Search Results

Purpose: Wearable physical activity monitors present new ethical considerations for researchers and research ethics boards. Best practice guidelines are needed for research involving wearable monitors and should consider how these devices may impact participants outside of the research context. This study examines the perceptions of university students who wore activity monitors for research purposes in order to inform such guidelines. Methods: Focus groups were held with university students who wore digital self-tracking devices for a study examining sleep and physical activity. Questions focused on motivations to wear a physical activity monitor for research, understandings of how personal digital data generated by self-tracking devices are used and accessed, and perceptions of privacy. Results: 83% of students trusted the research process and were motivated to contribute to scientific knowledge by wearing a digital tracking device. Most (83%) understood how their data were used and accessed for research purposes, but 79% were less clear on how data might be accessed and used by third parties. 79% of participants also agreed that different data carries different social and personal implications and thus should not be treated the same by researchers. Conclusions: Protocols for research involving wearable monitors should include briefing/debriefing sessions to clarify data privacy, storage, and use issues. Researchers should also consider how wearing these devices might prompt unexpected emotional and other responses and the social implications of use for participants. The concept of privacy requires further exploration in the context of digital data collection using commercial devices.

Purpose: To examine the efficacy of intermittent sequential pneumatic compression (ISPC) on exercise recovery and subsequent performance, when implemented between a 20-min cycling bout (simulated scratch race) and a 4-min cycling test (simulated individual pursuit), as experienced during an Omnium track cycling competition. Methods: Twenty-one (13 male and 8 female, mean [SD]: age = 36 [14] y) trained cyclists completed a familiarization trial followed by 2 experimental trials in a counterbalanced, cross-over design. Participants performed a fixed-intensity 20-min cycling bout on a Wattbike cycle ergometer, followed by a 30-min recovery period where ISPC recovery boots or passive recovery was implemented. At the conclusion of the recovery period, participants performed a 4-min maximal cycling bout (4-min time trial [TT]). Average power (watts) for the 4-min TT, blood lactate concentration, and perceived total quality recovery (TQR) during the recovery period were used to examine the influence of ISPC. Results: There were no significant differences between trials for the 4-min TT (P = .08), with the effect deemed to be trivial (d = −0.08). There was an unclear effect (d [±90% confidence interval] = 0.26 [±0.78], P = .57) for ISPC vs passive recovery in the clearance of blood lactate during the recovery period. There was a small but not significant difference for perceived TQR in favor of ISPC (d [±90% confidence interval] = 0.27 [±0.27], P = .07). Conclusion: There was little additional benefit associated with the use of ISPC to enhance recovery and subsequent performance when used during the recovery period between 2 events in a simulated Omnium track cycling competition.

Purpose: Information from the Pittsburgh Sleep Quality Index (PSQI) and Athlete Sleep Behavior Questionnaire (ASBQ) provide the ability to identify the sleep disturbances experienced by athletes and their associated athlete-specific challenges that cause these disturbances. However, determining the appropriate support strategy to optimize the sleep habits and characteristics of large groups of athletes can be time-consuming and resource-intensive. The purpose of this study was to characterize the sleep profiles of elite athletes to optimize sleep-support strategies and present a novel R package, AthSlpBehaviouR, to aid practitioners with athlete sleep monitoring and support efforts. Methods: PSQI and ASBQ data were collected from a cohort of 412 elite athletes across 27 sports through an electronic survey. A k-means cluster analysis was employed to characterize the unique sleep-characteristic typologies based on PSQI and ASBQ component scores. Results: Three unique clusters were identified and qualitatively labeled based on the z scores of the PSQI components and ASBQ components: cluster 1, “high-priority; poor overall sleep characteristics + behavioral-focused support”; cluster 2, “medium-priority, sleep disturbances + routine/environment-focused support”; and cluster 3, “low-priority; acceptable sleep characteristics + general support.” Conclusions: The findings of this study highlight the practical utility of an unsupervised learning approach to perform clustering on questionnaire data to inform athlete sleep-support recommendations. Practitioners can consider using the AthSlpBehaviouR package to adopt a similar approach in athlete sleep screening and support provision.

Recent research has reported performance improvements after chronic NaHCO₃ ingestion in conjunction with high-intensity interval training (HIT) in moderately trained athletes. The purpose of the current study was to determine the effects of altering plasma H⁺ concentration during HIT through NaHCO₃ ingestion over 4 wk (2 HIT sessions/wk) in 12 Australian representative rowers (M ± SD; age 22 ± 3 yr, mass 76.4 ± 4.2 kg, VO_2peak 65.50 ± 2.74 ml · kg⁻¹ · min⁻¹). Baseline testing included a 2,000-m time trial and an incremental exercise test. After baseline testing, rowers were allocated to either a chronic NaHCO₃ (ALK) or placebo (PLA) group. Starting 90 min before each HIT session, subjects ingested a 0.3-g/kg body mass dose of NaHCO₃ or a placebo substance. Fingertip blood samples were taken throughout the study to analyze bicarbonate and pH levels. The ALK group did not produce any additional improvements in 2,000-m rowing performance time compared with PLA (p > .05). Magnitude-based inferential analysis indicated an unclear or trivial effect on 2,000-m power, 2,000-m time, peak power output, and power at 4 mmol/L lactate threshold in the ALK group compared with the PLA group. Although there was no difference between groups, during the study there was a significant mean (± SD) 2,000-m power improvement in both the ALK and PLA groups of 17.8 ± 14.5 and 15.2 ± 18.3 W, respectively. In conclusion, despite overall improvements in rowing performance after 4 wk of HIT, the addition of chronic NaHCO₃ supplementation during the training period did not significantly enhance performance further.

Beta-alanine may benefit short-duration, high-intensity exercise performance. The aim of this randomized double-blind placebo-controlled study was to examine the effects of beta-alanine supplementation on aspects of muscular performance in highly trained cyclists. Sixteen highly trained cyclists (mean ± SD; age = 24 ± 7 yr; mass = 70 ± 7kg; VO_2max = 67 ± 4ml·kg⁻¹·min–¹) supplemented with either beta-alanine (n = 8, 65 mg·kg⁻¹BM) or a placebo (n = 8; dextrose monohydrate) over 4 weeks. Pre- and postsupplementation cyclists performed a 4-minute maximal cycling test to measure average power and 30 reciprocal maximal isokinetic knee contractions at a fixed angular velocity of 180°·sec⁻¹ to measure average power/repetition, total work done (TWD), and fatigue index (%). Blood pH, lactate (La⁻) and bicarbonate (HCO₃ ^-) concentrations were measured preand postisokinetic testing at baseline and following the supplementation period. Beta-alanine supplementation was 44% likely to increase average power output during the 4-minute cycling time trial when compared with the placebo, although this was not statistically significant (p = .25). Isokinetic average power/repetition was significantly increased post beta-alanine supplementation compared with placebo (beta-alanine: 6.8 ± 9.9W, placebo: –4.3 ± 9.5 W, p = .04, 85% likely benefit), while fatigue index was significantly reduced (p = .03, 95% likely benefit). TWD was 89% likely to be improved following beta-alanine supplementation; however, this was not statistically significant (p = .09). There were no significant differences in blood pH, lactate, and HCO₃ ⁻ between groups (p > .05). Four weeks of beta-alanine supplementation resulted in worthwhile changes in time-trial performance and short-duration muscular force production in highly trained cyclists.