family-wise error rate. For example, when only the breast basket was active, with a sample size of 25, the power was 0.76 when the false-discovery rate was controlled at 0.05 but only 0.56 when the family-wise error rate was controlled at 0.05, indicating that impractical sample sizes for the phase II setting would be needed to achieve acceptable power while controlling the family-wise error rate in this setting of a trial with 10 baskets. Conclusion: Selection of the prior exchangeability probability based on calibration and incorporation of false-discovery rate control result in multisource exchangeability model designs with high power to detect promising treatments in the context of phase II basket trials.

We used a technique known as reach tracking to investigate how individual differences in working memory capacity (WMC) relate to the functioning of two processes proposed to underlie cognitive control: a threshold adjustment process that temporarily inhibits motor output in response to signals of conflict and a controlled selection process that recruits top-down control to guide stimulus-response translation. Undergraduates (N = 135) performed two WMC tasks (updating counters and symmetry span) and a reach-tracking version of the Eriksen flanker task. Consistent with previous research using button-press flanker tasks, WMC significantly correlated with response time (RT) performance, with higher WMC scores corresponding to smaller congruency effects. Given that RTs reflect the combined functioning of multiple processes underlying cognitive control, we interpreted this effect to reflect a general link between WMC and both the threshold adjustment process and controlled selection process. We also found a significant association between WMC and participants' reach trajectories, with higher WMC scores corresponding to more direct reach movements on incongruent trials involving stimulus-response overlap with the preceding trial. We interpreted this effect to reflect a more specific link between WMC and the functioning of the controlled selection process. We discuss the observed links between WMC and cognitive control in relation to the unity and diversity of executive functions framework and in relation to the role of prefrontal and striatal dopamine in supporting adaptive cognitive control. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Adaptive designs are gaining popularity in early phase clinical trials because they enable investigators to change the course of a study in response to accumulating data. We propose a novel design to simultaneously monitor several endpoints. These include efficacy, futility, toxicity and other outcomes in early phase, single-arm studies. We construct a recursive relationship to compute the exact probabilities of stopping for any combination of endpoints without the need for simulation, given pre-specified decision rules. The proposed design is flexible in the number and timing of interim analyses. A R Shiny app with user-friendly web interface has been created to facilitate the implementation of the proposed design.

Are intelligence and creativity distinct abilities, or do they rely on the same cognitive and neural systems? We sought to quantify the extent to which intelligence and creative cognition overlap in brain and behavior by combining machine learning of fMRI data and latent variable modeling of cognitive ability data in a sample of young adults (N = 186) who completed a battery of intelligence and creative thinking tasks. The study had 3 analytic goals: (a) to assess contributions of specific facets of intelligence (e.g., fluid and crystallized intelligence) and general intelligence to creative ability (i.e., divergent thinking originality), (b) to model whole-brain functional connectivity networks that predict intelligence facets and creative ability, and (c) to quantify the degree to which these predictive networks overlap in the brain. Using structural equation modeling, we found moderate to large correlations between intelligence facets and creative ability, as well as a large correlation between general intelligence and creative ability (r = .63). Using connectome-based predictive modeling, we found that functional brain networks that predict intelligence facets overlap to varying degrees with a network that predicts creative ability, particularly within the prefrontal cortex of the executive control network. Notably, a network that predicted general intelligence shared 46% of its functional connections with a network that predicted creative ability-including connections linking executive control and salience/ventral attention networks-suggesting that intelligence and creative thinking rely on similar neural and cognitive systems. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Individual differences in reading comprehension have often been explored using latent variable modeling (LVM), to assess the relative contribution of domain-general and domain-specific cognitive abilities. However, LVM is based on the assumption that the observed covariance among indicators of a construct is due to a common cause (i.e., a latent variable; Pearl, 2000). This is a questionable assumption when the indicator variables are measures of performance on complex cognitive tasks. According to Process Overlap Theory (POT; Kovacs & Conway, 2016), multiple processes are involved in cognitive task performance and the covariance among tasks is due to the overlap of processes across tasks. Instead of a single latent common cause, there are thought to be multiple dynamic manifest causes, consistent with an emerging view in psychometrics called network theory (Barabási, 2012; Borsboom & Cramer, 2013). In the current study, we reanalyzed data from Freed et al. (2017) and compared two modeling approaches: LVM (Study 1) and psychometric network modeling (Study 2). In Study 1, two exploratory LVMs demonstrated problems with the original measurement model proposed by Freed et al. Specifically, the model failed to achieve discriminant and convergent validity with respect to reading comprehension, language experience, and reasoning. In Study 2, two network models confirmed the problems found in Study 1, and also served as an example of how network modeling techniques can be used to study individual differences. In conclusion, more research, and a more informed approach to psychometric modeling, is needed to better understand individual differences in reading comprehension.

