The Integrated Model of Sport Confidence: A Canonical Correlation and Mediational Analysis

The main purpose of the study was to examine crucial parts of Vealey’s (2001) integrated framework hypothesizing that sport confidence is a mediating variable between sources of sport confidence (including achievement, self-regulation, and social climate) and athletes’ affect in competition. The sample consisted of 386 athletes, who completed the Sources of Sport Confidence Questionnaire, Trait Sport Confidence Inventory, and Dispositional Flow Scale-2. Canonical correlation analysis revealed a confidence-achievement dimension underlying flow. Bias-corrected bootstrap confidence intervals in AMOS 20.0 were used in examining mediation effects between source domains and dispositional flow. Results showed that sport confidence partially mediated the relationship between achievement and  self-regulation domains and flow, whereas no significant mediation was found for social climate. On a subscale level, full mediation models emerged for achievement and flow dimensions of challenge–skills balance, clear goals, and concentration on the task at hand.

Effectiveness and feasibility of virtual reality and gaming system use at home by older adults for enabling physical activity to improve health-related domains: a systematic review

Background
use of virtual reality and commercial gaming systems (VR/gaming) at home by older adults is receiving attention as a means of enabling physical activity.

Objective
to summarise evidence for the effectiveness and feasibility of VR/gaming system utilisation by older adults at home for enabling physical activity to improve impairments, activity limitations or participation.

Methods
a systematic review searching 12 electronic databases from 1 January 2000–10 July 2012 using key search terms. Two independent reviewers screened yield articles using pre-determined selection criteria, extracted data using customised forms and applied the Cochrane Collaboration Risk of Bias Tool and the Downs and Black Checklist to rate study quality.

Results
fourteen studies investigating the effects of VR/gaming system use by healthy older adults and people with neurological conditions on activity limitations, body functions and physical impairments and cognitive and emotional well-being met the selection criteria. Study quality ratings were low and, therefore, evidence was not strong enough to conclude that interventions were effective. Feasibility was inconsistently reported in studies. Where feasibility was discussed, strong retention (≥70%) and adherence (≥64%) was reported. Initial assistance to use the technologies, and the need for monitoring exertion, aggravation of musculoskeletal symptoms and falls risk were reported.

Conclusions
existing evidence to support the feasibility and effectiveness VR/gaming systems use by older adults at home to enable physical activity to address impairments, activity limitations and participation is weak with a high risk of bias. The findings of this review may inform future, more rigorous research.

Adapting the task : what preservice teachers notice when adapting mathematical tasks

This paper reports on an in-depth study that explores preservice teachers’ pedagogical adaptations to a rich mathematical task. Data were collected from six elementary preservice teachers working in pairs to first solve a mathematics problem and then design adaptations to make the problem more accessible and more challenging for diverse learners. Results indicate that preservice teachers are able to draw upon a range of strategies to vary the mathematical content, the context, and the question asked. However, they also did not notice or attend to how their adaptations changed the mathematical structure of the problem. This study provides insights into what is involved in learning to adapt classroom mathematical tasks as an important pedagogical practice.

The International Society for Bipolar Disorders (ISBD) Task Force report on the nomenclature of course and outcome in bipolar disorders

Objectives:  Via an international panel of experts, this paper attempts to document, review, interpret, and propose operational definitions used to describe the course of bipolar disorders for worldwide use, and to disseminate consensus opinion, supported by the existing literature, in order to better predict course and treatment outcomes. Methods:  Under the auspices of the International Society for Bipolar Disorders, a task force was convened to examine, report, discuss, and integrate findings from the scientific literature related to observational and clinical trial studies in order to reach consensus and propose terminology describing course and outcome in bipolar disorders. Results:  Consensus opinion was reached regarding the definition of nine terms (response, remission, recovery, relapse, recurrence, subsyndromal states, predominant polarity, switch, and functional outcome) commonly used to describe course and outcomes in bipolar disorders. Further studies are needed to validate the proposed definitions. Conclusion:  Determination and dissemination of a consensus nomenclature serve as the first step toward producing a validated and standardized system to define course and outcome in bipolar disorders in order to identify predictors of outcome and effects of treatment. The task force acknowledges that there is limited validity to the proposed terms, as for the most part they represent a consensus opinion. These definitions need to be validated in existing databases and in future studies, and the primary goals of the task force are to stimulate research on the validity of proposed concepts and further standardize the technical nomenclature.

Factorial multi-task learning : a Bayesian nonparametric approach

Multi-task learning is a paradigm shown to improve the performance of related tasks through their joint learning. However, for real-world data, it is usually difficult to assess the task relatedness and joint learning with unrelated tasks may lead to serious performance degradations. To this end, we propose a framework that groups the tasks based on their relatedness in a subspace and allows a varying degree of relatedness among tasks by sharing the subspace bases across the groups. This provides the flexibility of no sharing when two sets of tasks are unrelated and partial/total sharing when the tasks are related. Importantly, the number of task-groups and the subspace dimensionality are automatically inferred from the data. To realize our framework, we introduce a novel Bayesian nonparametric prior that extends the traditional hierarchical beta process prior using a Dirichlet process to permit potentially infinite number of child beta processes. We apply our model for multi-task regression and classification applications. Experimental results using several synthetic and real datasets show the superiority of our model to other recent multi-task learning methods. Copyright 2013 by the author(s).