A New Structural Equation Modeling of Psychophysiological Measures and Multidimensional State Anxiety Induced by Autogenic Training

The effectiveness of Autogenic Training on the stress response is two-fold: Produces a switch from sympathetic (fight/flight) dominance to parasympathetic dominance with increased activity of the rest/digest, relaxation/restorative system. Biofeedback is an evidence-based mind-body technique where individuals learn to consciously control their physiology. Most psychophysiological research investigating the link between anxiety and physiology has been conducted in the laboratory. When anxiety is measured as it occurs naturally in a real-life setting, it is more representative of that experienced by individuals in their day to day lives especially during sport competition.In competitive ten-pin bowling, it is most probable that technical and psychological skills. Thus, by using various psychophysiological measures, we can examine state anxiety level of the ten-pin bowlers. From the existing literature search, no previous studies have investigated the correlations of Autogenic Training on Psychophysiological Measures and Multidimensional State Anxiety with Structural Model with a Reflective Model Constructs with PLS-SEM in sport psychology research. At such, the main aim of this study was to construct a statistical model using SmartPLS to explore the linear relationships of single independent variable (Autogenic Training) on the multiple dependent variables (Psychophysiological Measures & Multidimensional State Anxiety) in elite bowlers prior to competition.Through the analysis of the structural equation model using formal study data, CR and AVE of the model indicated that measurement model had good internal consistency, convergent validity, and discriminant validity. The path shows that the influence of independent variables on dependent variables. Also, from the analysis of the structural model, the R² value (coefficient of determination) showed that the model has higher prediction accuracy. In addition, the SRMR results obtained indicate that the model fits well. Therefore, this model can be put forward for the use in managing the multidimensional state anxiety of the athletes prior to competition.