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J Pain Symptom Manage ; 57(4): 820-827, 2019 04.
Article in English | MEDLINE | ID: mdl-30684634

ABSTRACT

OBJECTIVES: To validate and use the Chinese Version of the M. D. Anderson Symptom Inventory Gastrointestinal Cancer Module (MDASI-GI-C) to assess the symptom burden of Chinese-speaking patients with gastrointestinal cancer. METHODS: In total, 527 patients with postoperative or advanced digestive tract tumors were enrolled in the trial, who had definitive diagnoses and different treatments in our cancer center. MDASI-GI-C was administered to these patients between February and December 2017. The item-scale correlations and internal consistency were evaluated. Construct validity was established by factor analysis. Hierarchical cluster analysis was performed. RESULTS: Cronbach's alpha of the symptom severity and interference subscales was 0.842 and 0.859, respectively. Construct validity revealed a four-factor structure. Known-group validity was established by comparing the MDASI-GI-C scores between patients having different Karnofsky Performance Status scores (≤70 or >70), which were observed to have significant differences. The overall mean subscale scores for the core and interference subscales were 1.63 ± 2.02 and 2.17 ± 2.34, respectively. Fatigue, disturbed sleep, and lack of appetite had the highest scores for most serious symptoms. No significant differences in age, working status, and educational level were found. CONCLUSIONS: MDASI-GI-C is a reliable and valid tool for assessing cancer-related symptoms in Chinese-speaking patients with digestive tract tumors, facilitates the understanding of the common symptoms of patients with digestive tract tumors, and enables timely management of these symptoms. Cognitive debriefing demonstrated that the patients found MDASI-GI-C to be an easy-to-use and understandable instrument.


Subject(s)
Gastrointestinal Neoplasms/diagnosis , Adult , Aged , Aged, 80 and over , Factor Analysis, Statistical , Female , Humans , Male , Middle Aged , Psychometrics , Reproducibility of Results , Severity of Illness Index , Symptom Assessment , Translations
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