Impact of Weighted Blankets on Sleep Quality

Overview

Weighted blankets have been used to improve sleep quality in children with neurodevelopmental disorders. It is not known, however, whether weighted blankets can improve overnight sleep in healthy adults and those with poor sleep quality and what is the optimal weight of those blankets for achieving the best results. AIMS: The purpose of the present study is to investigate the effect of 4 different weights of weighted blankets on sleep in participants with low sleep quality.

Study Design Subjects will be randomly assigned into 4 conditions each one week apart: 1) The Control condition (CON), where subjects will be covered with their usual home blanket, without any extra weight; 2) The 7 kg condition, where subjects will be covered with a blanket weighing 7 kg; 3) The 9 kg condition, where subjects will be covered with a blanket weighing 9 kg; 4) The 14 kg condition, where subjects will be covered with a blanket weighing 14 kg. All measurements will be conducted at the participant's home, at the same time of the day, under the conditions to which each individual is accustomed in their daily routine for sleeping, including their typical room temperature, lighting, and background noise. Procedure All measurements will be conducted in participants' homes with data analysis performed at the Lifestyle Medicine Laboratory, 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, SOMNOmedics AG, Randersacker, Germany) for staging sleep architecture. Additionally, two temperature thermistors (iButton) will be placed on each participant: one on the pectoralis major muscle and the quadriceps muscle to measure skin temperature. A third thermistor will be placed on the bedside table to record ambient room/environment temperature throughout the night. Measurements of vital signs such as heart rate and blood pressure also will be recorded with an automotive blood pressure monitor \[OMRON Bronze Upper Arm Blood Pressure Monitor, Easy One-Touch Operation\]. All participants will be free to sleep in their preferred position at their own preferred time, with no restrictions on their sleeping posture during the intervention however, they will not share their bed with their partner the night of the investigation. Data Analysis Data analysis includes overnight (at least 8 hours) PSG-EEG recordings and thermistor temperature data. Body Composition Body composition will be assessed using anthropometric measurements including BMI, and bioimpedance (Tanita DC-360 S, Serinth) under standard methodology. 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. 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 be analyzed in 30-second epochs using SOMNOmedics PSG analysis software (Domino panel ver. 3.0.0.8) with manual editing. The HomeSleepTest REM+ device will be used for PSG, with electrodes placed according to the 10/20 system on key brain regions: Fp1 (left) and M1 for EEG, and near the eyes for EOG. This setup ensures accurate monitoring of sleep architecture and high-fidelity recordings of brain activity and eye movements. 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). Measurement of Skin and Environmental Temperature Skin temperature will be measured at 1-minute intervals for an entire night's recording (at least 8 hours) using wireless iButton sensors (DS1921H, Maxim/Dallas Semiconductor Corp., USA). The iButtons will be programmed before their application on the skin, as outlined by the manufacturer. The devices will be placed at two body sites: the pectoralis major muscle and the quadriceps muscle. Additionally, a separate iButton will be positioned in the room where the measurement took place to record the environmental temperature. Skin temperature will be calculated using an equation based on the average temperature recorded at the two body sites during the study procedure. 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. Furthermore, 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. Additionally, a General Linear Model (GLM) Repeated Measures ANOVA will be applied to assess changes in iButton sensors, recorded skin and environmental temperature across the 4 different conditions. 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 were conducted using G\*Power 3.1. The a prior "GLM": Repeated measures, within factors" method was used to calculate the power analysis. The resulting minimum required sample size to achieve 85% power was 14 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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