https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49807 Wed 31 May 2023 16:21:01 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:39543 Wed 27 Jul 2022 14:24:29 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:39542 Wed 27 Jul 2022 14:23:46 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23850 Wed 24 Nov 2021 15:53:07 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42510 0.05). High ratings of participant satisfaction (4.73), enjoyment (4.54) and perceived value (4.54) were observed. Conclusion: This study demonstrates the efficacy and feasibility of delivering a novel HIIT program in the university setting.]]> Wed 24 Aug 2022 09:46:23 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:35678 Wed 15 Mar 2023 14:43:50 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:6808 Wed 11 Apr 2018 14:32:33 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:2673 Wed 11 Apr 2018 11:37:31 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:6810 Wed 11 Apr 2018 10:54:52 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:26881 Wed 11 Apr 2018 10:35:39 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:11859 0.05) in girls and the test of the mediated effect was non-significant (p > 0.05). Perceived body attractiveness was found to mediate the relationship between body fat % and physical self-worth among boys and girls. Physical self-worth is associated with different components of health-related fitness in adolescent girls and boys. Mediation analysis can be used to provide insights into the complex interrelationships between variables.]]> Wed 11 Apr 2018 09:45:26 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:38654 Wed 06 Dec 2023 09:52:54 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:48749 Wed 05 Apr 2023 13:41:29 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:18826 Wed 04 Sep 2019 10:59:40 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:38655 Wed 04 May 2022 15:19:55 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:46750 Tue 29 Nov 2022 15:25:49 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:46676 Tue 29 Nov 2022 09:28:29 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:51133 Tue 22 Aug 2023 15:57:59 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:37702 Tue 16 Mar 2021 18:05:52 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:44266 Tue 11 Oct 2022 13:59:33 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31351 Thu 30 Jan 2020 10:58:08 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29965 Thu 17 Mar 2022 14:41:51 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:11862 Thu 12 Apr 2018 14:12:02 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:7234 Sat 24 Mar 2018 08:33:46 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:1398 Sat 24 Mar 2018 08:28:01 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:10572 Sat 24 Mar 2018 08:10:45 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21444 P < 0.04) in participants (n = 8) who increased training load (completed light training then heavy training) and, although maximal rate of heart rate increase did not change (P = 0.27), within-individual changes in work were correlated with changes in maximal rate of heart rate increase (r = 0.87, P = 0.005). Work during 5 min cycle time-trial increased 6.5% (P < 0.001) in 9 participants who decreased training load (completed heavy training then light training) and maximal rate of heart rate increase increased 28% (P = 0.002) but the changes in maximal work were not related to changes in rate of heart rate increase (r = 0.32, P = 0.40). Heart rate recovery tended to track changes in 5 min cycle time-trial work following increases and decreases in training load (r = 0.65–0.75, P = 0.03–0.08). Conclusions: Maximal rate of heart rate increases during cycling at 100 W tracks reductions in exercise performance when training load is increased, but not performance improvements when training loads are reduced. Maximal rate of heart rate increase may be a useful adjunct to heart rate recovery for tracking changes in exercise performance.]]> Sat 24 Mar 2018 08:05:43 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:18261 Sat 24 Mar 2018 08:04:54 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:17557 Sat 24 Mar 2018 08:03:52 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:19646 p < 0.001) trials compared to 120 and 180 min following ingestion for the 6 and 9 mg kg⁻¹ fed trials, respectively (p < 0.001). Peak concentration was greater in the 9 mg kg⁻¹ fasted trial than the corresponding fed condition (70 ± 9 μmol L⁻¹ and 56 ± 6 μmol L⁻¹, respectively) and both were greater than the 6 mg kg⁻¹ conditions (44 ± 8 μmol L⁻¹ and 38 ± 8 μmol L⁻¹ for 6 mg kg⁻¹ fasted and fed, respectively). Area under the caffeine curve was significantly greater (p < 0.001) in the 9 mg kg⁻¹ fasted trial (3262 μmol L⁻¹ h⁻¹), whilst areas were lowest in the 6 mg kg⁻¹ fed trial (1644 μmol L⁻¹ h⁻¹). Conclusions: A high carbohydrate meal consumed prior to caffeine ingestion significantly reduced serum caffeine concentrations and delayed time to peak concentration. Differences in research findings between caffeine supplementation studies may, at least in part, be related to variations in postprandial timing of caffeine intake. The influence of postprandial timing should be considered when athletes consume caffeine with the aim of enhancing performance.]]