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The simplified Chinese version of the Nonrestorative Sleep Scale in Chinese young adults and measurement invariance across language and age

BMC Psychology volume 13, Article number: 258 (2025) Cite this article

Abstract

Background

To assess the psychometric properties of the simplified Chinese version of the Nonrestorative Sleep Scale (NRSS) in Chinese young adults and examine measurement invariance across language and age.

Methods

After cognitive debriefing, the simplified Chinese NRSS was administered to university students in mainland China in this cross-sectional survey (Study 1). The Pittsburgh Sleep Quality Index (PSQI), the Patient Health Questionnaire (PHQ-4), and sociodemographic characteristics were also self-reported. The sample was randomly split into two halves to examine the scale structure using exploratory factor analysis (EFA) and asses the psychometric properties of the identified structure by confirmatory factor analysis (CFA), respectively. Incorporating data from two additional studies (Study 2: a survey of Hong Kong Chinese adults; Study 3: a survey of mainland Chinese adolescents), multigroup CFA models were conducted to examine the measurement invariance across language and age, followed by a t-test to determine group differences once invariance was established.

Results

In the 570 participants of Study 1 (28.8% male, age 20.2 ± 1.5 years), the EFA revealed a four-factor structure. The root mean square error of approximation, comparative fit index, and standardized root mean square residual in the CFA model were 0.053, 0.995, and 0.054, respectively. The statistically significant correlations of NRSS with PSQI (r = − 0.61) and PHQ-4 (r = − 0.53) demonstrated the convergent validity of NRSS. The internal consistency of the whole scale was 0.84. Measurement invariance was concluded between traditional and simplified Chinese NRSS and between young adults and adolescents with the change of comparative fit index and root mean square error of approximation smaller than 0.010. The effect size (Cohen’s d) of difference between mainland Chinese adults and Hong Kong Chinese adults ranged from 0.193 to 0.771, while that between mainland Chinese adults and adolescents ranged from 0.027 to 0.345.

Conclusion

The simplified Chinese 12-item NRSS is valid and reliable for assessing NRS among Chinese young adults, and it can be used to measure and compare NRS between individuals using simplified Chinese and traditional Chinese, as well as across different age groups within the simplified Chinese user population.

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Background

Adequate sleep is essential to maintain vital activities and basic functions for all individuals. Biological rhythms, physiological functions, cognitive activity, and psychological health could not be carried or restored without sleep [1]. The social-ecological model of sleep puts forward that the “downstream” of insufficient sleep or poor sleep quality covers numerous adverse health outcomes across multiple domains, including general health, cardiovascular health, metabolic health, mental health, immunological health, and human performance [2].

During the last two decades, nonrestorative sleep (NRS) has gained growing attention in addition to other frequently reported sleep-related problems, such as difficulty initiating and maintaining sleep [3,4,5,6]. NRS usually refers to an individual’s unrefreshed feeling after normal sleep duration [7]. NRS, despite its inconsistent definitions and varied measurements, has been reported to be associated with different health-related problems, such as chronic diseases, psychiatric problems, and increased mental health [8,9,10]. It would also cause function-related problems like daytime fatigue, decreased daytime performance, and occupational and non-occupational accidents [11]. Studies of Hong Kong Chinese adults found that NRS was prevalent among them, and the association with health-related quality of life revealed that NRS warrants attention [12, 13]. Previous literature also showed that 30.9% of the Chinese population had insomnia symptoms [14], and 19.2% of the Chinese population had poor sleep quality in mainland China [15]. Furthermore, one recent study showed that 43.8% of mainland Chinese young adults stayed up past midnight, 27.4% had sleep efficiency under 85%, 25.7% experienced insomnia, 27.7% reported sleep durations under 7 h, 66.6% had sleep disturbances, and 55.6% showed signs of daytime dysfunction [16]. Therefore, the sleep conditions of mainland Chinese young adults are of significant concern to promote their well-being. However, the NRS among Chinese adults who speak and read simplified Chinese has been underexplored because of the absence of a standardized instrument for measuring it.

For a more comprehensive assessment of NRS, three patient-reported outcome measures (PROMs) were developed because of the “subjective” nature of NRS, namely the Nonrestorative Sleep Scale (NRSS), the Restorative Sleep Questionnaire weekly version (RSQ-W), and the Restorative Sleep Questionnaire daily version (RSQ-D) [17, 18]. The Nonrestorative Sleep Scale (NRSS) is the first standard instrument developed to assess NRS [17]. In 2012, Wilkinson et al. employed a new paradigm inspired by the diagnosis of insomnia to serve as the foundation for the development of NRSS in English, with the aim of encouraging collaboration across disciplines on NRS [17, 19]. This new paradigm identifies NRS as both a symptom of various medical and psychiatric conditions and as a disorder on its own, echoing observations in NRS [17, 19]. For example, NRS has a significant relationship with chronic fatigue syndrome but can manifest independently as well [7].

