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Life sciences · Observational Study
ClinicalTrials.gov · October 7, 2026
No summary has been generated for this record yet. What follows is drawn from its source metadata only.
Observational Study.
No findings were extractable from the material analysed.
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
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Registry record from ClinicalTrials.gov (NCT06747689). This is a study registration, not published results. Lead sponsor: Dokuz Eylul University. Recruitment status: RECRUITING. Study type: OBSERVATIONAL. Enrollment: 207 participants (ESTIMATED). Conditions: Heart Failure, Sleep Quality, Self Care, Cognitive Function. Primary outcome measures: Sleep quality , From December 2024 to January 2026; Self Care , From December 2024 to January 2026. Brief summary: The research will be conducted as a prospective and relational study to longitudinally investigate the effect of sleep quality on self-care in patients with heart failure (HF) and to evaluate the relationship between self-care, sleep quality, and cognitive functions. The sample size was calculated using the multiple linear regression model with the G\*Power Version 3.1 program. Based on a medium effect size of 0.15, an alpha of 0.05, a power of 0.95, and 18 predictors, the sample size was determined to be 188. Considering a potential dropout rate of 10%, it was decided to complete the study with a minimum of 207 participants. Data will be collected from patients who apply to the Dokuz Eylül University Cardiology Outpatient Clinic and meet the inclusion criteria. After signing the informed consent form, participants will be followed up at baseline, the 1st month, the 3rd month, and the 6th month by telephone. The Statistical Package for Social Sciences (SPSS) 24.0 will be used to analyze the numerical data of the research. Descriptive statistics, including number, percentage, mean, and standard deviation, as well as inferential statistics such as the χ2 test, t-test for independent groups, and multiple linear regression, will be employed in the data analysis.