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Mediator Effect of Sleep Hygiene Practices on Relationships Between Sleep Quality and Other Sleep-Related Factors in Chinese Mainland University Students a
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Jin Li , Kaina Zhou , Xiaomei Li , Miao Liu , Shaonong Dang , Duolao d
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Department of Nursing Xi'an Jiaotong University Health Science Center b
Department of Nursing, First Affiliated Hospital Xi'an Jiaotong University c
Department of Epidemiology and Biostatistics, School of Public Health Xi'an Jiaotong University Health Science Center d
Department of Medical Statistics, Faculty of Epidemiology and Population Health London School of Hygiene and Tropical Medicine Published online: 30 Oct 2014.
To cite this article: Jin Li, Kaina Zhou, Xiaomei Li, Miao Liu, Shaonong Dang, Duolao Wang & Xia Xin (2014): Mediator Effect of Sleep Hygiene Practices on Relationships Between Sleep Quality and Other Sleep-Related Factors in Chinese Mainland University Students, Behavioral Sleep Medicine, DOI: 10.1080/15402002.2014.954116 To link to this article: http://dx.doi.org/10.1080/15402002.2014.954116
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Behavioral Sleep Medicine, 00:1–15, 2014 Copyright © Taylor & Francis Group, LLC ISSN: 1540-2002 print/1540-2010 online DOI: 10.1080/15402002.2014.954116
Mediator Effect of Sleep Hygiene Practices on Relationships Between Sleep Quality and Other Sleep-Related Factors in Chinese Mainland University Students Jin Li, Kaina Zhou, and Xiaomei Li Department of Nursing Xi’an Jiaotong University Health Science Center
Miao Liu Department of Nursing, First Affiliated Hospital Xi’an Jiaotong University
Shaonong Dang Department of Epidemiology and Biostatistics, School of Public Health Xi’an Jiaotong University Health Science Center
Duolao Wang Department of Medical Statistics, Faculty of Epidemiology and Population Health London School of Hygiene and Tropical Medicine
Xia Xin Department of Nursing, First Affiliated Hospital Xi’an Jiaotong University
This study examined the mediator effect of sleep hygiene practices (SHP) on relationships between sleep quality and other sleep-related factors in Chinese mainland university students using structural equation modeling analysis. Of the 413 students, 41.4% had poor sleep quality. Gender, academic stress, relaxed psychological status, good physical status, and SHP had significant direct effects on sleep quality; relaxed psychological status had significant direct effect on SHP and indirect
Correspondence should be addressed to Xiaomei Li, No. 76 Yanta Western Road, Xi’an, Shaanxi Province, China, 710061. E-mail: [email protected]
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effect on sleep quality via SHP. The direct, indirect, and total effects of gender, academic stress, relaxed psychological status, good physical status, and SHP explained 25% of the variance in sleep quality. The Chinese mainland university students had relative poor sleep quality. SHP was a mediator between sleep quality and relaxed psychological status.
Poor sleep quality is a common problem in university students of mainland China (Zhou et al., 2012). The prevalence of poor sleep quality is around 30% in university students (Feng, Chen, & Yang, 2005; Yang et al., 2011; Zhou, 2013), which is higher than that in the general population (22.4%; Chen, Yang, & Shi, 2004). Given that a majority of university students are in late adolescence and early adulthood, their sleep quality and related problems could differ from nonstudents of their age due to living situation, education stress, and academic workload (Galambos, Vargas Lascano, Howard, & Maggs, 2013; Gaultney, 2011). According to published studies, poor sleep quality is detrimental to university students in their psychosomatic health, learning capacity, academic performance, daytime function, and routine safety (Lohsoonthorn et al., 2013; Pallos, Gergely, Yamada, Miyazaki, & Okawa, 2007; Zawadzki, Graham, & Gerin, 2013). Previous studies show that sleep quality of university students mainly associates with the following factors, including sociodemographics (e.g., gender, income, living environment; Feng, Chen, & Yang, 2005; Hoefelmann, Lopes, da Silva, Moritz, & Nahas, 2013), psychological status (e.g., anxiety, depression, and perceived stress level; Feng, Chen, & Yang, 2005; Lemma, Gelaye, Berhane, Worku, & Williams, 2012; Zawadzki, Graham, & Gerin, 2013), physical quality (e.g., endurance, speed and strength quality; Yu, Ma, Chen, & Ye, 2013), individual behaviors (e.g., cigarette smoking, alcohol consumption, and stimulants use; Kenney, LaBrie, Hummer, & Pham, 2012; Lemma, Patel, et al., 2012; Vélez et al., 2013), and daily experiences (e.g., stress, heavy academic workload, skipping breakfast, Internet addition, interpersonal relationships, and new social experiences; Cheng et al., 2012; Galambos, Dalton, & Maggs, 2009; Zhou, 2013). Another important factor relating to sleep quality of university students is sleep hygiene practices (SHP; Brick, Seely, & Palermo, 2010; Brown, Buboltz, & Soper, 2002; Suen, Tam, & Hon, 2010). SHP refers to the behaviors or habits and the environment that are assumed to influence sleep quality by promoting or inhibiting better sleep (Lacks & Rotert, 1986; LeBourgeois, Giannotti, Cortesi, Wolfson, & Harsh, 2005). SHP influences sleep quality via the behaviors or habits such as sleep schedules, daytime naps, consumption of alcohol, tobacco, or caffeine, exercise schedule, staying on one’s bed for non-sleep-related activities, and sleep environment factors such as light, temperature, noise, and ventilation (Jefferson et al., 2005). A study from Hong Kong indicates that SHP significantly associates with sleep quality after adjusting for age, gender, year of study, and type of residence in university students, explaining 19.4% of the variance in sleep quality (Suen, Tam, & Hon, 2010). According to published studies, most of the influencing factors of sleep quality in university students were explored by using univariate analysis or regression analysis; therefore, the findings were limited to direct effect of the factors and did not take interaction into consideration. The structural equation modeling (SEM) analysis is the method considering direct, indirect, and total effect of the variables, but few studies employed it in examining the effects of influencing factors on sleep quality (Onyper, Thacher, Gilbert, & Gradess, 2012). Of the sleep-related factors, SHP has the characteristics of sleep-related behaviors or habits and closely relates
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to sleep quality (Brown, Buboltz, & Soper, 2002); however, the mediator role of SHP on relationships between sleep quality and other sleep-related factors is still unclear. Few studies explore the relationships among the factors of sociodemographics, psychological status, physical quality, individual behaviors, daily experiences, and SHP and sleep quality. Therefore, the purpose of this study was to examine the mediator effect of SHP on relationships between sleep quality and other sleep-related factors (i.e., demographics, daily experiences, stress experiences, and self-rated psychosomatic status) using SEM analysis in Chinese mainland university students. The hypotheses were that (a) demographics, daily experiences, stress experiences, self-rated psychosomatic status, and SHP have direct effects on sleep quality, and (b) SHP has a mediator role between sleep quality and demographics, daily experiences, stress experiences, and self-rated psychosomatic status. Findings of the study will help to provide evidence for developing comprehensive intervention programs in improving sleep quality in the university student population.
METHOD Ethics Statement The study protocol was reviewed and approved by the Human Research Ethics Committee of Xi’an Jiaotong University. Written informed consent was obtained from each student before the questionnaire survey.
Subjects and Data Collection Subjects were students of two universities in Xi’an, China. The sample was selected by clustering sampling. Inclusion criteria were full-time students without any other jobs; exclusion criteria were having a history of chronic medical or psychotic disorders or refusal to give written informed consent. Data were collected from October 2009 to November 2010. Data collection included characteristics of the students, SHP, and sleep quality. All of the data collection instruments were self-administered questionnaires completed by the students independently. Data collectors were responsible for the questionnaire distribution, checking, and returning.
Measures Characteristics of the students. Characteristics of the students included demographics (4 items, i.e., age, gender, degree, and number of roommates), daily experiences (6 items, responded as yes or no for the first five items; i.e., regular activity-resting schedule, abundant extracurricular life, conflict of interpersonal relationship, perplexed emotion, family life events, and average hours of nighttime computer use), stress experiences (3 items, responded as yes or no; i.e., academic stress, job-seeking stress, and economic stress) and self-rated psychosomatic status (2 items, responded as yes or no; i.e., relaxed psychological status and good physical status). The responses of these variables were based on the period over the past month.