The original English NRSS has undergone translation into several languages, including traditional Chinese for general adults in Hong Kong and simplified Chinese for adolescents in mainland China, with all versions confirming a four-factor structure, while the traditional Chinese version also concluded a bi-factor model [20, 21]. Moreover, studies have identified age as one of the most frequently cited sociodemographic variables affecting NRS, but a consensus has yet to be achieved. Younger adults have been reported to experience more NRS [22]. In contrast, other research has found that NRS is more prevalent among middle-aged adults than among younger or older age groups [23]. Furthermore, the linguistic and written differences in Hong Kong, where Cantonese is spoken and traditional Chinese is used, hinder sleep comparisons of sleep with mainland China. Hong Kong is known as a sleepless city, where sleep problems are highly prevalent among the general population [24]. Therefore, a standardized and reliable tool to measure NRS across age and language would reveal NRS disparities and related factors of it in China, which would facilitate the interventions for NRS.

The direct comparison of scores between different groups requires that the measurement be invariant across different groups. Specifically, measurement invariance determines if an instrument is interpreted equivalently or similarly, such as wording or content, by various individuals with diverse backgrounds [25]. It can be evaluated in multigroup confirmatory factor analysis (CFA) by progressively testing configural invariance, metric invariance, and scalar invariance with restrictions of equal factor structure, equal factor loadings, and equal intercepts being added to the previous CFA models, respectively [21]. Scalar invariance is adequate for evaluating observed mean differences between groups [21].

Hence, this study aimed to evaluate the psychometric properties of the simplified Chinese version of NRSS in mainland Chinese adults. Second, exploring whether NRSS shows measurement invariance across language and age could facilitate the comparison of NRS across language and age and enhance the understanding of NRS and sleep issues among Chinese populations. Third, to assess the difference in NRS between mainland Chinese adults and Hong Kong Chinese adults and the difference between young adults and adolescents.

Methods

Linguistic validation of the simplified Chinese NRSS

The original simplified Chinese version of NRSS was obtained by the research team using standard forward-backward translation procedures when it was adapted for Chinese adolescents in 2019 [21]. Before cognitive briefing and administering the simplified Chinese NRSS in young adults, a committee meeting with four members who were experienced in scale validation, statistical analysis, and sleep was convened in 2023 to discuss whether the translations and contents were applied to young adults. The experts researched a consensus on the wording and determined the applicability to young adults without major revision. Six university students were then approached to evaluate the scale length, whether the items of the simplified Chinese version were relevant to NRS, and whether the items were clarified enough. All six respondents rated the length as moderate, five of six rated the relevance and clarity of items very high or high, while one rated relevance as moderate. Given the positive feedback, the final version of the simplified Chinese NRSS was finalized without additional modifications.

Sample and procedures

We totally recruited three datasets to investigate the measurement invariance, with two datasets extracted from our previous studies.

Study 1

An internet-based cross-sectional survey of students attending Shenzhen University and Nanjing Medical University was conducted from April 29, 2023 to March 26, 2024. Eligible participants were those who were capable of reading and understanding simplified Chinese and completing the questionnaires according to their true feelings and conditions on their own. Individuals who were taking drugs for sleep problems or diagnosed with mental illness were excluded from this study.

This study adopted convenience sampling, and the potential participants were approached in classes, where they were briefed on the aims, study procedures, inclusion criteria, and exclusion criteria of this study. They were invited in classes and by e-messages to voluntarily complete the self-administered online questionnaires through Wenjuanxing, a widely used electronic survey platform in mainland China. The study procedures were also introduced to potential participants at the beginning of the online questionnaires, including the use of their anonymous data for academic publications. Written informed consent was obtained when they clicked “Next” on the title page before they started the questionnaires. Ethics approval for this study was obtained from the Institutional Review Board of Shenzhen University [No.: PN-202300022] and the Institutional Review Board of Nanjing Medical University [No.: (2023) 585].

The whole sample of Study 1 was randomly split into two halves, with each half used for a factor analysis. Following the guideline suggesting a minimum of 20 subjects per item for factor analysis, we planned to recruit 480 subjects [26].

Study 2

Data from 500 general adults were successfully approached in the Hong Kong community to complete the traditional Chinese NRSS, which was utilized with data from Study 1 for evaluating the measurement invariance between simplified Chinese and traditional Chinese [13]. The sampling procedure was described in our previous article [13]. The linguistic validation of the traditional Chinese NRSS and the sampling procedure had been described in our earlier study [20].

Study 3

A total of 481 adolescents from secondary and high schools in Nanjing, China, participated in the validation study of the simplified Chinese NRSS [21]. Both the students and their parents/guardians gave written informed consent before the adolescents completed the paper questionnaires [21]. Data from these adolescents on the simplified NRSS were employed with data from Study 1 to examine the measurement invariance across age.

Measures

Nonrestorative sleep scale (NRSS)

The NRSS includes 12 items, which can be grouped into four subscales, including refreshment from sleep (3 items), physical/medical symptoms of NRS (4 items), daytime functioning (3 items), and affective symptoms (2 items) [17]. Items belonging to the physical/medical symptoms of NRS subscale and affective symptoms subscale are negatively worded, so scores of these items need to be reversed before scoring [17]. The simplified Chinese version administered in this study was scored as the English version [21]. By combining the adjacent answers, the ten items answered using a 1–10 Likert scale were re-coded to form a 1–5 scale with a total score ranging from 12 to 60. Higher scores on the global scale or each subscale indicate less NRS. The details of the simplified Chinese NRSS in adolescents have been reported [21].

Pittsburgh sleep quality index (PSQI)

The PSQI consists of 19 self-rating questions to assess sleep quality over the past month, including seven components: subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disorders, sleep medication use, and daytime dysfunction [27]. The score of each component ranged from 0 to 3, and the global score ranged from 0 to 21, with higher scores indicating worse sleep quality [27]. Both the simplified Chinese and traditional Chinese versions of PSQI have been validated as reliable and valid [28, 29].

