3.1 Participants
A total of 453 cancer patients were recruited, and 439 with integral data were analyzed in our study, including 139 with lung cancer, 116 with breast cancer, 108 with colorectal cancer and 76 with gastrointestinal cancer. Of the participants, 45.79% (n=201) were male and 54.21% (n=238) were female. Average age at diagnosis was 57.08±9.23 years. Most participants (92.71%) were married. Regarding disease severity (stage of cancer), most participants were at stage III (n=150, 34.17%) and stage II (n=138, 31.44%); 120 participants (27.33%) had continuously received comprehensive treatment including surgery and adjuvant radiotherapy or chemotherapy. Other demographic information is presented in Table 1.
3.2 Descriptive analysis of resilience, SPB and social support
The basic descriptive statistics for resilience, SPB and social support are shown in Tables 1–3. The average standard score for the CD-RISC was 61.48±14.43, which was lower than the 65.34±14.27 points reported for the Chinese norm. The mean score for SPB was 31.80±7.68. The total score for social support was 41.82 ± 7.47 points, which is lower than the 44.34 ± 8.38 points for the Chinese norm.
3.2.1 Resilience and its influencing factors
The mean scores for the three subscales for resilience were 31.26±7.87 for tenacity, 20.58±5.01 for strength and 9.64±2.38 for optimism. Patients more than 60 years old were more optimistic than younger ones (F=4.48, p=0.035). Patients with colorectal cancer had the highest score (65.40±16.46) for resilience and breast cancer patients had the lowest (58.52±12.69) (F=5.51, p=0.001). The mean score for resilience decreased as cancer stage increased, but no significant difference was found. The mean score for resilience in male patients was higher than for females, especially in the tenacity dimension (F=4.48, P=0.035). The mean score for resilience increased as education level increased (F=3.50, P=0.031), as did that of the strength dimension (F=3.98, P=0.019). Patients with a full-time job had a higher mean score for resilience on all three factors than unemployed patients (F=8.25, P=0.004). No significant difference was found between urban and rural residents, or between married and unmarried status. Resilience level differed significantly by insurance type (F=2.99, P=0.031), household income per year (F=3.97, P=0.020), and treatment type (t =4.70, P=0.031), and the same trend was found in the three dimensions.
3.2.2 SPB and its influencing factors
The scores on the subscales of the SPB were 12.49±3.75 for the emotional dimension, 15.61±3.55 for the physical dimension and 3.70±1.13 for the economic dimension. Patients with no job (t=8.09, P=0.005), rural residents (t=15.07, P=0.000), those with a lower household income (F=8.68, P=0.000) and those holding the new rural cooperative medical scheme (NRCMS) (F=4.55, P=0.040) had a higher SPB score, with statistical significance. The same difference was seen with the three subscales. For the economic dimension, patients with a lower education level had higher scores (F=4.68, P=0.010). No significant difference was found for other factors.
3.2.3 Social support and its influencing factors
The mean score for subjective support was 25.46±4.25, for objective support 9.10±2.97 and for utilization of support 7.26±2.07. Patients who had undergone higher education (F=7.22, P=0.001), those with a full-time job (t=8.11, P=0.005), who were married (t=22.22, P<0.001), with higher household income (F=14.69, P<0.001) and urban employee’s basic medical insurance (UEBMI) (F=3.73, P=0.011) had higher social support. Consistent results were obtained across all dimensions except employment status and insurance type for subjective support and marital status and insurance type for utilization of support.
3.3 Correlation analysis among resilience, SPB and social support
The correlations among resilience, SPB and social support are shown in Table 4. After adjusting for sex, age at diagnosis, occupation, marital status, education, family income and type of insurance, resilience was negatively correlated with emotional burden (r=-0.114, P=0.018), and positively correlated with total social support (r=0.354, P<0.001). SPB was negatively correlated with utilization of social support (r=0.179, P<0.001).
3.4 Factors affecting analysis for resilience
We estimated the factors affecting resilience using generalized linear models (Table 5). After adjusting for the groups with different demographic and clinical characteristics with significant independent main effects, the emotional and physical burden and social support strongly influenced resilience.
3.5 Path analysis of SPB in the process of resilience affected by social support
The specific results are shown in Table 6. The results of the regression analysis of SPB on social support showed R2 of 1.70%, indicating that SPB could explain 1.70% of the variance in social support. The results of the regression analysis of SPB on resilience showed R2 of 1.30%, indicating that SPB could explain 1.30% of the variance of resilience. The results of the regression analysis of SPB and social support on resilience showed R2 of 14.20%, indicating that SPB and social support could explain 53.2% of the variance in resilience. At the same time, the SPB showed no effect on resilience, indicating that the effects of SPB on resilience acted through social support. Social support therefore plays an intermediary role in the process of SPB affecting resilience.