Observation as a method to enhance collective efficacy: An integrative review

Objectives This review provides an integrative argument for the use of observation as an intervention to manipulate individual collective efficacy beliefs in sports teams. Design An exploration of the conceptual and empirical evidence underpinning observation-based interventions for increasing collective efficacy. Method A presentation of reflections on the following. First, we reflect on existing techniques used to increase self- and collective efficacy beliefs. Second, we consider collective efficacy in the context of observational learning and the various modeling techniques employed in the sports and motor performance literature. Third, we highlight relevant literature from neuroscience, outlining the analogous neural pathways evident for social cognition (i.e., collective efficacy) and observation. Results This review presents a case for the use of observation interventions to manipulate collective efficacy, drawing upon social psychological frameworks of human behavior, the observation-based literature, and contemporary understanding of brain and behavior. Conclusions Observation-based interventions are suited for collective efficacy manipulation in sport. There is a need to advance understanding of this relationship in order to maximize improvements in collective efficacy across group contexts

Movement Demands of Elite U20 International Rugby Union Players

The purpose of this study was to quantify movement demands of elite international age grade (U20) rugby union players during competitive tournament match play. Forty elite professional players from an U20 international performance squad were monitored using 10 Hz global positioning systems (GPS) during 15 international tournament matches during the 2014/15 and 2015/16 seasons. Data on distances, velocities, accelerations, decelerations, high metabolic load (HML) distance and efforts, and number of sprints were derived. Data files from players who played over 60 min (n = 161) were separated firstly into Forwards and Backs, and more specifically into six positional groups; FR--Front Row (prop & hooker), SR--Second Row, BR--Back Row (Flankers & No.8), HB--Half Backs (scrum half & outside half), MF--Midfield (centres), B3--Back Three (wings & full back) for match analysis. Analysis revealed significant differences between forwards and backs positions. Backs scored higher on all variables measured with the exception of number of moderate accelerations, decelerations (no difference). The centres covered the greatest total distance with the front row covering the least (6.51 ± 0.71 vs 4.97 ± 0.75 km, p < 0.001). The front row also covered the least high speed running (HSR) distance compared to the back three (211.6 ± 112.7 vs 728.4 ± 150.2 m, p < 0.001) who covered the most HSR distance, affirming that backs cover greater distances but forwards have greater contact loads. These findings highlight for the first time differences in the movement characteristics of elite age grade rugby union players specific to positional roles

Who said “there is no ‘I’ in team”? The effects of observational learning content level on efficacy beliefs in groups

Objectives To investigate the effects of individual-level observational learning (OLINDV), team-level observational learning (OLTEAM), and multi-level observational learning (OLMULTI) on efficacy beliefs, task cohesion, and performance across three studies in sports teams. Design Cross-sectional, experimental and single-case designs were employed across the three studies, respectively. Method Study 1 used a cross-sectional design to explore the predictive relationship between OLINDV and OLTEAM use, and collective efficacy and task cohesion in 210 team sports athletes. Study 2 used a repeated-measures experimental design to compare effects of OLINDV versus OLTEAM interventions on collective and self-efficacy in two soccer teams. Study 3 used a single-case A-A-B-B design to assess the effectiveness of OLMULTI interventions on self-efficacy, collective efficacy, task cohesion and performance in an elite age-grade rugby union team across a competitive season. Results In study 1, both OLINDV and OLTEAM use predicted collective efficacy, but only OLTEAM use predicted task dimensions of cohesion. In study 2, collective efficacy increased for both the OLINDV and OLTEAM interventions while self-efficacy increased only for the OLINDV intervention. In study 3, visual and effect size analyses indicated increased self-efficacy, collective efficacy task cohesion, and performance for the team during the off- and in-season intervention phases where the OLMULTI interventions were administered alongside usual sporting involvement (training sessions and/or competitive fixtures). Conclusions The novel findings of this investigation show that OLINDV, OLTEAM and OLMULTI interventions can enhance efficacy beliefs in practical contexts and warrant application in groups across domains

Dexamethasone Administration During Definitive Radiation and Temozolomide Renders a Poor Prognosis in a Retrospective Analysis of Newly Diagnosed Glioblastoma Patients

BACKGROUND: Dexamethasone (DXM) is commonly used in the management of cerebral edema in patients diagnosed with glioblastoma multiforme (GBM). Bevacizumab (BEV) is FDA-approved for the progression or recurrence of GBM but has not been shown to improve survival when given for newly diagnosed patients concurrently with radiation (RT) and temozolomide (TMZ). Both DXM and BEV reduce cerebral edema, however, DXM has been shown to induce cytokine cascades which could interfere with cytotoxic therapy. We investigated whether DXM would reduce survival of GBM patients in the setting of concurrent TMZ and BEV administration. METHODS: We reviewed the treatment of all 73 patients with GBM who received definitive therapy at our institution from 2005 to 2013 with RT (60 Gy) delivered with concurrent daily TMZ (75 mg/m2). Of these, 34 patients also were treated with concurrent BEV (10 mg/kg every two weeks). Patients received adjuvant therapy (TMZ or TMZ/Bev) until either progression, discontinuation due to toxicity, or 12 months after radiation completion. All patients who had GBM progression with TMZ were offered BEV for salvage therapy, with 19 (56 %) receiving BEV. RESULTS: With a median follow-up of 15.6 months, 67 (91.8 %) patients were deceased. The OS for the entire cohort was 15.9 months, while the PFS was 7.7 months. The extent of resection was a prognostic indicator for OS (p  = .0044). The median survival following gross tumor resection (GTR) was 22.5 months, subtotal resection (STR) was 14.9 months, and biopsy was 12.1 months. The addition of BEV to TMZ with RT was borderline significantly associated with increased PFS (9.4 vs. 5.1 months, p = 0.0574) although was not significantly associated with OS (18.1 vs. 15.3 months respectively, p  = 0.3064). In patients receiving TMZ, DXM use concurrent with RT was a poor prognostic indicator of both OS (12.7 vs. 22.6 months, p = 0.003) and PFS (3.6 vs. 8.4 months, p p = 0.4818). On multivariable analysis, DXM use predicted an unfavorable OS hazard ratio (HR) = 1.72, p = 0.045). CONCLUSIONS: Our results with TMZ, BEV, and RT are similar to previous studies in terms of PFS and OS. DXM use during RT with concurrent TMZ correlated with reduced OS and PFS unless BEV was administered

