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Efficacy and cost-effectiveness of an ACT and compassion-based intervention for women with breast cancer: study protocol of two randomised controlled trials {1}.
Trials
January 2025
Center for Research in Neuropsychology and Cognitive and Behavioral Intervention, Faculty of Psychology and Education Sciences, University of Coimbra, Coimbra, Portugal.
Background: Breast cancer is the most diagnosed cancer in women worldwide and carries a considerable psychosocial burden. Interventions based on Acceptance and Commitment Therapy (ACT) and compassion-based approaches show promise in improving adjustment and quality of life in people with cancer. The Mind programme is an integrative ACT and compassion-based intervention tailored for women with breast cancer, which aims to prepare women for survivorship by promoting psychological flexibility and self-compassion.
View Article and Find Full Text PDFProcess-based therapy vs. routine-CBT for difficult-to-treat mood and anxiety disorders: study protocol for a randomized controlled trial.
Trials
December 2024
Department of Psychology, Philipps University Marburg, Schulstr. 12, 35037, Marburg/Lahn, Germany.
Background: Process-based therapy (PBT) is a new framework to intervention planning, based on the use of ecological momentary assessment (EMA) data and dynamic and idiographic network analyses. Support for its applicability has been reported from a single-case studies. Here, we examine the feasibility and effectiveness of PBT in a larger clinical sample.
View Article and Find Full Text PDFOdor prediction of whiskies based on their molecular composition.
Commun Chem
December 2024
Department of Sensory Analytics and Technologies, Fraunhofer Institute for Process Engineering and Packaging IVV, Freising, Germany.
Aroma compositions are usually complex mixtures of odor-active compounds exhibiting diverse molecular structures. Due to chemical interactions of these compounds in the olfactory system, assessing or even predicting the olfactory quality of such mixtures is a difficult task, not only for statistical models, but even for trained assessors. Here, we combine fast automated analytical assessment tools with human sensory data of 11 experienced panelists and machine learning algorithms.
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