Patient health questionnaire-4 (PHQ-4)

The PHQ-4, comprising the PHQ-2 and General Anxiety Disorder-2 (GAD-2), was used to screen for depression and anxiety [30]. PHQ-2 covers two items assessing the frequency of depressive symptoms, while the GAD-2 encompasses two items evaluating core anxiety symptoms in the past two weeks [30]. Validation studies show that both the simplified and traditional Chinese versions of the PHQ-4 are reliable and valid [31, 32]. All items were rated on a Likert 4 scale, ranging from 0 (not at all) to 3 (nearly every day). Higher total scores indicate more severe symptoms of depression [30].

Sociodemographics

Sociodemographic characteristics, including age and gender, were collected.

Statistical analysis

All data analysis was conducted with R-4.3.2. Individuals who completed the NRSS with 50% missing values or less were included in the final data analysis. All the scale scores were summarized using mean ± standard deviation (SD) if normally distributed. The floor and ceiling percentages of NRSS were calculated to examine the scaling properties, indicating the proportions of participants achieving the lowest or highest possible scale scores, respectively [33].

The entire sample of Study 1 was randomly split into two halves, with one half designated as the training sample and the other half as the validation sample. With the training sample, an exploratory factor analysis (EFA) was performed to determine the most appropriate structure of the Chinese NRSS in adults. Specifically, we calculated the Kaiser-Meyer-Olkin (KMO) and conducted Bartlett’s Test of Sphericity to assess the appropriateness of EFA with the training sample (requirement: KMO ≥ 0.70 and statistical significance of Bartlett’s Test of Sphericity) [34]. Upon confirmation, the number of factors was determined through parallel analysis and scree plot analysis, utilizing factor loadings acquired via minimal residual (MINRES) on the polychoric correlation, followed by oblimin rotation [35]. Oblimin rotation, which is the most commonly used oblique technique, is preferred for factor analysis to allow the factors to correlate and provide an accurate and reproducible solution, especially where correlation among factors was generally expected [35, 36]. A polychoric correlation matrix combined with MINRES estimation is proposed because of its ability to analyze polytomous items with a few graded response categories that do not fulfill the average difficulty and discrimination assumptions [37]. A factor loading of at least 0.4 was considered satisfied [38]. The EFA was conducted under R with the packages “psych” and “GPArotation” [39, 40].

We assessed the factorial validity of the structure identified by EFA and the bifactor model obtained by the traditional Chinese version through CFA using the validation sample [20]. The diagonal weighted least squares (DWLS) estimation was employed to address the ordinal nature of the item responses [41]. We examined the goodness of fit through the root mean square error of approximation (RMSEA), comparative fit index (CFI), and standardized root mean square residual (SRMR) [42]. An acceptable fit for a CFA model was defined as having values of RMSEA at 0.08 or below, CFI at 0.95 or above, and SRMR at 0.08 or below [42].

Following confirmation of the factor structure of the simplified Chinese NRSS with Study 1 data, we additionally utilized data from Study 2 and data from Study 3 to examine the measurement invariance across language and age, respectively, through multigroup CFA models. The standard configural invariance, metric invariance, and scalar invariance were progressively evaluated [43]. Invariance was determined if the associated change in CFI was smaller than 0.010 and the change in RMSEA was smaller than 0.015 in each step [43]. The CFA models were analyzed under R with the package “lavaan” [44].

Considering the fact that NRS was associated with sleep quality and depression, Spearman’s rank correlation coefficients between NRSS and PSQI, as well as PHQ-4, were calculated to examine the convergent validity of the Chinese version of NRSS [20]. In addition, internal consistency was examined via the values of Cronbach’s α.

After the validity and reliability of the simplified Chinese in adults and measurement invariance across language and age were established, the independent t-test was applied to compare the scores of NRSS between different groups. The effect size of Cohen’s d was obtained for each comparison to indicate the magnitude of the difference [45]. For all data analysis, a two-tailed P-value smaller than 0.05 was deemed statistically significant.

Results

Demographic characteristics and NRS status

A total of 570 (28.8% male) students with an average age of 20.2 (SD: 1.5, range: 18–30) years answered the simplified Chinese questionnaires and were included in the analysis. The mean global score of the NRSS of the overall sample (n = 570) was 42.4 (SD = 7.2). The floor and ceiling rates of the scale scores were 0–1% and 1–12%, respectively (Table 1). The mean age of the adolescents who answered the simplified Chinese version was 16 years old (SD: 1; range: 13–18) [21], while that of the adults who answered the traditional Chinese version was 39 years old (SD: 12; range: 18–80) [13].

Table 1 Global and subscales scores of simplified Chinese NRSS (n = 570)
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Exploration of scale structure

With the training sample, the KMO yielded a value of 0.82, indicating high sampling adequacy, and Bartlett’s Test of Sphericity demonstrated statistical significance (P < 0.001). Four factors were identified from parallel analysis and the scree plot, which explained 71.2% of the total variance. The factor structure is inconsistent with the English version. Table 2 shows the rotated factor loadings corresponding to the parallel analysis and the corrected item-scale correlation.