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Sleep hygiene practices (SHP). SHP was evaluated using the Chinese version of the second part of the Sleep Hygiene Awareness and Practice Scale (SHAP), which is the valid tool for sleep assessment developed by Lacks and Rotert (1986). It consists of 19 items describing sleep-related behaviors or habits and sleep environment. The students were instructed to rate the average frequencies a week they engaged in the behavioral practices on the 8-point Likert scale (from 0 D none per week to 7 D every day per week) over the past month. Items 1 to 15 describe inadequate SHP and positive-scored, whereas items 16 to 19 describe adequate SHP and reverse-scored. The total score is the sum of the 19 item scores (range: 0 to 133), with the higher score demonstrating worse SHP. Although the SHAP has been used in sleep research in the university student population (Brown, Buboltz, & Soper, 2002), no published psychometric data for it was found. Pittsburgh Sleep Quality Index (PSQI). Sleep quality was assessed using the Chinese version of the PSQI. It consists of 19 items measuring different aspects of sleep quality and sleep disturbances during a one-month period, including subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, sleep medication use, and daytime dysfunction (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989). A total sleep quality score (range: 0 to 21) can be derived, with the higher score indicating poorer sleep quality. The PSQI has been widely accepted as both valid and reliable (Aloba, Adewuya, Ola, & Mapayi, 2007; Tzeng, Fu, & Lin, 2012). The original PSQI has good internal consistency (Cronbach’s ˛ D 0:83) and test– retest .r D 0:85/ reliability; the sensitivity and specificity are 89.6% and 86.5% respectively according to the critical value of 5 (Buysse et al., 1989). Liu et al. (1996) translated the original PSQI into Chinese and evaluated its psychometric properties. Cronbach’s ˛ is 0.72, test–retest reliability is 0.81, and the factor loading coefficients of the 7 components are all above 0.50. A cut-off score of 7 is found having a sensitivity of 98.3% and a specificity of 90.3%. In this study, Cronbach’s ˛ was 0.75. The PSQI total score of 7 was used as the criterion for discriminating between the students with good sleep quality (PSQI < 7) and the students with poor sleep quality (PSQI > 7).
Data Analyses The collected data were analyzed using SPSS 20.0 and AMOS 17.0 (SPSS Inc., Chicago, IL). Summarizing continuous variables used mean and standard deviation (SD), while summarizing categorical variables used frequencies and percentages. Independent samples t-test was applied to compare sleep quality between good sleep students and poor sleep students. Multiple linear regression analysis was employed to identify the significant influencing factors of the PSQI total score. According to the principle of parsimony, the significant factors were selected in SEM analysis (Wu, 2010). SEM analysis was performed using maximum likelihood bootstrapping method. Since the observed variables were not normally distributed, the bootstrapping method was used because it is not based on the multivariate normality assumption for the endogenous variables (Zhang, 2011). Standardized direct, indirect, and total effects with corresponding 95% bias-corrected confidence interval were measured based on 1,000 random samples (the subsample of the bootstrapping method) generated by computer (Zhang, 2011). According to the method of
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Baron et al. (1986), the mediator effect of SHP was examined via three stages. First, independent variables had significant direct effects on mediator; second, independent variables had significant direct effects on outcome variable; third, independent variables had significant indirect effects and mediator had a significant direct effect on outcome variable. The model fit was tested with three fit indices: absolute, incremental, and 0.90), adjusted goodness-of-fit index (AGFI; desired value 0.90), root mean square error of approximation (RMSEA; desired value < 0.08) and 2 value (desired significance p > 0:05). The incrementalfit indices are Tracker-Lewis index (TLI; desired value 0.90) and comparative fit index (CFI; desired value 0.90). The parsimonious-fit index is normed chi-square (i.e., the ratio of c 2 /df; desired value 1.0–3.0; Wu, 2010). A value of p < 0:05 (two-tailed) was considered statistically significant.
RESULTS A total of 430 students were eligible for the study, and 413 (96.0%) completed the questionnaires. Seventeen students were excluded for having a history of chronic medical disorders (n D 8, 1.9%) or because they refused to give written informed consent (n D 9, 2.1%). The mean age of the 413 students was 20.44 ˙ 1.99 (range: 17–37) years, 192 (46.5%) were males. Two hundred and ninety-three (70.9%) were in a Bachelor degree program. All of the students lived in residence halls, with 4:81 ˙ 1:12 (range: 2 to 8) having roommates. Over the past month, daily experiences of the students included regular activity-resting schedule (n D 103, 24.9%), abundant extracurricular life (n D 45, 10.9%), conflict of interpersonal relationship (n D 158, 38.3%), perplexed emotion (n D 220, 53.3%), and family life events (n D 69, 16.7%); the average hours of nighttime computer use (from 7 pm to 3 am; Mesquita & Reimao, 2010) were 1:80 ˙ 1:94 (range: 0–8). Stress experiences of the students included academic stress (n D 353, 85.5%), job-seeking stress (n D 238, 57.6%), and economic stress (n D 277, 67.1%). About 40% of the students rated relaxed psychological status (n D 166, 40.2%) and good physical status (n D 187, 45.3%; Table 1). The overall mean SHP score was 30:03 ˙ 10:52 (range: 9–70). Among inadequate SHP (items 1 to 15), “take a nap during daytime” had the highest score .3:74 ˙ 2:33/, while “use sleep medications regularly” had the lowest score .0:02 ˙ 0:35/. Among adequate SHP (items 16 to 19), “do exercise after 2 pm” had the highest score .5:60 ˙ 1:84/, while “maintain a comfortable temperature during sleep” had the lowest score (2:14 ˙ 2:46; Table 2). The PSQI total score was 7:42 ˙ 2:13, with sleep efficiency had the highest score .2:93 ˙ 0:44/ and sleep medication use had the lowest score .0:02 ˙ 0:20/. Of the 413 students, 171 (41.4%) had poor sleep quality (PSQI total score > 7). Independent samples t-test showed that the PSQI scores of good sleep students were lower than that of poor sleep students (P < 0.05), except sleep efficiency [mean difference: 0.05; 95% confidence interval: 0.14, 0.03] (P D 0.24) and sleep medication use [ 0.04 ( 0.08, 0.002)] (P D 0.06; Table 3). Multiple linear regression analysis showed that the significant variables of sleep quality were gender (Beta D 0.16, P D 0.013), academic stress (Beta D 0.12, P D 0.012), relaxed psychological status (Beta D 0.12, P D 0.015), good physical status (Beta D 0.16, P < 0.001), and SHP (Beta D 0.32, P < 0.001; Table 4).
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TABLE 1 Characteristics of the University Students in the Sample (N D 413)
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Characteristics Demographics Age (years) (mean ˙ SD) (range: 17–37) Gender (n, %) Male Female Degree (n, %) Associate Bachelor Master and above Number of roommates (mean ˙ SD) (range: 2–8) Daily experiencesa Regular activity-resting schedule (n, %) Yes No Abundant extracurricular life (n, %) Yes No Conflict of interpersonal relationship (n, %) Yes No Perplexed emotion (n, %) Yes No Family life events (n, %) Yes No Average hours of nighttime computer useb (mean ˙ SD) (range: 0–8) Stress experiencesa Academic stress (n, %) Yes No Job-seeking stress (n, %) Yes No Economic stress (n, %) Yes No Self-rated psychosomatic statusa Relaxed psychological status (n, %) Yes No Good physical status (n, %) Yes No
Profiles
20.44 ˙ 1.99 192 (46.5) 221 (53.5) 55 (13.3) 293 (70.9) 65 (15.7) 4.81 ˙ 1.12
103 (24.9) 310 (75.1) 45 (10.9) 368 (89.1) 158 (38.3) 255 (61.7) 220 (53.3) 193 (46.7) 69 (16.7) 344 (83.3) 1.80 ( 1.94
353 (85.5) 60 (14.5) 238 (57.6) 175 (42.4) 277 (67.1) 136 (32.9)
166 (40.2) 247 (59.8) 187 (45.3) 226 (54.7)
Note. SD: standard deviation. a The responses of daily experiences, stress experiences, and self-rated psychosomatic status were based on the period over the past month. b Nighttime computer use refers to computer use from 7:00 p.m. to 3:00 a.m.
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TABLE 2 Scores of Each Item in Sleep Hygiene Practices of University Students (N D 413) Mean ˙ SD
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Items of Sleep Hygiene Practices
3.74 ˙ 2.02 ˙ 2.03 ˙ 0.04 ˙ 0.02 ˙ 0.25 ˙ 0.08 ˙ 0.06 ˙ 0.64 ˙ 0.50 ˙ 0.11 ˙ 0.91 ˙ 1.25 ˙ 1.86 ˙ 0.39 ˙ 3.46 ˙ 4.91 ˙ 5.60 ˙ 2.14 ˙ 30.03 ˙
1. Take a nap during daytime. 2. Go to bed hungry. 3. Go to bed thirsty. 4. Smoking more than one package per day. 5. Use sleep medications regularly. 6. Drink beverages containing caffeine within 4 hours of bedtime. 7. Have beer (or other drinks with alcohol) within 2 hours of bedtime. 8. Take medications containing caffeine within 4 hours of bedtime. 9. Bring worries with you when you go to bed. 10. Worry about night-time sleep ability. 11. Drink for improving sleep. 12. Perform active exercise within 2 hours of bedtime. 13. Sleep in a bright bedroom. 14. Sleep in a noisy bedroom. 15. Sleep with bed partner. 16. Sleep approximately the same length of time each night.* 17. Set aside time to relax/perform relaxing exercise before bedtime.* 18. Do exercise after 2:00 p.m.* 19. Maintain a comfortable temperature during sleep.* Overall mean score
2.33 2.23 2.30 0.43 0.35 0.92 0.46 0.43 1.56 1.47 0.65 1.56 2.10 2.30 1.23 2.60 2.54 1.84 2.46 10.52
Note. SD: standard deviation. *The item was reverse-scored.
