RESUMEN

Introduction: With rapid advancements in natural language processing (NLP), predicting personality using this technology has become a significant research interest. In personality prediction, exploring appropriate questions that elicit natural language is particularly important because questions determine the context of responses. This study aimed to predict levels of neuroticism-a core psychological trait known to predict various psychological outcomes-using responses to a series of open-ended questions developed based on the five-factor model of personality. This study examined the model's accuracy and explored the influence of item content in predicting neuroticism. Methods: A total of 425 Korean adults were recruited and responded to 18 open-ended questions about their personalities, along with the measurement of the Five-Factor Model traits. In total, 30,576 Korean sentences were collected. To develop the prediction models, the pre-trained language model KoBERT was used. Accuracy, F1 Score, Precision, and Recall were calculated as evaluation metrics. Results: The results showed that items inquiring about social comparison, unintended harm, and negative feelings performed better in predicting neuroticism than other items. For predicting depressivity, items related to negative feelings, social comparison, and emotions showed superior performance. For dependency, items related to unintended harm, social dominance, and negative feelings were the most predictive. Discussion: We identified items that performed better at neuroticism prediction than others. Prediction models developed based on open-ended questions that theoretically aligned with neuroticism exhibited superior predictive performance.

RESUMEN

Life activities profoundly influence well-being, mental health, and quality of life. The COVID-19 pandemic has heightened the importance of monitoring these activities for psychological and emotional health. However, existing measurement tools are limited, particularly for assessing psychological health. To address this gap, we developed and validated the Core Life Activities (CORE) scale, comprising five key factors (sleep, exercise, learning, diet, and social relationships) identified in neuroscience, cognitive psychology, and gerontology. In Study 1 (n = 1,137), exploratory and confirmatory factor analyses supported a single-factor structure with good model fit (χ2 = 6.377, df = 3, TLI = 0.992, CFI = 0.998, RMSEA = 0.031), demonstrating robust internal consistency (Cronbach's alpha = 0.776) and test-retest reliability (intraclass correlation coefficient = 0.522, p < 0.001). The CORE exhibited significant convergent validity with mental health screening tools for depressive and anxiety disorders and suicidality. Study 2 (n = 684) confirmed a significant correlation between CORE and the World Health Organisation Quality of Life Brief Version, complementing the convergent validity found in Study 1. In addition, discriminant validity was confirmed by a non-significant correlation with the COVID-19 Preventive Behavior Scale. The findings establish the CORE as a reliable and valid tool, offering a simple yet comprehensive measure for assessing core life activities with potential applications in diverse environments.

RESUMEN

The formation of categories is known to distort perceptual space: representations are pushed away from category boundaries and pulled toward categorical prototypes. This phenomenon has been studied with artificially constructed objects, whose feature dimensions are easily defined and manipulated. How such category-induced perceptual distortions arise for complex, real-world scenes, however, remains largely unknown due to the technical challenge of measuring and controlling scene features. We address this question by generating realistic scene images from a high-dimensional continuous space using generative adversarial networks and using the images as stimuli in a novel learning task. Participants learned to categorize the scene images along arbitrary category boundaries and later reconstructed the same scenes from memory. Systematic biases in reconstruction errors closely tracked each participant's subjective category boundaries. These findings suggest that the perception of global scene properties is warped to align with a newly learned category structure after only a brief learning experience.

RESUMEN

Face ensemble coding is the perceptual ability to create a quick and overall impression of a group of faces, triggering social and behavioral motivations towards other people (approaching friendly people or avoiding an angry mob). Cultural differences in this ability have been reported, such that Easterners are better at face ensemble coding than Westerners are. The underlying mechanism has been attributed to differences in processing styles, with Easterners allocating attention globally, and Westerners focusing on local parts. However, the remaining question is how such default attention mode is influenced by salient information during ensemble perception. We created visual displays that resembled a real-world social setting in which one individual in a crowd of different faces drew the viewer's attention while the viewer judged the overall emotion of the crowd. In each trial, one face in the crowd was highlighted by a salient cue, capturing spatial attention before the participants viewed the entire group. American participants' judgment of group emotion more strongly weighed the attended individual face than Korean participants, suggesting a greater influence of local information on global perception. Our results showed that different attentional modes between cultural groups modulate social-emotional processing underlying people's perceptions and attributions.

