ObjectiveTo translate the Perceived Stress Questionnaire (PSQ) into Chinese, validate its reliability and validity in nursing students and investigate the perceived stress level of nursing students.MethodForward- and back-translation combined with expert assessment and cross-cultural adaptations were used to construct the Chinese version of the PSQ (C-PSQ). This research adopted a stratified sampling method among 1,519 nursing students in 30 classes of Ningbo College of Health Sciences to assess the reliability and validity of the C-PSQ. Among them, we used the Recent C-PSQ (only the last month).ResultsThe C-PSQ retained all 30 items of the original scale. Principal component analysis extracted five factors that explained 52.136% of the total variance. The S-CVI/Ave was 0.913. Concurrent validity was 0.525 and 0.567 for anxiety and depression respectively. The results of the confirmatory factor analysis were as follows: χ2/df = 4.376, RMR = 0.023, GFI = 0.921, AGFI = 0.907, CFI = 0.916, RMSEA = 0.048, PNFI = 0.832, PGFI = 0.782, CN = 342 and AIC/CAIC = 0.809. The scale’s Cronbach’s alpha was 0.922, and Cronbach’s α of each dimension was 0.899 (worries/tension), 0.821 (joy), 0.688 (overload), 0.703 (conflict), 0.523 (self-realization). The correlation coefficient between the first and second test, the first and third test and the second and third test was 0.725, 0.787 and 0.731, respectively. Mean values and distribution of overall PSQ index in nursing students was 0.399 ± 0.138. Different demographic factors were significantly associated with the perceived stress of nursing students.ConclusionThe C-PSQ has an appropriate reliability and validity, which means that the scale can be used as a universal tool for psychosomatic studies. The perceived stress of nursing students was relatively high. Further studies are needed.

There is an increasing amount of evidence exploring the adverse effects of perceived stress or anxiety and depression independently on sleep quality during the COVID-19 outbreak, although the underlying mechanisms are unclear. The aim of the current study was to explore the role of anxiety and depression as a potential mediator between perceived stress and sleep quality among health care workers. Methods: Data were collected through an online survey using the snowball sampling method and comprised 588 current health care workers in Zhejiang and Hubei provinces, China, from February to March 2020. We administered the Sleep Quality Questionnaire (SQQ), the Perceived Stress Scale (PSS-10), the Patient Health Questionnaire (PHQ-4) and the sociodemographic characteristics and COVID-19-related characteristics questionnaire. Structural equation modelling (SEM) was used to examine the direct and indirect relationships between perceived stress, anxiety and depression, and sleep quality. Results:The average scores for sleep quality and perceived stress were 16.01 (95% CI [15.40, 16.57]) and 15.46 (95% CI [15.05, 15.87]), respectively. The positive rates of anxiety and depression symptom tests were 9.86% and 10.37%, respectively. The SEM results indicated that the original relationship between perceived stress and sleep quality was beta = 0.52 (P < 0.001) and reduced to beta = 0.25 (P = 0.045) while introducing anxiety and depression as mediating variables. Perceived stress was positively associated with anxiety and depression (beta = 0.78, P = 0.014), and anxiety and depression were positively associated with sleep quality (beta = 0.42, P < 0.001). Conclusion:Poor sleep quality and high perceived stress were common during the COVID-19 crisis. Reducing perceived stress could help reduce anxiety and depression symptoms, thereby improving sleep quality among health care workers. In an attempt to promote psychological resources, we should perhaps take multiple measures, including personal tailored intervention and organizational humanistic concern.

Background Self-compassion has been regarded as a key psychological construct and a protective factor of mental health status. The focus of the present study was to adapt the Self-Compassion Scale (SCS) into Chinese, assess the validity and reliability of the measure and test measurement invariance (MI) across nursing students and medical workers. Methods The current study assessed the psychometric properties and invariance of the SCS-Short Form (SCS-SF) in two samples of 2676 from nursing students and medical workers. For construct validity, confirmatory and exploratory factor analyses (CFAs and EFAs) were conducted. Using Perceived Stress Questionnaire , Short Form-8 Health Survey (SF-8) and Goldberg Anxiety and Depression Scale, we evaluated concurrent validity and convergent/divergent validity. For reliability, internal consistency and test–retest analysis were employed. Multi-group analyses were conducted to examine MI of the different SCS-models across populations. Results CFA showed that the proposed six-factor second‐order model could not be replicated and the six-factor first‐order model was a reasonable to mediocre fitting model in both samples. EFA supported a three-factor structure which consisted of one positive and two negative factors. CFA confirmed that the hypothesized three-factor structure with 10 items ultimately was considered as the optimal model on the fitted results. The SCS-SF‐10 (10 items form) also demonstrated acceptable internal consistency and test–retest reliability, as well as strong concurrent validity with measures of stress perception, health status, anxious and depressive symptoms. Convergent/divergent validity was not satisfactory. Multi-group CFAs provided support for the validity of the established models. Conclusion The Chinese version of the SCS-SF‐10 has sound psychometric properties and can be applied to efficiently assess self-compassion in Chinese-speaking populations. The current study contributes to the identification and measurement of self-compassion after adversities.

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.