A systematic review and meta-analysis of randomized controlled trials to determine if motivational interviewing leads to increased physical activity, cardiorespiratory fitness or functional exercise capacity in people with chronic health conditions. Seven electronic databases (MEDLINE, PsychINFO, EMBASE, AMED, CINHAL, SPORTDiscus and the Cochrane Central Register of Controlled trials) were searched from inception until January 2014. Two reviewers independently examined publications for inclusion. Trials were included if participants were adults (>18 years), had a chronic health condition, used motivational interviewing as the intervention and examined physical activity, cardiorespiratory fitness or functional exercise capacity. Two reviewers independently extracted data. Risk of bias within trials was assessed using the Physiotherapy Evidence Database Scale. Meta-analyses were conducted with standardized mean differences and 95% confidence intervals (CIs) were calculated. The Grades of Recommendation, Assessment, Development and Evaluation approach was used to evaluate the quality of the evidence. Eleven publications (of ten trials) were included. There was moderate level evidence that motivational interviewing had a small effect in increasing physical activity levels in people with chronic health conditions relative to comparison groups (standardized mean differences = 0.19, 95% CI 0.06 to 0.32, p = 0.004). Sensitivity analysis based on trials that confirmed treatment fidelity produced a larger effect. No conclusive evidence was observed for cardiorespiratory fitness or functional exercise capacity. The addition of motivational interviewing to usual care may lead to modest improvements in physical activity for people with chronic health conditions.

Following a bout of heavy resistance training, the muscle is in both a fatigued and potentiated state with subsequent muscle performance depending on the balance between these two factors. To date, there is no uniform agreement about the optimal acute recovery required between the heavy resistance training and subsequent muscle performance to gain performance benefits. The aim of the present study was to determine the recovery time required to observe enhanced muscle performance following a bout of heavy resistance training. Twenty professional rugby players performed a countermovement jump at baseline and ∼15 s, 4, 8, 12, 16, 20, and 24 min after a bout of heavy resistance training (three sets of three repetitions at 87% one-repetition maximum squat). Power output, jump height, and peak rate of force development were determined for all countermovement jumps. Despite an initial decrease in countermovement jump performance after the heavy resistance training (P < 0.001), participants' performance increased significantly following 8 min recovery (P < 0.001) (i.e. jump height increased by 4.9%, s = 3.0). The findings suggest that muscle performance during a countermovement jump can be markedly enhanced following bouts of heavy resistance training provided that adequate recovery (∼8 min) is allowed between the heavy resistance training and the explosive activity.

Ambulatory heart rate monitors and clinical electrocardiographic (ECG) devices are capable of measuring the length of consecutive cardiac periods (RR intervals). The aim of the study was to assess the agreement between the Polar 810 s heart rate monitor (Polar) and the Reynolds digital ambulatory ECG using Pathfinder software version 8.4 (Reynolds v8.4) during cycle ergometry. For this purpose, eight subjects completed incremental cycling exercise that began at 60 W and increased by 30 W each 2-minute period until volitional fatigue. Simultaneous recording of the ECG (Reynolds Pathfinder), RR interval (Polar), and respiratory parameters (Metamax 3B) were undertaken at rest and throughout the exercise period. No significant differences were found in RR intervals measured by Polar and Reynolds v8.4 at any relative intensity. Polar and Reynolds v8.4 displayed strong linear relationships at all relative intensities (r² = 0.927 to 0.998). Bland and Altman analyses between Polar and Reynolds v8.4 consistently demonstrated minimal bias in absolute RR interval (< 0.10 ms) and the limits of agreement for group differences in RR interval and heart rate were less than ± 10 ms and ± 2 beats · min^-1 for all relative intensities, respectively. Power spectral analysis provided similar results for both systems in all bandwidths studied during rest and low intensity exercise. However, significant differences and large relative limits of agreement (> 100 % of mean of paired means) were identified in UF at intensities > 40 % V·O_2max, HF at intensities > 60 % V·O_2max and LF during exercise at 80 - 100 % V·O_2max. These findings demonstrate that RR intervals and heart rate measurements obtained using Polar and Reynolds v8.4 are in good agreement. However, caution should be exercised when interpreting spectral analysis of RR interval data derived from different acquisition systems during physical activity.