Asunto(s)

RESUMEN

This study investigated the similarity-based clustering mechanism of multifeature stimuli, wherein items are separated or grouped based on their similarity in visual working memory (VWM). In particular, we investigated whether clustering occurred at an individual feature level or at an integrated object level when participants encoded objects with multiple features for VWM. To test this, we conducted two experiments in which participants remembered and reconstructed a randomly chosen feature (either color or orientation) from one of five presented stimuli. As a key manipulation, we kept the distributions of the two feature dimensions constant while controlling the conjunction between the two dimensions in two different conditions: congruent conjunction (CC) and incongruent conjunction (IC). With this manipulation, we expected to observe the same number of clusters regardless of the conjunction condition when clustering occurred at the feature level. However, we expected a different number of clusters for CC and IC conditions when clustering occurred at the object level. Across two experiments, we consistently observed evidence that favored feature-level clustering. Nevertheless, we found that the swap error rates increased in the IC condition only when two features had to be encoded in VWM. These results suggest that clustering occurs at the feature level in VWM and that feature-level clustering influences item-level feature binding. Therefore, our study demonstrated the flexibility of representational units in VWM.

Asunto(s)

RESUMEN

Background: Self-report multiple choice questionnaires have been widely utilized to quantitatively measure one's personality and psychological constructs. Despite several strengths (e.g., brevity and utility), self-report multiple choice questionnaires have considerable limitations in nature. With the rise of machine learning (ML) and Natural language processing (NLP), researchers in the field of psychology are widely adopting NLP to assess psychological construct to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that of psychology due to small data sets and unvalidated modeling practices. Aims: The current article introduces the study method and procedure of phase II which includes the interview questions for the five-factor model (FFM) of personality developed in phase I. This study aims to develop the interview (semi-structured) and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology (phase 1), and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress (phase 2). The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction. Methods: Phase I (pilot) study was conducted to fifty-nine native Korean adults to acquire the personality-related text data from the interview (semi-structured) and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 300 Korean adults will be recruited using a convenience sampling method via online survey. The text data collected from interviews will be analyzed using the natural language processing. The results of the online survey including demographic data, depression, anxiety, and personality inventories will be analyzed together in the model to predict individuals' FFM of personality and the level of psychological distress (phase 2).

RESUMEN

Precisely characterizing mental representations of visual experiences requires careful control of experimental stimuli. Recent work leveraging such stimulus control has led to important insights; however, these findings are constrained to simple visual properties like color and line orientation. There remains a critical methodological barrier to characterizing perceptual and mnemonic representations of realistic visual experiences. Here, we introduce a novel method to systematically control visual properties of natural scene stimuli. Using generative adversarial networks (GANs), a state-of-the-art deep learning technique for creating highly realistic synthetic images, we generated scene wheels in which continuously changing visual properties smoothly transition between meaningful realistic scenes. To validate the efficacy of scene wheels, we conducted two behavioral experiments that assess perceptual and mnemonic representations attained from the scene wheels. In the perceptual validation experiment, we tested whether the continuous transition of scene images along the wheel is reflected in human perceptual similarity judgment. The perceived similarity of the scene images correspondingly decreased as distances between the images increase on the wheel. In the memory experiment, participants reconstructed to-be-remembered scenes from the scene wheels. Reconstruction errors for these scenes resemble error distributions observed in prior studies using simple stimulus properties. Importantly, perceptual similarity judgment and memory precision varied systematically with scene wheel radius. These findings suggest our novel approach offers a window into the mental representations of naturalistic visual experiences.