Table 2 Factor loadings by exploratory factor analysis and internal reliability of the simplified Chinese NRSS (n = 275)
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Confirmation of the factor structure

In order to test whether the four-factor model derived from the EFA was reasonable, CFA models were performed using the validation sample. The bifactor model of the traditional Chinese version was compared with the four-factor model. The fitting indexes of the four-factor model (RMSEA = 0.053, CFI = 0.995, SRMR = 0.054) were better than those of the bifactor model (Table 3). The standardized factor loadings of the four-factor model were all above 0.4, and the standardized coefficients of the four-factor model are shown in Fig. 1.

Table 3 Model fit indices in confirmatory factor analysis of the Chinese NRSS (n = 295)
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Fig. 1
figure 1

Standardized coefficients of a four-factor structure for the 12-item Chinese NRSS (n = 295)

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Measurement invariance across language and age groups

Table 4 shows the assessment of configural, metric, and scalar invariances between simplified Chinese and traditional Chinese in adults and between young adults and adolescents with simplified Chinese versions. The model fit indices were all in an acceptable range, with all the △CFI and △RMSEA values smaller than 0.010 and 0.015, respectively. Hence, scalar invariance was established between the simplified Chinese and the traditional Chinese and between young adults and adolescents.

Table 4 Model fit indices in confirmatory factor analysis of the Chinese NRSS
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Convergent validity

Table 5 shows that the scores of the global scale and its four subscales were moderately associated with the PSQI and PHQ-4, with correlation coefficients ranging from − 0.61 to − 0.34 (all P < 0.01).

Table 5 Correlations between Chinese NRSS scores and global scores of other subjective scales (n = 232)
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Scale-scale correlations and internal consistency

The global score of the simplified Chinese version of NRSS demonstrated strong associations with its subscales, with coefficients of Spearman’s rank correlation ranging between 0.55 and 0.79. The subscales were moderate with each other, with scale-scale correlations in the range of 0.25 to 0.60 (Table 6). The Cronbach’s α for the global scale, the refreshment from sleep, physical/medical symptoms of NRS, daytime functioning, and affective symptoms subscales were 0.84, 0.77, 0.77, 0.87, and 0.55, respectively.

Table 6 Scale-scale correlations of the simplified Chinese NRSS (n = 570)
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Comparison of NRSS between different populations

Upon measurement invariance was concluded, and the mean between the young adults and the Hong Kong Chinese adults and adolescents were compared. Independent t-test showed that Hong Kong Chinese adults reported significantly better NRS conditions than the mainland Chinese young adults except for refreshment from sleep subscale (Table 7). The young adults reported better refreshment from sleep than adolescents while worse affective symptoms than adolescents (Table 7). The values of Cohen’s d ranged from 0.193 to 0.771 in terms of the difference between Hong Kong Chinese adults and mainland Chinese adults and ranged from 0.027 to 0.345 in terms of the difference between mainland Chinese adults and adolescents. The linear regression showed that age was only associated with the score of affective symptoms, while language was associated with refreshment from sleep, physical/medical symptoms of NRS, and affective symptoms (Table 8).

Table 7 Comparison of NRSS between different populations
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Table 8 The association of age and Language with NRSS subscales (n = 1551)
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Discussion

This study examined the reliability and validity of the simplified Chinese version of NRSS in Chinese young adults and the measurement invariance across language and age. Both the exploratory and confirmatory factor analyses showed that the simplified Chinese NRSS had good structural validity, and measurement invariance was concluded across language and age.

The EFA identified a four-factor model, which was in line with the structure of the original English version [17]. The corrected item-total correlation of Item 11 was marginally smaller than 0.3. However, the factor loading obtained by EFA and the standardized coefficient obtained by CFA were both greater than 0.4, and the model fit was satisfactory in the CFA. Therefore, this item was retained to ensure better alignment with the original version. Notably, although the bifactor model of 12-item NRSS showed a satisfactory model fit in this sample, the coefficient of the explained common variance was around 0.5, which was smaller than the cut-off values and couldn’t support the bifactor model [46]. Therefore, the bifactor model was not established.

The scalar level invariance between the simplified Chinese NRSS and the traditional Chinese version in adults, as well as that of the simplified Chinese version between young adults and adolescents, was established. Establishing metric and scalar invariance is crucial and sufficient when the research focus is on comparing observed mean differences between groups [47]. Hence, the raw scores of the Chinese NRSS across languages and age groups could be compared to identify whether there would be any significant difference between various groups.

As hypothesized, the observed associations of the simplified Chinese NRSS with the PSQI and PHQ-4 demonstrated its convergent validity [17]. NRS was found to be more frequent among poor sleepers [48]. Moreover, sleep quality and depression were found to be related to NRS [49]. Thus, relieving depression symptoms and improving sleep quality may help reduce the level of NRS [49].

The four subscales of the simplified Chinese NRSS were moderately associated with each other, with correlation coefficients ranging from 0.25 to 0.60, showing that these subscales measured essentially different aspects of NRS [21]. The correlation coefficient between the refreshment from sleep and daytime functioning subscales reached 0.60, reflecting results from prior English and Chinese validations [17, 20, 21]. As proposed before, people are anticipated to perform better if they feel more refreshed after sleep [50]. Hence, the stronger correlation between the two subscales than the others is reasonable. Hereto, the simplified Chinese NRSS is demonstrated to be valid and reliable for measuring NRS in mainland Chinese adults, and the measurement invariance was established across language and age.

