Background: Sleep quality is among the indicators associated with the quality of life of patients with cancer. A multitude of factors may affect patient sleep quality and are considered as associated predictive factors. The aim of this study was to examine the predictors of poor sleep quality in Moroccan women with gynecological cancer after radical surgery.
Methods: A cross-sectional study was carried out at the Oncology Department of the Ibn Rochd University Hospital, Casablanca (Morocco), on women who had undergone radical surgery for gynecological cancer (n = 100; mean age: 50.94 years). To assess sleep quality, symptoms of depression and anxiety, self-esteem and body image, the following translated and validated Arabic versions of the tools were used: Pittsburgh Sleep Quality Index (PSQI), Hospital Anxiety and Depression Scale, Rosenberg's Self-Esteem Scale and Body Image Scale. To determine predictors of sleep quality, multiple linear and hierarchical regressions were used.
Results: 78% of participants were considered poor sleepers, most of them exhibited very poor subjective quality (53%), longer sleep onset latency (55%), short period of sleep (42%) and low rate of usual sleep efficiency (47%). 79% of these patients did not use sleep medication and 28% were in poor shape during the day. Waking up in the middle of the night or early in the morning and getting up to use the bathroom were the main reasons for poor sleep quality. Higher PSQI scores were positively correlated with higher scores of anxiety, depression, body image dissatisfaction and with lower self-esteem (p < 0.001). The medical coverage system, body image dissatisfaction and low self-esteem predicted poor sleep quality. After controlling for the socio-demographic variables (age and medical coverage system), higher body image dissatisfaction and lower self-esteem significantly predicted lower sleep quality.
Conclusion: Body image dissatisfaction and lower self-esteem were positively linked to sleep disturbance in women with gynecological cancer after undergone radical surgery. These two predictors require systematic evaluation and adequate management to prevent sleep disorders and mental distress as well as improving the quality of life of these patients.
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http://dx.doi.org/10.1186/s12905-021-01375-5 | DOI Listing |
J Geriatr Psychiatry Neurol
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Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China.
Within the global population, depression and anxiety are common among older adults. Tai Chi is believed to have a positive impact on these disturbances. This study examined the network structures of depression and anxiety among older Tai Chi practitioners vs non-practitioners.
View Article and Find Full Text PDFWound Repair Regen
January 2025
Research Unit for Plastic Surgery, University of Southern Denmark, Odense, Denmark.
The WOUND-Q is a patient-reported outcome measure for individuals with any type of chronic wound. This study aimed to identify patient and wound factors associated with the four WOUND-Q health-related quality of life (HRQL) scales: Life impact, Psychological, Sleep, and Social. Adults with a chronic wound were recruited internationally through clinical settings between August 2018 and May 2020, and through an online platform (i.
View Article and Find Full Text PDFJ Pain Res
December 2024
Department of Pain, The First People's Hospital of Zunyi City, Zunyi, Guizhou Province, 563000, People's Republic of China.
Objective: To compare the application effects of short-term peripheral nerve stimulation (st-PNS) and pulsed radiofrequency (PRF) technology in postherpetic neuralgia (PHN).
Methods: A retrospective analysis was conducted on the clinical data of 127 PHN patients from our hospital. Based on the treatment interventions received, patients were divided into a control group (n=63, treated with PRF) and an observation group (n=64, treated with st-PNS).
Front Digit Health
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Faculty of Engineering and Computing, Liwa College, Abu Dhabi, United Arab Emirates.
The evolution of artificial intelligence (AI) has revolutionised numerous aspects of our daily lives, with profound implications across various sectors, including healthcare. Although the concept of AI in healthcare was introduced in the early 1970s, the integration of this technology in healthcare is still in the evolution phase. Despite barriers, the current decade is witnessing an increased utility of AI into diverse specialities of the medical field to enhance precision medicine, predict diagnosis, therapeutic results, and prognosis; this includes respiratory medicine, critical care, and in their allied specialties.
View Article and Find Full Text PDFObjective: To systematically evaluate the efficacy of hyperbaric oxygen therapy for non-motor symptoms in patients with Parkinson's disease.
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