Sports nutrition professionals aim to influence nutrition knowledge, dietary intake and body composition to improve athletic performance. Understanding the interrelationships between these factors and how they vary across sports has the potential to facilitate better-informed and targeted sports nutrition practice. This observational study assessed body composition (DXA), dietary intake (multiple-pass 24-hr recall) and nutrition knowledge (two previously validated tools) of elite and subelite male players involved in two team-based sports; Australian football (AF) and soccer. Differences in, and relationships between, nutrition knowledge, dietary intake and body composition between elite AF, subelite AF and elite soccer players were assessed. A total of 66 (23 ± 4 years, 82.0 ± 9.2 kg, 184.7 ± 7.7 cm) players participated. Areas of weaknesses in nutrition knowledge are evident (57% mean score obtained) yet nutrition knowledge was not different between elite and subelite AF and soccer players (58%, 57% and 56%, respectively, p > .05). Dietary intake was not consistent with recommendations in some areas; carbohydrate intake was lower (4.6 ± 1.5 g/kg/day, 4.5 ± 1.2 g/kg/day and 2.9 ± 1.1 g/kg/day for elite and subelite AF and elite soccer players, respectively) and protein intake was higher (3.4 ± 1.1 g/kg/day, 2.1 ± 0.7 g/kg/day and 1.9 ± 0.5 g/kg/day for elite and subelite AF and elite soccer players, respectively) than recommendations. Nutrition knowledge was positively correlated with fat-free soft tissue mass (n = 66; r² = .051, p = .039). This insight into known modifiable factors may assist sports nutrition professionals to be more specific and targeted in their approach to supporting players to achieve enhanced performance.

In this study, we examined the reliability and construct validity of new soccer skills tests. Twenty soccer players (10 professional and 10 recreational) repeated trials of passing, shooting, and dribbling skills on different days. Passing and shooting skills required players to kick a moving ball, delivered at constant speed, towards one of four randomly determined targets. Dribbling required players to negotiate seven cones over 20 m. Each trial consisted of 28 passes, 8 shots, and 10 dribbles. Ball speed, precision, and success were determined for all tests using video analysis. Systematic bias was small (<9% in all measures) and all outcome measures were similar between trials. Test–retest reliability statistics were as follows: ball speed (passing, shooting, dribbling; coefficient of variation [CV]: 6.5%, 6.9%, 2.4%; ratio limits of agreement [RLOA]: 0.958 ×/÷ 1.091, 0.990 ×/÷ 1.107, 0.993 ×/÷ 1.039), precision (passing, shooting, dribbling; CV: 10.0%, 23.5%, 4.6%; RLOA: 0.956 ×/÷ 1.147, 1.030 ×/÷ 1.356, 1.000 ×/÷ 1.068), and success (passing, shooting, dribbling; CV: 11.7%, 14.4%, 2.2%; RLOA: 1.017 ×/÷ 1.191, 0.913 ×/÷ 1.265, 0.996 ×/÷ 1.035). Professional players performed better than recreational players in at least one outcome measure for all skills. These findings demonstrate the reliability and validity of new soccer skill protocols.

Following a bout of high-intensity exercise of short duration (preload stimulus), the muscle is in both a fatigued and a potentiated (referred to as postactivation potentiation) state. Consequently, subsequent muscle performance depends on the balance between these 2 factors. To date, there is no uniform agreement about the optimal recovery required between the preload stimulus and subsequent muscle performance to gain optimal performance benefits. The aim of the present study was to determine the optimal recovery time required to observe enhanced muscle performance following the preload stimulus. Twenty-three professional rugby players (13 senior international players) performed 7 countermovement jumps (CMJs) and 7 ballistic bench throws at the following time points after a preload stimulus (3 repetition maximum [3RM]): baseline, approximately 15 seconds, and 4, 8, 12, 16, and 20 minutes. Their peak power output (PPO) was determined at each time point. Statistical analyses revealed a significant decrease in PPO for both the upper (856 +/- 121 W vs. 816 +/- 121 W, p < 0.001) and the lower (4,568 +/- 509 W vs. 4,430 +/- 495 W, p = 0.005) body when the explosive activity was performed approximately 15 seconds after the preload stimulus. However, when 12 minutes was allowed between the preload stimulus and the CMJ and ballistic bench throws, PPO was increased by 8.0 +/- 8.0% and 5.3 +/- 4.5%, respectively. Based on the above results, we conclude that muscle performance (e.g., power) can be significantly enhanced following a bout of heavy exercise (preload stimulus) in both the upper and the lower body, provided that adequate recovery (8-12 minutes) is given between the preload stimulus and the explosive activity.