The interplay between self-talk and body posture on physical performance: Analyzing a moderated serial multiple mediation model.

Prior research has shown that non-verbal behavior (e.g., overt head movements) can moderate the effects of positive and negative self-talk on physical performance. In the current studies, we aimed to extend existing research on self-talk by examining a different non-verbal behavior (i.e., body posture), as well as specifying some conditions under which body posture can interact with self-talk on physical performance from the Self-Validation Theory perspective. Most importantly, we proposed and tested a moderated serial multiple mediation model. In Studies 1 and 2, self-talk (i.e., positive vs. negative) and body posture (i.e., upright vs. slumped) were manipulated between participants. In Study 1, soccer players performed slalom and dribbling tests. In Study 2, athletes performed a push-up test. We hypothesized and found that positive (vs. negative) self-talk influenced physical performance to a greater extent for participants in the upright posture (i.e., validating) condition than for participants in the slumped posture (i.e., invalidating) condition. Furthermore, Study 3 was designed to analyze a moderated serial multiple mediation model. In this third study, self-talk was positive, body posture was manipulated, and the meaning of body posture was measured as a moderator. Results supported the proposed model, identifying the perceived validity of self-statements (i.e., the self-validation mechanism) and self-efficacy as serial mediators. That is, the meaning (i.e., validity-invalidity) moderated the effects of body posture on athletes' physical performance in a pull-up test, through the indirect effects of the perceived validity of self-statements and self-efficacy. Implications for self-talk research and application are discussed.

Validity of a Smartphone App Using Artificial Intelligence for the Real-Time Measurement of Barbell Velocity in the Bench Press Exercise.

ABSTRACT: Balsalobre-Fernández, C, Xu, J, Jarvis, P, Thompson, S, Tannion, K, and Bishop, C. Validity of a smartphone app using artificial intelligence for the real-time measurement of barbell velocity in the bench press exercise. J Strength Cond Res 37(12): e640-e645, 2023-The purpose of this study was to explore the validity and within-session reliability of the newly developed My Jump Lab application (app), which uses artificial intelligence techniques to monitor barbell velocity in real time. Twenty-seven sport science students performed 5 repetitions at 50 and 75% of their self-reported bench press 1 repetition maximum (1RM) during a single testing session, whereas barbell velocity was concurrently measured using the app (installed on an iPhone 12 Pro) and the GymAware linear position transducer (LPT). A very high correlation was observed between devices at each loading condition (50% 1RM: r = 0.90 [0.82-0.97]; 75% 1RM: r = 0.92 [0.86-0.98]). Results showed trivial differences between the app and LPT at both 50% 1RM (g = -0.06) and 75% 1RM (g = -0.12). Bland-Altman analysis showed a bias estimate of -0.010 m·s-1 and -0.026 m·s-1 for the 50 and 75% 1RM, respectively. Finally, similar levels of reliability, as revealed by the coefficient of variation, were observed for both devices (50% 1RM: LPT = 6.52%, app = 8.17%; 75% 1RM: LPT = 12.10%, app = 13.55%). Collectively, the findings of this study support the use of My Jump Lab for the measurement of real-time barbell velocity in the bench press exercise.

Mental, physical, and phychophysiological responses to FFP2/N95 face mask during HIIT in active women.

Training systems based on high-intensity interval training (HIIT) have experienced great influence in recent years within the context of exercise and sport. This study aims to provide insight on whether the immediate outcomes (e.g., central and peripheral acute responses) may be intensified or attenuated when a HIIT protocol is performed using a FFP2/N95 face mask in active healthy adult women. In other words, it strives to provide new findings relative to the use of face masks as a potential performance enhancing tool. In the current study, the same training session was carried out on two occasions under different conditions (i.e., with FFP2/N95 and without FFP2/N95) in a cross-over experimental design. The following study variables were assessed before and after the HIIT in both sessions: Lactate, cortisol, alpha-amylase, selective attention, countermovement jump (CMJ), and power output. Additionally, central and peripheral Rates of Perceived Exertion (RPE) were assessed before and during the HIIT. This study makes novel contributions to prior research, showing that the use of FFP2/N95 face mask (vs. no mask) yielded higher alpha-amylase, selective attention, and peripheral RPE scores. No significant differences were found for lactate, cortisol, CMJ, and power output. Interestingly, central RPE scores were significantly lower under FFP2/N95 face mask (vs. no mask) condition. The main suggestion in light of these results is that researchers and practitioners should consider potential peripheral and central responses to training stimuli when using FFP2/N95 face masks.

Gender differences in professional drivers' fatigue level measured with BAlert mobile app: A psychophysiological, time efficient, accessible, and innovative approach to fatigue management.

Addressing fatigue is useful in a variety of scenarios and activities. Fatigue has recently been studied from a psychophysiological standpoint. As a result, the expression and impact of peripheral and central fatigue has been evaluated. Driving is one occupation where tiredness has disastrous consequences. BAlert is a smartphone app that approaches exhaustion with psychophysiological measures. More specifically, it evaluates the level of fatigue via heart rate variability (HRV) data and the cognitive compromise via Stroop effect. The goal of this study is to determine if there are gender differences in fatigue levels among professional drivers using the BAlert app. Statistically significant differences were found in the number of hours awake, in different parameters of HRV (AVNN, PNN50, RMSSD, and SDNN), in the level of stress, as well as in the cognitive response evaluated through the app. The results are discussed and their implications for the management of work fatigue are presented.