Chinese BERNCA-NH shows acceptable preliminary psychometrics in 251 nursing assistants

Investigators translated and culturally adapted the Basel Extent of Rationing of Nursing Care for Nursing Homes (BERNCA-NH) into Chinese and evaluated its preliminary psychometric properties among nursing assistants in Chinese long-term care (LTC) facilities. This was a cross-sectional survey, not a systematic review or randomized trial.

Adaptation followed a standard multi-step process: forward translation, back-translation, synthesis, cognitive interviews, and expert review after obtaining permission from the original developers. A cross-sectional survey was then administered to 251 nursing assistants recruited by convenience sampling from LTC facilities in China. Analyses included descriptive statistics, item analysis, exploratory factor analysis, and internal consistency testing.

During adaptation, the team identified three main challenges: syntactic and idiomatic differences between English and Chinese, mismatch between some original care scenarios and the local LTC context, and multiple possible Chinese interpretations of certain English expressions. These required iterative resolution through cognitive interviewing and expert review.

Psychometric results were modest but supportive. The Chinese version showed good overall internal consistency (Cronbach's alpha = 0.815). Sampling adequacy for factor analysis was acceptable (KMO = 0.746), and Bartlett's test of sphericity was significant (chi-squared = 1579.889, df = 210, p < 0.001), indicating the correlation matrix was suitable for factor extraction.

The authors conclude the Chinese BERNCA-NH has acceptable preliminary psychometric properties and may serve as a preliminary tool for assessing unfinished (rationed) care among nursing assistants in Chinese LTC homes, while emphasizing that further validation is needed. They note the instrument may help identify priority areas for care improvement and support quality assessment and management in LTC settings. Convenience sampling and the single-country context are relevant limitations for generalizability.