Data Mining for Attitudinal and Belief Profiles Determination towards Hypnosis

Abstract

Data mining is a technique that aims to explain large data sets through patterns of behavior, associations, changes, or significant structures in the data. The main goal of this study was to analyze information about beliefs and attitudes towards hypnosis, evaluated by the Valencia Scale of Attitudes and Beliefs Toward Hypnosis, Client version (VSABTH-C) in two temporal moments with a total of 444 participants; developing decision trees in order to discover any sociodemographic factors influencing these variables. The results indicate some influence of gender, education level, and profession on the scores in the scale factors, thus women tended to get higher scores on factors such as Control and Fear; people with a higher educational level tended to get higher scores on factors that denote more positive attitudes and beliefs towards hypnosis; in addition, the psychologist participants showed more positive attitudes and beliefs regarding hypnosis. Considering these results, it would be interesting to carry out similar studies, increasing the size of the sample and also adding some new variables, in order to deepen this relationship and implement changes that would lead people to have more positive attitudes and beliefs regarding hypnosis.