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.

No evidence for contextual cueing beyond explicit recognition.

Many studies claim that visual regularities can be learned unconsciously and without explicit awareness. For example in the contextual cueing paradigm, studies often make claims using a standard reasoning based on two results: (1) a reliable response time (RT) difference between repeated vs. new stimulus displays and (2) a close-to-chance sensitivity when participants are asked to explicitly recognize repeated stimulus displays. From this pattern of results, studies routinely conclude that the sensitivity of RT responses is higher than that of explicit responses-an empirical situation we call Indirect Task Advantage (ITA). Many studies further infer from an ITA that RT effects were driven by a form of recognition that exceeds explicit memory: implicit recognition. However, this reasoning is flawed because the sensitivity underlying RT effects is never computed. To properly establish a difference, a sensitivity comparison is required. We apply this sensitivity comparison in a reanalysis of 20 contextual cueing studies showing that not a single study provides consistent evidence for ITAs. Responding to recent correlation-based arguments, we also demonstrate the absence of evidence for ITAs at the level of individual participants. This lack of ITAs has serious consequences for the field: If RT effects can be fully explained by weak but above-chance explicit recognition sensitivity, what is the empirical content of the label "implicit"? Thus, theoretical discussions in this paradigm-and likely in other paradigms using this standard reasoning-require serious reassessment because the current data from contextual cueing studies is insufficient to consider recognition as implicit.

Model-free decision making resists improved instructions and is enhanced by stimulus-response associations.

Human behaviour may be thought of as supported by two different computational-learning mechanisms, model-free and model-based respectively. In model-free strategies, stimulus-response associations are strengthened when actions are followed by a reward and weakened otherwise. In model-based learning, previous to selecting an action, the current values of the different possible actions are computed based on a detailed model of the environment. Previous research with the two-stage task suggests that participants' behaviour usually shows a mixture of both strategies. But, interestingly, a recent study by da Silva and Hare (2020) found that participants primarily deploy model-based behaviour when they are given detailed instructions about the structure of the task. In the present study, we reproduce this essential experiment. Our results confirm that improved instructions give rise to a stronger model-based component. Crucially, we also found a significant effect of reward that became stronger under conditions that favoured the development of strong stimulus-response associations. This suggests that the effect of reward, often taken as indicator of a model-free component, is related to stimulus-response learning.

An umbrella review of randomized control trials on the effects of physical exercise on cognition.

Extensive research links regular physical exercise to an overall enhancement of cognitive function across the lifespan. Here we assess the causal evidence supporting this relationship in the healthy population, using an umbrella review of meta-analyses limited to randomized controlled trials (RCTs). Despite most of the 24 reviewed meta-analyses reporting a positive overall effect, our assessment reveals evidence of low statistical power in the primary RCTs, selective inclusion of studies, publication bias and large variation in combinations of pre-processing and analytic decisions. In addition, our meta-analysis of all the primary RCTs included in the revised meta-analyses shows small exercise-related benefits (d = 0.22, 95% confidence interval 0.16 to 0.28) that became substantially smaller after accounting for key moderators (that is, active control and baseline differences; d = 0.13, 95% confidence interval 0.07 to 0.20), and negligible after correcting for publication bias (d = 0.05, 95% confidence interval -0.09 to 0.14). These findings suggest caution in claims and recommendations linking regular physical exercise to cognitive benefits in the healthy human population until more reliable causal evidence accumulates.

Learning to suppress a distractor may not be unconscious.

The additional singleton task has become a popular paradigm to explore visual statistical learning and selective attention. In this task, participants are instructed to find a different-shaped target among a series of distractors as fast as possible. In some trials, the search display includes a singleton distractor with a different color, making search more difficult. This singleton distractor appears more often in one location than in the remaining locations. The typical results of these experiments show that participants learn to ignore the area of the screen that is more likely to contain the singleton distractor. It is often claimed that this learning takes place unconsciously, because at the end of the experiment participants seem to be unable to identify the location where the singleton distractor appeared most frequently during the task. In the present study, we tested participants' awareness in three high-powered experiments using alternative measures. Contrary to previous studies, the results show clear evidence of explicit knowledge about which area of the display was more likely to contain the singleton distractor, suggesting that this type of learning might not be unconscious.

The role of working memory in probabilistic cuing of visual search.

