Subject demographic and clinical characteristics
Table 1 shows the demographic and clinical characteristics of the subjects. On average, patients were 43.2 years old (SD = 13.4). Of these, 147 (51.6%) are men, 84.2% (240) are married or cohabiting, 162 (56.9%) have junior college or higher education, 245 (86.0%) are urban, 222 (77.9%) %) have a job, and 119 (41.8%) reported a monthly household income of less than 5,000 yuan. Regarding clinical characteristics, the mean BMI was 27.3 kg/m.2 (standard deviation = 3.7). Of these subjects, 196 (68.8%) had a duration of NAFLD ≤6 months, the majority of subjects (243, 85.3%) had simple fatty liver, and 153 (53.7%) had comorbidities. 117 (41.1%) of those who had the disease received treatment.
Correlations between rumination, anxiety symptoms, resilience, and PSQI scores
The descriptive statistics of rumination, anxiety symptoms, resilience and PSQI scores and the correlations between them are shown in Table 2. PSQI scores revealed a strong positive correlation with anxiety symptoms (r = 0.524, P. < 0.01) and a weak positive correlation with brooding (r = 0.252, P. < 0.01), reflection (r = 0.272, P. < 0.01), rumination (r= 0.280, P.< 0.01). However, it was weakly and negatively correlated with resilience (r = -0.230, P.< 0.01). Anxiety symptoms were moderately positively correlated with brooding (r= 0.405, P.< 0.01), reflection (r= 0.388, P.< 0.01), rumination (r= 0.426, P.< 0.01) and a moderately negative correlation with resilience (r= -0.396, P.< 0.01). There was a strong positive correlation between brooding, reflection, and rumination. Resilience was inversely and weakly correlated with pessimism (r= -0.239, P.< 0.01), reflection (r= -0.233, P.< 0.01), rumination (r= -0.253, P.< 0.01).
The mediation model results are shown in Table 3. The path coefficients are: c(association of brooding, contemplation, rumination and PSQI scores), a(Relationship between brooding, introspection, rumination and anxiety symptoms), b(Relationship between anxiety symptoms and PSQI scores), c’(association of brooding, introspection, and rumination with PSQI scores after adding anxiety symptoms), and a× b(product of aWhenb, indicating the size of the mediation). In univariate analysis (Additional File 1), demographic and clinical variables such as age, gender, occupation, monthly household income, duration of NAFLD, and disease severity were associated with anxiety symptoms or PSQI scores. was (P.< 0.1). These variables were therefore added to the regression model as covariates. Anxiety symptoms played an important role in explaining the positive association with brooding (a×b= 0.187, 95% CI: 0.110 to 0.273), reflection (a×b= 0.169, 95% CI: 0.093–0.255) and rumination (a× b= 0.189, 95% CI: 0.111 to 0.274), PSQI scores, respectively. ratio ( a×b/ c× 100%), the role of anxiety symptoms was 77.3%, 64.3%, and 70.3%, respectively. For a dismal model, the explanatory power of the model (R.2), anxiety symptoms and PSQI scores reached 21.7% and 30.4%, respectively. For the reflection model, R.2 Anxiety symptoms and PSQI scores reached 19.7% and 30.9%, respectively. For the rumination model,R.2 Anxiety symptoms and PSQI scores reached 22.7% and 30.7%, respectively.
Moderate mediation model
Figure 2 shows the results of the tuned arbitration model. β= -0.175,P.< 0.01), reflection ( β= -0.137,P.< 0.01) and rumination ( β= -0.147,P.< 0.01) anxiety symptoms were significantly alleviated by resilience. An additional 4.9%, 3.3%, and 3.9% of the variance in anxiety symptoms was explained by interactions with brooding, introspection, rumination and resilience. These associations gradually decreased with increasing resilience. For the brood-anxiety symptom association, low resilience ( β= 0.438,P.< 0.001), medium resilience ( β= 0.264,P.< 0.001), high resilience ( β= 0.089,P.= 0.210); the relationship between remorse and anxiety symptoms is low resilience ( β= 0.366,P.< 0.001), medium resilience ( β= 0.229,P.< 0.001), high resilience ( β= 0.092,P.= 0.219); the association between rumination and anxiety symptoms was less resilient ( β= 0.414, P.< 0.001) moderate elasticity ( β= 0.266, P.< 0.001), high resilience (β= 0.119, P.= 0.100). The role of resilience mitigation is plotted in Figure 3. The associations between brooding, reflexes, and rumination and PSQI scores were not significantly moderated by resilience. For breeding models, R.2 Anxiety symptoms and PSQI scores reached 34.9% and 30.8%, respectively. For the reflection model,R.2 Anxiety symptoms and PSQI scores reached 32.2% and 31.1%, respectively. For the rumination model,R.2 Anxiety symptoms and PSQI scores reached 34.7% and 31.0%, respectively.
As shown in Table 4, the role of anxiety symptoms in explaining the association between brooding and PSQI scores steadily decreased with increasing resilience (low resilience: 0.200, 95% CI: 0.118, 0.302; moderate resilience: 0.120, 95% CI: 0.064, 0.192; high resilience: 0.041, 95% CI: -0.018, 0.109). For the reflection model, the role of anxiety symptoms was: low resilience ( 0.167, 95% CI: 0.098, 0.265), medium resilience (0.105, 95% CI: 0.051, 0.176), high resilience (0.042, 95% CI: – 0.027, 0.118). For the rumination model, the role of anxiety symptoms was: low resilience (0.187, 95% CI: 0.115, 0.289), moderate resilience (0.121, 95% CI: 0.064, 0.192) high resilience (0.054). , 95% CI: −0.011, 0.126).
The explanatory power of the models for anxiety symptoms and PSQI scores ranged from 19.7% to 34.9%. A series of power analyzes were determined using post hoc methods based on achieved data.R.2 (0.197 to 0.349 based on different models), sample size (285),α(0.05), and the number of predictors (9 or 10 for different models). As a result, this study yielded a statistical power level of greater than 0.999.