SEM analysis revealed that gender, academic stress, relaxed psychological status, good physical status and SHP had significant direct effects on sleep quality (P < 0.05). Specifically, relaxed psychological status had significant direct effect (path coefficient D 0.20, 95% confidence interval: 0.09, 0.28, P < 0.01) on SHP and indirect effect (path coefficient D 0.07,
TABLE 3 Comparisons of PSQI Scores Between Good Sleep Students (PSQI 7) and Poor Sleep Students (PSQI > 7; mean ˙ SD)
PSQI Scores Subjective sleep quality Sleep latency Sleep duration Sleep efficiency Sleep disturbance Sleep medication use Daytime dysfunction Total score
Overall (N D 413) 1.09 1.08 0.24 2.93 1.08 0.02 0.97 7.42
˙ ˙ ˙ ˙ ˙ ˙ ˙ ˙
0.65 0.89 0.50 0.44 0.49 0.20 0.72 2.13
Good Sleep Students (n D 242) 0.81 0.60 0.12 2.91 0.91 0.00 0.66 6.02
˙ ˙ ˙ ˙ ˙ ˙ ˙ ˙
0.47 0.59 0.34 0.50 0.40 0.06 0.59 1.03
Poor Sleep Students (n D 171) 1.50 1.75 0.42 2.96 1.31 0.04 1.42 9.40
˙ ˙ ˙ ˙ ˙ ˙ ˙ ˙
0.65 0.81 0.62 0.32 0.50 0.29 0.67 1.65
Mean Difference (95% CI) 0.70 1.15 0.29 0.05 0.40 0.04 0.76 3.38
( ( ( ( ( ( ( (
0.81, 0.59) 1.29, 1.02) 0.39, 0.20) 0.14, 0.03) 0.49, 0.31) 0.08, 0.002) 0.88, 0.64) 3.64, 3.12)
Note. PSQI: Pittsburgh sleep quality index. SD: standard deviation. 95% CI: 95% confidence interval.
p < 0.001 < 0.001 < 0.001 0.24 < 0.001 0.06 < 0.001 < 0.001
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TABLE 4 Influencing Factors of PSQI Total Score: Multiple Linear Regression Analysis (N D 413)
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Independent Variables* Age Gender Degree Number of roommates Regular activity-resting schedule Abundant extracurricular life Conflict of interpersonal relationship Perplexed emotion Family life events Average hours of nighttime computer use Academic stress Job-seeking stress Economic stress Relaxed psychological status Good physical status Sleep hygiene practices
B (95% CI) 0.01 ( 0.11, 0.13) 0.67 (0.14, 1.20) 0.16 ( 0.63, 0.31) 0.13 ( 0.43, 0.17) 0.23 ( 0.22, 0.67) 0.04 ( 0.57, 0.64) 0.16 ( 0.56, 0.25) 0.36 ( 0.75, 0.04) 0.45 ( 0.96, 0.06) 0.00 ( 0.11, 0.11) 0.71 ( 1.25, 0.16) 0.21 ( 0.21, 0.63) 0.006 ( 0.43, 0.44) 0.51 (0.10, 0.91) 0.69 (0.31, 1.08) 0.06 (0.05, 0.08)
Beta 0.01 0.16 0.04 0.07 0.05 0.006 0.04 0.08 0.08 0.00 0.12 0.05 0.001 0.12 0.16 0.32
p 0.85 0.013 0.51 0.39 0.32 0.90 0.45 0.08 0.09 0.99 0.012 0.32 0.98 0.015 < 0.001 < 0.001
R D 0:53, R 2 D 0:28, F D 9:64, p < 0:001. *Independent variables were characteristics in Table 1: gender (male D 1, female D 2), degree (associate D 1, bachelor D 2, master and above D 3), regular activity-resting schedule (yes D 1, no D 2), abundant extracurricular life (yes D 1, no D 2), conflict of interpersonal relationship (yes D 1, no D 2), perplexed emotion (yes D 1, no D 2), family life events (yes D 1, no D 2), academic stress (yes D 1, no D 2), job-seeking stress (yes D 1, no D 2), economic stress (yes D 1, no D 2), relaxed psychological status (yes D 1, no D 2), good physical status (yes D 1, no D 2) and quantitative variables (age, number of roommates, average hours of nighttime computer use and sleep hygiene practices). PSQI: Pittsburgh Sleep Quality Index. 95% CI: 95% confidence interval. Note. Boldface items indicate the significant independent variable.
95% confidence interval: 0.03, 0.10, P < 0.01) on sleep quality via SHP (Table 5). The SHP mediator effect model showed that relaxed psychological status explained 4% of the variance in SHP; the direct, indirect and total effects of gender, academic stress, relaxed psychological status, good physical status and SHP explained 25% of the variance in sleep quality. The model was acceptable with eligible fit indices (Figure 1).
DISCUSSION Findings of the study showed that the university students had relative poor sleep quality. The factors of gender, academic stress, relaxed psychological status, good physical status, and SHP had significant direct effects on sleep quality, supporting the first hypothesis; additionally, SHP was found to have a significant mediator effect between sleep quality and relaxed psychological status, supporting the second hypothesis that SHP has a mediator role between sleep quality and self-rated psychosomatic status.
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TABLE 5 Standardized Mediator Effect of Sleep Hygiene Practices and Standardized Direct/Indirect/Total Effect of Influencing Factors on Sleep Quality (N D 413)
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Standardized Effect Gender Direct (95% CI) Indirect (95% CI) Total (95% CI) Academic stress Direct (95% CI) Indirect (95% CI) Total (95% CI) Relaxed psychological status Direct (95% CI) Indirect (95% CI) Total (95% CI) Good physical status Direct (95% CI) Indirect (95% CI) Total (95% CI) Sleep hygiene practices Direct (95% CI) Indirect (95% CI) Total (95% CI)
Mediator (Sleep Hygiene Practices)
Sleep Quality (PSQI Total Score)
0.02 ( 0.13, 0.06) — 0.02 ( 0.13, 0.06)
0.13* (0.03, 0.21) 0.01 ( 0.04, 0.02) 0.12* (0.008, 0.20)
0.02 ( 0.07, 0.13) — 0.03 ( 0.07, 0.13)
0.12** ( 0.20, 0.05) 0.01 ( 0.03, 0.05) 0.12** ( 0.19, 0.05)
0.20** (0.09, 0.28) — 0.20** (0.09, 0.28)
0.14** (0.06, 0.23) 0.07** (0.03, 0.10) 0.21** (0.12, 0.28)
0.09 (0.00, 0.21) — 0.09 (0.00, 0.21)
0.17** (0.07, 0.26) 0.03 (0.00, 0.07) 0.20** (0.09, 0.28)
— — —
0.34** (0.25, 0.43) — 0.34** (0.25, 0.43)
In this study, the students had relative higher PSQI scores than the data of other related reports. According to Yu et al. (2013), the university students (n D 2,744) in their study had relative lower scores in total PSQI .5:38 ˙ 2:49/ and in subjective sleep quality .0:84 ˙ 0:69/, sleep latency .0:77 ˙ 0:79/, sleep efficiency .0:14 ˙ 0:44/, and sleep disturbance .0:71 ˙ 0:56/ than that of the students in this study (total PSQI score: 7:42 ˙ 2:13; subjective sleep quality: 1:09 ˙ 0:65; sleep latency 1:08 ˙ 0:89; sleep efficiency: 2:93 ˙ 0:44; sleep disturbance: 1:08 ˙ 0:49). It demonstrates that the students in this study had relative poor sleep quality, especially in the sleep component of subjective sleep quality, sleep latency, sleep efficiency, and sleep disturbance. According to the cut-off score 7 of the Chinese PSQI, a considerable proportion (41.4%) of the students had poor sleep quality, which demonstrates that poor sleep quality was a common problem in the students of the study and more efforts should be taken to improve the sleep quality of the students. It is lower than the prevalence of poor sleep quality in university students of other countries (48.1% to 57.5%; Lemma, Gelaye, Berhane, Worku, & Williams, 2012a; Lohsoonthorn et al., 2013; Suen, Hon, & Tam, 2008), but higher than the prevalence in other Chinese mainland university students (around 30%; Feng, Chen, & Yang, 2005; Yang et al., 2011; Zhou, 2013), and the prevalence in general population (22.4%; Chen, Yang, & Shi, 2004), supporting that poor sleep quality is a common problem in the university student population (Vélez et al., 2013).
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FIGURE 1 Sleep hygiene practices (SHP) mediator effect model (GFI D 0.99, AGFI D 0.98, RMSEA D 0.03, 2 D 4:02, P D 0.26; CFI D 0.99, TLI D 0.97; NC D 1.34). GFI: goodness-of-fit index; AGFI: adjusted goodness-of-fit index; RMSEA: root mean square error of approximation; CFI: comparative fit index; TLI: Tracker-Lewis index; NC: normed chi-square; PSQI: Pittsburgh Sleep Quality Index.