[Correction Notice: An Erratum for this article was reported online in Emotion on Jan 7 2021 (see record 2021-06077-001). In the article, in the Results and Discussion sections for Study 2 and in Table 6, it was stated that RSPAN scores predicted spontaneous down-regulation of negative affect from one diary signal to the next. However, because RSPAN scores are a person-level variable, it is an error to describe the results in that way. RSPAN scores cannot predict variability within person (i.e., signal to signal) but rather predict variability between person (i.e., person to person). Hence, a corrected interpretation would be to state that the RSPAN predicted levels of negative affect across the experience sampling diary, even when considering trait and state levels of affect and variability in daily stress. The analysis remains correct and the findings remain meaningful.] We tested the association of 2 versions of the Reading Span Task of working memory capacity, a conventional neutral version (RSPAN-N) and an adapted task with incidental negative content (RSPAN-E), for predicting objective indicators (behavioral displays; autonomic activation) of negative emotion regulation during a laboratory provocation, as well as reported negative emotion in daily life experience sampling. Across 2 samples, both tasks demonstrated utility as estimates of spontaneous negative emotion regulation capacity, predicting down-regulation of negative emotion in daily life and during a lab challenge. In addition, scores from both tasks appear to be independent of self-reported distress, a confound often present in studies of emotion regulation. There was some incremental evidence that the RSPAN-E may have advantages over the RSPAN-N for predicting some indices of emotion processing. Together these findings provide further evidence for the role of working memory (among other executive-control abilities) in emotion regulatory processing and suggest that RSPAN tasks may have considerable potential as tools in research on emotion processing and emotion regulation in psychological health and adjustment. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Increasing research efforts are focused on explaining the cognitive bases of creativity. However, it remains unclear when and how cognitive factors such as intelligence and executive function uniqu...

Tian et al provide a framework for assessing population-level interventions of disease outbreaks through the construction of counterfactuals in a large-scale, natural experiment assessing the efficacy of mild, but early interventions compared to delayed interventions The technique is applied to the recent SARS-CoV-2 outbreak with the population of Shenzhen, China acting as the mild-but-early treatment group and a combination of several US counties resembling Shenzhen but enacting a delayed intervention acting as the control To help further the development of this framework and identify an avenue for further enhancement, we focus on the use and potential limitations of compartmental models In particular, compartmental models make assumptions about the communicability of a disease that may not perform well when they are used for large areas with multiple communities where movement is restricted To illustrate this phenomena, we provide a simulation of a directed percolation (outbreak) process on a simple stochastic block model with two blocks The simulations show that when transmissibility between two communities is severely restricted an outbreak in two communities resembles a primary and secondary outbreak potentially causing policy and decision makers to mistake effective intervention strategies with noncompliance or inefficacy of an intervention AMS 2000 subject classifications: Primary 37M05;secondary 62P10 © 2021 All Rights Reserved

While the traditional clinical trial design lays emphasis on testing the treatment effect between randomly assigned groups, it ignores the role of patient preference for a particular treatment in the trial. Yet, for healthcare providers who seek to optimize the patient-centered treatment strategy, the evaluation of a patient's psychology toward each treatment could be a key consideration. The two-stage randomized trial design allows researchers to test patient's preference and selection effects, in addition to the treatment effect. The current methodology for the two-stage design is limited to continuous and binary outcomes; this article extends the model to include count outcomes. The test statistics for preference, selection, and treatment effects are derived. Closed-form sample size formulae are presented for each effect. Simulations are presented to demonstrate the properties of the unstratified and stratified designs. Finally, we apply methods to the use of antimicrobials at the end of life to demonstrate the applicability of the methods.

We conducted an exploratory study of adult individual differences in the contents of mind-wandering experiences and in the moment-to-moment consistency of that off-task thought content within tasks. This secondary analysis of a published dataset (Kane et al., 2016) examined the content-based thought reports that 472–541 undergraduates made within five probed tasks across three sessions, and tested whether executive-control abilities (working memory capacity, attention-restraint ability), or personality dimensions of schizotypy (positive, disorganized, negative), predicted particular contents of task-unrelated thought (TUT) or the (in)stability of TUT content across successive thought reports. Latent-variable models indicated trait-like consistency in both TUT content and short-term TUT-content stability across tasks and sessions; some subjects mind-wandered about some things more than others, and some subjects were more temporally consistent in their TUT content than were others. Higher executive control was associated with more evaluative thoughts about task performance and fewer thoughts about current physical or emotional states; higher positive and disorganized schizotypy was associated with more fantastical-daydream and worry content. Contrary to expectations, executive ability correlated positively with TUT instability: higher-ability students had more shifting and varied TUT content within a task. Post hoc analysis suggested that better executive control predicted inconsistent TUT content because it also predicted shorter streaks of mind-wandering; tuning back in to task-related thought may decouple trains of off-task thought and afford novel spontaneous or cued thought content. [Data, sample analysis scripts and output, and article preprint are available via the Open Science Framework: https://osf.io/guhw7/].

