Objective: To determine the effectiveness of Problem Solving Technique in reducing anxiety and depression, and increased perceived well-being in women family caregivers of chronic patients.
Design: A clinical trial FIELD OF STUDY: Health centres in Tarragona, Spain, during 2007-2011.
Participants: A sample 122 caregivers of patients in home care programs that met the inclusion criteria, were assigned to intervention or control group according to a simple random process.
Interventions: In the experimental group, the nurses applied the Problem Solving Technique to the caregiver according to a four-session protocol. The nurses provided the usual care to the caregivers In the control group. One month after intervention, the dependent vriables were measured again in both groups. PRINCIPAL MEASUREMENT: The dependent variables of anxiety and depression were measured using the Goldberg scale, and the emotional well-being variable by the scale of emotional health of the primary caregiver.
Results: A statistically significant improvement was detected in the anxiety and depression symptoms, as well as the perceived well-being in the intervention group compared to the control group.
Conclusions: Implementation of the Problem Solving Technique is a useful therapeutic tool for reducing symptoms of distress in family caregivers of chronic patients.
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http://dx.doi.org/10.1016/j.aprim.2012.05.008 | DOI Listing |
Trends Cogn Sci
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Department of Psychology, Humboldt University Berlin, Berlin, Germany; Center for Cognitive Neuroscience, Duke University, Durham, NC 27708, USA.
Creative problem solving and memory are inherently intertwined: memory accesses existing knowledge while creativity enhances it. Recent studies show that insights often accompanying creative solutions enhance long-term memory. This insight memory advantage (IMA) is explained by the 'insight as prediction error (PE)' hypothesis which states that insights arise from PEs updating predictive solution models and thereby enhancing memory.
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January 2025
Department of Radiography, School of Allied Health Sciences, Faculty of Health Sciences and Veterinary Medicine, University of Namibia, P.O Box 13301, Windhoek, Namibia. Electronic address:
Introduction: Patient-centred care (PCC) is essential in radiography for polytrauma patients emphasising empathy, clear communication, and patient well-being. Polytrauma patients require tailored imaging approaches, often involving multiple modalities. Managing and handling these patients during imaging are key components of radiography training to develop the necessary competencies.
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January 2025
Department of Product & Systems Design Engineering, University of the Aegean, 84100 Syros, Greece.
This paper addresses the complex problem of multi-goal robot navigation, framed as an NP-hard traveling salesman problem (TSP), in environments with both static and dynamic obstacles. The proposed approach integrates a novel path planning algorithm based on the Bump-Surface concept to optimize the shortest collision-free path among static obstacles, while a Genetic Algorithm (GA) is employed to determine the optimal sequence of goal points. To manage static or dynamic obstacles, two fuzzy controllers are developed: one for real-time path tracking and another for dynamic obstacle avoidance.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Cyber Science and Engineering, Liaoning University, Shenyang 110036, China.
Recently, there has been a growing interest in underground construction safety, during activities such as subway construction, underground mining, and tunnel excavation. While Internet of Things (IoT) sensors help to monitor these conditions, large-scale deployment is limited by high power needs and complex tunnel layouts, making real-time response a critical challenge. A delay-sensitive multi-sensor multi-base-station routing scheduling method is proposed for the IoT in underground mining.
View Article and Find Full Text PDFMolecules
January 2025
Department of Physics, School of Physical Science and Technology, Ningbo University, Ningbo 315211, China.
Direct methods based on iterative projection algorithms can determine protein crystal structures directly from X-ray diffraction data without prior structural information. However, traditional direct methods often converge to local minima during electron density iteration, leading to reconstruction failure. Here, we present an enhanced direct method incorporating genetic algorithms for electron density modification in real space.
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