Vol.6 No.10 (October 2016)
Statistic Analysis of Medical Depression Index
Chongqing Medical and Pharmaceutical College students were selected to study on student poten-tial depression index with path analysis and principal components analysis from seven relevant factors (Doing group activities (X1), Office of students cadres (X2), Academic frustration (X3), Family economic conditions (X4), Emotion frustration (X5), Bodily injury (X6), Family emotional atmosphere (X7)). The main results were summarized as follows: 1) The results with correlation and path analysis: student potential depression index had the most significant positive correlations with emotion frustration and academic frustration, and negative correlation with family emotional atmosphere. Emotion frustration had the most positive influence on student potential depression index with the direct path coefficient 0.7371. The second was academic frustration with the direct path coefficient 0.1321. The influence sizes of other characters orderly were bodily injury (0.076), doing group activities (0.0089), family emotional atmosphere (−0.0870), family economic conditions (−0.0481) and office of students’ cadres (−0.0272). The absolute value of path coefficient for family emotional atmosphere was third, ranking after emotional frustration and academic frustration. 2) The results with principal components analysis: The contribution ratio of accumulated variance reached 91.08%. The 5 principal components reflected student potential depression index. The first principal component was a factor of inner pressure resistance; the second and the fifth principal components were a factor of participate in collective activities and organization ability; the third principal component was a factor of interpersonal relationship and the forth principal component was a factor of family economic conditions. Emotion frustration, academic frustration, and family emotional atmosphere were the most important factors to affect student potential depression index. Academic frustration ranked second after emotion frustration, not first. It showed that non academic factors influence student potential depression index and that it needs improvement of methods and areas for students’ psychological counseling.
陈俊意 , 兰 丁 , 郭 兵 (2016) 医学专科学校学生潜在忧郁指数的统计分析。 心理学进展， 6， 1117-1125. doi: 10.12677/AP.2016.610141
 赵振环, 黄悦勤, 李洁(2009). 广州地区常住人口精神障碍的患病率调查. 中国神经精神疾病杂志, 12(9), 35-38.
 周洁(2010). 五大人格问卷(BFI)的结构效度分析. 管理观察, 3(30), 35-38.
Goodwin, R. D., & Gotlib, I. H. (2004). Gender Differences in Depression: The Role of Personality Factors. Psychiatry Research, 126, 135-142.
 John, O. P., Donahue, E. M., & Kentle, R. L. (1991). The Big Five Inventory: Versions 4a and 54. Berkeley, CA: Institute of Personality and Social Research
Kendler, K. S. (1997). The Diagnostic Validity of Melancholic Major Depression in a Population-Based Sample of Female Twins. Archives of General Psychiatry, 54, 299-304.
Leventhal, A. M., & Rehm, L. P. (2005). The Empirical Status of Melancholia: Implications for Psychology. Clinical Psychology Review, 25, 25-44.
Michopoulos, I., Zervas, I. M., Pantelis, C. et al. (2008). Neuropsychological and Hypothalamic-Pituitary-Axis Function in Female Patients with Melancholic and Non-Melancholic Depression. European Archives of Psychiatry and Clinical Neuroscience, 258, 217-225.
Monzon, S., Gili, M., Vives, M. et al. (2010). Melancholic versus Nonmelancholic Depression: Differences on Cognitive Function. A Longitudinal Study Protocol. BMC Psychiatry, 10, 48.
Parker, G., McCraw, S., Blanch, B. et al. (2012). Discriminating Melancholic and Non-Melancholic Depression by Prototypic Clinical Features. Journal of Affective Disorders, 144, 199-207.
Sun, N., Li, Y., Cai, Y. et al. (2012). Comparison of Melancholic and Nonmelancholic Recurrent Major Depression in Han Chinese Women. Depression and Anxiety, 29, 4-9.