Validation of the Energy Conservation Strategies Inventory (ECSI).

CONTEXT: In applying good energy conservation strategies to relieve cancer-related fatigue, it is critical to first identify cancer patients who are at a high risk for poor energy conservation. However, instruments have not been developed to evaluate energy conservation strategies in an oncology setting. OBJECTIVES: The aim of this study was to validate an instrument that cancer patients may use to evaluate energy conservation strategies to overcome cancer-related fatigue. METHODS: The questionnaire development followed a four-phase process: 1) item generation and reduction, 2) construction, 3) pilot testing, and 4) field testing. Using relevant and priority criteria, as well as pilot testing, we developed a 25-item questionnaire. After field testing, five items were discarded. Finally, 20 items were included in the Energy Conservation Strategies Inventory (ECSI). Factor analysis, multitrait scaling analysis, and Cronbach's α were used to determine the construct validity and reliability. RESULTS: Factor analyses of data from 140 cancer patients resulted in the ECSI, which covers activities related to planning, overcoming distractions, labor saving, burden reducing, and comfort. All subscales (Cronbach's α range, 0.69-0.78) and total scores (Cronbach's α=0.87) were found to possess acceptable internal consistency. CONCLUSIONS: The good psychometric properties of the ECSI instrument show that it may be useful for measuring the frequency of energy conservation strategies used by cancer patients.

Depression in family caregivers of cancer patients: the feeling of burden as a predictor of depression.

PURPOSE: The purpose of this study was to explore the prevalence of and to identify the predictors of depression in family caregivers of cancer patients. PATIENTS AND METHODS: We enrolled 310 caregivers of cancer patients from the National Cancer Center, Korea, on this study and obtained demographic information for both patients and caregivers. To assess caregiver depression and its predictors, we used the Beck Depression Inventory (BDI), the Caregiver Quality of Life Index-Cancer, and the Family Impact Questionnaire. We used logistic regression analysis to identify independent predictors of caregiver depression. RESULTS: The majority (67%) of caregivers had high depression scores (BDI > 13), and 35% had very high depression scores (BDI > 21). In a multiple logistic regression model, caregivers who were women, the spouse of the patient, in poor health, feeling burdened, adapting poorly, unable to function normally, or caring for a patient with poor Eastern Cooperative Oncology Group performance status were more likely to experience depression (P < .01 for all values). CONCLUSION: Depression was highly prevalent among cancer patient family caregivers, and care burden was its best predictor. Interventions aimed at reducing the psychiatric effects of cancer should focus not only on the patient but also on the caregiver.

[Family functioning and quality of life of the family care-giver in cancer patients].

PURPOSE: The purpose of this study was to identify the relationship among quality of life, family coherence, family hardiness, and family resources of the family care-giver caring for a cancer patient. METHOD: Data was collected by questionnaires from 137 families with a cancer patient at a General Hospital and Government Cancer Hospital. Data was analyzed using descriptive statistics, pearson correlation coefficients, and stepwise multiple regression. RESULTS: The score of quality of life showed a significant positive correlation with the score of the level of family sense of coherence, family hardiness, and family resources. The most powerful predictor of quality of life was sense of coherence and the variance was 30%. A combination of sense of coherence and family resources account for 34 % of the variance in quality of life of the family care-giver caring for a cancer patient. CONCLUSION: The results showed that family sense of coherence, hardiness, and family resources were significant influencing factors on the quality of life of the family care-giver caring for a cancer patient.

Korean version of the caregiver quality of life index-cancer (CQOLC-K).

OBJECTIVE: The aim of this study was to develop and evaluate the internal consistency and construct validity of a Korean version of the Caregiver Quality of Life Index-Cancer (CQOLC-K). METHODS: The CQOLC-K was administered to 270 caregivers, along with the Medical Outcomes Study Short Form-36 (SF-36) and the Beck Depression Inventory (BDI). RESULTS: Internal consistency of the CQOLC-K (0.90) and all inter-scale correlations were significant in the expected direction (p < 0.001). Convergent validity was supported with moderate to strong correlations between the CQOLC-K and the mental component scores of the SF-36 (r = 0.39-0.58), and between the CQOLC-K and the two BDI scores (r = 0.50 and 0.60). Divergent validity was supported by weaker or negligible correlations between the CQOLC-K and the physical component scores of the SF-36 (r = 0.16-0.30). Contrasting groups validity showed that the CQOLC-K was able to distinguish clearly between patients differing in treatment history (p < 0.005), performance status (p < 0.005), care area (p < 0.005), and length of time after diagnosis (p < 0.005). CONCLUSION: These findings support the internal consistency reliability and construct validity of the Korean version of the CQOLC-K. The instrument can be used to measure quality of life in caregivers of cancer patients in clinical and epidemiological research.

[Influencing factors on symptoms of stress among hospital staff nurses].

PURPOSE: The purpose of this study was to identify the factors influencing Symptoms of Stress among hospital staff nurses. METHOD: Data was collected by questionnaires from 249 hospital staff nurses in three General Hospital. The data were analyzed using descriptive statistics, pearson correlation coefficients, and stepwise multiple regression. RESULTS: The score of the symptoms of stress showed a significantly positive correlation with the score of work stress(r=.22, p=.00). The symptoms of stress showed a significantly negative correlation with the score of social support(r=-.28, p=.00), self efficacy(r=-.31, p=.00), and hardiness(r=-.24, p=.00). The most powerful predictor of symptoms of stress was social support and the variance explained was 16%. A combination of social support, ways of coping, and work stress account for 32% of the variance in symptoms of stress among hospital staff nurses. CONCLUSION: This study suggests that social support, ways of coping, self efficacy, hardiness, and work stress are significantly influencing factors on symptoms of stress among hospital staff nurses.