The ability to sustain attention is often measured with either objective performance indicators, like within-person RT variability, or subjective self-reports, like mind wandering propensity. A more construct valid approach, however, may be to assess the covariation in these performance and self-report measures, given that each of these is influenced by different sources of measurement error. If the correlation between performance-variability and self-report measures reflects the sustained attention construct, then task manipulations aimed at reducing the sustained attention demands of tasks should reduce the correlation between them (in addition to reducing mean levels of variability and mind wandering). The current study investigated this claim with a combined experimental-correlation approach. In two experiments (Ns ~ 1500 each), participants completed tasks that either maximized or minimized the demand for sustained attention. Our demand manipulations successfully reduced the mean levels of sustained attention failures in both the objective and subjective measures, in both experiments. In neither experiment, however, did the covariation between these measures change as a function of the sustained attention demands of the tasks. We can therefore claim only minimal support for the construct validity of our measurement approach to sustained attention.

Considerable research has examined the prevalence and apparent consequences of task-unrelated thoughts (TUTs) in both laboratory and authentic educational settings. Few studies, however, have explored methods to reduce TUTs during learning; those few studies tested small samples or used unvalidated TUT assessments. The present experimental study attempted to conceptually replicate or extend previous findings of interpolated testing and pretesting effects on TUT and learning. In a study of 195 U.S. undergraduates, we investigated whether interpolated testing (compared to interpolated restudy) and pretesting on lecture-relevant materials (compared to pretesting on conceptually related but lecture-irrelevant materials) would reduce TUTs during a video lecture on introductory statistics. Subjects completed either a content-matched or content-mismatched pretest on statistics concepts and then watched a narrated lecture slideshow. During the lecture, half of the sample completed interpolated tests on the lecture material and half completed interpolated restudy of that material. All subjects responded to unpredictably presented thought probes during the video to assess their immediately preceding thoughts, including TUTs. Following the lecture, students reported on their situational interest elicited by the lecture and then completed a posttest. Interpolated testing significantly reduced TUT rates during the lecture compared to restudying, conceptually replicating previous findings—but with a small effect size and no supporting Bayes-factor evidence. We found statistical evidence for neither an interpolated testing effect on learning, nor an effect of matched-content pretesting on TUT rates or learning. Interpolated testing might have limited utility to support students’ attention, but varying effect sizes across studies warrants further work.

Progress in the areas of genomics, disease pathways, and drug discovery has advanced into clinical and translational cancer research. The latest innovations in clinical trials have followed with master protocols, which are defined by inclusive eligibility criteria and devised to interrogate multiple therapies for a given tumor histology and/or multiple histologies for a given therapy under one protocol. The use of master protocols for oncology has become more common with the desire to improve the efficiency of clinical research and accelerate overall drug development. Basket trials have been devised to ascertain the extent to which a treatment strategy offers benefit to various patient subpopulations defined by a common molecular target. Conventionally conducted within the phase II setting, basket designs have become popular as drug developers seek to effectively evaluate and identify preliminary efficacy signals among clinical indications identified as promising in preclinical study. This article reviews basket trial designs in oncology settings and discusses several issues that arise with their design and analysis.

Mind-wandering assessment relies heavily on the thought probe technique as a reliable and valid method to assess momentary task-unrelated thought (TUT), but there is little guidance available to help researchers decide how many probes to include within a task. Too few probes may lead to unreliable measurement, but too many probes might artificially disrupt normal thought flow and produce reactive effects. Is there a "Goldilocks zone" for how few thought probes can be used to reliably and validly assess individual differences in mind-wandering propensity? We address this question by reanalyzing two published datasets (Study 1, n = 541; Study 2, ns ≈ 260 per condition) in which thought probes were presented in multiple tasks. Our primary analyses randomly sampled probes in increments of two for each subject in each task. A series of confirmatory factor analyses for each probe "bin" size tested whether the latent correlations between TUT rate and theoretically relevant constructs like working memory capacity, attention-control ability, disorganized schizotypy, and retrospective self-reported mind wandering changed as more probes assessed the TUT rate. TUT rates were remarkably similar across increasing probe-bin sizes and zero-order correlations within and between tasks stabilized at 8-10 probes; moreover, TUT-rate correlations with other latent variables stabilized at about 8 thought probes. Our provisional recommendation (with caveats) is that researchers may use as few as 8 thought probes in prototypical cognitive tasks to gain reliable and valid information about individual differences in TUT rate.

