The effects of feedback valence and style on need satisfaction, self-talk, and perseverance among tennis players : an experimental study

Grounded in self-determination theory, this experimental study examined whether the valence (ire., positive vs. negative) and style (i.e., autonomy-supportive vs. controlling) of normative feedback impact the self-talk, motivational experiences (i.e., psychological need satisfaction and enjoyment), and behavioral functioning (i.e., perseverance and performance) of tennis players (N = 120; M-age = 24.50 +/- 9.86 years). Positive feedback and an autonomy-supportive style positively influenced players' enjoyment and perseverance, with psychological need satisfaction and self-talk playing an intervening role. While positive feedback yielded its beneficial effect via greater competence satisfaction and decreased negative self-talk, the beneficial impact of an autonomy-supportive communication style was explained via greater autonomy satisfaction

Coaching the coach : intervention effects on need-supportive coaching behavior and athlete motivation and engagement

The present intervention study examined whether youth sport coaches can be trained in adopting a need-supportive (i.e., autonomy support and structure) coaching style to the benefit of youth athletes' autonomous motivation and engagement. Participants were 43 coaches (33 men, 10 women) and 326 youth athletes (221 boys, 105 girls), active in 12 team or individual sports. Sport coaches were randomly assigned to either a control or intervention condition. The training involved a workshop trajectory spanning four sessions on how to incorporate a (more) need-supportive coaching style. As for coaches' self-reported coaching style, results of multilevel modelling revealed positive effects on autonomy support and control at posttest, and additional effect on structure and control from pre-test to follow-up (i.e., 4 months later) compared to coaches in the control condition. As for athletes' reports, multilevel modelling showed that athletes of coaches in the intervention, relative to those involved in the control group, perceived their coach to be more autonomy-supportive, more structuring, and less chaotic from pre-to posttest, with these effects being more pronounced for athletes of team sports. Further, athletes of coaches in the intervention group reported being more autonomously motivated and more engaged compared to those of coaches in the control group. Overall, the present findings indicate that sport coaches can become more skilled in adopting a need-supportive coaching style, to the benefit of athletes' autonomous motivation and engagement

International STakeholder NETwork (ISTNET): creating a developmental neurotoxicity (DNT) testing road map for regulatory purposes

A major problem in developmental neurotoxicity (DNT) risk assessment is the lack of toxicological hazard information for most compounds. Therefore, new approaches are being considered to provide adequate experimental data that allow regulatory decisions. This process requires a matching of regulatory needs on the one hand and the opportunities provided by new test systems and methods on the other hand. Alignment of academically and industrially-driven assay development with regulatory needs in the field of DNT is a core mission of the International STakeholder NETwork (ISNET) in DNT testing. The first meeting of ISTNET was held in Zurich on 23-24 January 2014 in order to explore the concept of adverse outcome pathway (AOP) to practical DNT testing. AOPs were considered promising tools to promote test systems development according to regulatory needs. Moreover, the AOP concept was identified as an important guiding principle to assemble predictive integrated testing strategies (ITSs) for DNT. The recommendations on a roadmap towards AOP-based DNT testing is considered a stepwise approach, operating initially with incomplete AOPs for compound grouping, and focussing on key events of neurodevelopment. Next steps to be considered in follow-up activities are the use of case studies to further apply the AOP concept in regulatory DNT testing, making use of AOP intersections (common key events) for economic development of screening assays, and addressing the transition from qualitative descriptions to quantitative network modelling.JRC.I.5-Systems Toxicolog

Report of the 1st and 2nd Mystery of Reactive Oxygen Species Conferences

Non peer reviewe

International STakeholder NETwork (ISTNET): creating a developmental neurotoxicity (DNT) testing road map for regulatory purposes

A major problem in developmental neurotoxicity (DNT) risk assessment is the lack of toxicological hazard information for most compounds. Therefore, new approaches are being considered to provide adequate experimental data that allow regulatory decisions. This process requires a matching of regulatory needs on the one hand and the opportunities provided by new test systems and methods on the other hand. Alignment of academically and industrially driven assay development with regulatory needs in the field of DNT is a core mission of the International STakeholder NETwork (ISTNET) in DNT testing. The first meeting of ISTNET was held in Zurich on 23-24 January 2014 in order to explore the concept of adverse outcome pathway (AOP) to practical DNT testing. AOPs were considered promising tools to promote test systems development according to regulatory needs. Moreover, the AOP concept was identified as an important guiding principle to assemble predictive integrated testing strategies (ITSs) for DNT. The recommendations on a road map towards AOP-based DNT testing is considered a stepwise approach, operating initially with incomplete AOPs for compound grouping, and focussing on key events of neurodevelopment. Next steps to be considered in follow-up activities are the use of case studies to further apply the AOP concept in regulatory DNT testing, making use of AOP intersections (common key events) for economic development of screening assays, and addressing the transition from qualitative descriptions to quantitative network modelling