Movement Demands of Elite Under-20s and Senior International Rugby Union Players

This study compared the movement demands of elite international Under-20 age grade (U20s) and senior international rugby union players during competitive tournament match play. Forty elite professional players from an U20 and 27 elite professional senior players from international performance squads were monitored using 10Hz global positioning systems (GPS) during 15 (U20s) and 8 (senior) international tournament matches during the 2014 and 2015 seasons. Data on distances, velocities, accelerations, decelerations, high metabolic load (HML) distance and efforts, and number of sprints were derived. Data files from players who played over 60 min (n = 258) were separated firstly into Forwards and Backs, and more specifically into six positional groups; FR–Front Row (prop & hooker), SR–Second Row, BR–Back Row (Flankers & No.8), HB–Half Backs (scrum half & outside half), MF–Midfield (centres), B3 –Back Three (wings & full back) for match analysis. Linear mixed models revealed significant differences between U20 and senior teams in both the forwards and backs. In the forwards the seniors covered greater HML distance (736.4 ± 280.3 vs 701.3 ± 198.7m, p = 0.01) and severe decelerations (2.38 ± 2.2 vs 2.28 ± 1.65, p = 0.05) compared to the U20s, but performed less relative HSR (3.1 ± 1.6 vs 3.2 ± 1.5, p < 0.01), moderate (19.4 ± 10.5 vs 23.6 ± 10.5, p = 0.01) and high accelerations (2.2 ± 1.9 vs 4.3 ± 2.7, p < 0.01) and sprint•min-1 (0.11 ± 0.06 vs 0.11 ± 0.05, p < 0.01). Senior backs covered a greater relative distance (73.3 ± 8.1 vs 69.1 ± 7.6 m•min-1, p < 0.01), greater High Metabolic Load (HML) distance (1138.0 ± 233.5 vs 1060.4 ± 218.1m, p < 0.01), HML efforts (112.7 ± 22.2 vs 98.8 ± 21.7, p < 0.01) and heavy decelerations (9.9 ± 4.3 vs 9.5 ± 4.4, p = 0.04) than the U20s backs. However, the U20s backs performed more relative HSR (7.3 ± 2.1 vs 7.2 ± 2.1, p <0.01) and sprint•min-1 (0.26 ± 0.07 vs 0.25 ± 0.07, p < 0.01). Further investigation highlighted differences between the 6 positional groups of the teams. The positional groups that differed the most on the variables measured were the FR and MF groups, with the U20s FR having higher outputs on HSR, moderate & high accelerations, moderate, high & severe decelerations, HML distance, HML efforts, and sprints•min-1. For the MF group the senior players produced greater values for relative distance covered, HSR, moderate decelerations, HML distance and sprint•min-1. The BR position group was most similar with the only differences seen on heavy accelerations (U20s higher) and moderate decelerations (seniors higher). Findings demonstrate that U20s internationals appear to be an adequate ‘stepping stone’ for preparing players for movement characteristics found senior International rugby, however, the current study highlight for the first time that certain positional groups may require more time to be able to match the movement demands required at a higher playing level than others. Conditioning staff must also bear in mind that the U20s players whilst maintaining or improving match movement capabilities may require to gain substantial mass in some positions to match their senior counterparts

Match play performance characteristics that predict post-match creatine kinase responses in professional rugby union players

Background: Rugby union players can take several days to fully recover from competition. Muscle damage induced during the match has a major role in player recovery; however the specific characteristics of match play that predict post-match muscle damage remains unclear. We examined the relationships between a marker of muscle damage and performance characteristics associated with physical contacts and high-speed movement in professional rugby union players. Methods: Twenty-eight professional rugby union players (15 forwards, 13 backs) participated in this study. Data were obtained from 4 European Cup games, with blood samples collected 2 h pre, and 16 and 40 h post-match, and were subsequently analysed for creatine kinase (CK). Relationships between changes in CK concentrations and number of physical contacts and high-speed running markers, derived from performance analysis and global positioning system (GPS) data, were assessed. Results: Moderate and moderate-large effect-size correlations were identified between contact statistics from performance analysis and changes in CK at 16 and 40 h post match in forwards and backs, respectively (e.g. backs; total impacts vs. ΔCK (r = 0.638, p < 0.01) and Δ% CK (r = 0.454, p < 0.05) 40 h post-match). Furthermore, moderate effect-size correlations were found between measures of high-speed running and sprinting, and changes in CK at 16 and 40 h post-match within the backs (e.g. high-speed running distance vs. ΔCK (r = 0.434, p = 0.056) and Δ% CK (r = 0.437, p = 0.054) 40 hrs post-match). Conclusions: Our data demonstrate that muscle damage induced by professional rugby union match play is to some extent predicted by the number of physical contacts induced during performance. Furthermore, we show for the first time that muscle damage in backs players is predicted by high-speed running measures derived from GPS. These data increase the understanding of the causes of muscle damage in rugby union; performance markers could potentially be used to tailor individual recovery strategies and subsequent training following rugby union competition