Modeling and imagery are distinct but related psychological skills. However, despite sharing similar cognitive processes, they have traditionally been investigated separately. While modeling has shown similar psychological and physical performance benefits as imagery, it remains an understudied technique within applied sport psychology. Social cognitive and direct perception approaches remain often-used explanations for the effectiveness of modeling on skill acquisition; however, emergent neuropsychological explanations provide evidence to support these earlier theories and a link to the imagery literature. With advances in technology and the development of applied frameworks, there is renewed interest in exploring modeling effects and how they parallel imagery use in applied settings. Specifically, modeling research has expanded beyond controlled laboratory settings to explore the effect of various theoretical models on motor performance and related cognitions within practice and competitive settings. The emergence of affordable video editing technology makes it easy for coaches and athletes to incorporate modeling into practice. The accessibility of video technology has sparked applied research on how various forms of modeling influence motor performance and cognitions, such as confidence and motivation. These applied investigations demonstrate the complementary nature of modeling and imagery in enhancing sport performance and skill acquisition, while highlighting the challenges in separating modeling and imagery effects. Both literatures offer possibilities for new methodological approaches and directions for studying these psychological skills in tandem as well as independently. Thus, there is much that imagery and modeling researchers can learn from each other in sport and other performance settings.
Barbi Law, Phillip Post, and Penny McCullagh
What are the local consequences of a global climate change? This question is important for proper handling of risks associated with weather and climate. It also tacitly assumes that there is a systematic link between conditions taking place on a global scale and local effects. It is the utilization of the dependency of local climate on the global picture that is the backbone of downscaling; however, it is perhaps easiest to explain the concept of downscaling in climate research if we start asking why it is necessary. Global climate models are our best tools for computing future temperature, wind, and precipitation (or other climatological variables), but their limitations do not let them calculate local details for these quantities. It is simply not adequate to interpolate from model results. However, the models are able to predict large-scale features, such as circulation patterns, El Niño Southern Oscillation (ENSO), and the global mean temperature. The local temperature and precipitation are nevertheless related to conditions taking place over a larger surrounding region as well as local geographical features (also true, in general, for variables connected to weather/climate). This, of course, also applies to other weather elements. Downscaling makes use of systematic dependencies between local conditions and large-scale ambient phenomena in addition to including information about the effect of the local geography on the local climate. The application of downscaling can involve several different approaches. This article will discuss various downscaling strategies and methods and will elaborate on their rationale, assumptions, strengths, and weaknesses. One important issue is the presence of spontaneous natural year-to-year variations that are not necessarily directly related to the global state, but are internally generated and superimposed on the long-term climate change. These variations typically involve phenomena such as ENSO, the North Atlantic Oscillation (NAO), and the Southeast Asian monsoon, which are nonlinear and non-deterministic. We cannot predict the exact evolution of non-deterministic natural variations beyond a short time horizon. It is possible nevertheless to estimate probabilities for their future state based, for instance, on projections with models run many times with slightly different set-up, and thereby to get some information about the likelihood of future outcomes. When it comes to downscaling and predicting regional and local climate, it is important to use many global climate model predictions. Another important point is to apply proper validation to make sure the models give skillful predictions. For some downscaling approaches such as regional climate models, there usually is a need for bias adjustment due to model imperfections. This means the downscaling doesn’t get the right answer for the right reason. Some of the explanations for the presence of biases in the results may be different parameterization schemes in the driving global and the nested regional models. A final underlying question is: What can we learn from downscaling? The context for the analysis is important, as downscaling is often used to find answers to some (implicit) question and can be a means of extracting most of the relevant information concerning the local climate. It is also important to include discussions about uncertainty, model skill or shortcomings, model validation, and skill scores.
