خوددلسوزی عنوان پیش بینی کننده امن اجتماعی در دانشجویان دانشگاه ترکیه
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|38919||2015||7 صفحه PDF||سفارش دهید||4371 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Revista Latinoamericana de Psicología, Volume 47, Issue 1, 2015, Pages 43–49
Abstract There are few studies that have examined the role of self-compassion in the context of social life, while self-compassion appears to enhance interpersonal relationship skills. The purpose of this study is to examine the predictive role of self-compassion on social safeness. Participants were 401 university students (213 women, 188 men; M age= 20.5 yr.). In this study, the Self-compassion Scale and the Social Safeness and Pleasure Scale were used. The relationships between self-compassion and social safeness were examined using correlation analysis and multiple regression analysis. In the correlation analysis, self-kindness, common humanity, and mindfulness factors of self-compassion were found to be positively related, and self-judgment, isolation, and over-identification factors of self-compassion were found to be negatively related to social safeness. According to regression results, social safeness was predicted positively by mindfulness, self-kindness, and common humanity. Further isolation predicted social safeness in a negative way. The regression model explained 28% of the variance in social safeness. Together, the findings illuminate the importance of self-compassion on social adjustment. The results are discussed in the light of the related literature.
نتیجه گیری انگلیسی
Results Descriptive data and inter-correlations Table 1 shows the means, standard deviations, inter-correlations, and internal consistency coefficients of the variables used. Table 1. Descriptive statistics, alphas, and inter-correlations of the variables Variables 1 2 3 4 5 6 7 1. Self-kindness — 2. Self-judgment -.25a — 3. Common humanity .53a -.16a — 4. Isolation -.18a .56a -.09 — 5. Mindfulness .66a -.26a .61a -.17a — 6. Over-identification -.21a .60a -.18b .65a -.32a — 7. Social safeness .45a -.23a .42a -.15a .46a -.20a — Mean 14.62 11.93 11.29 11.20 12.01 10.67 37.91 Standard deviation 3.95 4.56 3.22 3.71 3.66 3.79 8.87 Cronbach's α .70 .80 .73 .79 .66 .85 .79 a p < .01. b p < .05. Table options Self-kindness, common humanity, and mindfulness were found positively and self-judgment, isolation, and over-identification were found negatively associated with social safeness. There were also significant correlations between dimensions of self-compassion. Self-kindness, common humanity, and mindfulness were positively correlated with one another while self-judgment, isolation, and over-identification were positively associated with one another. On the other hand, self-kindness, common humanity, and mindfulness were negatively related to self-judgment, isolation, and over-identification. Multiple regression analysis Before applying regression, assumptions of multiple regression were verified. In order to run parametric tests, the data were examined for normality by means of the Kolmogorov-Smirnov test. The Kolmogorov-Smirnov test indicated normality of distributions of test scores for all tests in the current study, and hierarchical multiple regression analysis was subsequently conducted. Outliers are cases that have data values that are very different from the data values for the majority of cases in the data set. Outliers were investigated using Mahalanobis distance. A case is an outlier if the probability associated with its D2 is .001 or less ( Tabachnick & Fidell, 2001). Based on this criterion, nine pieces of data were labeled as outliers and they were deleted. Multicollinearity was verified by means of variance inflation factors (VIF). All VIF values were less than 10 ( Tabachnick & Fidell, 2001), which indicated that there was no severe multicollinearity. Multiple regression analysis was performed in which the dependent variable was social safeness and the independent variables were dimensions of self-compassion. According to the results of multiple regression analysis, summarized in table 2, mindfulness entered the equation first, accounting for 21% of the variance in predicting social safeness (R2 = .21, adjusted R2 = .21, F(1, 398) = 105,795, p < .01). Self-kindness entered secondly accounting for an additional 4% variance (R2 = .25, ΔR2 = .05, adjusted R2 = .25, F(2, 397) = 66,023, p < .01). Common humanity entered thirdly accounting for an additional 2% variance (R2 = .27, ΔR2 = .02, adjusted R2 = .27, F(3, 396) = 48,930, p < .01). Isolation entered last, accounting for an additional 1% variance (R2 = .28, ΔR2 = .01, adjusted R2 = .27, F(4, 395) = 38,291, p < .01). Despite the initial regression design included mindfulness, common humanity, self-kindness, over-identification, isolation, and self-judgment as independent variables, the last regression model involved mindfulness, self-kindness, common humanity, and isolation as predictors of social safeness and accounted for 28% of the variance. The standardized beta coefficients indicated the relative influence of the variables in last model with mindfulness (β = .18, p < .01), self-kindness (β = .21, p < .01), common humanity (β = .19, p < .01), and isolation (β = −.10, p < .01) all significantly influencing social safeness and self-kindness was the strongest predictor. Table 2. Summary of multiple regression analysis for variables predicting social safeness Model Variables B Standard error of B β t * Model 1 Constant 24.57 1.36 18.10 Mindfulness 1.11 .11 .46 10.29 Model 2 Constant 20.94 1.54 13.57 Mindfulness .69 .14 .29 4.97 Self-kindness .59 .13 .26 4.58 Model 3 Constant 19.04 1.63 11.71 Mindfulness .49 .15 .20 3.25 Self-kindness .50 .13 .22 3.79 Common humanity .51 .15 .19 3.36 Model 4 Constant 22.25 2.17 10.25 Mindfulness .45 .15 .18 2.96 Self-kindness .46 .13 .21 3.53 Common humanity .52 .15 .19 3.42 Isolation -.19 .09 -.10 -2.21 * All p < .05.