P-Curve Analysis of the Köhler Motivation Gain Effect in Exercise Settings: A Demonstration of a Novel Technique to Estimate Evidential Value Across Multiple Studies

Background Practitioners and researchers may not always be able to adequately evaluate the evidential value of findings from a series of independent studies. This is partially due to the possibility of inflated effect size estimates for these findings as a result of researcher manipulation or selective reporting of analyses (i.e., p-hacking). In light of the possible overestimation of effect sizes in the literature, the p-curve analysis has been proposed as a worthwhile tool that may help identify bias across a series of studies focused on a single effect. The p-curve analysis provides a measure of the evidential value in the published literature and might highlight p-hacking practices. Purpose Therefore, the purpose of this paper is to introduce the mechanics of the p-curve analysis to individuals researching phenomena in the psychosocial aspects of behavior and provide a substantive example of a p-curve analysis using findings from a series of studies examining a group dynamic motivation gain paradigm. Methods We performed a p-curve analysis on a sample of 13 studies that examined the Köhler motivation gain effect in exercise settings as a means to instruct readers how to conduct such an analysis on their own. Results The p-curve for studies examining the Köhler effect demonstrated evidential value and that this motivation effect is likely not a byproduct of p-hacking. The p-curve analysis is explained, as well as potential limitations of the analysis, interpretation of the results, and other uses where a p-curve analysis could be implemented.

Human Psychophysiological Activity Estimation Based on Smartphone Camera and Wearable Electronics

This paper presents a study related to human psychophysiological activity estimation based on a smartphone camera and sensors. In recent years, awareness of the human body, as well as human mental states, has become more and more popular. Yoga and meditation practices have moved from the east to Europe, the USA, Russia, and other countries, and there are a lot of people who are interested in them. However, recently, people have tried the practice but would prefer an objective assessment. We propose to apply the modern methods of computer vision, pattern recognition, competence management, and dynamic motivation to estimate the quality of the meditation process and provide the users with objective information about their practice. We propose an approach that covers the possibility of recognizing pictures of humans from a smartphone and utilizes wearable electronics to measure the user’s heart rate and motions. We propose a model that allows building meditation estimation scores based on these parameters. Moreover, we propose a meditation expert network through which users can find the coach that is most appropriate for him/her. Finally, we propose the dynamic motivation model, which encourages people to perform the practice every day.

KEMATANGAN JIWA BERAGAMA

Human beings have two experiences; a) physical, and b) spiritual. The physical growth is based on the chronological age, then that is known as adultery. Whereas the spiritual growth is based on the capability level, and the top of this growth is known as maturity. The growth level that is achieved by every individual will be different. Anyone can be adult physically, not spiritually. To be adult spiritually, someone may be mature in his/her personality soul. The people's soul is mature when the people's mature soul is interrelated with religiosity that is known as a maturity of religious soul. 17zere are six characteristics of maturity: 1) having a good differentiation, 2) having dynamic motivation in spiritual life, 3) having proper implementation of the religion consistently and productively, 4) having comprehensive point of view, 5) having integrated point of view and 6) having high motivation in finding and serving the God.