Asunto(s)

RESUMEN

BACKGROUND: Gaming disorder (GD) has been listed in the International Classification of Diseases 11th Revision. Studies on GD prevalence have been highly heterogeneous, and there are significant gaps in prevalence estimates. Few studies have examined what methodological and demographic factors could explain this phenomenon. Therefore, this meta-analytic study quantifies globally reported GD prevalence rates and explores their various moderating variables. METHODS: Prevalence estimates were extracted from 61 studies conducted before December 3, 2020, which included 227,665 participants across 29 countries. Subgroup and moderator analyses were used to investigate the potential causes of heterogeneity, including region, sample size, year of data collection, age group, study design, sampling method, survey format, sample type, risk of bias, terminology, assessment tool, and male proportion. RESULTS: The overall pooled prevalence of GD was 3.3% (95% confidence interval: 2.6-4.0) (8.5% in males and 3.5% in females). By selecting only 28 representative sample studies, the prevalence estimate was reduced to 2.4% (95% CI 1.7-3.2), and the adjusted prevalence estimate using the trim-and-fill method was 1.4% (95% CI 0.9-1.9). High heterogeneity in GD prevalence rates was influenced by various moderators, such as participant variables (e.g., region, sample size, and age) and study methodology (e.g., study design, sampling method, sample type, terminology, and instrument). The moderator analyses revealed that the sample size, mean age, and study quality were negatively associated with GD prevalence. CONCLUSIONS: This study confirms that GD prevalence studies were highly heterogeneous based on participant demographics and research methodologies. Various confounding variables, such as sampling methods, sample types, assessment tools, age, region, and cultural factors have significantly influenced the GD prevalence rates. Prevalence estimates are likely to vary depending on study quality. Further epidemiological studies should be conducted using rigorous methodological standards to more accurately estimate GD prevalence.

Asunto(s)

RESUMEN

We investigated whether clustering based on feature similarity improves the representational quality of visual working memory (VWM). We hypothesized that similar items are organized into clusters, and their recall precision increases with fewer clusters because of reduced memory load. In a series of 6 experiments, participants remembered orientations or colors of several stimuli and estimated the orientation (color) of cued item(s). We measured recall bias to identify whether items formed cluster(s) and measured recall precision to determine the effect of clustering on the representational quality of VWM. In Experiments 1 and 2, orientation similarity was manipulated to partition stimuli into 1, 2, or 3 clusters. In Experiment 3, we varied both the number of stimuli and their similarities such that 5 items were summarized into a smaller number of clusters than 3 items. We consistently found that similar items formed a cluster, and that the precision of the individual items increased with fewer clusters regardless of the number of items. We also observed the same clustering effects using color stimuli when participants were to remember items' colors (Experiment 4). However, a task-irrelevant feature was not potent enough to cluster items and did not increase the precision (Experiment 5). In Experiment 6, we varied item similarity and found that response errors were correlated within the same cluster but not across different clusters. Taken together, these results suggest that clusters formed by similar items can impact the representation of VWM; thus, acting as one of representational units of VWM. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Asunto(s)

RESUMEN

Continuous flash suppression (CFS) entails presentation of a stationary target to one eye and an animated sequence of arrays of geometric figures, the mask, to the other eye. The prototypical CFS sequence comprises different sized rectangles of various colors, dubbed Mondrians. Presented as a rapid, changing sequence to one eye, Mondrians or other similarly constructed textured arrays can abolish awareness of the target viewed by the other eye for many seconds at a time, producing target suppression durations much longer than those associated with conventional binocular rivalry. We have devised an animation technique that replaces meaningless Mondrian figures with recognizable visual objects and scenes as inducers of CFS, allowing explicit manipulation of the visual semantic content of those masks. By converting each image of these CFS sequences into successively presented objects or scenes each comprised of many small, circular patches of color, we create pointillist CFS sequences closely matched in terms of their spatio-temporal power spectra. Randomly rearranging the positions of the pointillist patches scrambles the images so they are no longer recognizable. CFS sequences comprising a stream of different objects produces more robust interocular suppression than do sequences comprising a stream of different scenes, even when the two categories of CFS are matched in root mean square contrast and spatial frequency content. Factors promoting these differences in CFS potency could range from low-level, image-based features to high-level factors including attention and recognizability. At the same time, object- and scene-based CFS sequences, when themselves suppressed from awareness, do not differ in their durations of suppression, implying that semantic content of those images comprising CFS sequences are not registered during suppression. The pointillist technique itself offers a potentially useful means for examining the impact of high-level image meaning on aspects of visual perception other than interocular suppression.

Asunto(s)