Between-group comparisons show that good sleep students had better overall sleep quality than that of poor sleep students, with significant differences in the scales of subjective sleep quality, sleep latency, sleep duration, sleep disturbance, and daytime dysfunction. It indicates that the major problems of poor sleep students were taking a long time to fall asleep, getting insufficient sleep, being disturbed during sleep, and low daytime study/work efficiency, which subsequently lead to dissatisfaction of subjective sleep quality and poor overall sleep quality (Galambos, Dalton, & Maggs, 2009; Galambos, Nargas Lascano, Howard, & Maggs, 2013; Hoefelmann, Lopes, da Silva, Moritz, & Nahas, 2013). Sleep efficiency and sleep medication use had no significant differences between good sleep students and poor sleep students. The probable explanation is that poor sleep efficiency .2:93 ˙ 0:44/ and rare use of sleep medicine .0:02 ˙ 0:20/ were common in the students of this study. Specifically, poor sleep efficiency represents inappropriate of the bedtime and wake time schedule. If the students had inappropriate bedtime and wake time schedules, they would have irregular sleep rhythms, which consequently lead to poor sleep efficiency. For example, late bedtime and early wake time will lead to sleep deficiency and longer daytime sleepiness, while either late bedtime and late wake time or early bedtime and late wake time will lead to longer sleep and biological sleep rhythm disorders. In this study, 75.1% students had irregular activity-resting schedules, indicating that more efforts should be taken to explore scientific scheduling of bedtimes and rise times to help the students maintaining adequate sleep.
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Characteristics, gender, academic stress, relaxed psychological status, and good physical status were significant factors relating to sleep quality. Regarding gender, female students had poorer sleep quality than that of male students, which is consistent with the findings of other studies (Cheng et al., 2012; Lemma, Gelaye, et al., 2012); Lemma, Patel, et al., 2012). The probable explanation is that females require more sleep time than males and exhibit a higher level of daytime sleepiness (Lee et al., 2014; Oginska & Pokorski, 2006; Rotenberg, Portela, & Duarte, 2001). Other studies based on general population also found that females have a higher prevalence of difficulty initiating sleep, difficulty maintaining sleep, and experiencing early morning awakening than males (Santos-Silva et al., 2010; Xiang et al., 2008). Therefore, sleep quality of female students should be given more attention while developing interventions; some programs such as sleep-related physiological health education or movement-based courses (e.g., Pilates, taiji quan, Yoga) might be good choices for addressing poor sleep quality (Caldwell, Harrison, Adams, Quin, & Greeson, 2010; Caldwell, Harrison, Adams, & Triplett, 2009; Kline et al., 2011) and cognitive-behavioral techniques for insomnia. Academic stress was the significant factor that leads to poor sleep quality. In this study, 85.5% students had academic stress, indicating that it is a common problem in the university student population (Galambos et al., 2009). Generally speaking, academic stress relates to a heavy study workload. In this situation, the students are often undergoing later bedtimes and early rise times, leading to insufficient sleep; meanwhile, the stressful feeling is harmful to the students’ psychological health. Both sleep deficiency and negative psychological status result in poor sleep quality (Galambos et al., 2013; Kang & Chen, 2009; Lemma, Gelaye, et al., 2012). Accordingly, proper interventions should be used to deal with academic stress and the corresponding unpleasant feeling, such as psychological counseling, music therapy, and selfrelaxation training (Harmat, Takacs, & Bodizs, 2008; Sun, Kang, Wang, & Zeng, 2013; Wang, 2010; Yan, Chen, & Zhu, 2010; Yu, 2009; Zhang, 2013), so that the students’ sleep quality can be improved. With respect to self-rated psychosomatic status, relaxed psychological status and good physical status were beneficial to maintaining good sleep quality. This is in line with the findings of previous studies (Lemma, Gelaye, et al., 2012; Liu, Wang, Cui, & Jia, 2012; Yu et al., 2013), supporting the importance of keeping good psychological and physical health for good sleep quality (Soffer-Dudek, Sadeh, Dahl, & Rosenblat-Stein, 2011; Test, Canfi, Eyal, Shoam-Vardi, & Sheiner, 2011). However, more than half students in this study did not have relaxed psychological status (59.8%) or good physical status (54.7%), reflecting tension and physical inactivity. Life transitions and daily experiences in university compound student stress in the competitive academic environment (Galambos et al., 2013). Such an environment leads to stressful feelings, negative psychological states, and less time for physical activity, which is detrimental to sleep quality. Thus, it is recommended that schools provide psychological counseling and intervention (Galambos et al., 2013); additionally, physical activity and doing exercise are of benefit to improve physical health and to reduce psychological stress (Chen et al., 2009; Kline et al., 2011; Sun et al., 2013). These strategies would be helpful to improve poor sleep quality. Specifically, SHP had the largest direct effect on sleep quality, with higher SHP score relating to higher PSQI total score, indicating that inadequate SHP was detrimental to sleep quality. Inadequate SHP with higher scores included daytime naps .3:74 ˙ 2:33/, going to bed hungry .2:02 ˙ 2:23/ or thirsty .2:03 ˙ 2:30/, and sleep interrupted by light .1:25 ˙ 2:10/ or
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noise .1:86 ˙ 2:30/. Although prior studies did not reveal an adverse effect of daytime naps on night sleep (Dhand & Dhand, 2006), longer daytime naps (> 30 min) may lead to difficulty of nocturnal sleep, especially for poor sleepers (St George, Delbaere, Williams, & Lord, 2009). Night noise was regarded as the main cause of sleep interruption in university students (60%) (Sweileh et al., 2011), indicating that the students had a poor sleep environment. However, going to bed hungry or thirsty and sleep interrupted by light were not reported in other similar studies, which is probably due to heterogeneity of sleep habits or environment of the students across universities. The remaining inadequate SHP (i.e., smoking, drinking, caffeine use, and sleep medication use) were lower scored (with the mean score < 1), revealing that these unhealthy sleep-related behaviors or habits still existed among the students (Kenney et al., 2012; Lemma, Patel, et al., 2012). The four adequate SHPs were higher scored (with mean score > 2), indicating lack of exercise, not relaxing prior to sleep, inconsistent daily sleep duration, and room temperatures uncomfortable for the students. To improve sleep quality, sleep hygiene education and sleep environment modulation (e.g., temperature and light) should be considered in the intervention programs (Chen, Kuo, & Chueh, 2010). Of the four significant direct factors (i.e., gender, academic stress, relaxed psychological status, and good physical status), only relaxed psychological status was found to have a significant indirect effect on sleep quality via SHP, that is, SHP had a mediator effect on the relationship between sleep quality and relaxed psychological status. It is in line with the published finding that sleep quality can be indirectly impacted by psychological status via sleep-related behaviors or habits (Wong et al., 2013). Additionally, relaxed psychological status had a larger direct effect (path coefficient D 0.20) on SHP than on PSQI total score (path coefficient D 0.14), indicating that SHP was more sensitive to psychological status change than sleep quality. For the students, entering university is a major life transition, which is characterized by leaving home, reduced parental supervision, new social opportunities with its commitments, new social experiences, heavy academic workload, and other extracurricular activities. Such life transitions result in a negative psychological status including stressful feelings, anxiety, or depression (Taylor & Bramoweth, 2010), leading to an irregular sleep schedule (e.g., later bedtimes and later rise times) and unhealthy individual behaviors (e.g., smoking, alcohol use, stimulant consumption, medication use for sleep; Galambos et al., 2013; Vélez et al., 2013), and eventually decreasing sleep quality. Therefore, attention should be paid to the interaction between psychological status and SHP; both behavioral and psychological interventions should be considered while developing sleep quality interventions (Kaku et al., 2012; Nishinoue et al., 2012). With respect to the SHP mediator effect model, although the good-fit indices were high, the pass coefficients of gender, academic stress, relaxed psychological status, and good physical status were low, indicating the weak effects of these variables on sleep quality as well as the weak effect of relaxed psychological status on SHP. These significant pass coefficients were probably caused by a simulated large sample size using the bootstrapping method, which does not represent practical significance. Therefore, the strong effects of the above-mentioned variables on sleep quality and SHP need further study in future work. There were some limitations of the study. First, the self-report data of sleep quality lacked objective information. Second, due to the use of subjective self-report for all measures used, it is possible that these relationships are inflated due to response biases. Third, this is a crosssectional study; a follow-up study is recommended to explore the factors influencing sleep
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quality. Fourth, the study was conducted in Xi’an, which limited the generalization of the results to all university students. The Chinese mainland university students in this study had relative poor sleep quality. Gender, academic stress, relaxed psychological status, good physical status, and SHP were significant direct factors of sleep quality. SHP had a mediator effect on the relationship between sleep quality and relaxed psychological status. A comprehensive intervention considering both SHP and psychological status is recommended to improve sleep quality in the university student population. FUNDING We thank the Dreyfus Health Foundation, New York, for funding this study.