We propose a two-stage design for a single arm clinical trial with an early stopping rule for futility. This design employs different endpoints to assess early stopping and efficacy. The early stopping rule is based on a criteria determined more quickly than that for efficacy. These separate criteria are also nested in the sense that efficacy is a special case of, but usually not identical to, the early stopping endpoint. The design readily allows for planning in terms of statistical significance, power, expected sample size, and expected duration. This method is illustrated with a phase II design comparing rates of disease progression in elderly patients treated for lung cancer to rates found using a historical control. In this example, the early stopping rule is based on the number of patients who exhibit progression-free survival (PFS) at 2 months post treatment follow-up. Efficacy is judged by the number of patients who have PFS at 6 months. We demonstrate our design has expected sample size and power comparable with the Simon two-stage design but exhibits shorter expected duration under a range of useful parameter values.

Mind wandering assessment relies heavily on the thought probe technique as a reliable and valid method to assess momentary task-unrelated thought (TUT), but there is little guidance available to help researchers decide how many probes to include within a task. Too few probes may lead to unreliable measurement, but too many probes might artificially disrupt normal thought flow and produce reactive effects. Is there a “Goldilocks zone” for how few thought probes can be used to reliably and validly assess individual differences in mind wandering propensity? We address this question by reanalyzing two published datasets (Study 1, n = 541; Study 2, n’s ≈ 260 per condition) in which thought probes were presented in multiple tasks. Our primary analyses randomly sampled probes in increments of two for each subject in each task. A series of confirmatory factor analyses for each probe “bin” size tested whether the latent correlations between TUT rate and theoretically relevant constructs like working memory capacity, attention control ability, disorganized schizotypy, and retrospective self-reported mind wandering changed as more probes assessed TUT rate. TUT rates were remarkably similar across increasing probe-bin sizes and zero-order correlations within and between tasks stabilized at 8–10 probes; moreover, TUT-rate correlations with other latent variables stabilized at about 8 thought probes. Our provisional recommendation (with caveats) is that researchers may use as few as 8 thought probes in prototypical cognitive tasks to gain reliable and valid information about individual differences in TUT rate.

Psychology faces a measurement crisis, and mind-wandering research is not immune. The present study explored the construct validity of probed mind-wandering reports (i.e., reports of task-unrelated thought [TUT]) with a combined experimental and individual-differences approach. We examined laboratory data from over 1000 undergraduates at two U.S. institutions, who responded to one of four different thought-probe types across two cognitive tasks. We asked a fundamental measurement question: Do different probe types yield different results, either in terms of average reports (average TUT rates, TUT-report confidence ratings), or in terms of TUT-report associations, such as TUT rate or confidence stability across tasks, or between TUT reports and other consciousness-related constructs (retrospective mind-wandering ratings, executive-control performance, and broad questionnaire trait assessments of distractibility–restlessness and positive-constructive daydreaming)? Our primary analyses compared probes that asked subjects to report on different dimensions of experience: TUT-content probes asked about what they’d been mind-wandering about, TUT-intentionality probes asked about why they were mind-wandering, and TUT-depth probes asked about the extent (on a rating scale) of their mind-wandering. Our secondary analyses compared thought-content probes that did versus didn’t offer an option to report performance-evaluative thoughts. Our findings provide some “good news”—that some mind-wandering findings are robust across probing methods—and some “bad news”—that some findings are not robust across methods and that some commonly used probing methods may not tell us what we think they do. Our results lead us to provisionally recommend content-report probes rather than intentionality- or depth-report probes for most mind-wandering research.

Psychology faces a measurement crisis, and mind-wandering research is not immune. The present study explored the construct validity of probed mind-wandering reports (i.e., reports of task-unrelated thought [TUT]) with a combined experimental and individual-differences approach. We examined laboratory data from over 1,000 undergraduates at two U.S. institutions, who responded to one of four different thought-probe types across two cognitive tasks. We asked a fundamental measurement question: Do different probe types yield different results, either in terms of average reports (average TUT rates, TUT-report confidence ratings), or in terms of TUT-report associations, such as TUT rate or confidence stability across tasks, or between TUT reports and other consciousness-related constructs (retrospective mind-wandering ratings, executive-control performance, and broad questionnaire trait assessments of distractibility–restlessness and positive-constructive daydreaming)? Our primary analyses compared probes that asked subjects to report on different dimensions of experience: TUT-content probes asked about what they’d been mind-wandering about, TUT-intentionality probes asked about why they were mind-wandering, and TUT-depth probes asked about the extent (on a rating scale) of their mind-wandering. Our secondary analyses compared thought-content probes that did versus didn’t offer an option to report performance-evaluative thoughts. Our findings provide some “good news”—that some mind-wandering findings are robust across probing methods—and some “bad news”—that some findings are not robust across methods and that some commonly used probing methods may not tell us what we think they do. Our results lead us to provisionally recommend content-report probes rather than intentionality- or depth-report probes for most mind-wandering research.

