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Shakiba Oftadeh-Moghadam and Paul Gorczynski

, Pacific Islands, and South Africa 990 (941:49) M  = 25.0 SD  = 4.0 Distress: Distress Screener (based on the 4DSQ) Anxiety/depression: 12-item GHQ-12 Sleep disturbance: PROMIS (short form) Eating disorders: The Eating Disorder Screen for primary Care Adverse alcohol use: Three-item AUDIT-C Distress: 17

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Shona L. Halson, Renee N. Appaneal, Marijke Welvaert, Nirav Maniar, and Michael K. Drew

quality and a global score as well as subcomponents of sleep quality are generated. The 7 subcomponents of the PSQI were calculated and represent: (1) subjective sleep quality, (2) sleep latency, (3) sleep duration, (4) sleep efficiency, (5) sleep disturbances, (6) use of sleep medication, and (7) daytime

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Andrea Stracciolini, Caitlin M. McCracken, William P. Meehan III, and Matthew D. Milewski

Purpose: To study mental health, sleep duration, and daytime sleepiness in young athletes. Methods: A cross-sectional questionnaire study was conducted. The main outcome measures included sleep duration and daytime sleepiness. Results: Study participants included 756 athletes with a mean age of 13.5 years. A total of 39% (n = 296/756) reported not meeting current sleep recommendations for age. Athletes >12 years and with a self-reported anxiety and/or depression history were less likely to meet sleep recommendations and showed higher daytime sleepiness (adjusted odds ratio [aOR] = 1.29, 95% confidence interval [CI] [1.2, 1.4], β [SE] = 3.06 [0.74], respectively). Athletes with goal-oriented reasons for playing versus enjoyment (52% vs. 35%, aOR = 1.70, 95% CI [1.12, 2.58]) were less likely to meet sleep recommendations. Night time internet access and weeknight homework hours were negatively associated with sleep recommendations (aOR = 1.68, 95% CI [1.68, 2.47] and aOR = 3.11, 95% CI [1.82, 5.3]) and positively associated with daytime sleepiness (β [SE] = 1.44 [0.45] and 2.28 [0.59]). Conclusions: Many young athletes are not meeting sleep recommendations. Associated factors include mental health, reasons for play, internet access, and homework demand.

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Daniel Liebzeit, Cynthia Phelan, Chooza Moon, Roger Brown, and Lisa Bratzke

The purpose of this investigation is to examine differences in rest-activity patterns and sleep characteristics in older adults with heart failure (HF) and healthy older adults. The sample included older adults with HF (n = 20) and a reference group of healthy older adults (n = 20). Traditional cosinor analysis was used to assess three parameters of rest–activity from wrist actigraphy data: amplitude (range of activity), mesor (mean activity), and acrophase (time of peak activity). Traditional sleep characteristics were also determined from actigraphy data: total sleep time (TST), sleep latency (SL), sleep efficiency (SE), and wake after sleep onset (WASO). The HF group demonstrated significantly lower mesor and amplitude than the reference group (p < .01). The HF group had significantly greater TST (p < .01), but the groups had similar SE, SL, and WASO. Despite similar sleep characteristics to healthy older adults, overall rest–activity patterns were significantly dampened in those with HF.

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Haresh T. Suppiah, Paul B. Gastin, and Matthew W. Driller

with a more nuanced appreciation of the potential sleep disturbances faced by athletes, as well as the athlete-specific challenges that may cause these disturbances. While studies have highlighted the prevalence of poor sleep duration and quality, and suboptimal sleep hygiene behaviors in athletes

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Jessica Murphy, Christopher Gladney, and Philip Sullivan

latency), the number of sleep disturbances throughout the night, and how restored one feels upon awakening ( Harvey et al., 2008 ; Ohayon et al., 2017 ; Pilcher, Ginter, & Sadowsky, 1997 ). Sleep disturbances contribute most to sleep quality scores and are closely linked with severity of self

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Amélie Apinis-Deshaies, Maxime Trempe, and Jonathan Tremblay

lead to sleep disturbances. This was done by correlating sleep quantity and quality with factors such as the external TL, the traveling distance, the location (home vs away), the timing of the matches (night vs day), and the match result (win vs loss). Methods Subjects Fifty male American Hockey League

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Jie Yu, Cindy H.P. Sit, Angus Burnett, Catherine M. Capio, Amy S.C. Ha, and Wendy Y.J. Huang

The purpose of this study was to examine the effects of fundamental movement skills (FMS) training on FMS proficiency, self-perceived physical competence (SPC), physical activity (PA), and sleep disturbance in children with developmental coordination disorder (DCD) compared with children with typical development (TD). A total of 84 children were allocated into either experimental group (DCD[exp], TD[exp]) who received 6 weeks of FMS training or control groups (DCD[con], TD[con]). FMS were assessed using the Test of Gross Motor Development-2, whereas PA was monitored using accelerometers. SPC and sleep disturbance were evaluated using questionnaires. Results showed that the DCD[exp] group had significantly higher scores in FMS and SPC compared with the DCD[con] group at posttest. The DCD[exp] group scored lower in sleep disturbance at follow-up when compared with posttest. It is suggested that short-term FMS training is effective in improving FMS and SPC and reducing sleep disturbances for children with DCD.

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QinLong Li, Charles J. Steward, Tom Cullen, Kaixuan Che, and Yue Zhou

psychophysiological benefits of HRV biofeedback may in turn reduce SOL 11 and scores of sleep disturbance. 12 To date, there is very limited research using this intervention in athletic populations. During the 2022 Beijing Winter Olympics, many athletes will be under high levels of physiological and psychological

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Johnpaul Caia, Shona L. Halson, Patrick M. Holmberg, and Vincent G. Kelly

exacerbated sleep disturbances on the night of competition, all correlations were nonsignificant suggesting that other confounders (eg, exposure to floodlights, postmatch alcohol consumption, sleep environment) may also cause sleep disturbance, not just caffeine consumption. These findings add to the scant