98%
921
2 minutes
20
The State-Trait Inventory for Cognitive and Somatic Anxiety (STICSA) is a widely used measure of state and trait anxiety. Within the Classical Testing Theory model, consistent findings provide support for its multidimensional factor structure, discriminant, convergent, and nomological validity, as well as age and gender invariance, across healthy and clinical samples. Nevertheless, some issues regarding STICSA dimensionality and item-scale composition remain unresolved (e.g., both bifactor and two-factor models were found to fit data equally well). The goal of this study was to investigate the STICSA's dimensionality within the Item Response Theory, and to assess the tenability of the bifactor model as a plausible model over the multidimensional model. The sample consisted of 3338 Italian participants (58.21% females; 41.79% males) with an average age of 35.65 years (range: 18-99; SD = 20.25). Both bifactor and two-correlated dimensions of the STICSA scales were confirmed to fit data by applying the multidimensional Item Response Theory (mIRT). While the bifactor model showed better fit indices, the multidimensional model was more accurate and precise (0.86-0.88) in estimating state and trait latent anxiety. A further comparison between multidimensional item parameters revealed that the multidimensional and bifactor models were equivalent. Findings showed that the STICSA is an accurate and precise instrument for measuring somatic and cognitive symptomatology dimensions within state and trait anxiety. The use of the state/trait total score requires special attention from the clinicians and researchers to avoid bias in the psychodiagnostic assessment.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10451624 | PMC |
http://dx.doi.org/10.3390/bs13080628 | DOI Listing |
Commun Biol
September 2025
Department of General and Applied Biology, São Paulo State University (UNESP), Institute of Bioscience, Rio Claro, SP, Brazil.
Symbiotic relationships shape the evolution of organisms. Fungi in the genus Escovopsis share an evolutionary history with the fungus-growing "attine" ant system and are only found in association with these social insects. Despite this close relationship, there are key aspects of Escovopsis evolution that remain poorly understood.
View Article and Find Full Text PDFIntroduction: The present study examined whether college students could be categorized into distinct subgroups that differed in their distracted driving and walking frequencies.
Method: A sample of 277 college students participated in this study. They completed an online survey measuring their frequencies of distracted driving and walking, trait impulsivity (relatively stable characteristics of individuals to act spontaneously without considering the potential consequences), and behavioral impulsivity (process-oriented construct reflecting impulsive decision-making).
J Genet Genomics
September 2025
State Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangd
The genetic basis of early-stage salt tolerance in alfalfa (Medicago sativa L.), a key factor limiting its productivity, remains poorly understand. To dissect this complex trait, we integrate genome-wide association study (GWAS) and transcriptomics (RNA-seq) from 176 accessions within a machine learning based genomic prediction framework.
View Article and Find Full Text PDFMethods
September 2025
School of Computer and Information Engineering, Henan University, Kaifeng, Henan, China; Henan Key Laboratory of Big Data Analysis and Processing, Henan University, Kaifeng, Henan, China. Electronic address:
Genomic selection (GS) is a breeding technique that utilizes genomic markers to predict the genetic potential of crops and animals. This approach holds significant promise for accelerating the improvement of agronomic traits and addressing food security challenges. While traditional breeding methods based on statistical or machine learning techniques have been useful in predicting traits for some crops, they often fail to capture the complex interactions between genotypes and phenotypes.
View Article and Find Full Text PDFJ Pediatr Nurs
September 2025
Health Sciences University Zeynep Kamil Gynecology and Pediatrics Training and Research Hospital, Department of Pediatrics, İstanbul, Turkey. Electronic address:
Introduction: This study aimed to evaluate the effectiveness of Quantum Touch in reducing transfer anxiety among children and their parents during admission from the emergency department to inpatient units.
Methods: A randomized controlled trial was conducted with 60 children aged 5 to 10 years and their parents in a pediatric emergency department of a training and research hospital in Turkey. Data were collected using the "Information Form", "Children's Anxiety Meter-State", "Children's Fear Scale" "Visual Analog Scale" and "State and Trait Anxiety Inventory".