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Mediator Effect of Sleep Hygiene Practices on Relationships Between Sleep Quality and Other Sleep-Related Factors in Chinese Mainland University Students a
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Jin Li , Kaina Zhou , Xiaomei Li , Miao Liu , Shaonong Dang , Duolao d
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Wang & Xia Xin a
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Department of Nursing Xi'an Jiaotong University Health Science Center b
Department of Nursing, First Affiliated Hospital Xi'an Jiaotong University c
Department of Epidemiology and Biostatistics, School of Public Health Xi'an Jiaotong University Health Science Center d
Department of Medical Statistics, Faculty of Epidemiology and Population Health London School of Hygiene and Tropical Medicine Published online: 30 Oct 2014.
To cite this article: Jin Li, Kaina Zhou, Xiaomei Li, Miao Liu, Shaonong Dang, Duolao Wang & Xia Xin (2014): Mediator Effect of Sleep Hygiene Practices on Relationships Between Sleep Quality and Other Sleep-Related Factors in Chinese Mainland University Students, Behavioral Sleep Medicine, DOI: 10.1080/15402002.2014.954116 To link to this article: http://dx.doi.org/10.1080/15402002.2014.954116
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Behavioral Sleep Medicine, 00:1–15, 2014 Copyright © Taylor & Francis Group, LLC ISSN: 1540-2002 print/1540-2010 online DOI: 10.1080/15402002.2014.954116
Mediator Effect of Sleep Hygiene Practices on Relationships Between Sleep Quality and Other Sleep-Related Factors in Chinese Mainland University Students Jin Li, Kaina Zhou, and Xiaomei Li Department of Nursing Xi’an Jiaotong University Health Science Center
Miao Liu Department of Nursing, First Affiliated Hospital Xi’an Jiaotong University
Shaonong Dang Department of Epidemiology and Biostatistics, School of Public Health Xi’an Jiaotong University Health Science Center
Duolao Wang Department of Medical Statistics, Faculty of Epidemiology and Population Health London School of Hygiene and Tropical Medicine
Xia Xin Department of Nursing, First Affiliated Hospital Xi’an Jiaotong University
This study examined the mediator effect of sleep hygiene practices (SHP) on relationships between sleep quality and other sleep-related factors in Chinese mainland university students using structural equation modeling analysis. Of the 413 students, 41.4% had poor sleep quality. Gender, academic stress, relaxed psychological status, good physical status, and SHP had significant direct effects on sleep quality; relaxed psychological status had significant direct effect on SHP and indirect
Correspondence should be addressed to Xiaomei Li, No. 76 Yanta Western Road, Xi’an, Shaanxi Province, China, 710061. E-mail: [email protected]
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effect on sleep quality via SHP. The direct, indirect, and total effects of gender, academic stress, relaxed psychological status, good physical status, and SHP explained 25% of the variance in sleep quality. The Chinese mainland university students had relative poor sleep quality. SHP was a mediator between sleep quality and relaxed psychological status.
Poor sleep quality is a common problem in university students of mainland China (Zhou et al., 2012). The prevalence of poor sleep quality is around 30% in university students (Feng, Chen, & Yang, 2005; Yang et al., 2011; Zhou, 2013), which is higher than that in the general population (22.4%; Chen, Yang, & Shi, 2004). Given that a majority of university students are in late adolescence and early adulthood, their sleep quality and related problems could differ from nonstudents of their age due to living situation, education stress, and academic workload (Galambos, Vargas Lascano, Howard, & Maggs, 2013; Gaultney, 2011). According to published studies, poor sleep quality is detrimental to university students in their psychosomatic health, learning capacity, academic performance, daytime function, and routine safety (Lohsoonthorn et al., 2013; Pallos, Gergely, Yamada, Miyazaki, & Okawa, 2007; Zawadzki, Graham, & Gerin, 2013). Previous studies show that sleep quality of university students mainly associates with the following factors, including sociodemographics (e.g., gender, income, living environment; Feng, Chen, & Yang, 2005; Hoefelmann, Lopes, da Silva, Moritz, & Nahas, 2013), psychological status (e.g., anxiety, depression, and perceived stress level; Feng, Chen, & Yang, 2005; Lemma, Gelaye, Berhane, Worku, & Williams, 2012; Zawadzki, Graham, & Gerin, 2013), physical quality (e.g., endurance, speed and strength quality; Yu, Ma, Chen, & Ye, 2013), individual behaviors (e.g., cigarette smoking, alcohol consumption, and stimulants use; Kenney, LaBrie, Hummer, & Pham, 2012; Lemma, Patel, et al., 2012; Vélez et al., 2013), and daily experiences (e.g., stress, heavy academic workload, skipping breakfast, Internet addition, interpersonal relationships, and new social experiences; Cheng et al., 2012; Galambos, Dalton, & Maggs, 2009; Zhou, 2013). Another important factor relating to sleep quality of university students is sleep hygiene practices (SHP; Brick, Seely, & Palermo, 2010; Brown, Buboltz, & Soper, 2002; Suen, Tam, & Hon, 2010). SHP refers to the behaviors or habits and the environment that are assumed to influence sleep quality by promoting or inhibiting better sleep (Lacks & Rotert, 1986; LeBourgeois, Giannotti, Cortesi, Wolfson, & Harsh, 2005). SHP influences sleep quality via the behaviors or habits such as sleep schedules, daytime naps, consumption of alcohol, tobacco, or caffeine, exercise schedule, staying on one’s bed for non-sleep-related activities, and sleep environment factors such as light, temperature, noise, and ventilation (Jefferson et al., 2005). A study from Hong Kong indicates that SHP significantly associates with sleep quality after adjusting for age, gender, year of study, and type of residence in university students, explaining 19.4% of the variance in sleep quality (Suen, Tam, & Hon, 2010). According to published studies, most of the influencing factors of sleep quality in university students were explored by using univariate analysis or regression analysis; therefore, the findings were limited to direct effect of the factors and did not take interaction into consideration. The structural equation modeling (SEM) analysis is the method considering direct, indirect, and total effect of the variables, but few studies employed it in examining the effects of influencing factors on sleep quality (Onyper, Thacher, Gilbert, & Gradess, 2012). Of the sleep-related factors, SHP has the characteristics of sleep-related behaviors or habits and closely relates
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to sleep quality (Brown, Buboltz, & Soper, 2002); however, the mediator role of SHP on relationships between sleep quality and other sleep-related factors is still unclear. Few studies explore the relationships among the factors of sociodemographics, psychological status, physical quality, individual behaviors, daily experiences, and SHP and sleep quality. Therefore, the purpose of this study was to examine the mediator effect of SHP on relationships between sleep quality and other sleep-related factors (i.e., demographics, daily experiences, stress experiences, and self-rated psychosomatic status) using SEM analysis in Chinese mainland university students. The hypotheses were that (a) demographics, daily experiences, stress experiences, self-rated psychosomatic status, and SHP have direct effects on sleep quality, and (b) SHP has a mediator role between sleep quality and demographics, daily experiences, stress experiences, and self-rated psychosomatic status. Findings of the study will help to provide evidence for developing comprehensive intervention programs in improving sleep quality in the university student population.
METHOD Ethics Statement The study protocol was reviewed and approved by the Human Research Ethics Committee of Xi’an Jiaotong University. Written informed consent was obtained from each student before the questionnaire survey.
Subjects and Data Collection Subjects were students of two universities in Xi’an, China. The sample was selected by clustering sampling. Inclusion criteria were full-time students without any other jobs; exclusion criteria were having a history of chronic medical or psychotic disorders or refusal to give written informed consent. Data were collected from October 2009 to November 2010. Data collection included characteristics of the students, SHP, and sleep quality. All of the data collection instruments were self-administered questionnaires completed by the students independently. Data collectors were responsible for the questionnaire distribution, checking, and returning.
Measures Characteristics of the students. Characteristics of the students included demographics (4 items, i.e., age, gender, degree, and number of roommates), daily experiences (6 items, responded as yes or no for the first five items; i.e., regular activity-resting schedule, abundant extracurricular life, conflict of interpersonal relationship, perplexed emotion, family life events, and average hours of nighttime computer use), stress experiences (3 items, responded as yes or no; i.e., academic stress, job-seeking stress, and economic stress) and self-rated psychosomatic status (2 items, responded as yes or no; i.e., relaxed psychological status and good physical status). The responses of these variables were based on the period over the past month.
