| Objective The study aimed to investigate the status of cancer related fatigue (CRF) among patients with gastric cancer(GC), and to explore the relationship between positive psychological characters and CRF. so as to provide a theoretical foundation for obtaining the strategies of improving CRF among patients with GC.Methods 203 patients with GC were enrolled from three hospitals in China by adopting convenience sampling methods in this survey. The Cancer Related Fatigue Scale, the Herth Hope Scale, the Positive and Negative Affect Schedule (PANAS), and the Connor-Davidson Resilience Scale (CD-RISC10) were administered, t test, Pearson correlation and multiple liner regression were conducted to explore the relationship between positive psychological characters and CRF via SPSS 21.Results1. Socio-demographic and clinical information among patients with GCThe average was 75.64 years (SD=11.83),ranging from 20 to 86 years.72.4% of patients were males, and 62.1% of patients had a junior school or below.57.6% of patients had balance economic condition.73% of the patients had a normal BMI, the stage of diseases accounted for 27.1%,23.2%,28.6%, and 21.2% ranging from I to IV, respectively.51.7% of patients received surgery and chemotherapy.2. Status of CRF and its differences in socio-demographic and clinical information among patients with GCThe average scores of CRF was (28.19±8.18). The mean scores of each item of three dimensions of CRF from high to low were affective fatigue (2.14 ± 0.63), physical fatigue (1.87 ± 0.68), cognitive fatigue (1.67±0.76), respectively. Significant differences were found between CRF and economic condition, BMI. Additionally, there were no differences between CRF and other variables.3. Status of positive psychological characters and its correlations with CRF among patients with GC.The average scores of hope, resilience and positive affect were (34.01±5.36), (28.01±6.23), and (27.73±6.50).CRF and its dimensions were negatively related to hope, resilience and positive affect, while resilience and hope were positively related to positive affect.4. Hierarchical regression analysis of CRF among patients with GCThe study selected CRF and its dimensions as the dependent variables, hope, resilience and positive affect as independent variables, general demographic variables and clinical information related to CRF as first-level control variables. Results of Hierarchical Regression Analysis showed that hope trait, resilience and positive affect were negatively associated with CRF (β1=-0.165, β2=-0.225,β3=-0.343, all P <0.01; R2= 0.365, △R2= 0.273) and affective fatigue (βi,=-0.179, P<0.01; β△2=-0.161, P<0.05; β3=-0.380, P<0.001; R2= 0.280, △R2= 0.267); meanwhile, resilience and positive affect were also negatively associated with physical fatigue{β =-0.218,β2=-0.233, P<0.01; R2= 0.268, △R2= 0.143); finally, hope trait and positive affect were negatively related to cognitive fatigue (β1=-0.168, P<0.01;β2-0.242, P<0.01; R2= 0.157, △R2= 0.137).5. Mediating effect of positive affect between hope trait and CRF among patients with GCThe study selected CRF as the dependent variables, hope trait as independent variable, positive affect as mediating variable, general demographic variables and clinical information related to CRF as first-level control variables. Mediation analysis showed that the regression coefficients for hope trait and positive affect were negatively associated with CRF{β2=-0.215,β3=-0.420, Both P<0.01). When positive affect was added, the regression coefficients for hope trait were reduced from β1=-0.289 to β2=-0.215, indicating that positive could mediate the relationship between hope trait and CRF. The bootstrapping method showed that the path coefficient of the indirect effect of hope trait through PA was β=-0.112 (95%CI: 0.250,-0.047; P<0.05).6. Mediating effect of positive affect between resilience and CRF among patients with GCThe study selected CRF as the dependent variables, resilience as independent variable, positive affect as mediating variable, general demographic variables and clinical information related to CRF as first-level control variables. Mediation analysis showed that the regression coefficients for resilience and positive affect were negatively associated with CRF (β2=-0.270,β3=-0.356, Both P<0.001). When positive affect was added, the regression coefficients for resilience were reduced from β1=-0.410 to β2=-0.270, indicating that positive could mediate the relationship between resilience and CRF. The bootstrapping method showed that the path coefficient of the indirect effect of resilience through PA was β=-0.180 (95%CI: 0.291,-0.095; P＜0.001).Conclusions1. Patients with GC were prone to experience cancer related fatigue, indicating a server fatigue that interfered with day-day-functioning.2. Scores of CRF and its dimensions were negatively related to hope, resilience and positive affect among patients with GC, while resilience and hope were positively related to positive affect.3. Hope, resilience and positive affect could negatively predict the CRF of patients with GC. Taking action to enhance the level of hope, resilience and positive affect could improve CRF.4. Positive affect could partially mediate the relationship between resilience, hope trait and CRF, respectively. |
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