In a typical probabilistic cuing experiment, participants are asked to find a visual target among a series of distractors. Although participants are not informed about this, the target appears more frequently in one region of the display, resulting in faster search times for targets located in this region. This bias is thought to depend on a habit-like attentional control mechanism, unconstrained by the availability of working memory (WM) resources. However, the only study that has explored this feature in the past suffers from methodological shortcomings that leave the results open to alternative explanations. In three experiments, we aimed to confirm whether probabilistic cuing is unaffected by visual, spatial, and spatiotemporal WM load. For each experiment, one group of participants performed the visual search task during the retention interval of a WM task (high-load group), whereas another group of participants (no-load group) carried out the visual search task after the WM task. We hypothesized that the probabilistic cuing effect would be larger for the no-load group compared to the high-load group. This hypothesis was confirmed in one experiment, but exploratory analyses suggest that the results can be highly dependent on the analytic approach, casting doubts on its robustness. Overall, our results provide partial support for the hypothesis that probabilistic cuing is not affected by a secondary task. However, given that some analyses reveal an effect of WM load, we conclude that it might be premature to rule out the possibility that the expression of this attentional bias requires WM resources. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The role of working memory in contextual cueing of visual attention.

It is usually easier to find objects in familiar contexts that we have seen before. The type of learning that underlies this facilitation, known as contextual cueing, has been understood as an incidental and automatic process given that, among other reasons, it seems to be independent of working memory (WM) resources. This claim has found support in previous research showing that contextual cueing can be acquired latently, while participants perform a demanding WM task. However, previous studies have not always found this pattern of results and, in general, the available evidence is far from conclusive. The aim of the present study was to clarify the role of WM in contextual learning with two large-sample, confirmatory experiments. Our results show a robust contextual cueing effect even when visuospatial working memory resources were recruited by a demanding secondary task.

Raising awareness about measurement error in research on unconscious mental processes.

Experimental psychologists often neglect the poor psychometric properties of the dependent measures collected in their studies. In particular, a low reliability of measures can have dramatic consequences for the interpretation of key findings in some of the most popular experimental paradigms, especially when strong inferences are drawn from the absence of statistically significant correlations. In research on unconscious cognition, for instance, it is commonly argued that the lack of a correlation between task performance and measures of awareness or explicit recollection of the target stimuli provides strong support for the conclusion that the cognitive processes underlying performance must be unconscious. Using contextual cuing of visual search as a case study, we show that given the low reliability of the dependent measures collected in these studies, it is usually impossible to draw any firm conclusion about the unconscious character of this effect from correlational analyses. Furthermore, both a psychometric meta-analysis of the available evidence and a cognitive-modeling approach suggest that, in fact, we should expect to see very low correlations between performance and awareness at the empirical level, even if both constructs are perfectly related at the latent level. Convincing evidence for the unconscious character of contextual cuing and other effects will most likely demand richer and larger data sets, coupled with more powerful analytic approaches.

Is probabilistic cuing of visual search an inflexible attentional habit? A meta-analytic review.

In studies on probabilistic cuing of visual search, participants search for a target among several distractors and report some feature of the target. In a biased stage the target appears more frequently in one specific area of the search display. Eventually, participants become faster at finding the target in that rich region compared to the sparse region. In some experiments, this stage is followed by an unbiased stage, where the target is evenly located across all regions of the display. Despite this change in the spatial distribution of targets, search speed usually remains faster when the target is located in the previously rich region. The persistence of the bias even when it is no longer advantageous has been taken as evidence that this phenomenon is an attentional habit. The aim of this meta-analysis was to test whether the magnitude of probabilistic cuing decreases from the biased to the unbiased stage. A meta-analysis of 42 studies confirmed that probabilistic cuing during the unbiased stage was roughly half the size of cuing during the biased stage, and this decrease persisted even after correcting for publication bias. Thus, the evidence supporting the claim that probabilistic cuing is an attentional habit might not be as compelling as previously thought.

The evidential value of research on cognitive training to change food-related biases and unhealthy eating behavior: A systematic review and p-curve analysis.

Cognitive bias modification (CBM), which retrains implicit biases towards unhealthy foods, has been proposed as a promising adjunct to improve the efficacy of weight loss interventions. We conducted a systematic review of research on three CBM approaches (i.e., cue-specific inhibitory control, approach bias modification, and attentional bias modification) for reducing unhealthy eating biases and behavior. We performed a p-curve analysis to determine the evidential value of this research; this method is optimally suited to clarify whether published results reflect true effects or false positives due to publication and reporting biases. When considering all CBM approaches, our results suggested that the findings of CBM trials targeting unhealthy eating are unlikely to be false positives. However, only research on attentional bias modification reached acceptable levels of power. These results suggest that CBM interventions may be an effective strategy to enhance the efficacy of weight loss interventions. However, there is room for improvement in the methodological standards of this area of research, especially increasing the statistical power can help to fully clarify the clinical potential of CBM, and determine the role of potential moderators.

