Assessing Measurement Properties of a Simplified Chinese Version of Sleep Condition Indicator (SCI-SC) in Community Residents

Abstract

Background: The study aimed to assess the measurement properties of a simplified Chinese version of the Sleep Condition Indicator (SCI-SC) in the community. Methods: A psychometric evaluation through an observational cross-sectional survey design was conducted. Community residents (N = 751) in Hangzhou, China completed the SCI-SC and the simplified Chinese version of the Sleep Quality Questionnaire (SQQ) in July 2021. Data were randomly split into a development sample (N = 375) for model development by exploratory factor analysis (EFA) and a holdout sample (N = 376) for validation by confirmatory factor analysis (CFA). Multi-group CFA (MGCFA) was used to assess configural, metric, scalar, and strict measurement invariance across gender, age, marital status, body mass index (BMI), napping habits, generic exercise, hobby, and administered survey. Moreover, statistical analyses were performed to determine the reliability (alpha and omega) and construct validity of the instrument. Results: Both factor analyses showed a stable solution with two dimensions of Sleep Pattern and Sleep-Related Impact. Good structural validity, robust internal consistency, and construct validity with the SQQ were demonstrated. There was evidence of strict invariance across gender, BMI, napping habits, generic exercise, hobby, and administered survey subgroups, but only metric and scalar invariances were established across age and marital status groups, respectively. Conclusions: The SCI-SC demonstrated promising psychometric properties, with high SQQ concordance and consistent structure of the original version. The SCI-SC can be used by sleep researchers as well as healthcare professionals in various contexts in detecting risks for insomnia disorder in the community.

Keywords

• Sleep Condition Indicator
• measurement invariance
• psychometrics
• community