Comparison of NRS between mainland Chinese young adults and Hong Kong Chinese adults showed that Hong Kong Chinese adults reported significantly better NRS conditions than mainland Chinese young adults except for the refreshment from sleep subscale, with coefficients of the effect size ranging from 0.193 to 0.771. Previous studies showed that middle-aged adults reported more NRS than either the younger or older adults measured by asking “refreshment from sleep” [23, 51]. The average ages were 20 and 39 for the mainland Chinese young adults and Hong Kong Chinese adults, respectively. However, the linear regression preliminarily showed that age was only associated with the score of affective symptoms. Specifically, the older people showed less affective symptoms of NRS than the younger group. The difference between the other three subscales and the overall scale might be due to risk variables that were not covered in this study. In addition, language contributed to the difference in refreshment from sleep, physical/medical symptoms of NRS, and affective symptoms. Potential rationale should be considered holistically, such as differences in sleep culture, lifestyle, and other variables that might be associated with NRS, especially since the evidence showed that Hong Kong was one of the most sleep-deprived places in the world [24]. For example, Hong Kong Chinese adults are more influenced by Western cultures and consume more coffee, which was demonstrated to help daytime function and potential protective influence on affective symptoms [52, 53]. Moreover, previous research indicates that elevated room temperatures and high humidity levels contribute to increased awakenings and reduced sleep efficiency. The climatic conditions, including temperature and humidity, differed between Hong Kong and Nanjing [23]. Therefore, more comprehensive studies involving potential associated factors and confounders with an adequate sample should be conducted to identify the possible influencing factors, and in-depth studies, such as laboratory studies on the underlying mechanism of specific dimensions, could be applied to help explore the differences between different populations [54].

Compared to adolescents, mainland Chinese young adults exhibited better sleep refreshment but worse affective symptoms. However, the effect sizes were smaller than 0.2 except for that of refreshment from sleep (0.345), which was medium. Academic stress among Chinese adolescents is known to be high because of competitive examinations, and they frequently suffer from sleep deprivation and poor sleep quality [55]. Therefore, they might feel less refreshed from sleep than the university students who have overcome the pressure of the national college entrance examination. However, university students might be more vulnerable to emotional problems since they begin to contact the complex society, face more sources of stress, and undergo the transition to adulthood despite primary study and examination during adolescence [56]. Furthermore, university students usually are far away from family and parents, which may make them less emotionally supported [56]. Moreover, previous studies reported that young adults had poor sleep habits, such as staying up late due to increased mobile phone use [16]. However, these variations might result from factors beyond the scope of this study, suggesting that future research should consider exploring influences like lifestyle and sleep practice.

To our knowledge, this study made the first effort to assess the psychometric properties of the simplified Chinese NRSS among mainland Chinese young adults, while simultaneously examining its cross-linguistic applicability (i.e., simplified Chinese vs. traditional Chinese) and age-group generalizability (i.e., adults and adolescents). Second, this study revealed significant disparities in NRSS patterns between mainland Chinese adults and their Hong Kong counterparts, as well as between adult and adolescent populations within mainland China. These empirical findings not only advance our understanding of cross-cultural and developmental variations in NRS but also provide crucial directions for future research to identify potential underlying factors contributing to these observed differences. However, several limitations of the study are worth noting. First, due to the anonymous sampling limitation, the test-retest reliability of the simplified Chinese NRSS in adults could not be verified. It would be preferable to gather a new sample to assess test-retest reliability. Second, some researchers suggest that a minimum of three items per factor be maintained for factorial validity. Whether additional items should be incorporated into the scale could be investigated in future studies. Nevertheless, the total score is recommended as the primary measure for NRS. Third, report bias is unavoidable as all questionnaires were voluntarily self-reported by students. Although some studies have tried to investigate whether specific objective parameters would indicate the condition of NRS, no gold standard has been verified. Future studies involving instruments such as polysomnography or electroencephalograms are worth the attention of sleep specialists. Lastly, expanding invariance testing would be valuable for facilitating meaningful comparisons across cultural, demographic, and temporal contexts, contributing to a deeper understanding of the underlying mechanisms of NRS. In addition, once longitudinal invariance is established, longitudinal studies could explore the potential “upstream” factors of NRS, thereby enhancing NRS intervention approaches.

Conclusions

To conclude, the 12-item simplified Chinese NRSS is a reliable and valid tool to evaluate NRS among Chinese young adults, and the score could be compared between the simplified Chinese NRSS and traditional Chinese NRSS and between adolescents and young adults with the simplified Chinese version to enhance our understanding of sleep problems in these ethnic groups.

Data availability

The datasets generated and/or analyzed during the current study are not publicly available due to confidentiality.

References

  1. Hou Z, Chen Y, Sun Y, Song C, Deng H, Cheng N, et al. Sleep duration and insomnia with comorbid depression and anxiety symptoms in Chinese adults: A cross-sectional study. Nat Sci Sleep. 2023;15:1079-91. https://doiorg.publicaciones.saludcastillayleon.es/10.2147/NSS.S440584

  2. Grandner MA. Chapter 5 - Social-ecological model of sleep health. In: Grandner MA, editor. Sleep and Health: Academic Press; 2019;45–53.

