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
Shona L. Halson, Renee N. Appaneal, Marijke Welvaert, Nirav Maniar, and Michael K. Drew
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.
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.
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
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.
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
Michelle Biggins, Helen Purtill, Peter Fowler, Kieran O’Sullivan, and Roisin Cahalan
, such as sleep extension, napping, and sleep hygiene have been advocated to support athletes who are required to travel internationally for their sport. 4 However, knowledge around the management of sleep disturbances associated with long-haul travel is largely based on nonathletic cohorts, with a lack
Javier Raya-González, Aaron T. Scanlan, María Soto-Célix, Alejandro Rodríguez-Fernández, and Daniel Castillo
was administered in the morning following testing. In this regard, a higher ( P < .05) prevalence of insomnia and urine output was apparent after caffeine ingestion compared with the placebo, with no significant changes in other side effects measured. The sleep disturbances with caffeine are likely
Asaduzzaman Khan and Nicola W. Burton
The time spent by adolescents in electronic screen-based activities has been associated with obesity and other adverse health outcomes; however, little is known about screen-based behaviors in Asian adolescents. The purpose of this study was to describe the prevalence, patterns, and correlates of recreational screen-based behaviors among adolescents in Bangladesh.
A total of 758 students (52% girls), aged 13 to 16 years, from 8 secondary schools of Dhaka city, Bangladesh, completed a survey in which the Adolescent Sedentary Activity Questionnaire was used to collect information on screen time. Total screen time was categorized as ≤2 h/day (low) or >2 h/day (high).
Approximately 79% of the adolescents had high recreational screen time, with similar values for boys (78%) and girls (80%). Median reported recreational screen time was 4.0 h/day; boys had longer times (4.3 h/day) than girls (3.6 h/day). Multivariable analyses showed that high screen time was more common among boys than girls and was positively associated with commuting to school by car, consumption of fast food ≥3 times/week, having sleep disturbance, and high family income.
This study identified high rates of recreational screen time among urban adolescents in Bangladesh and specific correlates of prolonged screen time; the results underscore the need to develop pragmatic strategies to reduce sedentariness among adolescents in Bangladesh.
Carter Hughes, Kevin Hunt, Brian Cox, John Raybon, and Rebecca M. Lopez
onset latency, sleep efficiency, and WASO). Secondary outcomes: overnight melatonin production levels, health-related quality of life measured with CHQ-50, parent report. Primary outcomes: ImPACT battery, sleep quantity, and sleep disturbances measured by the PCSS. Primary outcomes: PedsQL MFS (general