Imagery or video feedback : which is the "route" to strategic improvement?

The implementation of imagery and video feedback programs has become an important tool for aiding athletes in achieving peak performance (Halliwell, 1990). The purpose of the study was to determine the effect of strategic imagery training and video feedback on immediate performance. Participants were two university goaltenders. An alternating treatment design (ATD; Barlow & Hayes, 1979; Tawney & Gast, 1984) was employed. The strategies were investigated using three plays originating from the right side by a right-handed shooting defenceman from the blueline. The baseline condition consisted of six practices and was used to establish a stable and "ideal" measure of performance. The intervention conditions included alternating the use of strategic imagery (Cognitive general; Paivio, 1985) and video feedback. Both participants demonstrated an increase in the frequency of Cognitive general use. Specific and global performance measures were assessed to determine the relative effectiveness of the interventions. Poor inter-rater reliability resulted in the elimination of specific performance measures. Consequently, only the global measure (i.e., save percentage) was used in subsequent analyses. Visual inspection of participant save percentage was conducted to determine the benefits of the intervention. Strategic imagery training resulted in performance improvements for both participants. Video feedback facilitated performance for Participant 2, but not Participant 1. Results are discussed with respect to imagery and video interventions and the challenges associated with applied research. KEYWORDS: imagery, video, goaltenders, alternating treatment design.

Comparison of non-HDL cholesterol and waist circumference vs. triglyceride levels and waist circumference in predicting coronary heart disease risk

BACKGROUND: Dyslipidemia is recognized as a major cause of coronary heart disease (CHD). Emerged evidence suggests that the combination of triglycerides (TG) and waist circumference can be used to predict the risk of CHD. However, considering the known limitations of TG, non-high-density lipoprotein (non-HDL = Total cholesterol - HDL cholesterol) cholesterol and waist circumference model may be a better predictor of CHD. PURPOSE: The Framingham Offspring Study data were used to determine if combined non-HDL cholesterol and waist circumference is equivalent to or better than TG and waist circumference (hypertriglyceridemic waist phenotype) in predicting risk of CHD. METHODS: A total of3,196 individuals from Framingham Offspring Study, aged ~ 40 years old, who fasted overnight for ~ 9 hours, and had no missing information on nonHDL cholesterol, TG levels, and waist circumference measurements, were included in the analysis. Receiver Operator Characteristic Curve (ROC) Area Under the Curve (AUC) was used to compare the predictive ability of non-HDL cholesterol and waist circumference and TG and waist circumference. Cox proportional-hazards models were used to examine the association between the joint distributions of non-HDL cholesterol, waist circumference, and non-fatal CHD; TG, waist circumference, and non-fatal CHD; and the joint distribution of non-HDL cholesterol and TG by waist circumference strata, after adjusting for age, gender, smoking, alcohol consumption, diabetes, and hypertension status. RESULTS: The ROC AUC associated with non-HDL cholesterol and waist circumference and TG and waist circumference are 0.6428 (CI: 0.6183, 0.6673) and 0.6299 (CI: 0.6049, 0.6548) respectively. The difference in the ROC AVC is 1.29%. The p-value testing if the difference in the ROC AVCs between the two models is zero is 0.10. There was a strong positive association between non-HDL cholesterol and the risk for non-fatal CHD within each TO levels than that for TO levels within each level of nonHDL cholesterol, especially in individuals with high waist circumference status. CONCLUSION: The results suggest that the model including non-HDL cholesterol and waist circumference may be superior at predicting CHD compared to the model including TO and waist circumference.