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Showing 2 results for Structural Equation Model

Armin Ehsani, Imanollah Bigdeli, Hussein Kareshki,
Volume 8, Issue 2 (10-2020)
Abstract

Integrated approaches try to connect different constructs in different theories and reinterpret them using a common conceptual framework. In this research, using the concept of processing levels, an integrated, three-level model of the cognitive systems has been proposed. In order to build an integrative framework for systematic interpretation of cognitive tests results, processing levels are divided into three categories of Feature-Oriented, Semantic and Conceptual Level. Since nervous system picks stimuli based on their features, processing levels in this framework is categorized based on the volume of stimuli's information, while Semantic network relates Feature-Oriented and Self-Oriented levels. To assessment the model quantitatively, 207 participants with impaired valance system from psychological clinics in Mashhad were selected by available sampling method. Participants' cognitive function was measured by The Beck Depression Inventory II, Semantic Distance Test, Verbal Fluency Test, Dot Probe Test, Stroop Test, Implicit Association Test and Wisconsin Card Sorting Test. Tets scores were organized as predictive variables, and the three processing levels were considered as mediating variables. The model's structure was analyzed through Structural Equation Model method with an exploratory approach. The best fitted model of data confirmed the three-level division of the research data. In this model, the path coefficient between semantic and conceptual constructions obtained 0.4. These results suggest that Feature-Oriented, Semantic, and Conceptual levels of cognition are differently processed, and cognitive tests results could be compared just in similar level according to the information volume of stimuli used. In previous studies, the relationship between Verbal Fluency test scores and the severity of Beck depressive score has often been controversial. Using the concept of processing levels, the relationship between these two variables have been reinterpreted.

Mis Saeedeh Moradi, Dr Hadi Parhoon,
Volume 13, Issue 3 (12-2025)
Abstract

Abstract
The present study was conducted to examine the mediating role of self-efficacy in the relationship between inhibitory control, cognitive flexibility, and perceived organizational support and teachers’ job burnout.. Within the framework of the post-positivist paradigm, a quantitative approach was employed using a correlational design based on structural equation modeling.
A total of 370 teachers working in schools in Kermanshah during the 1403–1404 academic year were selected through convenience sampling. The following instruments were used for data collection: the Executive Functioning Scale (Holst & Thorell, 2018), the Cognitive Flexibility Scale (Dennis & Vander Wal, 2010), the Perceived Organizational Support Questionnaire (Eisenberger et al., 1986), the Teacher Self-Efficacy Scale (Schannen-Moran & Woolfolk Hoy, 2001), and the Teacher Burnout Scale (Chang et al., 2020).Data were analyzed using SPSS 27 and SmartPLS 4 within the framework of structural equation modeling. The results indicated that the research model had a good fit with the data.
The findings revealed that inhibition control had a direct and significant effect on teacher burnout (β = -0.377, t = 3.264, p = 0.001) and on self-efficacy (β = 0.271, t = 3.750, p < 0.001). Cognitive flexibility influenced teacher burnout (β = -0.200, t = 3.064, p < 0.002) and self-efficacy (β = 0.244, t = 3.264, p < 0.001). Perceived organizational support affected teacher burnout (β = -0.273, t = 2.339, p = 0.020) and self-efficacy (β = 0.215, t = 2.887, p < 0.001). Self-efficacy had a direct effect on teacher burnout (β = -0.64, t = 4.96, p < 0.001; β = 0.616, t = 6.015, p < 0.001).
These results suggest that part of the predictive effect of inhibition control, cognitive flexibility, and perceived organizational support on teacher burnout can be explained by self-efficacy. Furthermore, the study variables collectively accounted for 63% of the variance in teacher burnout.



 

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