This study investigated what academic traits, attitudes, and habits predict individual differences in task-unrelated thought (TUT) during lectures, and whether this TUT propensity mediates associations between academic individual differences and course outcomes (final grade and situational interest evoked by material). Undergraduates (N = 851) from ten psychology classes at two US universities responded to thought probes presented during two early-course lectures; they also indicated sitting in the front, middle, or back of the classroom. At each probe, students categorized their thought content, such as indicating on-task thought or TUT. Students also completed online, academic-self-report questionnaires at the beginning of the course and a situational interest questionnaire at the end. Average TUT rate was 24% but individuals’ rates varied widely (SD = 18%). TUT rates also increased substantially from the front to back of the classroom, and modestly from the first to second half of class periods. Multiple-group analyses (with ten classroom groups) indicated that: (a) classroom media-multitasking habits, initial interest in the course topic, and everyday propensity for mind-wandering and boredom accounted for unique variance in TUT rate (beyond other predictors); (b) TUT rate accounted for unique (modest) variance in course grades and situational interest; and (c) classroom media multitasking and propensity for mind-wandering and boredom had indirect associations with course grades via TUT rate, and these predictor variables, along with initial interest, had indirect associations with end-of-term situational interest via TUT rate. Some academic traits and behaviors predict course outcomes in part because they predict off-task thought during class. Supplementary Information The online version contains supplementary material available at 10.3758/s13421-021-01156-3.

Recent mental health initiatives have called for a shift away from purely report-based conceptualizations of psychopathology toward a biobehaviorally oriented framework. The current work illustrates a measurement-oriented approach to challenges inherent in efforts to integrate biological and behavioral indicators with psychological-report variables. Specifically, we undertook to quantify the construct of inhibitory control (inhibition-disinhibition) as the individual difference dimension tapped by self-report, task-behavioral, and brain response indicators of susceptibility to disinhibitory problems (externalizing proneness). In line with prediction, measures of each type cohered to form domain-specific factors, and these factors loaded in turn onto a cross-domain inhibitory control factor reflecting the variance in common among the domain factors. Cross-domain scores predicted behavioral-performance and brain-response criterion measures as well as clinical problems (i.e., antisocial behaviors and substance abuse). Implications of this new cross-domain model for research on neurobiological mechanisms of inhibitory control and health/performance outcomes associated with this dispositional characteristic are discussed.

People’s ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis—connectome-based predictive modeling—to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences (r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems—intrinsic functional networks that tend to work in opposition—suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

Background Wearable devices have been widely used in clinical studies to study daily activity patterns, but the analysis remains a major obstacle for researchers. Objective This study proposes a novel method to characterize sleep-activity rhythms using actigraphy and further use it to describe early childhood daily rhythm formation and examine its association with physical development. Methods We developed a machine learning–based Penalized Multiband Learning (PML) algorithm to sequentially infer dominant periodicities based on the Fast Fourier Transform (FFT) algorithm and further characterize daily rhythms. We implemented and applied the algorithm to Actiwatch data collected from a cohort of 262 healthy infants at ages 6, 12, 18, and 24 months, with 159, 101, 111, and 141 participants at each time point, respectively. Autocorrelation analysis and Fisher test in harmonic analysis with Bonferroni correction were applied for comparison with the PML. The association between activity rhythm features and early childhood motor development, assessed using the Peabody Developmental Motor Scales-Second Edition (PDMS-2), was studied through linear regression analysis. Results The PML results showed that 1-day periodicity was most dominant at 6 and 12 months, whereas one-day, one-third–day, and half-day periodicities were most dominant at 18 and 24 months. These periodicities were all significant in the Fisher test, with one-fourth–day periodicity also significant at 12 months. Autocorrelation effectively detected 1-day periodicity but not the other periodicities. At 6 months, PDMS-2 was associated with the assessment seasons. At 12 months, PDMS-2 was associated with the assessment seasons and FFT signals at one-third–day periodicity (P Conclusions The proposed PML algorithm can effectively conduct circadian rhythm analysis using time-series wearable device data. The application of the method effectively characterized sleep-wake rhythm development and identified the association between daily rhythm formation and motor development during early childhood.

Prospective memory (PM) is the cognitive ability to remember to fulfill intended action plans at the appropriate future moment. Current theories assume that PM fulfillment draws on attentional processes. Accordingly, pending PM intentions interfere with other ongoing tasks to the extent to which both tasks rely on the same processes. How do people manage the competition between PM and ongoing-task demands? Based on research relating mind wandering and attentional control (KaneMcVay, 2012), we argue that people may not only change the way they process ongoing-task stimuli when given a PM intention, but they may also engage in less off-task thinking than they otherwise would. That is, people focus more strongly on the tasks at hand and dedicate considerable conscious thought to the PM goal. We tested this hypothesis by asking subjects to periodically report on their thoughts during prototypical PM (and control) tasks. Task-unrelated thought rates dropped when participants performed an ongoing task while holding a PM intention versus performing the ongoing task alone (Experiment 1), even when PM demands were minimized (Experiment 2) and more so when PM execution was especially rewarded (Experiment 3). Our findings suggest that PM demands not only elicit a cost to ongoing-task processing, but they also induce a stronger on-task focus and promote conscious thoughts about the PM intention. (PsycINFO Database Record