  3. Li Y, Zhang X, Winkelman JW, Redline S, Hu FB, Stampfer M, et al. Association between insomnia symptoms and mortality: A prospective study of U.S. men. Circulation. 2014;129(7):737 − 46. https://doiorg.publicaciones.saludcastillayleon.es/10.1161/circulationaha.113.004500

  4. Bernert RA, Turvey CL, Conwell Y, Joiner TE Jr. Association of poor subjective sleep quality with risk for death by suicide during a 10-year period: A longitudinal, population-based study of late life. JAMA Psychiatry. 2014;71(10):1129-37. https://doiorg.publicaciones.saludcastillayleon.es/10.1001/jamapsychiatry.2014.1126

  5. Mun CJ, Davis MC, Campbell CM, Finan PH, Tennen H. Linking nonrestorative sleep and activity interference through pain catastrophizing and pain severity: An intraday process model among individuals with fibromyalgia. J Pain. 2020;21(5–6):546 − 56. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jpain.2019.09.001

  6. Saitoh K, Yoshiike T, Kaneko Y, Utsumi T, Matsui K, Nagao K, et al. Associations of nonrestorative sleep and insomnia symptoms with incident depressive symptoms over 1–2 years: Longitudinal results from the Hispanic Community Health Study/Study of Latinos and Sueño Ancillary Study. Depress Anxiety. 2022;39(5):419 − 28. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/da.23258

  7. Stone KC, Taylor DJ, McCrae CS, Kalsekar A, Lichstein KL. Nonrestorative sleep. Sleep Med Rev. 2008;12(4):275 − 88. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.smrv.2007.12.002

  8. Okamoto M, Kobayashi Y, Nakamura F, Musha T. Association between nonrestorative sleep and risk of diabetes: A cross-sectional study. Behav Sleep Med. 2017;15(6):483 − 90. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/15402002.2016.1163701

  9. Kawada T. Feeling refreshed by sleep can predict psychological wellbeing assessed using the general health questionnaire in male workers: A 3-year follow-up study. Psychiatry Investig. 2012;9(4):418 − 21. https://doiorg.publicaciones.saludcastillayleon.es/10.4306/pi.2012.9.4.418

  10. Zhang J, Lam SP, Li SX, Li AM, Wing YK. The longitudinal course and impact of non-restorative sleep: A five-year community-based follow-up study. Sleep Med. 2012;13(6):570-6. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.sleep.2011.12.012

  11. Chiu HY, Wang MY, Chang CK, Chen CM, Chou KR, Tsai JC, et al. Early morning awakening and nonrestorative sleep are associated with increased minor non-fatal accidents during work and leisure time. Accid Anal Prev. 2014;71:10 − 4. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.aap.2014.05.002

  12. Li S, Fong DYT, Wong JYH, McPherson B, Lau EYY, Ip MSM. The association between nonrestorative sleep and health-related quality of life in Chinese adults: A cross-sectional study. Qual Life Res. 2021;30(9):2521–2530. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s11136-021-02832-2

  13. Li S, Fong DYT, Wong JYH, McPherson B, Lau EYY, Huang L, et al. Noise sensitivity associated with nonrestorative sleep in Chinese adults: A cross-sectional study. BMC public health. 2021;21(1):643. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12889-021-10667-2

  14. Guo J, Yang L, Xu Y, Zhang C, Luo X, Liu S, et al. Prevalence and risk factors associated with insomnia symptoms among the Chinese general public after the coronavirus disease 2019 epidemic was initially controlled. Nat Sci Sleep. 2021;13:703 − 12. https://doiorg.publicaciones.saludcastillayleon.es/10.2147/nss.s307996

  15. Wang J, Wu J, Liu J, Meng Y, Li J, Zhou P, et al. Prevalence of sleep disturbances and associated factors among Chinese residents: A web-based empirical survey of 2019. J Glob Health. 2023;13:04071. https://doiorg.publicaciones.saludcastillayleon.es/10.7189/jogh.13.04071

  16. Zhou SJ, Wang LL, Yang R, Yang XJ, Zhang LG, Guo ZC, et al. Sleep problems among Chinese adolescents and young adults during the coronavirus-2019 pandemic. Sleep Med. 2020;74:39–47. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.sleep.2020.06.001

  17. Wilkinson K, Shapiro C. Development and validation of the Nonrestorative Sleep Scale (NRSS). J Clin Sleep Med. 2013;9(9):929 − 37. https://doiorg.publicaciones.saludcastillayleon.es/10.5664/jcsm.2996

  18. Drake CL, Hays RD, Morlock R, Wang F, Shikiar R, Frank L, et al. Development and evaluation of a measure to assess restorative sleep. J Clin Sleep Med. 2014;10(7):733–741, 741A-741E. https://doiorg.publicaciones.saludcastillayleon.es/10.5664/jcsm.3860

  19. Wilkinson K, Shapiro C. Nonrestorative sleep: Symptom or unique diagnostic entity? Sleep Med. 2012;13(6):561-9. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.sleep.2012.02.002

  20. Li S, Fong DYT, Wong JYH, Wilkinson K, Shapiro C, Choi EPH, et al. Nonrestorative sleep scale: Reliable and valid for the Chinese population. Qual Life Res. 2019;28(6):1685-92. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s11136-019-02134-8

  21. Li S, Fong DYT, Xu Y, Wilkinson K, Shapiro C, Wong JYH. Measurement properties of the simplified Chinese version of Nonrestorative Sleep Scale in adolescents. Health Soc Care Community. 2021;29(6):e299-e307. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/hsc.13354