Publication bias and low power in field studies on goal priming.

Research on goal priming asks whether the subtle activation of an achievement goal can improve task performance. Studies in this domain employ a range of priming methods, such as surreptitiously displaying a photograph of an athlete winning a race, and a range of dependent variables including measures of creativity and workplace performance. Chen, Latham, Piccolo and Itzchakov (Chen et al. 2021 J. Appl. Psychol. 70, 216-253) recently undertook a meta-analysis of this research and reported positive overall effects in both laboratory and field studies, with field studies yielding a moderate-to-large effect that was significantly larger than that obtained in laboratory experiments. We highlight a number of issues with Chen et al.'s selection of field studies and then report a new meta-analysis (k = 13, N = 683) that corrects these. The new meta-analysis reveals suggestive evidence of publication bias and low power in goal priming field studies. We conclude that the available evidence falls short of demonstrating goal priming effects in the workplace, and offer proposals for how future research can provide stronger tests.

Contextual cuing of visual search does not guide attention automatically in the presence of top-down goals.

Visual search is faster when it occurs within repeated displays, a phenomenon known as contextual cuing (CC). CC has been explained as the result of an automatic orientation of attention toward a target item driven by learned distractor-target associations. In 3 experiments we tested the specific hypothesis that CC is an automatic process of attentional guidance. Participants first searched for a T target in a standard CC procedure. Then, they experienced the same repeated configurations (with the T still present), but now searched for a Y target that was positioned either in a location on the same, or on a different side, from the old T target. Results suggested that there was no interference caused by the old T-target: target search was not affected by the relative positions of the T and Y. Instead, we found a general facilitation in search times for repeated configurations (Experiments 1 and 2). This main effect disappeared when the need for visual search was eliminated in Experiment 3 using a "feature search task". These results suggest that repeated sets of distractors did not trigger an uncontrollable response toward the position of the T; instead, CC was produced by perceptual learning processes. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Deep Learning With Anaphora Resolution for the Detection of Tweeters With Depression: Algorithm Development and Validation Study.

BACKGROUND: Mental health problems are widely recognized as a major public health challenge worldwide. This concern highlights the need to develop effective tools for detecting mental health disorders in the population. Social networks are a promising source of data wherein patients publish rich personal information that can be mined to extract valuable psychological cues; however, these data come with their own set of challenges, such as the need to disambiguate between statements about oneself and third parties. Traditionally, natural language processing techniques for social media have looked at text classifiers and user classification models separately, hence presenting a challenge for researchers who want to combine text sentiment and user sentiment analysis. OBJECTIVE: The objective of this study is to develop a predictive model that can detect users with depression from Twitter posts and instantly identify textual content associated with mental health topics. The model can also address the problem of anaphoric resolution and highlight anaphoric interpretations. METHODS: We retrieved the data set from Twitter by using a regular expression or stream of real-time tweets comprising 3682 users, of which 1983 self-declared their depression and 1699 declared no depression. Two multiple instance learning models were developed-one with and one without an anaphoric resolution encoder-to identify users with depression and highlight posts related to the mental health of the author. Several previously published models were applied to our data set, and their performance was compared with that of our models. RESULTS: The maximum accuracy, F1 score, and area under the curve of our anaphoric resolution model were 92%, 92%, and 90%, respectively. The model outperformed alternative predictive models, which ranged from classical machine learning models to deep learning models. CONCLUSIONS: Our model with anaphoric resolution shows promising results when compared with other predictive models and provides valuable insights into textual content that is relevant to the mental health of the tweeter.

The Challenge of Inferring Unconscious Mental Processes.

Studies of unconscious mental processes often compare a performance measure (e.g., some assessment of perception or memory) with a measure of awareness (e.g., a verbal report or forced-choice response) of the critical cue or contingency taken either concurrently or separately. The resulting patterns of bivariate data across participants lend themselves to several analytic approaches for inferring the existence of unconscious mental processes, but it is rare for researchers to consider the underlying generative processes that might cause these patterns. We show that bivariate data are generally insufficient to discriminate single-process models, with a unitary latent process determining both performance and awareness, from dual-process models, comprising distinct latent processes for performance and awareness. Future research attempting to isolate and investigate unconscious processes will need to employ richer types of data and analyses.

Is the habit system altered in individuals with obesity? A systematic review.

