Relationship between foot strike pattern,running speed,and footwear condition in recreational distance runners

Compared to competitive runners, recreational runners appear to be more prone to injuries, which have been associated with foot strike patterns. Surprisingly, only few studies had examined the foot strike patterns outside laboratories. Therefore, this study compared the foot strike patterns in recreational runners at outdoor tracks with previously reported data. We also investigated the relationship between foot strike pattern, speed, and footwear in this cohort. Among 434 recreational runners analysed, 89.6% of them landed with rearfoot strike (RFS). Only 6.9 and 3.5% landed with midfoot and forefoot, respectively. A significant shift towards non-RFS was observed in our cohort, when compared with previously reported data. When speed increased by 1 m/s, the odds of having forefoot strike and midfoot strike relative to RFS increased by 2.3 times and 2.6 times, respectively. Runners were 9.2 times more likely to run with a forefoot strike in minimalists compared to regular running shoes, although 70% of runners in minimalists continued to use a RFS. These findings suggest that foot strike pattern may differ across running conditions and runners should consider these factors in order to mitigate potential injury.     

A novel sleep optimisation programme to improve athletes’ well-being and performance

Objectives: To improve well-being and performance indicators in a group of Australian Football League (AFL) players via a six-week sleep optimisation programme. Design: Prospective intervention study following observations suggestive of reduced sleep and excessive daytime sleepiness in an AFL group. Methods: Athletes from the Adelaide Football Club were invited to participate if they had played AFL senior-level football for 1–5 years, or if they had excessive daytime sleepiness (Epworth Sleepiness Scale [ESS] >10), measured via ESS. An initial education session explained normal sleep needs, and how to achieve increased sleep duration and quality. Participants (n?=?25) received ongoing feedback on their sleep, and a mid-programme education and feedback session. Sleep duration, quality and related outcomes were measured during week one and at the conclusion of the six-week intervention period using sleep diaries, actigraphy, ESS, Pittsburgh Sleep Quality Index, Profile of Mood States, Training Distress Scale, Perceived Stress Scale and the Psychomotor Vigilance Task. Results: Sleep diaries demonstrated an increase in total sleep time of approximately 20?min (498.8?±?53.8 to 518.7?±?34.3; p?<?.05) and a 2% increase in sleep efficiency (p?<?0.05). There was a corresponding increase in vigour (p?<?0.001) and decrease in fatigue (p?<?0.05). Conclusions: Improvements in measures of sleep efficiency, fatigue and vigour indicate that a sleep optimisation programme may improve athletes’ well-being. More research is required into the effects of sleep optimisation on athletic performance.     

Exploring athletes’ perceptions of coach stress in elite sport environments

The present study aimed to extend research that has focused on the identification of stressors associated with coaching practice by systematically evaluating how such stressors effect athletes, and more broadly, the coach–athlete relationship. A total of 13 professional- and national-level athletes were interviewed to address the three study aims: how they detect when a coach is encountering stressors, how coach experiences of stress effects them as an athlete, and how effective the coach is when experiencing stress. Following content analysis, the data suggested athletes were able to detect when a coach was experiencing stress and this was typically via a variety of verbal and behavioural cues. Despite some positive effects of the coach experiencing stress, the majority were negative and varied across a range of personal influences on the athlete, and effects on the general coaching environment. It was also the broad view of the athletes that coaches were less effective when stressed, and this was reflected in performance expectations, perceptions of competence, and lack of awareness. The findings are discussed in relation to the existing theory and with reference to their implications for applied practice, future research, and development of the coach–athlete relationship.     

Performing under pressure: Exploring the psychological state underlying clutch performance in sport

Clutch performance is improved performance under pressure. However, little research has examined the psychological state experienced by athletes in these situations. Therefore, this study qualitatively examined the subjective experience underlying clutch performance across a range of sports (e.g., team, individual) and standards (Olympic to recreational athletes). Sixteen athletes (M_age = 27.08 years; SD = 6.48) took part in in-depth, semi-structured interviews primarily after an exceptional performance (M = 4.38 days later; SD = 3.14). Data were analysed inductively and thematically. Clutch states involved 12 characteristics, including heightened and deliberate concentration, intense effort, and heightened awareness, which distinguished the experience of clutch from other optimal psychological states such as flow. Other characteristics, such as perceptions of control, were also reported and supported previous experimental research on clutch. These findings present in-depth qualitative insights into the psychological state underlying clutch performance, and are discussed in relation to the existing literature on optimal psychological states in sport.     

Examining coaches’ perceptions of how their stress influences the coach–athlete relationship

This study extends recent coach stress research by evaluating how coaches perceive their stress experiences to affect athletes, and the broader coach–athlete relationship. A total of 12 coaches working across a range of team sports at the elite level took part in semi-structured interviews to investigate the 3 study aims: how they perceive athletes to detect signals of coach stress; how they perceive their stress experiences to affect athletes; and, how effective they perceive themselves to be when experiencing stress. Following content analysis, data suggested that coaches perceived athletes able to detect when they were experiencing stress typically via communication, behavioural, and stylistic cues. Although coaches perceived their stress to have some positive effects on athletes, the overwhelming effects were negative and affected “performance and development”, “psychological and emotional”, and “behavioural and interaction” factors. Coaches also perceived themselves to be less effective when stressed, and this was reflected in their perceptions of competence, self-awareness, and coaching quality. An impactful finding is that coaches are aware of how a range of stress responses are expressed by themselves, and to how they affect athletes, and their coaching quality. Altogether, findings support the emerging view that coach stress affects their own, and athlete performance.