Objective: To investigate the relationship between self-awareness of functional status and performance of Instrumental Activities of Daily Living (IADL), and self-reports of quality of life (QOL) in persons with multiple sclerosis (MS).
Design: A between-groups design, using a correlational approach to examine the relationship between self-awareness of functional status, IADL and QOL.
Participants: We studied 47 individuals with clinically definite MS and 26 healthy controls (HCs).
Measures: The Functional Behavior Profile was completed by both participants and their informants. Participants' scores were subtracted from those of their informants', and the absolute value was used as the self-awareness/concordance score. The Executive Function Performance Test measured IADL performance; QOL was measured with the Functional Assessment of Multiple Sclerosis.
Results: MS participants showed lower levels of self-awareness relative to HCs. Significant correlations were observed between performance of IADL, reports of QOL and self-awareness levels of functional status. However, reports of QOL were not significantly correlated with performance of IADL.
Conclusions: The positive association between self-awareness of functional status with IADL performance and QOL reports provides support for the role of awareness in rehabilitation.
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http://dx.doi.org/10.1037/a0014556 | DOI Listing |
BMC Psychiatry
January 2025
Department of Psychiatry Sleep Medical Center, Nanfang Hospital Southern Medical University, No. 1838 North Guangzhou Avenue, Guangzhou, 510515, China.
Background: Patients with obstructive sleep apnea (OSA) frequently experience sleep disturbance and psychological distress, such as depression and anxiety, which may have a negative impact on their health status and functional abilities. To gain a more comprehensive understanding of the symptoms of depression, anxiety, and sleep disturbance in patients with OSA, the current study utilized network analysis to examine the interconnections among these symptoms.
Methods: Depressive and anxiety symptoms were evaluated using the Hospital Anxiety and Depression Scale (HADS), and sleep disturbance symptoms were evaluated using the Pittsburgh Sleep Quality Index (PSQI).
BMC Oral Health
January 2025
Department of Restorative Dentistry, Periodontology and Endodontology, University Medicine Greifswald, Greifswald, Germany.
Background: Despite considerable improvements in oral health in recent decades, caries and periodontitis are still widespread, ranking among the most prevalent diseases worldwide and requiring future research. The German National Cohort (NAKO Gesundheitsstudie, NAKO) is a large-scaled, multidisciplinary, nationwide, multi-centre, population-based, prospective cohort study with oral examinations that aims to provide a resource to study risk factors for major diseases. The aim of the present article is to provide the methodological background, to report on the data quality, and to present initial results of the oral examinations.
View Article and Find Full Text PDFBMC Cancer
January 2025
Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China.
Background: The albumin-to-creatinine ratio (ACR) is known to predict prognosis in liposarcoma patients, but its role in other tumors remains unclear. This study aimed to evaluate the prognostic relationship between ACR and common solid tumors.
Methods: Data from the Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) between 2013 and 2022 were used to analyze patients under 65 years old with solid tumors.
Nat Hum Behav
January 2025
Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
We conducted a genome-wide association study on income among individuals of European descent (N = 668,288) to investigate the relationship between socio-economic status and health disparities. We identified 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes (the Income Factor). Our polygenic index captures 1-5% of income variance, with only one fourth due to direct genetic effects.
View Article and Find Full Text PDFBackground: Coronary heart disease (CHD) and depression frequently co-occur, significantly impacting patient outcomes. However, comprehensive health status assessment tools for this complex population are lacking. This study aimed to develop and validate an explainable machine learning model to evaluate overall health status in patients with comorbid CHD and depression.
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