  22. Ohayon MM, Roth T. What are the contributing factors for insomnia in the general population? J Psychosom Res. 2001;51(6):745 − 55. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/s0022-3999(01)00285-9

  23. Ohayon MM. Prevalence and correlates of nonrestorative sleep complaints. Arch Intern Med. 2005;165(1):35–41. https://doiorg.publicaciones.saludcastillayleon.es/10.1001/archinte.165.1.35

  24. Bedford LE, Tang EHM, Dong W, Wong CKH, Tse ETY, Ng APP, et al. Who reports insufficient and disturbed sleep? Results from a representative population-based health survey in Hong Kong. BMJ Open. 2022;12(9):e058169. https://doiorg.publicaciones.saludcastillayleon.es/10.1136/bmjopen-2021-058169

  25. Putnick DL, Bornstein MH. Measurement invariance conventions and reporting: The state of the art and future directions for psychological research. Dev Rev 2016;41:71–90. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.dr.2016.06.004

  26. Anthoine E, Moret L, Regnault A, Sébille V, Hardouin JB. Sample size used to validate a scale: A review of publications on newly-developed patient reported outcomes measures. Health Qual Life Outcomes. 2014;12:176. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12955-014-0176-2

  27. Buysse DJ, Reynolds CF, 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/0165-1781(89)90047-4

  28. Chong AML, Cheung C-k. Factor structure of a Cantonese-version Pittsburgh Sleep Quality Index. Sleep and Biological Rhythms 2012;10(2):118–125. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1479-8425.2011.00532.x

  29. Guo S, Sun W, Liu C, Wu S. Structural validity of the Pittsburgh Sleep Quality Index in Chinese undergraduate students. Front Psychol. 2016;7:1126. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fpsyg.2016.01126

  30. Löwe B, Wahl I, Rose M, Spitzer C, Glaesmer H, Wingenfeld K, et al. A 4-item measure of depression and anxiety: Validation and standardization of the Patient Health Questionnaire-4 (PHQ-4) in the general population. J Affect Disord. 2010;122(1–2):86–95. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jad.2009.06.019

  31. Qian J, Jiang M, Chen C, Chen Y, Yu D, Li C. Reliability and validity of the ultra-brief screening scale for depression and anxiety in outpatients clinics of community healthcare centers (In Chinese). Journal of Internal Medicine Concepts & Practice. 2021;16(2):116–120. https://doiorg.publicaciones.saludcastillayleon.es/10.16138/j.1673-6087.2021.02.010

  32. Fong TCT, Ho RTH, Yip PSF. Psychometric properties of the Patient Health Questionnaire-4 among Hong Kong young adults in 2021: Associations with meaning in life and suicidal ideation. Front Psychiatry. 2023;14:1138755. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fpsyt.2023.1138755

  33. Terwee CB, Bot SD, de Boer MR, van der Windt DA, Knol DL, Dekker J, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007;60(1):34–42. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jclinepi.2006.03.012

  34. Watkins MW. Exploratory factor analysis: A guide to best practice. J Black Psychol. 2018;44(3):219 − 46. https://doiorg.publicaciones.saludcastillayleon.es/10.1177/0095798418771807

  35. Costello AB, Osborne JW. Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Pract Assess Res Eval. 2005;10(1):7. https://doiorg.publicaciones.saludcastillayleon.es/10.7275/jyj1-4868

  36. Pallant J. SPSS survival manual: A step by step guide to data analysis using SPSS. edn. Maidenhead: Open University Press/McGraw-Hill. 2010;4.

  37. Lloret S, Ferreres A, Hernández A, Tomás I. The exploratory factor analysis of items: Guided analysis based on empirical data and software. Anales de Psicología. 2017;33(2):417–432. https://doiorg.publicaciones.saludcastillayleon.es/10.6018/analesps.33.2.270211

  38. Kim H, Ku B, Kim JY, Park YJ, Park YB. Confirmatory and exploratory factor analysis for validating the Phlegm Pattern Questionnaire for healthy subjects. Evid Based Complement Alternat Med. 2016;2696019. https://doiorg.publicaciones.saludcastillayleon.es/10.1155/2016/2696019

  39. Revelle W. psych: Procedures for psychological, psychometric, and personality research. 2024. https://cran.r-project.org/web/packages/psych/index.html. Accessed 18 June 2024.

  40. Bernaards C, Gilbert P, Jennrich R. GPArotation: Gradient projection factor rotation. 2024. https://cran.r-project.org/web/packages/GPArotation/index.html. Accessed 18 June 2024.

  41. Li CH. Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behav Res Methods. 2016;48(3):936 − 49. https://doiorg.publicaciones.saludcastillayleon.es/10.3758/s13428-015-0619-7

  42. Fong DY, Lam CL, Mak KK, Lo WS, Lai YK, Ho SY, et al. The Short Form-12 Health Survey was a valid instrument in Chinese adolescents. J Clin Epidemiol. 2010;63(9):1020-9. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jclinepi.2009.11.011

  43. Chen FF. Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct Equ Modeling. 2007;14:464–504. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/10705510701301834

  44. Rosseel Y, Jorgensen TD, Wilde LD, Oberski D, Byrnes J, Vanbrabant L, et al. lavaan: Latent Variable Analysis. 2024. https://cran.r-project.org/web/packages/psych/index.html. Accessed 18 June 2024.