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Sleep hygiene practices (SHP). SHP was evaluated using the Chinese version of the second part of the Sleep Hygiene Awareness and Practice Scale (SHAP), which is the valid tool for sleep assessment developed by Lacks and Rotert (1986). It consists of 19 items describing sleep-related behaviors or habits and sleep environment. The students were instructed to rate the average frequencies a week they engaged in the behavioral practices on the 8-point Likert scale (from 0 D none per week to 7 D every day per week) over the past month. Items 1 to 15 describe inadequate SHP and positive-scored, whereas items 16 to 19 describe adequate SHP and reverse-scored. The total score is the sum of the 19 item scores (range: 0 to 133), with the higher score demonstrating worse SHP. Although the SHAP has been used in sleep research in the university student population (Brown, Buboltz, & Soper, 2002), no published psychometric data for it was found. Pittsburgh Sleep Quality Index (PSQI). Sleep quality was assessed using the Chinese version of the PSQI. It consists of 19 items measuring different aspects of sleep quality and sleep disturbances during a one-month period, including subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, sleep medication use, and daytime dysfunction (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989). A total sleep quality score (range: 0 to 21) can be derived, with the higher score indicating poorer sleep quality. The PSQI has been widely accepted as both valid and reliable (Aloba, Adewuya, Ola, & Mapayi, 2007; Tzeng, Fu, & Lin, 2012). The original PSQI has good internal consistency (Cronbach’s ˛ D 0:83) and test– retest .r D 0:85/ reliability; the sensitivity and specificity are 89.6% and 86.5% respectively according to the critical value of 5 (Buysse et al., 1989). Liu et al. (1996) translated the original PSQI into Chinese and evaluated its psychometric properties. Cronbach’s ˛ is 0.72, test–retest reliability is 0.81, and the factor loading coefficients of the 7 components are all above 0.50. A cut-off score of 7 is found having a sensitivity of 98.3% and a specificity of 90.3%. In this study, Cronbach’s ˛ was 0.75. The PSQI total score of 7 was used as the criterion for discriminating between the students with good sleep quality (PSQI < 7) and the students with poor sleep quality (PSQI > 7).
Data Analyses The collected data were analyzed using SPSS 20.0 and AMOS 17.0 (SPSS Inc., Chicago, IL). Summarizing continuous variables used mean and standard deviation (SD), while summarizing categorical variables used frequencies and percentages. Independent samples t-test was applied to compare sleep quality between good sleep students and poor sleep students. Multiple linear regression analysis was employed to identify the significant influencing factors of the PSQI total score. According to the principle of parsimony, the significant factors were selected in SEM analysis (Wu, 2010). SEM analysis was performed using maximum likelihood bootstrapping method. Since the observed variables were not normally distributed, the bootstrapping method was used because it is not based on the multivariate normality assumption for the endogenous variables (Zhang, 2011). Standardized direct, indirect, and total effects with corresponding 95% bias-corrected confidence interval were measured based on 1,000 random samples (the subsample of the bootstrapping method) generated by computer (Zhang, 2011). According to the method of
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Baron et al. (1986), the mediator effect of SHP was examined via three stages. First, independent variables had significant direct effects on mediator; second, independent variables had significant direct effects on outcome variable; third, independent variables had significant indirect effects and mediator had a significant direct effect on outcome variable. The model fit was tested with three fit indices: absolute, incremental, and 0.90), adjusted goodness-of-fit index (AGFI; desired value 0.90), root mean square error of approximation (RMSEA; desired value < 0.08) and 2 value (desired significance p > 0:05). The incrementalfit indices are Tracker-Lewis index (TLI; desired value 0.90) and comparative fit index (CFI; desired value 0.90). The parsimonious-fit index is normed chi-square (i.e., the ratio of c 2 /df; desired value 1.0–3.0; Wu, 2010). A value of p < 0:05 (two-tailed) was considered statistically significant.
RESULTS A total of 430 students were eligible for the study, and 413 (96.0%) completed the questionnaires. Seventeen students were excluded for having a history of chronic medical disorders (n D 8, 1.9%) or because they refused to give written informed consent (n D 9, 2.1%). The mean age of the 413 students was 20.44 ˙ 1.99 (range: 17–37) years, 192 (46.5%) were males. Two hundred and ninety-three (70.9%) were in a Bachelor degree program. All of the students lived in residence halls, with 4:81 ˙ 1:12 (range: 2 to 8) having roommates. Over the past month, daily experiences of the students included regular activity-resting schedule (n D 103, 24.9%), abundant extracurricular life (n D 45, 10.9%), conflict of interpersonal relationship (n D 158, 38.3%), perplexed emotion (n D 220, 53.3%), and family life events (n D 69, 16.7%); the average hours of nighttime computer use (from 7 pm to 3 am; Mesquita & Reimao, 2010) were 1:80 ˙ 1:94 (range: 0–8). Stress experiences of the students included academic stress (n D 353, 85.5%), job-seeking stress (n D 238, 57.6%), and economic stress (n D 277, 67.1%). About 40% of the students rated relaxed psychological status (n D 166, 40.2%) and good physical status (n D 187, 45.3%; Table 1). The overall mean SHP score was 30:03 ˙ 10:52 (range: 9–70). Among inadequate SHP (items 1 to 15), “take a nap during daytime” had the highest score .3:74 ˙ 2:33/, while “use sleep medications regularly” had the lowest score .0:02 ˙ 0:35/. Among adequate SHP (items 16 to 19), “do exercise after 2 pm” had the highest score .5:60 ˙ 1:84/, while “maintain a comfortable temperature during sleep” had the lowest score (2:14 ˙ 2:46; Table 2). The PSQI total score was 7:42 ˙ 2:13, with sleep efficiency had the highest score .2:93 ˙ 0:44/ and sleep medication use had the lowest score .0:02 ˙ 0:20/. Of the 413 students, 171 (41.4%) had poor sleep quality (PSQI total score > 7). Independent samples t-test showed that the PSQI scores of good sleep students were lower than that of poor sleep students (P < 0.05), except sleep efficiency [mean difference: 0.05; 95% confidence interval: 0.14, 0.03] (P D 0.24) and sleep medication use [ 0.04 ( 0.08, 0.002)] (P D 0.06; Table 3). Multiple linear regression analysis showed that the significant variables of sleep quality were gender (Beta D 0.16, P D 0.013), academic stress (Beta D 0.12, P D 0.012), relaxed psychological status (Beta D 0.12, P D 0.015), good physical status (Beta D 0.16, P < 0.001), and SHP (Beta D 0.32, P < 0.001; Table 4).
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TABLE 1 Characteristics of the University Students in the Sample (N D 413)
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Characteristics Demographics Age (years) (mean ˙ SD) (range: 17–37) Gender (n, %) Male Female Degree (n, %) Associate Bachelor Master and above Number of roommates (mean ˙ SD) (range: 2–8) Daily experiencesa Regular activity-resting schedule (n, %) Yes No Abundant extracurricular life (n, %) Yes No Conflict of interpersonal relationship (n, %) Yes No Perplexed emotion (n, %) Yes No Family life events (n, %) Yes No Average hours of nighttime computer useb (mean ˙ SD) (range: 0–8) Stress experiencesa Academic stress (n, %) Yes No Job-seeking stress (n, %) Yes No Economic stress (n, %) Yes No Self-rated psychosomatic statusa Relaxed psychological status (n, %) Yes No Good physical status (n, %) Yes No
Profiles
20.44 ˙ 1.99 192 (46.5) 221 (53.5) 55 (13.3) 293 (70.9) 65 (15.7) 4.81 ˙ 1.12
103 (24.9) 310 (75.1) 45 (10.9) 368 (89.1) 158 (38.3) 255 (61.7) 220 (53.3) 193 (46.7) 69 (16.7) 344 (83.3) 1.80 ( 1.94
353 (85.5) 60 (14.5) 238 (57.6) 175 (42.4) 277 (67.1) 136 (32.9)
166 (40.2) 247 (59.8) 187 (45.3) 226 (54.7)
Note. SD: standard deviation. a The responses of daily experiences, stress experiences, and self-rated psychosomatic status were based on the period over the past month. b Nighttime computer use refers to computer use from 7:00 p.m. to 3:00 a.m.
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TABLE 2 Scores of Each Item in Sleep Hygiene Practices of University Students (N D 413) Mean ˙ SD
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Items of Sleep Hygiene Practices
3.74 ˙ 2.02 ˙ 2.03 ˙ 0.04 ˙ 0.02 ˙ 0.25 ˙ 0.08 ˙ 0.06 ˙ 0.64 ˙ 0.50 ˙ 0.11 ˙ 0.91 ˙ 1.25 ˙ 1.86 ˙ 0.39 ˙ 3.46 ˙ 4.91 ˙ 5.60 ˙ 2.14 ˙ 30.03 ˙
1. Take a nap during daytime. 2. Go to bed hungry. 3. Go to bed thirsty. 4. Smoking more than one package per day. 5. Use sleep medications regularly. 6. Drink beverages containing caffeine within 4 hours of bedtime. 7. Have beer (or other drinks with alcohol) within 2 hours of bedtime. 8. Take medications containing caffeine within 4 hours of bedtime. 9. Bring worries with you when you go to bed. 10. Worry about night-time sleep ability. 11. Drink for improving sleep. 12. Perform active exercise within 2 hours of bedtime. 13. Sleep in a bright bedroom. 14. Sleep in a noisy bedroom. 15. Sleep with bed partner. 16. Sleep approximately the same length of time each night.* 17. Set aside time to relax/perform relaxing exercise before bedtime.* 18. Do exercise after 2:00 p.m.* 19. Maintain a comfortable temperature during sleep.* Overall mean score
2.33 2.23 2.30 0.43 0.35 0.92 0.46 0.43 1.56 1.47 0.65 1.56 2.10 2.30 1.23 2.60 2.54 1.84 2.46 10.52
Note. SD: standard deviation. *The item was reverse-scored.
