Adolescent sleep patterns are often measured with self-report ( Lewandowski, Toliver-Sokol, & Palermo, 2011 ) or actigraphy ( Galland et al., 2018 ). Although self-report is easier to administer, lower in cost, and requires less technical expertise than actigraphy, it is often affected by social
Robert J. Brychta, Vaka Rögnvaldsdóttir, Sigríður L. Guðmundsdóttir, Rúna Stefánsdóttir, Soffia M. Hrafnkelsdóttir, Sunna Gestsdóttir, Sigurbjörn A. Arngrímsson, Kong Y. Chen and Erlingur Jóhannsson
Allison Naber, Whitney Lucas Molitor, Andy Farriell, Kara Honius and Brooke Poppe
( Koltyn, 2002 ; Mathesom et al., 2013 ). One method that may be beneficial in altering lifestyle habits and health behaviors is through the utilization of wearable technology. When measuring activity levels, this technology is referred to as actigraphy, which is used to objectively measure physical
Catherine R. Marinac, Mirja Quante, Sara Mariani, Jia Weng, Susan Redline, Elizabeth M. Cespedes Feliciano, J. Aaron Hipp, Daniel Wang, Emily R. Kaplan, Peter James and Jonathan A. Mitchell
within an individual. We, therefore, tested if the timing of meals, light exposure, physical activity, and sleep were associated with body mass index (BMI) in a sample of healthy adults who recorded the timing of behaviors over multiple days using a novel smartphone application and actigraphy. We first
Jacopo A. Vitale, Giuseppe Banfi, Andrea Galbiati, Luigi Ferini-Strambi and Antonio La Torre
present study was to evaluate actigraphy-based sleep behavior and perceived recovery before and after a night game in top-level volleyball athletes. We hypothesized that we would detect lower sleep quality and perceived recovery both in the night immediately precompetition and postcompetition compared
Andressa Silva, Fernanda V. Narciso, Igor Soalheiro, Fernanda Viegas, Luísa S.N. Freitas, Adriano Lima, Bruno A. Leite, Haroldo C. Aleixo, Rob Duffield and Marco T. de Mello
and importance of the research. The procedures were started after direction by the team. Methodology Actigraphy In the present study, the players’ sleep behavior was monitored using an Actiwatch 2 wrist activity monitor actigraph (Philips Respironics, Andover, MA), which continuously measured the
Barbara Resnick, Elizabeth Galik, Marie Boltz, Erin Vigne, Sarah Holmes, Steven Fix and Shijun Zhu
engage in a moderate or vigorous level of activity ( Fjeldsoe, Winkler, Marshall, Eakin, & Reeves, 2013 ; Gennuso, Matthews, & Colbert, 2015 ). Objective measures with actigraphy, which is a noninvasive method to monitor activity and rest, are also challenging, as age-appropriate accelerometer cut
Benita J. Lalor, Shona L. Halson, Jacqueline Tran, Justin G. Kemp and Stuart J. Cormack
characteristics should be evaluated in combination with habitual sleep values from an appropriate baseline period. Critically, due to the mismatch between subjective and objective measures of sleep quality in both phases, actigraphy should be used to evaluate sleep in athlete populations. The shorter sleep
Ryan S. Falck, Glenn J. Landry, Keith Brazendale and Teresa Liu-Ambrose
Evidence suggests sleep and physical activity (PA) are associated with each other and dementia risk. Thus, identifying reliable methods to quantify sleep and PA concurrently in older adults is important. The MotionWatch 8© (MW8) wrist-worn actigraph provides reliable estimates of sleep quality via 14 days of measurement; however, the number of days needed to monitor PA by MW8 for reliable estimates is unknown. Thus, we investigated the number of days of MW8 wear required to assess PA in older adults. Ninety-five adults aged > 55 years wore MW8 for ≥ 14 days. Spearman-Brown analyses indicated the number of monitoring days needed for an ICC = 0.95 was 6–7 days for sedentary activity, 9–10 days for light activity, and 7–8 days for moderate-to-vigorous PA. These results indicate 14 days of MW8 monitoring provides reliable estimates for both sleep and PA. Thus, MW8 is ideal for future investigations requiring concurrent measures of both sleep quality and PA.
Dana L. Wolff-Hughes, Eugene C. Fitzhugh, David R. Bassett and James R. Churilla
Accelerometer-derived total activity count is a measure of total physical activity (PA) volume. The purpose of this study was to develop age- and gender-specific percentiles for daily total activity counts (TAC), minutes of moderate-to-vigorous physical activity (MVPA), and minutes of light physical activity (LPA) in U.S. adults.
Waist-worn accelerometer data from the 2003-2006 National Health and Nutrition Examination Survey were used for this analysis. The sample included adults >20 years with >10 hours accelerometer wear time on >4 days (N = 6093). MVPA and LPA were defined as the number of 1-minute epochs with counts >2020 and 100 to 2019, respectively. TAC represented the activity counts acquired daily. TAC, MVPA, and LPA were averaged across valid days to produce a daily mean.
Males in the 50th percentile accumulated 288 140 TAC/day, with 357 and 22 minutes/day spent in LPA and MVPA, respectively. The median for females was 235 741 TAC/day, with 349 and 12 minutes/day spent in LPA and MVPA, respectively.
Population-referenced TAC percentiles reflect the total volume of PA, expressed relative to other adults. This is a different approach to accelerometer data reduction that complements the current method of looking at time spent in intensity subcategories.
Benjamin G. Serpell, Barry G. Horgan, Carmen M.E. Colomer, Byron Field, Shona L. Halson and Christian J. Cook
Approval to conduct this research was granted by the University of Canberra and Australian Institute of Sport Human Research Ethics Committees. All participants voluntarily gave informed consent to participate. Sleep Monitoring Throughout the monitoring period, all participants wore a wrist actigraphy