| Literature DB >> 33100455 |
Angyang Li1, Shuo Wang2, Minmin Cai3, Ruiqi Sun3, Xiangping Liu1.
Abstract
Concern for the psychological health of people affected by the COVID-19 pandemic is necessary. Previous studies suggested that self-compassion contributes to life-satisfaction. However, little is known about the mechanism underlying this relation. This study investigated the relationship between self-compassion and life-satisfaction among Chinese self-quarantined residents during the COVID-19 pandemic. Furthermore, we examined the mediating effect of positive coping and the moderating role of gender in this relation. Participants consist of 337 self-quarantined residents (129 men, 208 women) from a community in China, who completed measures of demographic information, Self-Compassion Scale, Satisfaction with Life Scale, and Simplified Coping Style Questionnaire. The results revealed that self-compassion was positively linked with life-satisfaction. Moreover, positive coping partially mediated the relationship between self-compassion and life-satisfaction for males and not females. In the female group, self-compassion was positively linked with positive coping and life-satisfaction; however, positive coping and life-satisfaction were not significantly linked. These findings indicated that intervention focus on self-compassion could increase life-satisfaction in self-quarantined people during the COVID-19, and self-compassion may contribute to life-satisfaction via positive coping only in the male.Entities:
Keywords: COVID-19 pandemic; Chinese self-quarantined residents; Gender; Life-satisfaction; Positive coping; Self-compassion
Year: 2020 PMID: 33100455 PMCID: PMC7576372 DOI: 10.1016/j.paid.2020.110457
Source DB: PubMed Journal: Pers Individ Dif ISSN: 0191-8869
Fig. 1Proposed moderated mediation model.
Note. This figure illustrates the proposed model of the current study. Self-compassion relates to life-satisfaction via positive coping. Gender moderates the relationship between positive coping and life-satisfaction.
Demographic characteristic of the participants (n = 337).
| Variables | N | % |
|---|---|---|
| Female | 208 | 62.7 |
| Male | 129 | 38.2 |
| 18–25 | 6 | 1.8 |
| 26–30 | 11 | 3.3 |
| 31–40 | 129 | 38.3 |
| 41–50 | 112 | 33.2 |
| 51–60 | 68 | 20.2 |
| ≥60 | 11 | 3.3 |
| Students | 7 | 2.1 |
| Teacher | 43 | 12.8 |
| Human resource | 24 | 7.1 |
| Production worker | 25 | 7.4 |
| Customer service | 3 | 0.9 |
| Salesman | 14 | 4.2 |
| Professional employee | 11 | 3.3 |
| Technical employee | 2 | 0.6 |
| Officer | 4 | 1.2 |
| Support crew | 10 | 3.0 |
| Manager | 3 | 0.9 |
| Others | 191 | 56.7 |
| Very low | 5 | 1.50 |
| Low | 111 | 32.90 |
| Medium | 182 | 54.00 |
| High | 39 | 11.60 |
| Never | 1 | 0.30 |
| Rarely | 27 | 8.0 |
| Often | 166 | 49.3 |
| Always | 143 | 42.4 |
Results of independent-sample t-test in different gender among variables (n = 337).
| Male ( | Female ( | Cohen's | ||||
|---|---|---|---|---|---|---|
| 3.97 | 0.57 | 3.99 ± 0.53 | 3.94 ± 0.63 | 0.66 | 0.507 | 0.086 |
| 1.65 | 0.61 | 1.51 ± 0.67 | 1.78 ± 0.55 | −3.81 | <0.001 | 0.443 |
| 4.43 | 1.22 | 4.46 ± 1.28 | 4.40 ± 1.22 | 0.49 | 0.63 | 0.048 |
Pearson correlations among variables (n = 337).
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |
|---|---|---|---|---|---|---|---|---|
| 1. LS | – | |||||||
| 2. PC | 0.21 | – | ||||||
| 3. SC | 0.43 | 0.29 | – | |||||
| 4. Gender | 0.05 | 0.02 | −0.03 | – | ||||
| 5. Age | 0.11 | 0.13 | 0.08 | 0.04 | – | |||
| 6. Occupation | 0.03 | −0.01 | 0.10 | 0.17 | 0.54 | – | ||
| 7. SES | 0.09 | 0.28 | 0.23 | −0.12 | 0.00 | −0.10 | – | |
| 8. AD | 0.15 | 0.31 | 0.23 | −0.09 | 0.19 | 0.04 | 0.49 | – |
Notes. SC = self-compassion, PC = positive coping, LS = life-satisfaction, AD = attention-degree of COVID-19: 0 = never, 1 = rarely, 2 = often, 3 = always, SES = subjective economic status: very low = 1, low = 2, medium = 3, high = 4, very high = 5, gender: male = 0; female = 1.
p < .05(two-tailed).
p < .01(two-tailed).
p < .001(two-tailed).
Mediation model and moderated mediation model (N = 337).
| Process | Variables | Model 4 | Model 14 | ||||
|---|---|---|---|---|---|---|---|
| β | SE | t | β | SE | t | ||
| 1. Mediator variable model (PC) | constant | −0.16 | 0.25 | −0.65 | −1.89 | 0.25 | −7.65 |
| SC | 0.24 | 0.06 | 4.28 | 0.24 | 0.06 | 4.28 | |
| Age | 0.05 | 0.02 | 2.17 | 0.05 | 0.02 | 2.17 | |
| Occupation | −0.01 | 0.01 | −1.67 | −0.01 | 0.01 | −1.67 | |
| SES | 0.12 | 0.05 | 2.19 | 0.12 | 0.05 | 2.19 | |
| AD | 0.16 | 0.06 | 2.82 | 0.16 | 0.06 | 2.82 | |
| R2 = 0.42, | R2 = 0.42, | ||||||
| 2. Dependent variable model (LS) | constant | 0.77 | 0.50 | 1.55 | 0.88 | 0.55 | 1.61 |
| SC | 0.61 | 0.10 | 6.14 | 0.61 | 0.10 | 6.12 | |
| PC | 0.08 | 0.05 | 1.68 | 0.13 | 0.11 | 1.12 | |
| Age | −0.01 | 0.01 | −1.07 | 0.08 | 0.05 | 1.68 | |
| Occupation | −0.07 | 0.11 | −0.61 | −0.02 | 0.01 | −1.23 | |
| SES | 0.12 | 0.12 | 1.03 | −0.08 | 0.11 | −0.75 | |
| AD | 0.77 | 0.5 | 1.55 | 0.12 | 0.77 | 0.11 | |
| Gender | 0.16 | 0.13 | 1.28 | ||||
| PC ∗ gender | −0.41 | 0.17 | −2.41 | ||||
| R2 = 0.42, | R2 = 0.43, F( | ||||||
Notes. SC = self-compassion, PC = positive coping, LS = life-satisfaction, AD = attention-degree of COVID-19: 0 = never, 1 = rarely, 2 = often, 3 = always, ses = subjective economic status: very low = 1, low = 2, medium = 3, high = 4, very high = 5, gender: male = 0; female = 1, CI = confidence interval. All βs in this table are unstandardized coefficients.
p < .05(two-tailed).
p < .001(two-tailed).
Fig. 2Gender as a moderator of the relationship between positive coping and life-satisfaction.
Note. PC = positive coping. Low PC means one standard deviation below the mean of PC; High PC means one standard deviation above the mean of PC. This figure illustrates gender differences in the relationship between positive coping and life-satisfaction. For the male group, positive coping positively relates to life-satisfaction. For the female group, positive coping is not significantly linked with life-satisfaction.