> Sat 24 Mar 2018 08:01:09 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:18966 Sat 24 Mar 2018 07:58:53 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:19160 Sat 24 Mar 2018 07:52:20 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:19161 2.3mgkg⁻¹ > placebo; p<0.001). Conclusions: There was large individual variation in plasma pseudoephedrine concentration between subjects following pseudoephedrine administration. A number of factors clearly influence the uptake and appearance of pseudoephedrine in the blood and these are not yet fully understood. Combined with subsequent differences in plasma pseudoephedrine between individuals, this may partially explain the present findings and also the inconsistencies in performance following pseudoephedrine administration in previous studies.]]> Sat 24 Mar 2018 07:52:20 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:5147 Sat 24 Mar 2018 07:49:40 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:28286 cyc) and running at 8 km/h (rHRI_run) in 13 male triathletes following two weeks of light-training (LT), two weeks of heavy-training (HT) and a two-day recovery period (RP). A five min cycling time-trial assessed performance and peak oxygen consumption (VO_2peak). Results: Performance likely decreased following HT (Effect size ± 90% confidence interval = -0.18 ± 0.09), then very likely increased following RP (0.32 ± 0.14). rHRI_cyc very likely decreased (-0.48 ± 0.24), and rHRIrun possibly decreased (-0.33 ± 0.48), following HT. Changes in both measures were unclear following RP. Steady-state HR was almost certainly lower (-0.81 ± 0.31) during rHRI_cyc than rHRI_run. A large correlation was found between reductions in performance and rHRI_run (r ± 90%; CI = 0.65 ± 0.34) from LT to HT, but was unclear for rHRI_cyc. Trivial within-subject correlations were found between rHRI and performance, but the strength of relationship between rHRI_run and performance was largely associated with VO_2peak following LT (r = -0.58 ± 0.38). Conclusions: Performance reductions were most sensitively tracked by rHRI_run following HT. This may be due to rHRI_run being assessed at a higher intensity than rHRI_cyc, inferred from a higher steady-state HR and supported by a stronger within-subject relationship between rHRI_run and performance in individuals with a lower VO_2peak, in whom the same exercise intensity would represent a greater physiological stress. rHRI assessed at relatively high exercise intensities may better track performance changes.]]> Sat 24 Mar 2018 07:41:23 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:26108 Sat 24 Mar 2018 07:39:54 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29263 0.6). There were inverse within-subject relationships between indices of HRR and performance (r = −0.6, p ≤ 0.004). Peak HR decreased 3.2 ± 5.1 bpm following heavy training (p = 0.06) and significantly increased 4.9 ± 4.3 bpm following recovery (p = 0.004). There was a moderate within-subject relationship between peak HR and exercise performance (r = 0.7, p ≤ 0.001). Controlling for peak HR reduced the relationships between HRR and performance (r = −0.4–0.5, p < 0.05). Conclusions: This study demonstrated that HRR tracks short-term changes in exercise performance within-individuals, such that increases in HRR are associated with poorer exercise performance following heavy training. Peak HR can be compromised under conditions of fatigue, and needs to be taken into account in HRR analyses.]]> Sat 24 Mar 2018 07:39:14 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29565 N = 22). Pre-season musculoskeletal screening (incorporating mobility, stability and neural tests) and seasonal injury data were analysed for predictive relationships, and associations between potential predictor variables and injury status. Results: Injuries requiring medical attention occurred at a rate of 3.6 injuries/athlete, while injuries resulting in disability occurred at a rate of 0.6 injuries/athlete, with the lumbar spine the main site of injury (23% and 33%, respectively). Wrist and hand injury resulted in the highest number of days of disability (110 days), followed by injury to the lumbar spine (87 days). Across the season 75% of injuries to the lumbar spine occurred in the latter half of the season. The only screening measure predictive of injured/uninjured status was better left-sided single-leg decline-squat performance (OR = 0.29; 95% CI = 0.09-0.88; p = 0.03), while increasing age was significantly (p = 0.03) associated with thoracic (OR = 1.48; 95% CI = 1.03-2.12) and lumbar spine (OR = 1.46; 95% CI = 1.04-2.04) injury. Conclusions: Though clinically useful, current screening protocols do not adequately assess the risk of seasonal injury in elite Olympic class sailors, and should be revised. Due to the increased risk of spinal injury and potential lost/modified participation in older Olympic class sailors, injury prevention activities should be individualised and age appropriate.]]