SEM analysis revealed that gender, academic stress, relaxed psychological status, good physical status and SHP had significant direct effects on sleep quality (P < 0.05). Specifically, relaxed psychological status had significant direct effect (path coefficient D 0.20, 95% confidence interval: 0.09, 0.28, P < 0.01) on SHP and indirect effect (path coefficient D 0.07,
TABLE 3 Comparisons of PSQI Scores Between Good Sleep Students (PSQI 7) and Poor Sleep Students (PSQI > 7; mean ˙ SD)
PSQI Scores Subjective sleep quality Sleep latency Sleep duration Sleep efficiency Sleep disturbance Sleep medication use Daytime dysfunction Total score
Overall (N D 413) 1.09 1.08 0.24 2.93 1.08 0.02 0.97 7.42
˙ ˙ ˙ ˙ ˙ ˙ ˙ ˙
0.65 0.89 0.50 0.44 0.49 0.20 0.72 2.13
Good Sleep Students (n D 242) 0.81 0.60 0.12 2.91 0.91 0.00 0.66 6.02
˙ ˙ ˙ ˙ ˙ ˙ ˙ ˙
0.47 0.59 0.34 0.50 0.40 0.06 0.59 1.03
Poor Sleep Students (n D 171) 1.50 1.75 0.42 2.96 1.31 0.04 1.42 9.40
˙ ˙ ˙ ˙ ˙ ˙ ˙ ˙
0.65 0.81 0.62 0.32 0.50 0.29 0.67 1.65
Mean Difference (95% CI) 0.70 1.15 0.29 0.05 0.40 0.04 0.76 3.38
( ( ( ( ( ( ( (
0.81, 0.59) 1.29, 1.02) 0.39, 0.20) 0.14, 0.03) 0.49, 0.31) 0.08, 0.002) 0.88, 0.64) 3.64, 3.12)
Note. PSQI: Pittsburgh sleep quality index. SD: standard deviation. 95% CI: 95% confidence interval.
p < 0.001 < 0.001 < 0.001 0.24 < 0.001 0.06 < 0.001 < 0.001
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TABLE 4 Influencing Factors of PSQI Total Score: Multiple Linear Regression Analysis (N D 413)
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Independent Variables* Age Gender Degree Number of roommates Regular activity-resting schedule Abundant extracurricular life Conflict of interpersonal relationship Perplexed emotion Family life events Average hours of nighttime computer use Academic stress Job-seeking stress Economic stress Relaxed psychological status Good physical status Sleep hygiene practices
B (95% CI) 0.01 ( 0.11, 0.13) 0.67 (0.14, 1.20) 0.16 ( 0.63, 0.31) 0.13 ( 0.43, 0.17) 0.23 ( 0.22, 0.67) 0.04 ( 0.57, 0.64) 0.16 ( 0.56, 0.25) 0.36 ( 0.75, 0.04) 0.45 ( 0.96, 0.06) 0.00 ( 0.11, 0.11) 0.71 ( 1.25, 0.16) 0.21 ( 0.21, 0.63) 0.006 ( 0.43, 0.44) 0.51 (0.10, 0.91) 0.69 (0.31, 1.08) 0.06 (0.05, 0.08)
Beta 0.01 0.16 0.04 0.07 0.05 0.006 0.04 0.08 0.08 0.00 0.12 0.05 0.001 0.12 0.16 0.32
p 0.85 0.013 0.51 0.39 0.32 0.90 0.45 0.08 0.09 0.99 0.012 0.32 0.98 0.015 < 0.001 < 0.001
R D 0:53, R 2 D 0:28, F D 9:64, p < 0:001. *Independent variables were characteristics in Table 1: gender (male D 1, female D 2), degree (associate D 1, bachelor D 2, master and above D 3), regular activity-resting schedule (yes D 1, no D 2), abundant extracurricular life (yes D 1, no D 2), conflict of interpersonal relationship (yes D 1, no D 2), perplexed emotion (yes D 1, no D 2), family life events (yes D 1, no D 2), academic stress (yes D 1, no D 2), job-seeking stress (yes D 1, no D 2), economic stress (yes D 1, no D 2), relaxed psychological status (yes D 1, no D 2), good physical status (yes D 1, no D 2) and quantitative variables (age, number of roommates, average hours of nighttime computer use and sleep hygiene practices). PSQI: Pittsburgh Sleep Quality Index. 95% CI: 95% confidence interval. Note. Boldface items indicate the significant independent variable.
95% confidence interval: 0.03, 0.10, P < 0.01) on sleep quality via SHP (Table 5). The SHP mediator effect model showed that relaxed psychological status explained 4% of the variance in SHP; the direct, indirect and total effects of gender, academic stress, relaxed psychological status, good physical status and SHP explained 25% of the variance in sleep quality. The model was acceptable with eligible fit indices (Figure 1).
DISCUSSION Findings of the study showed that the university students had relative poor sleep quality. The factors of gender, academic stress, relaxed psychological status, good physical status, and SHP had significant direct effects on sleep quality, supporting the first hypothesis; additionally, SHP was found to have a significant mediator effect between sleep quality and relaxed psychological status, supporting the second hypothesis that SHP has a mediator role between sleep quality and self-rated psychosomatic status.
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TABLE 5 Standardized Mediator Effect of Sleep Hygiene Practices and Standardized Direct/Indirect/Total Effect of Influencing Factors on Sleep Quality (N D 413)
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Standardized Effect Gender Direct (95% CI) Indirect (95% CI) Total (95% CI) Academic stress Direct (95% CI) Indirect (95% CI) Total (95% CI) Relaxed psychological status Direct (95% CI) Indirect (95% CI) Total (95% CI) Good physical status Direct (95% CI) Indirect (95% CI) Total (95% CI) Sleep hygiene practices Direct (95% CI) Indirect (95% CI) Total (95% CI)
Mediator (Sleep Hygiene Practices)
Sleep Quality (PSQI Total Score)
0.02 ( 0.13, 0.06) — 0.02 ( 0.13, 0.06)
0.13* (0.03, 0.21) 0.01 ( 0.04, 0.02) 0.12* (0.008, 0.20)
0.02 ( 0.07, 0.13) — 0.03 ( 0.07, 0.13)
0.12** ( 0.20, 0.05) 0.01 ( 0.03, 0.05) 0.12** ( 0.19, 0.05)
0.20** (0.09, 0.28) — 0.20** (0.09, 0.28)
0.14** (0.06, 0.23) 0.07** (0.03, 0.10) 0.21** (0.12, 0.28)
0.09 (0.00, 0.21) — 0.09 (0.00, 0.21)
0.17** (0.07, 0.26) 0.03 (0.00, 0.07) 0.20** (0.09, 0.28)
— — —
0.34** (0.25, 0.43) — 0.34** (0.25, 0.43)
In this study, the students had relative higher PSQI scores than the data of other related reports. According to Yu et al. (2013), the university students (n D 2,744) in their study had relative lower scores in total PSQI .5:38 ˙ 2:49/ and in subjective sleep quality .0:84 ˙ 0:69/, sleep latency .0:77 ˙ 0:79/, sleep efficiency .0:14 ˙ 0:44/, and sleep disturbance .0:71 ˙ 0:56/ than that of the students in this study (total PSQI score: 7:42 ˙ 2:13; subjective sleep quality: 1:09 ˙ 0:65; sleep latency 1:08 ˙ 0:89; sleep efficiency: 2:93 ˙ 0:44; sleep disturbance: 1:08 ˙ 0:49). It demonstrates that the students in this study had relative poor sleep quality, especially in the sleep component of subjective sleep quality, sleep latency, sleep efficiency, and sleep disturbance. According to the cut-off score 7 of the Chinese PSQI, a considerable proportion (41.4%) of the students had poor sleep quality, which demonstrates that poor sleep quality was a common problem in the students of the study and more efforts should be taken to improve the sleep quality of the students. It is lower than the prevalence of poor sleep quality in university students of other countries (48.1% to 57.5%; Lemma, Gelaye, Berhane, Worku, & Williams, 2012a; Lohsoonthorn et al., 2013; Suen, Hon, & Tam, 2008), but higher than the prevalence in other Chinese mainland university students (around 30%; Feng, Chen, & Yang, 2005; Yang et al., 2011; Zhou, 2013), and the prevalence in general population (22.4%; Chen, Yang, & Shi, 2004), supporting that poor sleep quality is a common problem in the university student population (Vélez et al., 2013).
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FIGURE 1 Sleep hygiene practices (SHP) mediator effect model (GFI D 0.99, AGFI D 0.98, RMSEA D 0.03, 2 D 4:02, P D 0.26; CFI D 0.99, TLI D 0.97; NC D 1.34). GFI: goodness-of-fit index; AGFI: adjusted goodness-of-fit index; RMSEA: root mean square error of approximation; CFI: comparative fit index; TLI: Tracker-Lewis index; NC: normed chi-square; PSQI: Pittsburgh Sleep Quality Index.
