Background: Dementia has a negative impact on the quality of life of the person with dementia and their spouse caregivers, as well as on the couple's relationship, which can lead to high levels of distress for both partners. Hypnosis has been shown to be effective in managing distress and increasing the quality of the relationship.
Objective: The aim was to develop a standardized hypnosis intervention for couples confronted with Alzheimer's disease and evaluate its feasibility, acceptability, and helpfulness in managing the distress of both partners and increasing the quality of the relationship.
Methods: In a single-arm study, sixteen couples received the 8-week intervention. Qualitative and quantitative assessments were conducted pre- and post-intervention as well as three months after.
Results: 88.9% of couples (n = 16) of the final sample (n = 18) completed the intervention. Despite the negative representations of hypnosis, several factors led couples to accept to participate in this study: positive expectations, professional endorsement, medical application, non-drug approach, home-based, free, flexible, and couple-based intervention. The results showed a significant decrease in distress for both partners. These effects were maintained three months after the intervention. Couples felt more relaxed, had fewer negative emotions, accepted difficulties more easily, were more patient, and reported better communication and more affection in the relationship.
Conclusion: Overall, this pilot study shows the feasibility and acceptability of hypnosis with couples confronted with Alzheimer's disease. Although measures of the preliminary pre- and post-intervention effects are encouraging, confirmatory testing with a randomized controlled trial is needed.
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http://dx.doi.org/10.3233/JAD-220430 | DOI Listing |
J Chem Inf Model
January 2025
Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1218 S 5th Ave, Monrovia, California 91016, United States.
Bayesian network modeling (BN modeling, or BNM) is an interpretable machine learning method for constructing probabilistic graphical models from the data. In recent years, it has been extensively applied to diverse types of biomedical data sets. Concurrently, our ability to perform long-time scale molecular dynamics (MD) simulations on proteins and other materials has increased exponentially.
View Article and Find Full Text PDFFront Immunol
January 2025
Department of Neurological Care Unit, The First Affiliated Hospital of YangTze University, Jingzhou, Hubei, China.
Background: Recent years have seen persistently poor prognoses for glioma patients. Therefore, exploring the molecular subtyping of gliomas, identifying novel prognostic biomarkers, and understanding the characteristics of their immune microenvironments are crucial for improving treatment strategies and patient outcomes.
Methods: We integrated glioma datasets from multiple sources, employing Non-negative Matrix Factorization (NMF) to cluster samples and filter for differentially expressed metabolic genes.
Front Immunol
January 2025
Institut National de la Santé et de la Recherche Médicale (INSERM), Unité Mixte de Recherche U1236, Université Rennes, Etablissement Français du Sang Bretagne, LabEx IGO, Rennes, France.
Introduction: Myeloid cells trafficking from the periphery to the central nervous system are key players in multiple sclerosis (MS) through antigen presentation, cytokine secretion and repair processes.
Methods: Combination of mass cytometry on blood cells from 60 MS patients at diagnosis and 29 healthy controls, along with single cell RNA sequencing on paired blood and cerebrospinal fluid (CSF) samples from 5 MS patients were used for myeloid cells detailing.
Results: Myeloid compartment study demonstrated an enrichment of a peculiar classical monocyte population in 22% of MS patients at the time of diagnosis.
Front Nutr
January 2025
Laboratory of Biochemistry, Biotechnology, Food Technology and Nutrition (LABIOTAN), Department of Biochemistry-Microbiology, Joseph KI-ZERBO University, Ouagadougou, Burkina Faso.
Introduction: Burkina Faso is facing a serious public health problem of chronic malnutrition and mortality in children under the age of 5. To tackle this situation, a number of child nutrition interventions have been implemented. This study aims to assess the impact of these interventions on the nutritional status of children aged 0-5 years between 2018 and 2022.
View Article and Find Full Text PDFJ Biomed Opt
January 2025
CIFICEN (UNCPBA - CICPBA - CONICET), Tandil, Argentina.
Significance: In the last years, time-resolved near-infrared spectroscopy (TD-NIRS) has gained increasing interest as a tool for studying tissue spectroscopy with commercial devices. Although it provides much more information than its continuous wave counterpart, accurate models interpreting the measured raw data in real time are still lacking.
Aim: We introduce an analytical model that can be integrated and used in TD-NIRS data processing software and toolkits in real time.
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