BackgroundWearable devices have been widely used in clinical studies to study daily activity patterns, but the analysis remains the major obstacle for researchers.Study ObjectiveThis study proposed a novel method to characterize sleep-activity rhythms using actigraphy and further used it to describe early childhood daily rhythm formation and examine its association with physical development.MethodsWe developed a machine learning-based Penalized Multi-band Learning (PML) algorithm to sequentially infer dominant periodicities based on Fast Fourier Transform (FFT) and further characterize daily rhythms. We implemented and applied the algorithm to Actiwatch data collected from a 262 healthy infant cohort at 6-, 12-, 18-, and 24-month old, with 159, 101, 111, and 141 subjects participating at each time point respectively. Autocorrelation analysis and Fisher’s test for harmonic analysis with Bonferroni correction were applied to compare with PML. The association between activity rhythm features and early childhood motor development, assessed by Peabody Developmental Motor Scales-Second Edition (PDMS-2), was studied through linear regression.ResultsPML results showed that 1-day periodicity is most dominant at 6 and 12 months, whereas 1-day, 1/3-day, and 1/2-day periodicities are most dominant at 18 and 24 months. These periodicities are all significant in Fisher’s test, with 1/4-day periodicity also significant at 12 months. Autocorrelation effectively detected 1-day periodicity but not others. At 6 months, PDMS-2 is associated with assessment seasons. At 12 months, PDMS-2 is associated with seasons and FFT signals at 1/3-day periodicity (PP=.04). In particular, subcategories of stationary, locomotion, and gross motor are associated with FFT signals at 1/3-day periodicity (PConclusionsThe proposed PML algorithm can effectively conduct circadian rhythm analysis using time-series wearable device data. Application of the method effectively characterized sleep-wake rhythm development and identified the association between daily rhythm formation and motor development during early childhood.

The worst performance rule (WPR) is a robust empirical finding reflecting that people’s worst task performance shows stronger relations to cognitive ability compared to their average or best performance. However, recent meta-analytic work has proposed this be renamed the “not-best-performance” rule because mean and worst performance seem to predict cognitive ability to similar degrees (with both predicting ability better than best performance). We re-analyzed data from a previously published latent-variable study to test for worst vs. not-best performance across a variety of reaction time tasks in relation to two cognitive ability constructs: working memory capacity (WMC) and task-unrelated thought (TUT) rate. Using two methods of assessing worst performance—ranked-binning and ex-Gaussian-modeling approaches—we found evidence for both worst and not-best performance rules. WMC followed the not-best performance rule (correlating equivalently with mean and worst RTs) but TUT propensity followed the worst performance rule (correlating more strongly with worst RTs). Additionally, we created a mini-multiverse following different outlier exclusion rules to test the robustness of our findings; our findings remained stable across the different multiverse iterations. We provisionally conclude that the worst performance rule may only arise in relation to cognitive abilities closely linked to (failures of) sustained attention.

Christoff et al. [1] reject our family-resemblances framework for mind-wandering research [2] and instead seek to characterize mind-wandering with a necessary defining feature. As an example, they point to their ‘dynamic framework’ [3] that defines mind-wandering as thoughts that ‘proceed in a relatively free, unconstrained fashion.’ We outline three primary points of disagreement with their commentary and two points of clarification on the family-resemblances framework.

Intimates often discuss the causes of, and solutions to, their relationship problems with their partners, and this information can shape partners' behavior and thus facilitate problem resolution. Partners' ability to encode and later recall such discussions should lead to greater declines in the severity of those problems. This brief report presents the results from a broader longitudinal study in which newlywed couples completed tasks assessing their working memory capacity (WMC), engaged in problem-solving discussions, recalled those discussions after a short delay, and then reported the severity of the problems discussed over the course of a year. Greater WMC among partners was associated with greater declines in the severity of a relationship problem, mediated by partners' recall of the discussion of that problem, suggesting that WMC facilitated the long-term memory encoding of the problem discussion. This study is among the first to suggest that individual differences in basic cognitive abilities may affect conversation processing and recall, and thereby close relationships. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Green et al. (2017) raise two broad concerns with our two studies (Unsworth et al., 2015) showing little association between self-reported video-game experience and cognitive abilities: (a) Our analyses assumed linear gaming-cognition relationships and ignored possible confounding associations among different video-game genres, and (b) the video-game experience questionnaires were problematic and misapplied. We rebut these critiques in this Commentary.