Between-group comparisons show that good sleep students had better overall sleep quality than that of poor sleep students, with significant differences in the scales of subjective sleep quality, sleep latency, sleep duration, sleep disturbance, and daytime dysfunction. It indicates that the major problems of poor sleep students were taking a long time to fall asleep, getting insufficient sleep, being disturbed during sleep, and low daytime study/work efficiency, which subsequently lead to dissatisfaction of subjective sleep quality and poor overall sleep quality (Galambos, Dalton, & Maggs, 2009; Galambos, Nargas Lascano, Howard, & Maggs, 2013; Hoefelmann, Lopes, da Silva, Moritz, & Nahas, 2013). Sleep efficiency and sleep medication use had no significant differences between good sleep students and poor sleep students. The probable explanation is that poor sleep efficiency .2:93 ˙ 0:44/ and rare use of sleep medicine .0:02 ˙ 0:20/ were common in the students of this study. Specifically, poor sleep efficiency represents inappropriate of the bedtime and wake time schedule. If the students had inappropriate bedtime and wake time schedules, they would have irregular sleep rhythms, which consequently lead to poor sleep efficiency. For example, late bedtime and early wake time will lead to sleep deficiency and longer daytime sleepiness, while either late bedtime and late wake time or early bedtime and late wake time will lead to longer sleep and biological sleep rhythm disorders. In this study, 75.1% students had irregular activity-resting schedules, indicating that more efforts should be taken to explore scientific scheduling of bedtimes and rise times to help the students maintaining adequate sleep.
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Characteristics, gender, academic stress, relaxed psychological status, and good physical status were significant factors relating to sleep quality. Regarding gender, female students had poorer sleep quality than that of male students, which is consistent with the findings of other studies (Cheng et al., 2012; Lemma, Gelaye, et al., 2012); Lemma, Patel, et al., 2012). The probable explanation is that females require more sleep time than males and exhibit a higher level of daytime sleepiness (Lee et al., 2014; Oginska & Pokorski, 2006; Rotenberg, Portela, & Duarte, 2001). Other studies based on general population also found that females have a higher prevalence of difficulty initiating sleep, difficulty maintaining sleep, and experiencing early morning awakening than males (Santos-Silva et al., 2010; Xiang et al., 2008). Therefore, sleep quality of female students should be given more attention while developing interventions; some programs such as sleep-related physiological health education or movement-based courses (e.g., Pilates, taiji quan, Yoga) might be good choices for addressing poor sleep quality (Caldwell, Harrison, Adams, Quin, & Greeson, 2010; Caldwell, Harrison, Adams, & Triplett, 2009; Kline et al., 2011) and cognitive-behavioral techniques for insomnia. Academic stress was the significant factor that leads to poor sleep quality. In this study, 85.5% students had academic stress, indicating that it is a common problem in the university student population (Galambos et al., 2009). Generally speaking, academic stress relates to a heavy study workload. In this situation, the students are often undergoing later bedtimes and early rise times, leading to insufficient sleep; meanwhile, the stressful feeling is harmful to the students’ psychological health. Both sleep deficiency and negative psychological status result in poor sleep quality (Galambos et al., 2013; Kang & Chen, 2009; Lemma, Gelaye, et al., 2012). Accordingly, proper interventions should be used to deal with academic stress and the corresponding unpleasant feeling, such as psychological counseling, music therapy, and selfrelaxation training (Harmat, Takacs, & Bodizs, 2008; Sun, Kang, Wang, & Zeng, 2013; Wang, 2010; Yan, Chen, & Zhu, 2010; Yu, 2009; Zhang, 2013), so that the students’ sleep quality can be improved. With respect to self-rated psychosomatic status, relaxed psychological status and good physical status were beneficial to maintaining good sleep quality. This is in line with the findings of previous studies (Lemma, Gelaye, et al., 2012; Liu, Wang, Cui, & Jia, 2012; Yu et al., 2013), supporting the importance of keeping good psychological and physical health for good sleep quality (Soffer-Dudek, Sadeh, Dahl, & Rosenblat-Stein, 2011; Test, Canfi, Eyal, Shoam-Vardi, & Sheiner, 2011). However, more than half students in this study did not have relaxed psychological status (59.8%) or good physical status (54.7%), reflecting tension and physical inactivity. Life transitions and daily experiences in university compound student stress in the competitive academic environment (Galambos et al., 2013). Such an environment leads to stressful feelings, negative psychological states, and less time for physical activity, which is detrimental to sleep quality. Thus, it is recommended that schools provide psychological counseling and intervention (Galambos et al., 2013); additionally, physical activity and doing exercise are of benefit to improve physical health and to reduce psychological stress (Chen et al., 2009; Kline et al., 2011; Sun et al., 2013). These strategies would be helpful to improve poor sleep quality. Specifically, SHP had the largest direct effect on sleep quality, with higher SHP score relating to higher PSQI total score, indicating that inadequate SHP was detrimental to sleep quality. Inadequate SHP with higher scores included daytime naps .3:74 ˙ 2:33/, going to bed hungry .2:02 ˙ 2:23/ or thirsty .2:03 ˙ 2:30/, and sleep interrupted by light .1:25 ˙ 2:10/ or
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noise .1:86 ˙ 2:30/. Although prior studies did not reveal an adverse effect of daytime naps on night sleep (Dhand & Dhand, 2006), longer daytime naps (> 30 min) may lead to difficulty of nocturnal sleep, especially for poor sleepers (St George, Delbaere, Williams, & Lord, 2009). Night noise was regarded as the main cause of sleep interruption in university students (60%) (Sweileh et al., 2011), indicating that the students had a poor sleep environment. However, going to bed hungry or thirsty and sleep interrupted by light were not reported in other similar studies, which is probably due to heterogeneity of sleep habits or environment of the students across universities. The remaining inadequate SHP (i.e., smoking, drinking, caffeine use, and sleep medication use) were lower scored (with the mean score < 1), revealing that these unhealthy sleep-related behaviors or habits still existed among the students (Kenney et al., 2012; Lemma, Patel, et al., 2012). The four adequate SHPs were higher scored (with mean score > 2), indicating lack of exercise, not relaxing prior to sleep, inconsistent daily sleep duration, and room temperatures uncomfortable for the students. To improve sleep quality, sleep hygiene education and sleep environment modulation (e.g., temperature and light) should be considered in the intervention programs (Chen, Kuo, & Chueh, 2010). Of the four significant direct factors (i.e., gender, academic stress, relaxed psychological status, and good physical status), only relaxed psychological status was found to have a significant indirect effect on sleep quality via SHP, that is, SHP had a mediator effect on the relationship between sleep quality and relaxed psychological status. It is in line with the published finding that sleep quality can be indirectly impacted by psychological status via sleep-related behaviors or habits (Wong et al., 2013). Additionally, relaxed psychological status had a larger direct effect (path coefficient D 0.20) on SHP than on PSQI total score (path coefficient D 0.14), indicating that SHP was more sensitive to psychological status change than sleep quality. For the students, entering university is a major life transition, which is characterized by leaving home, reduced parental supervision, new social opportunities with its commitments, new social experiences, heavy academic workload, and other extracurricular activities. Such life transitions result in a negative psychological status including stressful feelings, anxiety, or depression (Taylor & Bramoweth, 2010), leading to an irregular sleep schedule (e.g., later bedtimes and later rise times) and unhealthy individual behaviors (e.g., smoking, alcohol use, stimulant consumption, medication use for sleep; Galambos et al., 2013; Vélez et al., 2013), and eventually decreasing sleep quality. Therefore, attention should be paid to the interaction between psychological status and SHP; both behavioral and psychological interventions should be considered while developing sleep quality interventions (Kaku et al., 2012; Nishinoue et al., 2012). With respect to the SHP mediator effect model, although the good-fit indices were high, the pass coefficients of gender, academic stress, relaxed psychological status, and good physical status were low, indicating the weak effects of these variables on sleep quality as well as the weak effect of relaxed psychological status on SHP. These significant pass coefficients were probably caused by a simulated large sample size using the bootstrapping method, which does not represent practical significance. Therefore, the strong effects of the above-mentioned variables on sleep quality and SHP need further study in future work. There were some limitations of the study. First, the self-report data of sleep quality lacked objective information. Second, due to the use of subjective self-report for all measures used, it is possible that these relationships are inflated due to response biases. Third, this is a crosssectional study; a follow-up study is recommended to explore the factors influencing sleep
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quality. Fourth, the study was conducted in Xi’an, which limited the generalization of the results to all university students. The Chinese mainland university students in this study had relative poor sleep quality. Gender, academic stress, relaxed psychological status, good physical status, and SHP were significant direct factors of sleep quality. SHP had a mediator effect on the relationship between sleep quality and relaxed psychological status. A comprehensive intervention considering both SHP and psychological status is recommended to improve sleep quality in the university student population. FUNDING We thank the Dreyfus Health Foundation, New York, for funding this study.
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