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

Background The RU_SATED scale is a multidimensional instrument measuring sleep health, consisting of Regularity, Satisfaction, Alertness, Timing, Efficiency, Duration dimensions. We adapted and validated the Chinese RU_SATED (RU_SATED-C) scale. Methods The RU_SATED-C scale was developed through a formal linguistic validation process and was validated in an observational longitudinal survey design. Healthcare students completed the RU_SATED scale, Sleep Quality Questionnaire, and Patient Health Questionnaire-4 among two sites of Hangzhou and Ningbo, China. Psychometric assessments included structural validity, longitudinal measurement invariance, convergent and divergent validity, internal consistency, and test–retest reliability. Results A total of 911 healthcare students completed the RU_SATED-C scale at baseline (Time 1, T1) and follow-up (Time 2, T2) with an average time interval of 7 days + 5.37 h. Confirmatory factor analysis (CFA) confirmed a single-factor model and resulted in an acceptable model fit. The two-factor model previously found in the Japanese version fit better than the one-factor model, whereas the one-factor model fit had a better fit than the two-factor model found in the English version. Longitudinal CFA resulted in negligible changes in fit indices for four forms of increasingly restrictive models and supported that a single-factor model was equivalent over time. The data also endorsed longitudinal measurement invariance among the two-factor models found in the English and Japanese samples. The RU_SATED-C scale total score displayed a moderately strong negative correlation with sleep quality; however, negligible associations were observed with anxiety and depression. Ordinal Cronbach’s alpha and Ordinal McDonald's omega at T1 and T2 ranged from suboptimal to acceptable. The RU_SATED-C scale and all items were significantly correlated across time intervals. Conclusion The RU_SATED-C scale is an easy-to-use instrument with potentially valid data for the measurement of multidimensional sleep health. Use of the RU_SATED-C scale can help raise awareness of sleep health and could pave the way for important efforts to promote healthy sleep.

show abstract

The RU_SATED as a measure of sleep health: cross-cultural adaptation and validation in Chinese healthcare students

Meng

Dong

Dzierzewski

et al. 2023

BMC Psychol

View full text Add to dashboard Cite

show abstract

Assessing psychometric properties and measurement invariance of the Sleep Quality Questionnaire among healthcare students

Huang,

Ma,

Spruyt

et al. 2024

BMC Psychol

View full text Add to dashboard Cite

Objective The sleep of healthcare students is worth discovering. Mental health and self-rated health are thought to be associated with sleep quality. As such, valid instruments to assess sleep quality in healthcare students are crucial and irreplaceable. This study aimed to investigate the measurement properties of the Sleep Quality Questionnaire (SQQ) for Chinese healthcare students. Methods Two longitudinal assessments were undertaken among healthcare students, with a total of 595, between December 2020 and January 2021. Measures include the Chinese version of the SQQ, Patient Health Questionnaire-4 (PHQ-4), Self-Rated Health Questionnaire (SRHQ), and sociodemographic questionnaire. Structural validity through confirmatory factor analysis (CFA) was conducted to examine factor structure of the SQQ. T-tests and ANOVAs were used to examine sociodemographic differences in sleep quality scores. Multi Group CFA and longitudinal CFA were respectively used to assess cross-sectional invariance and longitudinal invariance across two-time interval, i.e., cross-cultural validity. Construct validity, internal consistency, and test–retest reliability were correspondingly examined via Spearman correlation, Cronbach’s alpha and McDonald’s omega, and intraclass correlation coefficient. Multiple linear regression analysis was performed to examine incremental validity of the SQQ based on the PHQ-4 and SRHQ as indicators of the criterion variables. Results CFA results suggested that the two-factor model of the SQQ-9 (item 2 excluded) had the best fit. The SQQ-9 scores differed significantly by age, grade, academic stage, hobby, stress coping strategy, anxiety, depression, and self-rated health subgroups. Measurement invariance was supported in terms of aforesaid subgroups and across two time intervals. In correlation and regression analyses, anxiety, depression, and self-rated health were moderately strong predictors of sleep quality. The SQQ-9 had good internal consistency and test–retest reliability. Conclusion Good measurement properties suggest that the SQQ is a promising and practical measurement instrument for assessing sleep quality of Chinese healthcare students.

show abstract

Sleep quality and subjective well-being in healthcare students: examining the role of anxiety and depression

Zhu,

Meng,

Jiang

et al. 2023

Front. Public Health

View full text Add to dashboard Cite

ObjectiveSleep issues, negative emotions, and health conditions are commonly co-occurring, whereas their associations among healthcare students have yet to be elucidated. This study aimed to examine whether anxiety and depression mediate the relationship between sleep quality and subjective well-being in healthcare students.MethodsA cross-sectional survey was conducted among Chinese healthcare students (N = 348). A battery of paper-and-pencil questionnaires—the Sleep Quality Questionnaire (SQQ), World Health Organization-Five Well-Being Index (WHO-5), and Patient Health Questionnaire-4 (PHQ-4) were applied. Descriptive analysis with means (standard deviations) and counts (proportions), Spearman correlation analysis between the SQQ, WHO-5, and PHQ-4, and mediation analysis via structural equation models were performed.ResultsCorrelation analysis revealed statistically significant associations between sleep quality, anxiety and depression, and well-being among healthcare students. Mediation analysis identified that poor sleep quality produced relatively low levels of self-reported well-being, which were entirely attributable to anxiety and depression.ConclusionSleep quality was associated with subjective well-being, and this interrelationship was fully mediated by anxiety and depression. Interventions aimed at promoting sleep quality of healthcare students may contribute to promoting their well-being by reducing anxiety and depression.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

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

Cited by 4 publications

References 39 publications

The RU_SATED as a measure of sleep health: cross-cultural adaptation and validation in Chinese healthcare students

The RU_SATED as a measure of sleep health: cross-cultural adaptation and validation in Chinese healthcare students

Assessing psychometric properties and measurement invariance of the Sleep Quality Questionnaire among healthcare students

Sleep quality and subjective well-being in healthcare students: examining the role of anxiety and depression

Contact Info

Product

Resources

About