Affiliation:
1. Xiangya Nursing School of Central South University Changsha Hunan Province China
2. Clinical Nursing Teaching and Research Section The Second Xiangya Hospital of Central South University Changsha Hunan Province China
3. Department of Nephrology, Blood Purification Center The Second Xiangya Hospital of Central South University Changsha Hunan Province China
Abstract
AbstractLearned helplessness (LH) is an important concept in nursing. This study aimed to adapt and translate the Arthritis Helplessness Index scale into a Chinese version of an LH scale for maintenance hemodialysis patients in China (LHS‐MHD‐C), and to validate its psychometric properties. Data collected included LHS‐MHD‐C, as well as the Hospital Depression Scale (HADS‐D), and the Beck Hopelessness Scale (BHS) for assessing LHS‐MHD‐C's criterion validity (predictive and concurrent, respectively). The expert consultation and the pilot study demonstrated semantic and conceptual equivalence and content validity (except for Item 3, the item content validity ranged from 0.82 to 1, and the scale content validity was 0.95). An exploratory factor analysis (n = 146) eliminated three items and accepted 11 items for the two factors, explaining 63.87% of the total variance. A CFA (n = 218) showed that the two‐factors structure was consistent with the LH theory. The LHS‐MHD‐C can distinguish between maintenance hemodialysis (MHD) patients of different ages, education, working status, monthly income, and MHD duration. The scale had good concurrent validity with the BHS (r = .78,p < 0.01). Using the HADS‐D as a criterion, the LHS‐MHD‐C showed a sensitivity of 86.2% and a specificity of 96.8%. A total score of 36.5 may be the best cut‐off value for predicting MHD patients' depression. The scale showed good reliabilities (Cronbach'sαvalue of .759, test–retest reliability of 0.772, and split‐half reliability of 0.774). This study found that the LHS‐MHD‐C is a reliable and valid scale for assessing Chinese MHD patients' helplessness.
Funder
National Natural Science Foundation of China