> Sat 24 Mar 2018 07:37:54 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29980 Sat 24 Mar 2018 07:37:38 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:26156 Sat 24 Mar 2018 07:35:26 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:30897 r_s = 0.68, p < 0.05). Conclusions: Both instruments were found to be reliable and valid. However, compared to the Victorian FMS instrument, the CAMSA has the advantage of both process and product assessment, less time needed to administer and higher authenticity, and so may be an attractive alternative to the more traditional forms of FMS assessment, for use with early adolescent girls, in school settings.]]> Sat 24 Mar 2018 07:30:38 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23858 0.05). No significant increases in squat or bench press strength were observed after 12 weeks in the CON group. Increases in lower body strength were large in the LP group (ES: 1.64) and very large in the DUP group (ES: 2.33). Upper body strength changes were small in both groups (LP, ES: 0.57; DUP, ES: 0.31). Conclusions: Twelve weeks of LP or DUP resistance training are both effective at increasing maximal lower and upper body strength in adolescent rugby athletes. Additionally, twice weekly frequency of resistance training in adolescent rugby athletes with greater than 6-months resistance training experience is sufficient to elicit substantial increases in maximal strength.]]> Sat 24 Mar 2018 07:12:10 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23762 2max : 43.3 ± 5.7 ml kg^-1 min^-1) volunteered to participate. Heart rate (HR) and blood lactate concentration ([BLa]) were collected across eight competitive matches. Overall and positional player activity demands were calculated across three matches using time-motion analysis methodology. Activity frequencies, total durations and total distances were determined for various activity categories. Mean (±SD) HR responses of 162±3b min^-1 (82.4±1.3% HR_max) and 136±6b min^-1 (68.6±3.1% HR_max) were evident across live and total time during matches. A mean [BLa] of 3.7 ± 1.4 mmol L^-1 was observed across competition. Player activity demands were unchanged across match periods, with 1752±186 movements performed and 5214±315m travelled across total live match time. Furthermore, 39±3%, 52±2%, 5 ± 1% and 4±1% of total live time was spent performing low-intensity, moderate-intensity, high-intensity and dribbling activity. Positional comparisons revealed backcourt players performed more ball dribbling (p<0.001) and less standing/walking (p<0.01) and running (p<0.05) than frontcourt players. Together, these findings highlight the high intermittent demands and important contributions of both anaerobic and aerobic metabolic pathways during state-level female basketball competition.]]> Sat 24 Mar 2018 07:11:08 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23935 Sat 24 Mar 2018 07:10:11 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23907 Sat 24 Mar 2018 07:10:02 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:46627 Mon 28 Nov 2022 13:38:41 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23851 Mon 23 Sep 2019 11:27:40 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:21859 Mon 23 Sep 2019 10:35:56 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:32763 Mon 23 Jul 2018 12:49:18 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49437 Mon 15 May 2023 13:51:09 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:35522 Mon 08 Nov 2021 10:29:21 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:53006 Mon 06 Nov 2023 08:50:58 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42795 Mon 05 Sep 2022 09:01:30 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42173 Fri 19 Aug 2022 09:29:17 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:41744  15 years), and individuals engaging in sufficient levels of aerobic exercise training (AET) engaged in sufficient levels of RET (p < 0.05). Conclusions: The prevalence of Australian’s participating in regular RET programs is low and only a small proportion of participants meet ACSM guidelines for the quantity and quality of RET that is likely to provide health benefits. This has implications for public health policy and the future development and promotion of population-level RET guidelines.]]> Fri 12 Aug 2022 11:21:31 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49123 500 teachers were analysed. There was no statistically significant between group differences in any of the outcomes, including accelerometer measured physical activity, out-of-school-hours physical activity, HRQoL, and on-task behaviour. A statistically significant differential effect by sex was found for sedentary behaviour across the whole school day (3.16 min, 95% CI: 0.19, 6.13; p = 0.028), with females illustrating a greater difference between groups than males. Conclusions: Only negligible effects on student physical activity were found. Additional strategies including improving the quality of teacher's delivery of physical activity may be required to enhance effects.]]> Fri 05 May 2023 11:53:53 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31192 Fri 01 Apr 2022 09:26:37 AEDT ]]>