Self-tracking via smartphone app: Potential tool for athletes’ recovery self-management?

Abstract

Self-tracking technologies are possible approaches to support recovery self-management activities for athletes. These may have become even more appealing due to stay-at-home restrictions as part of the 2020 pandemic regulations. This study examined user behaviour of smartphone and wearable technologies among 217 athletes (29% women, M age = 26.9 ± 7 years). The online survey comprised demographic questions and standardised questionnaires to assess usage of technologies, sleep quality (Pittsburgh Sleep Quality Index), daytime sleepiness (Epworth Sleepiness Scale), attitudes about sleep (Dysfunctional Beliefs and Attitudes about Sleep Scale), bedtime procrastination (Bedtime Procrastination Scale), and self-control (Brief Self-Control Scale). Fitness apps (46.5%) were more popular than sleep apps (15.7%) followed by nutrition apps (12%). The correlation between sleep apps and the other two apps indicate that non-users of sleep apps are probably also non-users of fitness or nutrition apps. Wearables were more frequently used to track fitness activities (36.9%) than sleep (17.5%). Considering sex, type of sport, competition participation, and training volume, no remarkable characteristics among users versus non-users of sleep apps were identified. There were also no significant differences among sleep indices between sleep app users and non-users. However, self-control was highest among sleep app users compared to non-users (d = 0.58). Despite 34.1% being identified as poor sleepers, behavioural sleeping patterns were within normal range. The results imply that athletes are not as attracted to self-tracking technologies as expected, which makes them less vulnerable to unsubstantiated feedback and inappropriate interventions by those tools. This serves as a starting point to explore the potential of self-tracking ambulatory assessment for physical activity and sleep behaviour of athletes in the post-pandemic era.

Effects of sleep self-monitoring via app on subjective sleep markers in student athletes

“…It was assumed that athletes might have gained more interest in analysing and optimising their sleep during that period. However, the present findings do not support this assumption, which is also in line with another survey [19]. Moreover, the sample of student athletes may not be representative for youth athletes, among whom external factors (e.g.…”

“…At the same time, potential beneficial effects that were presumed through constructive sleep self-monitoring [ 7 ] were also not detected. In conclusion, it seems that student athletes are not as vulnerable and suggestable to sleep self-tracking as assumed [ 19 ]. Nevertheless, practitioners and athletes should draw on standardised sleep measures to monitor training and sleep [ 13 ], and address adequate sleep hygiene behaviour in order to support performance enhancement and health management.…”

A Narrative Review of the Link between Sport and Technology

“…In this way, by monitoring training loads, the likelihood of injury recurrence is greatly reduced [28,29]. Recovery activities can be self-managed, with specific indicators: sleep quality, daytime sleepiness, attitudes about sleep, and self-control [30].…”