Working with schools in identifying and overcoming emotional barriers to learning

This paper reports a case study on working closely with a secondary school, to enhance understanding of disruptive behaviour, through the use of bespoke Continuing Professional Development (CPD) materials. This project evolved from the researchers’ previous research on the extent to which teachers believe disruptive pupils can control their behaviour. A notable finding was the sizeable minority of teachers in both primary and secondary schools who appear to be unaware of the psychological underpinnings of disruptive behaviour. That is, that such behaviour frequently communicates unresolved emotional needs, rather than wilful defiance. The current project aims to develop, implement and evaluate CPD resources developed by the researchers, for a one-day staff training day at a secondary school in north England. Prior to training, school staff completed a questionnaire to “audit” their perceptions of disruptive behaviour in school. Following evaluation, the CPD materials will be made available to other schools. It is anticipated that the materials will enable greater mutual understanding and respect for the ways in which disruptive behaviour is perceived by practitioners and school staff. Moreover, they will provide an urgently needed means of facilitating a shared knowledge base and a shared language for addressing emotional barriers to learning.     

The use of skill tests to predict status in junior Australian football

This study examined whether skill tests were predictive of status in junior Australian football. Players were recruited from the 2013 under 18 (U18) West Australian Football League competition and classified into two groups: elite (state U18 squad representative; n = 25; 17.9 ± 0.5 years) and subelite (nonstate U18 squad representative; n = 25; 17.3 ± 0.6 years). Both groups completed the Australian football kicking (AFK) and Australian football handballing (AFHB) tests, assessing kicking accuracy/ball speed and handballing accuracy on dominant and nondominant sides. A multivariate analysis of variance (MANOVA) modelled the main effect of “status”, whilst logistic regression models were built for the predictive analysis using the same test parameters. Between-group differences were noted across all parameters, with the combination of kicking accuracy and ball speed on the dominant and nondominant sides being the best predictor of status for the AFK test (wi = 0.25, AUC = 89.4%) and the combination of accuracy on the dominant and nondominant sides being the best predictor of status for the AFHB test (wi = 0.80, AUC = 88.4%). The AFK and AFHB tests are predictive of status, suggesting that their use is warranted as a means of talent identification in junior Australian football.     

How should we categorise self-reported data on subsequent injuries?*

Classifying subsequent injuries is of high importance in injury epidemiology since a previous injury has been reported to increase the risk of a new injury or increase the risk of a more severe injury. Multiple reports have shown that self-reported data provide an extensive view of an injury problem and add valuable information to the understanding of the athlete’s health. The purpose of this study was to display a method that can be used to facilitate classification of subsequent injuries and to discuss challenges faced when categorising subsequent injuries based on self-reported data. The suitability of a new model for Subsequent Injuries Adjusted for Self-reported data (SIAS model) was demonstrated with sport injury data from a cohort of 101 adolescent elite track & field athletes, followed over 52 weeks. A total number of 71 subsequent injuries were identified. Of all subsequent injuries, recurrent injuries represented 69.0% (n?=?49) and 31.0% (n?=?22) were classified as new injuries. The majority of subsequent injuries (n?=?60, 84.5%) occurred after athletes had recovered from a previous injury. Of all subsequent injuries, 15.5% (n?=?11) represented injuries where athletes had not fully recovered from a previous injury. Application of the SIAS model allows for classification of subsequent injuries based on self-reported data on the recovery level of the athletes, the injury onset and injury type. The developed SIAS model follows the consensus recommendations of injury definition, injury classification and is an attempt to increase the understanding of the complex relationship of subsequent injuries in self-reported data sets.     

R&D subsidies & external collaborative breadth: Differential gains and the role of collaboration experience

External collaboration breadth is important for firms to acquire the knowledge needed to innovate. In this paper, we combine cross-sectional and longitudinal data from the Spanish Panel of Technological Innovation Survey (PITEC) to examine the indirect impact of R&D subsidies on firm external collaboration breadth. We contribute to understanding of the indirect impacts of R&D subsidies by first providing strong evidence of an economically significant average positive impact of R&D subsidies on firm external collaboration breadth. Second, our results advance understanding of the differential impacts of R&D subsidies by revealing the vast heterogeneity of the impact at the firm level, where approximately only half of treated firms experience a positive collaboration impact from R&D subsidies, while the remainder experience no impact or a negative effect. Finally, we advance understanding of the characteristics explaining the differential impact of R&D subsidies on external collaboration breadth by utilising the organisational learning literature to demonstrate the important role of firm collaboration experience.