Patterns of cognitive-emotional change after cognitive-behavioural treatment in emotional disorders: A 12-month longitudinal cluster analysis
Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Abierto Inglés Introduction The aim of this study was to use cluster analysis based on the trajectory of five cognitive-emotional processes (worry, rumination, metacognition, cognitive reappraisal and expressive suppression) over time to explore differences in clinical and performance variables in primary care patients with emotional symptoms. Methods We compared the effect of adding transdiagnostic cognitive-behavioural therapy (TD-CBT) to treatment as usual (TAU) according to cluster membership and sought to determine the variables that predicted cluster membership. 732 participants completed scales about cognitive-emotional processes, anxiety and depressive symptoms, functioning, and quality of life (QoL) at baseline, posttreatment, and at 12 months. Longitudinal cluster analysis and logistic regression analyses were carried out. Results A two-cluster solution was chosen as the best fit, named as “less” or “more” improvement in cognitive-emotional processes. Individuals who achieved more improvement in cognitive-emotional processes showed lower emotional symptoms and better QoL and functioning at all three time points. TAU+TD-CBT, income level, QoL and anxiety symptoms were significant predictors of cluster membership. Conclusions These results underscore the value of adding TD-CBT to reduce maladaptive cognitive-emotional regulation strategies. These findings highlight the importance of the processes of change in therapy and demonstrate the relevance of the patient’s cognitive-emotional profile in improving treatment outcomes. metadata Chen, Mu-Hong and Barrio-Martínez, Sara and Rodriguez-Perez, Noelia and Priede, Amador and Medrano, Leonardo Adrián and Muñoz-Navarro, Roger and Moriana, Juan Antonio and Carpallo-González, María and Prieto-Vila, Maider and Ruiz-Rodríguez, Paloma and Cano-Vindel, Antonio and González-Blanch, César mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, cesar.gonzalezblanch@uneatlantico.es (2024) Patterns of cognitive-emotional change after cognitive-behavioural treatment in emotional disorders: A 12-month longitudinal cluster analysis. PLOS ONE, 19 (5). e0301746. ISSN 1932-6203
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Abstract
Introduction The aim of this study was to use cluster analysis based on the trajectory of five cognitive-emotional processes (worry, rumination, metacognition, cognitive reappraisal and expressive suppression) over time to explore differences in clinical and performance variables in primary care patients with emotional symptoms. Methods We compared the effect of adding transdiagnostic cognitive-behavioural therapy (TD-CBT) to treatment as usual (TAU) according to cluster membership and sought to determine the variables that predicted cluster membership. 732 participants completed scales about cognitive-emotional processes, anxiety and depressive symptoms, functioning, and quality of life (QoL) at baseline, posttreatment, and at 12 months. Longitudinal cluster analysis and logistic regression analyses were carried out. Results A two-cluster solution was chosen as the best fit, named as “less” or “more” improvement in cognitive-emotional processes. Individuals who achieved more improvement in cognitive-emotional processes showed lower emotional symptoms and better QoL and functioning at all three time points. TAU+TD-CBT, income level, QoL and anxiety symptoms were significant predictors of cluster membership. Conclusions These results underscore the value of adding TD-CBT to reduce maladaptive cognitive-emotional regulation strategies. These findings highlight the importance of the processes of change in therapy and demonstrate the relevance of the patient’s cognitive-emotional profile in improving treatment outcomes.
Item Type: | Article |
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Subjects: | Subjects > Psychology |
Divisions: | Europe University of Atlantic > Research > Articles and books |
Date Deposited: | 30 May 2024 20:51 |
Last Modified: | 30 May 2024 20:51 |
URI: | https://repositorio.uneatlantico.es/id/eprint/12368 |
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Josep Alemany Iturriaga mail josep.alemany@uneatlantico.es, Álvaro Velarde-Sotres mail alvaro.velarde@uneatlantico.es, Javier Jorge mail , Kamil Giglio mail ,
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Technological firms invest in R&D looking for innovative solutions but assuming high costs and great (technological) uncertainty regarding final results and returns. Additionally, they face other problems related to R&D management. This empirical study tries to determine which of the factors favour or constrain the decision of these firms to engage in R&D. The analysis uses financial data of 14,619 ICT listed companies of 22 countries from 2003 to 2018. Additionally, macroeconomic data specific for the countries and the sector were used. For the analysis of dynamic panel data, a System-GMM method is used. Among the findings, we highlight that cash flow, contrary to the known theoretical models and empirical evidences, negatively impacts on R&D investment. Debt is neither the right source for R&D funding, as the effect is also negative. This suggests that ICT companies are forced to manage their R&D activities differently, relying more on other funding sources, taking advantage of growth opportunities and benefiting from a favourable macroeconomic environment in terms of growth and increased business sector spending on R&D. These results are similar in both sub-sectors and in all countries, both bank- and market based. The exception is firms with few growth opportunities and little debt.
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Carotenoids Intake and Cardiovascular Prevention: A Systematic Review
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Uterine leiomyomas are the most common benign, monoclonal, gynaecological tumors in a woman’s uterus, while leiomyosarcoma is a rare but aggressive condition caused by the malignant transformation of the myometrium. To overcome the common obstacles related to the methods usually used to study these pathologies, we aimed to devise three-dimensional models of myometrium, uterine leiomyoma and leiomyosarcoma cell lines, using two different types of biocompatible scaffolds. Specifically, we exploited the agarose gel matrix in common 6-well plates and the alginate matrix using Bioprinting INKREDIBLE + (CELLINK), a pneumatic extruded base equipped with a system with double printheads, and a UV printer LED curing system. Both methods allowed the development of 3D spheroids of all three cell types, that were also suitable for morphological investigations. We showed that all cell types embedded in both agarose and alginate formed spheroids in their growth medium. The spheroids successfully proliferated and self-organized into complex structures, developing a sustainable system that emulated the condition of the tissues through the accumulation of extracellular matrix. These models could be useful for a better understanding of pathophysiology, etiopathogenesis, and testing new methods or molecules from a preventive and therapeutic point of view.
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