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      Effects of dynamic bedroom lighting on measures of sleep and circadian rest-activity rhythm in inpatients with major depressive disorder

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          Abstract

          Bright light therapy is an effective treatment option for seasonal and non-seasonal affective disorders. However up to now, no study has investigated effects of dynamic bedroom lighting in hospitalized patients with major depression. A bedroom lighting system, which automatically delivered artificial dawn and dusk and blue-depleted nighttime lighting (DD-N lighting) was installed in a psychiatric ward. Patients with moderate to severe depression were randomly assigned to stay in bedrooms with the new lighting or standard lighting system. Patients wore wrist actimeters during the first two treatment weeks. Additionally, hospitalization duration and daily psychotropic medication were retrieved from patients’ medical charts. Data from thirty patients, recorded over a period of two weeks, were analyzed. Patients under DD-N lighting generally woke up earlier (+ 20 min), slept longer (week 1: + 11 min; week 2: + 27 min) and showed higher sleep efficiency (+ 2.4%) and shorter periods of nighttime awakenings (− 15 min). In the second treatment week, patients started sleep and the most active 10-h period earlier (− 33 min and − 64 min, respectively). This pilot study gives first evidence that depressed patients’ sleep and circadian rest/activity system may benefit from bedroom lighting when starting inpatient treatment.

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          G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences

          G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of the t, F, and chi2 test families. In addition, it includes power analyses for z tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free.
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            Automatic sleep/wake identification from wrist activity.

            The purpose of this study was to develop and validate automatic scoring methods to distinguish sleep from wakefulness based on wrist activity. Forty-one subjects (18 normals and 23 with sleep or psychiatric disorders) wore a wrist actigraph during overnight polysomnography. In a randomly selected subsample of 20 subjects, candidate sleep/wake prediction algorithms were iteratively optimized against standard sleep/wake scores. The optimal algorithms obtained for various data collection epoch lengths were then prospectively tested on the remaining 21 subjects. The final algorithms correctly distinguished sleep from wakefulness approximately 88% of the time. Actigraphic sleep percentage and sleep latency estimates correlated 0.82 and 0.90, respectively, with corresponding parameters scored from the polysomnogram (p < 0.0001). Automatic scoring of wrist activity provides valuable information about sleep and wakefulness that could be useful in both clinical and research applications.
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              Depression in sleep disturbance: A review on a bidirectional relationship, mechanisms and treatment

              Abstract Sleep disturbance is the most prominent symptom in depressive patients and was formerly regarded as a main secondary manifestation of depression. However, many longitudinal studies have identified insomnia as an independent risk factor for the development of emerging or recurrent depression among young, middle‐aged and older adults. This bidirectional association between sleep disturbance and depression has created a new perspective that sleep problems are no longer an epiphenomenon of depression but a predictive prodromal symptom. In this review, we highlight the treatment of sleep disturbance before, during and after depression, which probably plays an important role in improving outcomes and preventing the recurrence of depression. In clinical practice, pharmacological therapies, including hypnotics and antidepressants, and non‐pharmacological therapies are typically applied. A better understanding of the pathophysiological mechanisms between sleep disturbance and depression can help psychiatrists better manage this comorbidity.
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                Author and article information

                Contributors
                markus.canazei@uibk.ac.at
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                12 April 2022
                12 April 2022
                2022
                : 12
                : 6137
                Affiliations
                [1 ]GRID grid.5771.4, ISNI 0000 0001 2151 8122, Department of Psychology, , University of Innsbruck, ; Innrain 52f, 6020 Innsbruck, Austria
                [2 ]GRID grid.423956.f, Research Department, , Bartenbach GmbH, ; Rinnerstrasse 14, 6071 Aldrans, Austria
                [3 ]Abteilung Psychiatrie und Psychotherapie A, Regional Psychiatric Hospital, 6060 Hall in Tirol, Austria
                Article
                10161
                10.1038/s41598-022-10161-8
                9005730
                35414714
                406e5516-c5e2-4a18-b2a3-fd185c776d35
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 4 October 2021
                : 1 April 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100004955, Österreichische Forschungsförderungsgesellschaft;
                Award ID: 850747
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                psychology,human behaviour
                Uncategorized
                psychology, human behaviour

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