Methods: A sample of ethnic Chinese cancer patients (N = 159) were included in the multivariate model analysis. The data were from an international collaboration project conducted in 2011-2012 at northern Taiwan region. The sample included breast cancer and colon cancer patients. After consent, each participant completed a questionnaire booklet in which questions were included for demographics, illness perception, self-management practice, and quality of life. Illness perception was measured by Chinese version of the revised Illness Perception Questionnaire. Self-management practice was measured in the aspects of self-care efficacy, symptom self-care activity, and health maintenance resources. Quality of life was measured by the Quality of Life Scale. All questionnaires were available in bilingual versions. Data were analyzed in SPSS 23.0 and statistical significance was preset as Alpha = 0.05.
Results: The mean age of the sample was 55.55 years old, and 83% of the sample was female. The mean Karnofsky's Score was 78.43 (SD = 13.19). Seventy-two percent of the sample reported the religion preference was as Buddhism or Taoism. Thirty-three percent identified themselves as the primary caregivers. The overall sample reported moderate level of quality of life and self-care efficacy. On average, about five symptoms were reported from each participant. Stress and overwork were the common perceived causes of cancer reported in the sample. Walking and exercise were the commonly used daily health maintenance activities. The four-stage hierarchical multiple regression revealed that at stage one, demographic characteristics contributed significantly to the regression model (F (9,I2) = 4.48, p < .001) and accounted for 24% of the variation in quality of life. In step two, adding the illness perception subscale dimension variables explained an additional 18% of the variation in quality of life and this change in R2 was significant (F Change (8,119) = 4.46, p < .001). In step 3, adding self-care efficacy to the regression model only explained an additional 1% of the variation in quality of life and this change in R2 was not significant. However, the overall model was statistically significant (F (18,118) = 4.85, p < .001). The final model explained a total 43% of variance in quality of life (F (19,117) = 4.56, p < .001). Among all variables, the dimensions of consequence and personal control from the Illness Perception Questionnaire, and Karnofsky's Score were the significant predictors in the model.
Conclusion:
The overall results from this study showed that enhancing cancer patients' self-care efficacy and empowering patients to have positive personal control and attitude toward cancer and its treatment can significantly contribute to their quality of life. While the sample was focused on Taiwanese patients in this study, the proposed predicted model can be applied in other population. The emphasis of self-management in cancer patients' long-term quality of life has also been well established in the literature. Illness perception has also been supported to be the main covariate to quality of life in cancer patients can be employed to facilitate cancer patients for empowering their efficacy in self-management and active participation and planning for their adjustment with living with cancer. Further research can explore culturally-appropriate interventions to assist cancer patients to support their self-management. Variation in illness perceptions of cancer by different types of cancer should be considered in cancer survivorship planning and patient education.