Habit-like eating behavior is repeatedly pointed to as a key cognitive mechanism contributing to the emergence and maintenance of obesity. Here, we conducted a systematic review of the literature to assess the existent behavioral evidence for the Habit Hypothesis for Overeating (HHO) which states that obesity is the consequence of an imbalance between the habit and goal-directed reward learning systems, leading to overconsumption of food. We found a total of 19 studies implementing a variety of experimental protocols (i.e., free operant paradigm, slips-of-action test, two-step task, Pavlovian-to-Instrumental paradigm, probabilistic learning task) and manipulations. Taken together, the studies on clinical (binge eating disorder) and non-clinical individuals with overweight or obesity do not support the HHO conclusively. While the scientific literature on HHO is still in its infancy, the heterogeneity of the extant studies makes it difficult to evaluate the degree of convergence of these findings. Uncovering the role of reward learning systems in eating behaviors might have a transformative impact on public health.

Correction: Mental Fatigue Might be Not So Bad for Exercise Performance After All: A Systematic Review and Bias-Sensitive Meta-Analysis.

[This corrects the article DOI: 10.5334/joc.126.].

Correlation analysis to investigate unconscious mental processes: A critical appraisal and mini-tutorial.

As a method to investigate the scope of unconscious mental processes, researchers frequently obtain concurrent measures of task performance and stimulus awareness across participants. Even though both measures might be significantly greater than zero, the correlation between them might not, encouraging the inference that an unconscious process drives task performance. We highlight the pitfalls of this null-correlation approach and provide a mini-tutorial on ways to avoid them. As reference, we use a recent study by Salvador et al. (2018) reporting a non-significant correlation between the extent to which memory was suppressed by a Think/No-Think cue and an index of cue awareness. In the Null Hypothesis Significance Testing (NHST) framework, it is inappropriate to interpret failure to reject the null hypothesis (i.e., correlation = 0) as evidence for the null. Furthermore, psychological measures are often unreliable, which can dramatically attenuate the size of observed correlations. A Bayesian approach can circumvent both problems and compare the extent to which the data provide evidence for the null versus the alternative hypothesis (i.e., correlation > 0), while considering the usually low reliabilities of the variables. Applied to Salvador et al.'s data, this approach indicates no to moderate support for the claimed unconscious nature of participants' memory-suppression performance-depending on the model of the alternative hypothesis. Hence, more reliable data are needed. When analyzing correlational data, we recommend researchers to employ the Bayesian methods developed here (and made freely available as R scripts), rather than standard NHST methods, to take account of unreliability.

Is project-based learning effective among kindergarten and elementary students? A systematic review.

Project-based learning (PjBL) is becoming widespread in many schools. However, the evidence of its effectiveness in the classroom is still limited, especially in basic education. The aim of the present study was to perform a systematic review of the empirical evidence assessing the impact of PjBL on academic achievement of kindergarten and elementary students. We also examined the quality of studies, their compliance with basic prerequisites for a successful result, and their fidelity towards the key elements of PBL intervention. For this objective, we conducted a literature search in January 2020. The inclusion criteria for the review required that studies followed a pre-post design with control group and measured quantitatively the impact of PBL on content knowledge of students. The final sample included eleven articles comprising data from 722 students. The studies yielded inconclusive results, had important methodological flaws, and reported insufficient or no information about important aspects of the materials, procedure and key requirements from students and instructors to guarantee the success of PjBL. Educational implications of these results are discussed.

Testing (quizzing) boosts classroom learning: A systematic and meta-analytic review.

Over the last century hundreds of studies have demonstrated that testing is an effective intervention to enhance long-term retention of studied knowledge and facilitate mastery of new information, compared with restudying and many other learning strategies (e.g., concept mapping), a phenomenon termed the testing effect. How robust is this effect in applied settings beyond the laboratory? The current review integrated 48,478 students' data, extracted from 222 independent studies, to investigate the magnitude, boundary conditions, and psychological underpinnings of test-enhanced learning in the classroom. The results show that overall testing (quizzing) raises student academic achievement to a medium extent (g = 0.499). The magnitude of the effect is modulated by a variety of factors, including learning strategy in the control condition, test format consistency, material matching, provision of corrective feedback, number of test repetitions, test administration location and timepoint, treatment duration, and experimental design. The documented findings support 3 theories to account for the classroom testing effect: additional exposure, transfer-appropriate processing, and motivation. In addition to their implications for theory development, these results have practical significance for enhancing teaching practice and guiding education policy and highlight important directions for future research. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

To which world regions does the valence-dominance model of social perception apply?

Over the past 10 years, Oosterhof and Todorov's valence-dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov's methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov's original analysis strategy, the valence-dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence-dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 5 November 2018. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.7611443.v1 .