Zoonotic transmission of influenza A virus (IAV) between swine and workers in swine production facilities may play a role in the emergence of novel influenza strains with pandemic potential. Guidelines to prevent transmission of influenza to swine workers have been developed but there is a need for evidence-based decision-making about protective measures such as respiratory protection. A mathematical model was applied to estimate the risk of occupational IAV exposure to swine workers by contact and airborne transmission, and to evaluate the use of respirators to reduce transmission. The Markov model was used to simulate the transport and exposure of workers to IAV in a swine facility. A dose-response function was used to estimate the risk of infection. This approach is similar to methods previously used to estimate the risk of infection in human health care settings. This study uses concentration of virus in air from field measurements collected during outbreaks of influenza in commercial swine facilities, and analyzed by polymerase chain reaction. It was found that spending 25 min working in a barn during an influenza outbreak in a swine herd could be sufficient to cause zoonotic infection in a worker. However, this risk estimate was sensitive to estimates of viral infectivity to humans. Wearing an excellent fitting N95 respirator reduced this risk, but with high aerosol levels the predicted risk of infection remained high under certain assumptions. The results of this analysis indicate that under the conditions studied, swine workers are at risk of zoonotic influenza infection. The use of an N95 respirator could reduce such risk. These findings have implications for risk assessment and preventive programs targeting swine workers. The exact level of risk remains uncertain, since our model may have overestimated the viability or infectivity of IAV. Additionally, the potential for partial immunity in swine workers associated with repeated low-dose exposures or from previous infection with other influenza strains was not considered. Further studies should explore these uncertainties.

We examined the effects of interpolated retrieval from long-term memory (LTM) and short-term memory (STM) on list isolation in dual-list free recall and whether individual differences in working memory capacity (WMC) moderated those effects. Ninety-seven subjects completed study–test trials that included two study lists separated by either an exemplar generation task (LTM retrieval) or a two-back task (STM retrieval). Subjects then completed an externalized free recall task that allowed for the examination of response accessibility and monitoring. Individual differences in WMC were assessed using three complex span tasks: operation span, reading span, and rotation span. Correct recall and intratrial intrusion summary scores showed no effect of interpolated retrieval on either response accessibility or monitoring. However, serial-position curves for correct recall of List 1 showed larger primacy in the two-back than in the exemplar generation task for high-WMC subjects. We interpreted these results from a context change perspective, as showing that interpolated LTM retrieval accelerated context change for subjects who processed the context more effectively. We consider the implications of these findings for models of memory.

We introduce a discrete distribution suggested by curtailed sampling rules common in early-stage clinical trials. We derive the distribution of the smallest number of independent and identically distributed Bernoulli trials needed to observe either s successes or t failures. This report provides a closed-form expression for the mass function, moment generating function, and provides connections to other, standard distributions.

In recent years, several laboratory studies have indicated that healthy older adults exhibit a reduction in mind-wandering frequency compared with young adults. However, it is unclear if these findings extend to daily life settings. In the current study, using experience sampling over the course of a week in the daily life of 31 young and 20 older adults, we assessed age-related differences in: (a) mind-wandering frequency, (b) the relationship between affect and mind-wandering frequency, and (c) content of mind wandering. Older adults mind wandered less than young adults in daily life. Across age groups, negative affect was positively associated with mind-wandering occurrence. Finally, older adults reported that their thoughts were more pleasant, interesting, and clear compared with young adults, who had thoughts that were more dreamlike, novel, strange, and racing. Our results provide the first demonstration using thought sampling that older adults exhibit a reduction in mind-wandering frequency in daily life. Implications for current theories of age-related reductions in mind-wandering frequency are discussed. (PsycINFO Database Record

The relations between video-game experience and cognitive abilities were examined in the current study. In two experiments, subjects performed a number of working memory, fluid intelligence, and attention-control measures and filled out a questionnaire about their video-game experience. In Experiment 1, an extreme-groups analysis indicated that experienced video-game players outperformed nonplayers on several cognitive-ability measures. However, in Experiments 1 and 2, when analyses examined the full range of subjects at both the task level and the latent-construct level, nearly all of the relations between video-game experience and cognitive abilities were near zero. These results cast doubt on recent claims that playing video games leads to enhanced cognitive abilities. Statistical and methodological issues with prior studies of video-game experience are discussed along with recommendations for future studies.

A combined experimental–correlational study with a diverse sample (N = 182) from two research\ud sites tested a set of five a priori hypotheses about mind wandering and learning, using a realistic\ud video lecture on introductory statistics. Specifically, the study examined whether students’\ud vulnerability to mind wandering during the lecture would predict learning from, and situational\ud interest in, the video, and also whether longhand note-taking would help reduce mind\ud wandering, at least for some students. Half the subjects took notes during the video, and all\ud were subsequently tested on lecture content without notes. Regression and mediation analyses\ud indicated that: (a) several individual-differences variables (e.g., pretest score, prior math\ud interest, classroom media multitasking habits) uniquely predicted in-lecture mind wandering\ud frequency; (b) although the note-taking manipulation did not reduce mind wandering at the\ud group level, note-taking still reduced mind wandering for some individuals (i.e., those with lower\ud prior knowledge and those who took notes of high quality and quantity); (c) mind wandering\ud uniquely predicted both learning (posttest) and situational interest outcomes above and beyond\ud all other individual-differences variables; (d) moreover, mind wandering significantly mediated\ud the effects of several individual differences; and, finally, (e) not all types of mind wandering\ud were problematic—in fact, off-task reflections about lecture-related topics positively predicted\ud learning. These results, which were generally robust across the two sites, suggest that\ud educationally focused cognitive research may benefit from considering attentional processes\ud during learning as well as cognitive and noncognitive individual differences that affect attention\ud and learning. \ud