  45. Sullivan GM, Feinn R. Using effect size-or why the P value is not enough. J Grad Med Educ. 2012;4(3):279 − 82. https://doiorg.publicaciones.saludcastillayleon.es/10.4300/jgme-d-12-00156.1

  46. Rodriguez A, Reise SP, Haviland MG. Applying bifactor statistical indices in the evaluation of psychological measures. J Pers Assess. 2016;98(3):223 − 37. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/00223891.2015.1089249

  47. Schmitt N, Kuljanin G. Measurement invariance: Review of practice and implications. Hum Resour Manage Rev. 2008;18(4):210 − 22. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.hrmr.2008.03.003

  48. Bliwise NG. Factors related to sleep quality in healthy elderly women. Psychol Aging. 1992;7(1):83 − 8. https://doiorg.publicaciones.saludcastillayleon.es/10.1037//0882-7974.7.1.83

  49. Sarsour K, Van Brunt DL, Johnston JA, Foley KA, Morin CM, Walsh JK. Associations of nonrestorative sleep with insomnia, depression, and daytime function. Sleep Med. 2010;11(10):965 − 72. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.sleep.2010.08.007

  50. Stepanski EJ. The effect of sleep fragmentation on daytime function. Sleep. 2002;25(3):268–276. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/sleep/25.3.268

  51. Phillips B, Mannino D. Correlates of sleep complaints in adults: The ARIC study. J Clin Sleep Med. 2005;1(3):277 − 83. https://doiorg.publicaciones.saludcastillayleon.es/10.5664/jcsm.26344

  52. Li S, Fong DYT, Wang YZ, Lin Z, Shang XC, Gong WJ. Nonrestorative sleep and its associated factors in Chinese adolescents and the moderation effects of coffee or tea consumption. BMC public health 2024;24(1):2398. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12889-024-19936-2

  53. O’Callaghan F, Muurlink O, Reid N. Effects of caffeine on sleep quality and daytime functioning. Risk Manag Healthc Policy. 2018;11:263–271. https://doiorg.publicaciones.saludcastillayleon.es/10.2147/RMHP.S156404

  54. Wakasugi M, Kazama JJ, Narita I, Iseki K, Moriyama T, Yamagata K, et al. Association between combined lifestyle factors and non-restorative sleep in Japan: A cross-sectional study based on a Japanese health database. PLoS One. 2014;9(9):e108718. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pone.0108718

  55. Wang H, Fan X. Academic stress and sleep quality among Chinese adolescents: Chain mediating effects of anxiety and school burnout. Int J Environ Res Public Health. 2023;20(3):2219. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/ijerph20032219

  56. Stapley E, Vainieri I, Li E, Merrick H, Jeffery M, Foreman S, et al. A scoping review of the factors that influence families’ ability or capacity to provide young people with emotional support over the transition to adulthood. Front Psychol. 2021;12:732899. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fpsyg.2021.732899

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Acknowledgements

Ms. Anchu Hsu is gratefully acknowledged for her contribution in the backward translations. Mrs. Yan Xu and Mr. Huiming Li are gratefully acknowledged for their help in recruitment.

Funding

This study was supported by the National Natural Science Foundation of China [Grant No. 72204117], Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province [Grant No. 2022SJYB0297], the Health and Medical Research Fund [Grant No. 14150801], Project of “Nursing Science” Funded by the 4th Priority Discipline Development Program of Jiangsu Higher Education Institutions (Jiangsu Education Department [2023] No.11), 333 High-level personnel training Project of Jiangsu Province [Grant No. BRA2020069], and Shenzhen Stability Support Program in Colleges and Universities of China [Grant No. 20220810202707001].

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Author notes

  1. Yanzhe Wang and Weijie Gong contributed equally and are first author to this work.

Authors and Affiliations

  1. School of Nursing, Nanjing Medical University, Nanjing, China

    Yanzhe Wang, Zheng Lin & Sha Li

  2. Department of Family Medicine, Medical School, Shenzhen University, Shenzhen, China

    Weijie Gong

  3. School of Nursing, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

    Daniel Yee Tak Fong

  4. School of Public Health, Medical School, Shenzhen University, Shenzhen, China

    Ziyuan Yu & Ruiheng Nong

  5. School of Nursing & School of Public Health, Yangzhou University, Yangzhou, China

    Xingchen Shang

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Contributions

Daniel Yee Tak Fong, Sha Li, and Zheng Lin contributed to the conception and design of the study. Material preparation and data collection were performed by Yanzhe Wang, Weijie Gong, Daniel Yee Tak Fong, Ziyuan Yu, Ruiheng Nong, and Sha Li. Sha Li and Xingchen Shang performed data analysis. The first draft of the manuscript was written by Yanzhe Wang, Weijie Gong, and Sha Li. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Zheng Lin or Sha Li.

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This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Institutional Review Board of Shenzhen University [No.: PN-202300022] and the Institutional Review Board of Nanjing Medical University [No.: (2023) 585].

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Informed consent was obtained from all individual participants included in the study.

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Wang, Y., Gong, W., Fong, D.Y.T. et al. The simplified Chinese version of the Nonrestorative Sleep Scale in Chinese young adults and measurement invariance across language and age. BMC Psychol 13, 258 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40359-025-02577-4

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BMC Psychology

ISSN: 2050-7283

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