Introduction The Good Nursing Care Scale for Nurses (GNCS-N) measures nurses’ perceptions of nursing care quality, but no validated Indonesian version has been available. Objective(s) This study aimed to translate, adapt, and evaluate the construct validity and reliability of the Indonesian version of the GNCS-N (I-GNCSN). Method Following COSMIN-informed procedures, the GNCS-N underwent forward-back translation, expert review, and pilot testing. A cross-sectional study using convenience sampling was conducted among inpatient nurses, and 255 complete responses were retained for confirmatory factor analysis (CFA). A second-order CFA was performed in LISREL 8.72 because the GNCS-N has an established theory-based multidimensional structure. Model fit was evaluated using chi-square, RMSEA, SRMR, CFI, NNFI, NFI, GFI, and AGFI. Convergent validity was assessed using average variance extracted (AVE), and internal consistency was assessed using composite reliability and Cronbach’s alpha. Result The final I-GNCSN retained the original seven dimensions and 40 items. The re-estimated second-order CFA showed acceptable-to-good fit: chi-square = 1529.99, df = 708, RMSEA = 0.068 (90% CI 0.063-0.072), SRMR = 0.059, CFI = 0.98, NNFI = 0.98, and NFI = 0.96. GFI (0.77) and AGFI (0.73) remained below ideal thresholds and are therefore interpreted cautiously. Most standardized factor loadings were moderate to high, although one item showed comparatively weak performance and should be re-examined in future studies. Internal consistency remained acceptable, whereas convergent validity was weaker for constructs with AVE values below 0.50. Conclusion The I-GNCSN demonstrates acceptable structural validity and good internal consistency for use among Indonesian inpatient nurses. However, some fit indices remained suboptimal and convergent validity was mixed for several constructs; therefore, findings should be interpreted cautiously. Further studies should examine temporal stability, test the instrument in broader clinical settings, and re-evaluate weaker items.
Juanamasta et al. (Thu,) studied this question.