| BackgroundMobile phone dependent refers to the addiction state in which the physiological, psychological and social function of the individual are significantly impaired because of the immoderate use of mobile phone. With the popularization of network information, and the maturity of intelligence, mobile phone dependence is growing as a new type of addictive behavior, and the frequent use of mobile phone will increase the tendency. The vicious spiral and popularity of mobile phone dependence has become the research focus of public health and social psychology. Therefore, it is of great theoretical and practical significance to pay attention to the development of mobile phone dependence and attribution style, impulse and loneliness of college students.Objectives1. To get theoretical research evidence related to the situation of mobile phone dependence through investigation of the mobile phone dependence of college students;2. To investigate the relationship among mobile phone dependence and attributional style, loneliness, impulsiveness in college students and analyze their mechanism of action to provide theoretical support for improving the dependence.MethodsCluster random sampling method is adopted in this study. From October 1,2015 to March 1,2016, undergraduate students are selected as the research object in Xinxiang University, Xinxiang Medical University, Sanquan Medical College of Xinxiang Medical University and Henan Institute of Science and Technology with an average age of 21.39 ± 0.53, covering medicine, arts and science majors.1500 questionnaires were handed out while 1261 valid questionnaires were taken back. The Mobile Phone Addiction Index Scale (MPAI),the Attributional Style Questionnaire(ASQ),Barratt Impulsiveness Scale(BIS-11),UCLA Loneliness Scale(University of California at Los Angels)were adopted to investigate the relationship between college students'mobile phone dependence, attribution, impulsivity and loneliness, and to analyze their mechanism of action on mobile phone dependence. All data are encoded and the original database is established. SPSS13.0 and AMOS15.0 were adapted to statistically deal with the data. Statistical methods include statistics, independent samples test, one-way ANOVA, Pearson correlation analysis, stepwise regression analysis and path analysis etc. the test level was taken as ?=0.05 (bilateral inspection).Results1. In gender differences, female college students' positive attribution, negative attribution factor score was significantly higher than that of boys (t=4.561, P<0.001; t=7.384, P<0.001); male college students'loneliness score was significantly higher than that of girls (t=5.824, P<0.001). In grade differences, mobile phone dependence scores of the first grade, the fifth grade and the fourth grade were significantly higher than that of the second grade (t=2.549, P=0.013; t=2.798, P=0.010); negative attribution score of the fourth grade and the fifth grade were significantly higher than that of the third grade (t=2.332, P=0.021); impulse score of the first grade was significantly higher than that of the third grade and the fifth grade (t=4.356, P<0.001; t=3.986, P<0.001); the attribution score of the fourth grade and the fifth grade were significantly higher than that of the third grade (t=4.132, P<0.001); unplanned impulse score of the first grade was significantly higher than that of the third grade (t=2.367, P=0.018); loneliness score of the first grade was significantly higher than that of the third grade (t=3.357, P=0.006). In urban and rural areas, the negative attribution factors of urban college students were significantly higher than those of rural college students (t=2.905, P=0.004).2. The score of being uncontrolled under high positive attribution factors was significantly higher than that under low positive attribution factors (t=7.684, P<0.001); the total score of mobile phone dependence and the score of being uncontrolled, withdrawal, escape and ineffectiveness under high negative attribution factors were significantly higher than that under low negative attribution factors (t=9.621, P<0.001;t=6.986, P<0.001; t=8.684, P<0.001; t=6.395, P<0.001; t=5.586, P<0.001). The total score of mobile phone dependence and the score of being uncontrolled, withdrawal, escape and ineffectiveness under high impulsivity factors were significantly higher than that under low impulsivity factors. (t=13.631, t=5.766, P<0.001; t=7.663, P<0.001; t=9.439 P<0.001; t=9.552, P<0.001).3. Mobile phone dependence and the scores of positive attribution and negative attribution factors, impulsivity of attention, motoricity, and being unplanned, and loneliness showed a significant positive correlation; in attribution factors, the score of positive attribution factor and the score of negative attribution factor score was positively correlated, while it was negatively correlated with the score of impulsivity of attention, motoricity, and being unplanned, and loneliness. And the correlationship was statistically meaningless; in impulsive factors, the score of impulsivity of attention, motoricity, and being unplanned and the score of loneliness score was significantly positively correlated.4. Taking college students'mobile phone dependence as the dependent variable, and the score of positive attribution, negative attribution factor, impulse and loneliness as the indepen-dent variable, we can get the multiple stepwise regression equation: y=0.638+0.177x1+0.461x2+0.418x3 The independent variable negative attribution factor, the impulse and the sense of loneliness were 0.674 (F=127.862, P<0.001) to explain the variance of the dependent variable cell phone dependence.5. Through the construction of mobile phone dependence of model between impulsivity and loneliness, we can get that the loneliness of a direct effect on the mobile phone dependence is 0.42, and the intermediary function of impulsivity between loneliness and mobile phone dependence is 0.233, taking up 55.48% of the total effect.Conclusions1. The positive attribution and negative attribution of the female college students are higher than male students; the scores of loneliness of male college students are significantly higher than that of female students; the negative attribution of urban students is higher than that of rural students.2. The higher the negative attribution, impulse and loneliness, the more obvious the mobile phone dependence.3. Negative attribution factors, impulsivity and loneliness dependent variables to explain the variation of mobile phone R2 is 0.674; the direct effect of the loneliness on the mobile phone dependence is 0.42, the intermediary function of impulsivity between loneliness and mobile phone dependence is 0.233. Negative attribution, impulse and loneliness have positive prediction function on cell phone dependence. |
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