Sam Zizzi and Jana L. Fogaca
The process of learning to be a licensed and competent service provider in psychology typically involves supervision by a seasoned professional. Quality supervision is the cornerstone of effective, ethical practice in psychology. This process of supervision can take on many structures and involves a series of informal and formal meetings between the student and the professional. Sometimes, this supervision will involve co-therapy where the supervisor leads a session with the client while the student watches, or vice versa. The supervisor will direct students in how to prepare for and conduct their work and how to document their sessions and give them specific feedback to improve their skills. As students build competence, the supervisor may decide to give them more independence so they can make their own decisions about treatment plans and take a leadership role with clients. In exercise settings, this supervision process is a little different from sport settings. The focus of most exercise consultations with clients will be on changing health behavior instead of improving sport performance. Also, instead of spending time at practice fields or athletic events in a sport consultation, the students would be expected to spend time in fitness and wellness centers around clients with myriad health issues. These experiences are designed to help students feel autonomous in their decision-making, and to reduce their anxiety working with clients. This process may take a few months to a couple of years depending on the skills and training of the student before supervision.
Digital technologies are frequently said to have converged. This claim may be made with respect to the technologies themselves or to restructuring of the media industry over time. Innovations that are associated with digitalization (representing analogue signals by binary digits) often emerge in ways that cross the boundaries of earlier industries. When this occurs, technologies may be configured in new ways and the knowledge that supports the development of services and applications becomes complex. In the media industries, the convergence phenomenon has been very rapid, and empirical evidence suggests that the (de)convergence of technologies and industries also needs to be taken into account to understand change in this area. There is a very large literature that seeks to explain why convergence and (de)convergence phenomena occur. Some of this literature looks for economic and market-based explanations on the supply side of the industry, whereas other approaches explore the cultural, social, and political demand side factors that are important in shaping innovation in the digital media sector and the often unexpected pathways that it takes. Developments in digital media are crucially important because they are becoming a cornerstone of contemporary information societies. The benefits of digital media are often heralded in terms of improved productivity, opportunities to construct multiple identities through social media, new connections between close and distant others, and a new foundation for democracy and political mobilization. The risks associated with these technologies are equally of concern in part because the spread of digital media gives rise to major challenges. Policymakers are tasked with governing these technologies and issues of privacy protection, surveillance, and commercial security as well as ensuring that the skills base is appropriate to the digital media ecology need to be addressed. The complexity of the converged landscape makes it difficult to provide straightforward answers to policy problems. Policy responses also need to be compatible with the cultural, social, political, and economic environments in different countries and regions of the world. This means that these developments must be examined from a variety of disciplinary perspectives and need to be understood in their historical context so as take both continuities and discontinuities in the media industry landscape into account.
Ronald E. Smith and Frank L. Smoll
Coaches occupy a central role in sport, fulfilling instructional, organizational, strategic, and social relationship functions, and their relationships with athletes influence both skill development and psychosocial outcomes of sport participation. This review presents the major theoretical models and empirical results derived from coaching research, focusing on the measurement and correlates of coaching behaviors and on intervention programs designed to enhance coaching effectiveness. A strong empirical literature on motor skill development has addressed the development of technical sport skills, guided in part by a model that divides the skill acquisition process into cognitive, associative, and autonomous phases, each requiring specific coaching knowledge and instructional techniques. Social-cognitive theory’s mediational model, the multidimensional model of sport leadership, achievement goal theory, and self-determination theory have been highly influential in research on the psychosocial aspects of the sport environment. These conceptual models have inspired basic research on the antecedents and consequences of defined coaching behaviors as well as applied research on coach training programs designed to enhance athletes’ sport outcomes. Of the few programs that have been systematically evaluated, outcomes such as enjoyment, liking for coach and teammates, team cohesion, self-esteem, performance anxiety, athletes’ motivational orientation, and sport attrition can be influenced in a salutary fashion by a brief intervention with specific empirically derived behavioral guidelines that focus on creating a mastery motivational climate and positive coach-athlete interactions. However, other existing programs have yet to demonstrate efficacy in controlled outcome research.