Identifying the relationship between human self-esteem and general health using data mining

There exist a lot of data associated with psychology, nowadays. Using data mining science, the relation between different subjects including self-esteem, general health, depression, etc. can be detected. Self-esteem is considered a subject of great importance in psychology, since it is one of the most significant factors in favorable human growth which shows how one feels about his worthiness and self-confirmation. Depression is a psychic state which is identified by the person's unhappiness over time. Mental health, which is a significant moderator in the process of stress, plays a vital role in mitigating stress, increasing health, and improving the quality of life in the society. In order that the level of self-esteem would be measured, special questionnaires are used. Proper and accurate analysis of the questionnaires is one of the challenges of psychology. Several efforts have been made to improve the quality of processing psychological data by using through artificial intelligence. In the present paper, the relation between self-esteem and general health has been analyzed using Coopersmith's self-esteem questionnaire, Goldberg's general health questionnaire, clustering algorithms, and semantic data mining techniques. The results have shown that low self-esteem has a weak relationship with three out of four general health subscales; however, there has been a strong relationship with three subscales in high self-esteem levels.