Background: Cancer is often associated with negative psychosocial consequences not only for patients but also for their partners. These consequences are also influenced by the applied coping strategies.
Objective: The study examines the influence of Dyadic Coping (DC) on social support and psychological distress (symptoms of depression and anxiety) in haemato-oncological patients and their partners. Of particular interest is the significance of dyadic accordance (conformity) of the assessment of DC ("discrepancy indexes").
Methods: The study investigates 330 couples (haemato-oncological patients and their partners, average age patient 57.0 years, 63.3 percent male, 25.8 percent acute leukemia). In addition to Dyadic Coping Inventory (DCI), standardized instruments are used. Research data is being analyzed with t-tests, partial correlation and regression.
Results: Patients and partners use similar dyadic coping strategies, whereby partners assess coping behaviors of patients more accurately than vice versa. Regarding social support, the DC total score plays a more decisive role than discrepancy indexes, in particular with patients (R=20.4%). Conversely, discrepancy indexes explain a large part of the patients' variance (R=10.2%); regarding psychological stress, the DC total score shows no effects in this model.
Discussion: The results demonstrate the relevance of the DC discrepancy indexes as a measure for interpersonal accordance for psychosocial outcomes, especially for psychological distress. Further application-related research is necessary to generate reliable statements about these associations.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1055/s-0043-110137 | DOI Listing |
Rev Gaucha Enferm
January 2025
RISE - Rede de Investigação em Saúde. Porto, Portugal.
Objective: To map the literature on the use of exergames in the rehabilitation of school-age children with brain tumors, in any context.
Method: Scoping review protocol developed using the recommendations of the Joanna Briggs Institute. The search will include aggregators, databases, indexes, repositories, and research browsers, without limitation as to the year of publication.
J Educ Health Promot
November 2024
Legal Medicine Research Center, Legal Medicine Organization, Tehran, Iran.
Background: Multiple sclerosis and its progressive relapsing-remitting nature for MS patients is challenging and significantly affects the mental health of people with MS. We examined the direct effects of alexithymia and attachment on mental health and the indirect effect of attachment, alexithymia, loneliness, and perceived social support on the mental health of people with MS.
Materials And Methods: Three hundred and forty-five diagnosed with multiple sclerosis (MS) were deemed eligible for inclusion in the study and selected through the Iranian MS Association.
Soil contamination by heavy metals (HM) is a critical area of research. Traditional methods involving sample collection and lab analysis are effective but costly and time-consuming. This study explores whether geostatistical analysis with GIS and open data can provide a faster, more precise, and cost-effective alternative for HM contamination assessment without extensive sampling.
View Article and Find Full Text PDFJ Epidemiol
January 2025
NCD Epidemiology Research Center, Shiga University of Medical Science.
Background: Healthy life expectancy (HLE) is a population health indicator that is widely used in developed countries, but little is known about its relationships with combinations of non-communicable disease risk factors. This study was conducted to examine HLE at age 65 according to combinations of blood pressure levels, body mass index, smoking status, and diabetes mellitus (DM) in a Japanese population.
Methods: In a nationwide cohort study (NIPPON DATA90), data on these risk factors were obtained from participants in 1990 through physical examinations, blood tests, interviews, and questionnaires.
Open Heart
January 2025
Department of Molecular and Clinical Medicine, University of Gothenburg Institute of Medicine, Gothenburg, Sweden.
Purpose: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe (≥70%) stenosis in the left anterior descending artery (LAD), right coronary artery (RCA) or left circumflex artery (LCX) in iodine contrast-enhanced ECG-gated coronary CT angiography (CCTA) scans.
Methods: From a database of 6293 CCTA scans, we used pre-existing curved multiplanar reformations (CMR) images of the LAD, RCA and LCX arteries to create end-to-end deep-learning models for the detection of moderate or severe stenoses. We preprocessed the images by exploiting domain knowledge and employed a transfer learning approach using EfficientNet, ResNet, DenseNet and Inception-ResNet, with a class-weighted strategy optimised through cross-validation.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!