The association between working memory capacity (WMC) and the antisaccade task, which requires subjects to move their eyes and attention away from a strong visual cue, supports the claim that WMC is partially an attentional construct (Kane, Bleckley, Conway, & Engle, 2001; Unsworth, Schrock, & Engle, 2004). Specifically, the WMC-antisaccade relation suggests that WMC helps maintain and execute task goals despite interference from habitual actions. Related work has recently shown that mind wandering (McVay & Kane, 2009, 2012a, 2012b) and reaction time (RT) variability (Unsworth, 2015) are also related to WMC and they partially explain WMC's prediction of cognitive abilities. Here, we tested whether mind-wandering propensity and intraindividual RT variation account for WMC's associations with 2 antisaccade-cued choice RT tasks. In addition, we asked whether any influences of WMC, mind wandering, or intraindividual RT variation on antisaccade are moderated by (a) the temporal gap between fixation and the flashing location cue, and (b) whether targets switch sides on consecutive trials. Our quasi-experimental study reexamined a published dataset (Kane et al., 2016) comprising 472 subjects who completed 6 WMC tasks, 5 attentional tasks with mind-wandering probes, 5 tasks from which we measured intraindividual RT variation, and 2 antisaccade tasks with varying fixation-cue gap durations. The WMC-antisaccade association was not accounted for by mind wandering or intraindividual RT variation. WMC's effects on antisaccade performance were greater with longer fixation-to-cue intervals, suggesting that goal activation processes-beyond the ability to control mind wandering and RT variability-are partially responsible for the WMC-antisaccade relation. (PsycINFO Database Record

Reductions in function within the serotonin (5HT) neuronal system have long been proposed as etiological factors in depression. Selective serotonin reuptake inhibitors (SSRIs) are the most common treatment for depression, and their therapeutic effect is generally attributed to their ability to increase the synaptic levels of 5HT. Tryptophan hydroxylase 2 (TPH2) is the initial and rate-limiting enzyme in the biosynthetic pathway of 5HT in the CNS, and losses in its catalytic activity lead to reductions in 5HT production and release. The time differential between the onset of 5HT reuptake inhibition by SSRIs (minutes) and onset of their antidepressant efficacy (weeks to months), when considered with their overall poor therapeutic effectiveness, has cast some doubt on the role of 5HT in depression. Mice lacking the gene for TPH2 are genetically depleted of brain 5HT and were tested for a depression-like behavioral phenotype using a battery of valid tests for affective-like disorders in animals. The behavior of TPH2(-/-) mice on the sucrose preference test, tail suspension test, and forced swim test and their responses in the unpredictable chronic mild stress and learned helplessness paradigms was the same as wild-type controls. While TPH2(-/-) mice as a group were not responsive to SSRIs, a subset responded to treatment with SSRIs in the same manner as wild-type controls with significant reductions in immobility time on the tail suspension test, indicative of antidepressant drug effects. The behavioral phenotype of the TPH2(-/-) mouse questions the role of 5HT in depression. Furthermore, the TPH2(-/-) mouse may serve as a useful model in the search for new medications that have therapeutic targets for depression that are outside of the 5HT neuronal system.

Sports-related head impact and injury has become a very highly contentious public health and medico-legal issue. Near-daily news accounts describe the travails of concussed athletes as they struggle with depression, sleep disorders, mood swings, and cognitive problems. Some of these individuals have developed chronic traumatic encephalopathy, a progressive and debilitating neurodegenerative disorder. Animal models have always been an integral part of the study of traumatic brain injury in humans but, historically, they have concentrated on acute, severe brain injuries. This review will describe a small number of new and emerging animal models of sports-related head injury that have the potential to increase our understanding of how multiple mild head impacts, starting in adolescence, can have serious psychiatric, cognitive and histopathological outcomes much later in life. Sports-related head injury (SRHI) has emerged as a significant public health issue as athletes can develop psychiatric and neurodegenerative disorders later in life. Animal models have always been an integral part of the study of human TBI but few existing methods are valid for studying SRHI. In this review, we propose criteria for effective animal models of SRHI. Movement of the head upon impact is judged to be of primary importance in leading to concussion and persistent CNS dysfunction.