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Daytime napping enhances energy restoration, cognitive function, and memory as well as reducing fatigue and improving overall performance. Weighted blankets have been used for improving sleep quality and as a rehabilitation tool for children with neurodevelopmental disorders. It is not known, however, whether weighted blankets can improve short-duration naps like day-time napping and what is the optimal weight of those blankets for achieving the best results. The purpose of the present study is to investigate for the first time the effect of 4 different weighted blankets on sleep parameters on daytime napping.
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Study Design Subjects will be randomly assigned into 4 conditions each one week apart: 1) The Control condition (CON), where subjects will lay down and be covered with a cotton blanket identical in appearance and material to the weighted blanket but without any extra weight, 2) The 7 kg condition blanket, where subjects will lay down and be covered with a blanket weighing 7 kg; 3) The 9 kg condition blanket, where subjects will lay down and be covered with a blanket weighing 9 kg; 4) The 14 kg condition blanket, where subjects will lay down and be covered with a blanket weighing 14 kg. All measurements will be conducted at the same sleep lab, at the same time of the day, under controlled conditions, with a constant temperature of 22°C, and dimmed lighting (5 lux), while any possible external sound will be masked using white noise sound at 432 Hz and 55 decibels. The study is approved by the Human Research and Ethics Committee of the University of Thessaly (2329/07/02/2024). All Subjects will give their written informed consent prior to study participation.
Procedure All measurements will be performed in the Lifestyle Medicine Laboratory, at the Department of Physical Education and Sport Science of Trikala, in Thessaly, Greece.
Before the initiation of the study, subjects will complete a series of questionnaires and measurements related to overall health. Subjects will be connected to a portable EEG/EOG system (HST-mit-tablet, Somomedics AG, Randersacker, Germany) for staging sleep architecture. Before and after each condition, subjects will complete a relaxation sensation questionnaire (RSQ) for assessing the state of relaxation and perform 3 maximum handgrip attempts using the dominant hand for assessing the level of muscle strength. Measurements of vital signs such as heart rate and blood pressure will also be recorded with an automatic blood pressure monitor [OMRON Bronze Upper Arm Blood Pressure Monitor]. All the assessments will be conducted on a supine position prior to study initiation. The participants will be free to either sleep or stay awake during the whole intervention period. Furthermore, to ensure result validity and avoid familiarization effects, a random 25% sample of participants will be selected for an additional measurement to determine whether the findings will be influenced by familiarity with the laboratory environment.
Measuring Instruments Body Composition Body composition will be assessed using anthropometric measurements including BMI, and bioimpedance (Tanita DC-360 S, Serinth) under standard methodology.19
Questionnaires The following questionnaires will be administered using the interview method by experienced researchers. The Pittsburgh Sleep Quality Index (PSQI) will be used to assess sleep quality and the existence of any sleep abnormalities. The Short Form survey 36-item 36 quality of life questionnaire (SF-36) will be used to assess the quality of life. The Beck Depression Inventory (BDI) questionnaire will be used to assess depressive symptoms and signs. The Perceived Stress Scale (PSS) will be used to assess the level of stress. Finally, the Relaxation State Questionnaire (RSQ) will be used to assess state of relaxation.
Brain Activity / Sleep Architecture A portable sleep monitoring system will be used to assess sleep quality and quantity (Home Sleep Test, Somnomedics, GmbH, Germany). The system records EEG, EOG, and EMG signals overnight. EEG data will analyzed in 30-second epochs using SomnoMed-ics PSG analysis software (Domino panel ver. 3.0.0.8) with manual editing. Analysis of the sleep study will be reported as followed: Total Sleep Time (total amount of sleep time scored during the total recording time); Sleep Efficiency (Total sleep time/Time in bed); Sustained Sleep Efficiency (Total sleep time/(Time in bed - Sleep laten-cy stage 2); Sleep Latency (the period of time it takes for a person to fall asleep after they have gone to bed and tried to initiate sleep); Sleep Latency N1 (the period of time between wakefulness and when sleep begins); Sleep Latency N2 (the period of time between time in bed and sleep onset stage 2); REM Latency (the amount of time elapsed between the onset of sleep to the first REM stage); Wakes (the number of times an individual wakes up during the sleep period or transitions to full wakefulness after sleep onset).
Handgrip strength assessment The handgrip test will be used for the assessment of maximum isometric strength of the dominant hand and arm muscles (Marsden MG-4800 Hand Dynamometer) and used as a measurement of muscle tone alertness. Reduction of muscle strength after the intervention, will be assessed as reduction of muscle tone.
Statistical Analysis The statistical analysis will be performed using IBM SPSS Statistics version 29 (SPSS Inc., Chicago, U.S.A.) An independent samples T-test will be used to examine differences in baseline characteristics and questionnaires between male and female subjects. A General Linear Model (GLM) Repeated Measures ANOVA will be used to assess changes in all parameters among the 4 different conditions. Additionally, a General Linear Model (GLM) Repeated Measures ANOVA will be used to assess changes in all sleep parameters among the 4 different conditions between good and poor sleepers. A Regression Linear Model will be applied to evaluate the relationship between EEG parameters and the weight of the blankets used. Statistical significance will be set at p≤0.05. Data are presented as mean ± standard deviation (SD), unless otherwise specified. A Bonferroni post-hoc test will be performed to assess individual differences. To assess normality, the Shapiro-Wilk test will be used alongside graphical representations, including the Normal Q-Q plot, Detrended Normal Q-Q plot, and Box Plot. The significance level will be set at 5%. Beyond significance testing (p-value), the effect size will be also considered to evaluate the magnitude of the effect.
Power Analysis Sample size calculations have been conducted using G*Power 3.1. The post-hoc "GLM": Repeated measures, within factors" method has been used to calculate the power analysis. The resulting minimum required sample size to achieve 85% power will be 14 participants for 2-sided group-1 and group-2 errors 5% [(Effect size 0.60, Critical F 4.10, Ndf 2, Ddf 10, Power (1-β err pob) = 0.86 (86% power)].
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20 participants in 4 patient groups
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