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{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,8,3]],"date-time":"2023-08-03T04:30:09Z","timestamp":1691037009368},"reference-count":52,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,8,2]],"date-time":"2023-08-02T00:00:00Z","timestamp":1690934400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002428","name":"Austrian Science Fund","doi-asserted-by":"publisher","award":["P32028"]},{"name":"Centre for Cognitive Neuroscience Salzburg"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Life"],"abstract":"<jats:p>Due to the high demands of competitive sports, the sleep architecture of adolescent athletes may be influenced by their regular training. To date, there is no clear evidence on how training characteristics (intensity, time of day, number of sessions) influence sleep quality and quantity. 53 male soccer players (M = 14.36 years, SD = 0.55) of Austrian U15 (n = 45) and U16 elite teams (n = 8) were tested on at least three consecutive days following their habitual training schedules. Participants completed daily sleep protocols (7 a.m., 8 p.m.) and questionnaires assessing sleep quality (PSQI), chronotype (D-MEQ), competition anxiety (WAI-T), and stress\/recovery (RESTQ). Electrocardiography (ECG) and actigraphy devices measured sleep. Using sleep protocols and an ECG-based multi-resolution convolutional neural network (MCNN), we found that higher training intensity leads to more wake time, that later training causes longer sleep duration, and that one training session per day was most advantageous for sleep quality. In addition, somatic complaints assessed by the WAI-T negatively affected adolescent athletes\u2019 sleep. Individual training loads and longer recovery times after late training sessions during the day should be considered in training schedules, especially for adolescent athletes. MCNN modeling based on ECG data seems promising for efficient sleep analysis in athletes.<\/jats:p>","DOI":"10.3390\/life13081679","type":"journal-article","created":{"date-parts":[[2023,8,2]],"date-time":"2023-08-02T14:57:33Z","timestamp":1690988253000},"page":"1679","source":"Crossref","is-referenced-by-count":0,"title":["Soccer, Sleep, Repeat: Effects of Training Characteristics on Sleep Quantity and Sleep Architecture"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"http:\/\/orcid.org\/0000-0001-6484-1579","authenticated-orcid":false,"given":"Patricia","family":"Frytz","sequence":"first","affiliation":[{"name":"Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, University of Salzburg, 5020 Salzburg, Austria"},{"name":"Centre for Cognitive Neuroscience Salzburg (CCNS), University of Salzburg, 5020 Salzburg, Austria"},{"name":"Sport Psychology, Faculty of Sport Science, Leipzig University, 04109 Leipzig, Germany"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-7977-8557","authenticated-orcid":false,"given":"Dominik P. J.","family":"Heib","sequence":"additional","affiliation":[{"name":"Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, University of Salzburg, 5020 Salzburg, Austria"},{"name":"Centre for Cognitive Neuroscience Salzburg (CCNS), University of Salzburg, 5020 Salzburg, Austria"},{"name":"Institut Proschlaf, 5020 Salzburg, Austria"}]},{"given":"Kerstin","family":"Hoedlmoser","sequence":"additional","affiliation":[{"name":"Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, University of Salzburg, 5020 Salzburg, Austria"},{"name":"Centre for Cognitive Neuroscience Salzburg (CCNS), University of Salzburg, 5020 Salzburg, Austria"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,2]]},"reference":[{"key":"ref_1","unstructured":"Iber, C., Ancoli-Israel, S., Chesson, A., and Quan, S.F. (2007). The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Speci
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